{ "schema_version": 1, "updated_on": "2026-10-09", "license": "CC-BY-4.0", "attribution": "Jon Bishop", "scope_note": "A selected library of peer-reviewed marketing research, including empirical studies, evidence syntheses, and theory relevant to SaaS and technical founders. It is not a systematic review and does not imply that consumer findings directly generalize to B2B SaaS.", "records": [ { "slug": "optimal-free-trial-length-saas", "title": "Design and Evaluation of Optimal Free Trials", "category": "Acquisition and retention", "study_type": "Randomized field experiment and policy evaluation", "citation": "Yoganarasimhan, H., Barzegary, E., & Pani, A. (2023). Management Science, 69(6), 3220\u20133240.", "authors": [ "Hema Yoganarasimhan", "Ebrahim Barzegary", "Abhishek Pani" ], "year": 2023, "journal": "Management Science", "doi": "10.1287/mnsc.2022.4507", "doi_url": "https://doi.org/10.1287/mnsc.2022.4507", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4507", "accessible_url": "https://arxiv.org/abs/2006.13420", "access_label": "Open author preprint; publisher version may require access", "access_class": "open-full-text", "research_question": "How do different free-trial lengths affect subscriptions, and can trial length be assigned more effectively using customer characteristics?", "design": "A SaaS firm randomly assigned new users to 7-, 14- or 30-day trials. The authors compare uniform policies and evaluate personalized assignment rules using experimental data and inverse-propensity-score policy evaluation.", "sample_context": "337,724 new users across Australia, New Zealand, France, Germany, Japan, the United Kingdom and the United States; subscription and retention were followed for two years. The firm and product are anonymized.", "findings": "In this firm and experiment, a 7-day trial was the best uniform policy and increased subscriptions by 5.59% versus assigning everyone a 30-day trial. The best evaluated personalized policy, based on lasso, improved subscriptions by 6.81% versus that 30-day baseline; it also performed well on longer-run outcomes.", "limitations": "One anonymized SaaS firm, product, trial design and historical period. Personalized-policy performance depends on the covariates, experiment and evaluation method. The result is not a general recommendation to shorten every SaaS trial.", "founder_use": "Useful when designing a local randomized trial-length experiment. Treat the paper as a design and evaluation example; estimate outcomes for your own activation path, sales cycle and user mix.", "evidence_basis": "Full author preprint plus the peer-reviewed publisher record. Sample, random assignment, follow-up and headline results were checked in the paper text.", "source_ids": [ "01a0fb31-06c8-720e-a517-3b3d5ae402f8", "01a0fb32-a081-70c6-b96f-8a3af674177e" ], "corrections": [], "plain_english_summary": "In this firm and experiment, a 7-day trial was the best uniform policy and increased subscriptions by 5.59% versus assigning everyone a 30-day trial. For your marketing: This may be useful when designing a local randomized trial-length experiment.", "evidence_check": { "score": 5.0, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (337,724); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "personalization-email-marketing", "title": "Personalization in Email Marketing: The Role of Noninformative Advertising Content", "category": "Acquisition and retention", "study_type": "Randomized field experiments", "citation": "Sahni, N. S., Wheeler, S. C., & Chintagunta, P. (2018). Marketing Science, 37(2), 236\u2013258.", "authors": [ "Navdeep S. Sahni", "S. Christian Wheeler", "Pradeep K. Chintagunta" ], "year": 2018, "journal": "Marketing Science", "doi": "10.1287/mksc.2017.1066", "doi_url": "https://doi.org/10.1287/mksc.2017.1066", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2017.1066", "accessible_url": "https://www.gsb.stanford.edu/faculty-research/publications/personalization-email-marketing-role-non-informative-advertising", "access_label": "Publisher and author abstract; full article access may vary", "access_class": "abstract", "research_question": "Does adding consumer-specific but noninformative content to an email affect recipient response?", "design": "Randomized field experiments with three companies selling different products; email messages were tailored with details such as recipients\u2019 names.", "sample_context": "The experiments sent messages to millions of individuals. The abstract reports detailed results for a main experiment and replication across different advertiser objectives; it does not give a single pooled sample size.", "findings": "In the main experiment, adding the recipient\u2019s name to the subject line raised the open probability from 9.05% to 10.80%, increased sales leads from 0.39% to 0.51%, and reduced unsubscribes from 1.2% to 1.0%. Similar experiments at other firms found benefits across acquisition and retention objectives.", "limitations": "Effects are from specific companies, messages, audiences and campaign conditions. The main treatment is name insertion, not deep behavioral personalization. Email measurement and privacy practices have changed since these campaigns; the percentages should not be used as current benchmarks.", "founder_use": "A strong example of testing a narrowly defined personalization change with downstream outcomes. For a current campaign, randomize the treatment and measure outcomes that matter beyond opens.", "evidence_basis": "Publisher and Stanford GSB abstract; detailed full text was not available in the retrieved pages. The summary is restricted to the reported abstract results.", "source_ids": [ "01a0fb33-4932-724d-ab00-1c08c2a85563", "01a0fb32-066b-7438-8dd7-767c90574436" ], "corrections": [], "plain_english_summary": "In the main experiment, adding the recipient\u2019s name to the subject line raised the open probability from 9.05% to 10.80%, increased sales leads from 0.39% to 0.51%, and reduced unsubscribes from 1.2% to 1.0%. For your marketing: This is a strong example of testing a narrowly defined personalization change with downstream outcomes.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "paid-search-ebay-field-experiment", "title": "Consumer Heterogeneity and Paid Search Effectiveness: A Large-Scale Field Experiment", "category": "Paid media and measurement", "study_type": "Large-scale randomized geographic field experiment", "citation": "Blake, T., Nosko, C., & Tadelis, S. (2015). Econometrica, 83(1), 155\u2013174.", "authors": [ "Thomas Blake", "Chris Nosko", "Steven Tadelis" ], "year": 2015, "journal": "Econometrica", "doi": "10.3982/ECTA12423", "doi_url": "https://doi.org/10.3982/ECTA12423", "primary_url": "https://onlinelibrary.wiley.com/doi/abs/10.3982/ECTA12423", "accessible_url": "https://faculty.haas.berkeley.edu/stadelis/BNT_ECMA_rev.pdf", "access_label": "Publisher record and author-hosted paper", "access_class": "open-full-text", "research_question": "What is the causal short-run effect of paid search advertising on eBay, and how does it vary across consumers?", "design": "A large-scale field experiment varied paid-search advertising across geographic markets to estimate causal responses and compare users with different prior familiarity and purchase activity.", "sample_context": "eBay users and search activity in the markets included in the experiment. The findings concern one large, established online marketplace and the specific campaigns and time horizon studied.", "findings": "The authors report little measurable short-run benefit from brand-keyword ads in this setting. Non-brand ads had positive responses among some newer and infrequent users, while many ad-attributed actions came from customers whose behavior was not changed by advertising; estimated average returns were negative under the studied conditions.", "limitations": "One large company with strong brand recognition, specific paid-search campaigns, and short-run outcomes. The results do not imply that all paid search is ineffective, particularly for less familiar products or different auction and conversion conditions.", "founder_use": "Shows why platform-attributed conversions can overstate incrementality and why brand and non-brand traffic, user familiarity and holdout design should be analyzed separately.", "evidence_basis": "Peer-reviewed article metadata and author-hosted manuscript; findings summarized from the paper abstract and manuscript passages.", "source_ids": [ "01a0fb31-0759-7640-b71c-125b3fb2cf3d", "01a0fb33-07b6-7340-97ff-b0c0cbbfe31e", "01a0fb31-d8e1-7470-a1ac-2c1aa49fb8a9" ], "corrections": [], "plain_english_summary": "The study found little measurable short-run benefit from brand-keyword ads in this study. For your marketing: This shows why platform-attributed conversions can overstate incrementality and why brand and non-brand traffic, user familiarity and holdout design should be analyzed separately.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "referral-programs-customer-value", "title": "Referral Programs and Customer Value", "category": "Referrals and word of mouth", "study_type": "Longitudinal observational customer analysis", "citation": "Schmitt, P., Skiera, B., & Van den Bulte, C. (2011). Journal of Marketing, 75(1), 46\u201359.", "authors": [ "Philipp Schmitt", "Bernd Skiera", "Christophe Van den Bulte" ], "year": 2011, "journal": "Journal of Marketing", "doi": "10.1509/jm.75.1.46", "doi_url": "https://doi.org/10.1509/jm.75.1.46", "primary_url": "https://journals.sagepub.com/doi/abs/10.1509/jm.75.1.46", "accessible_url": "https://faculty.wharton.upenn.edu/wp-content/uploads/2012/04/Schmitt-Skiera-vandenBulte-2011-Referral-Programs-Customer-Value.pdf", "access_label": "Publisher abstract and author-hosted full paper", "access_class": "open-full-text", "research_question": "Are customers acquired through a referral program more valuable and loyal than other customers?", "design": "The authors tracked customer margins, retention and value over time and compared referred customers with nonreferred customers using observed customer and acquisition characteristics. Referral assignment was not randomized.", "sample_context": "Approximately 10,000 customers of one leading German bank followed for almost three years; customer lifetime value estimates use a six-year horizon described in the paper.", "findings": "Referred customers had higher contribution margins, though the margin difference declined over time; their retention advantage persisted. Their estimated average value was at least 16% higher than that of nonreferred customers with similar demographics and acquisition timing, but effects varied across segments.", "limitations": "Observational comparisons cannot remove all selection differences between referred and nonreferred customers. One bank, country, incentive program and financial-services context; results do not establish that referral incentives will create the same value for SaaS customers.", "founder_use": "A useful model for evaluating referral acquisition beyond raw sign-ups: compare retention, contribution margin and customer value, and inspect segment differences. Do not read the association as a universal causal referral lift.", "evidence_basis": "Peer-reviewed publisher abstract and author-hosted full paper.", "source_ids": [ "01a0fb31-cbb5-7738-8421-f51d39a03569", "01a0fb31-ee33-747c-ad8c-b7181043d255" ], "corrections": [], "plain_english_summary": "Referred customers had higher profits after variable costs, though the margin difference declined over time; their retention advantage persisted. For your marketing: This is a useful model for evaluating referral acquisition beyond raw sign-ups: compare retention, contribution margin and customer value, and inspect segment differences.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (10,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "what-makes-online-content-viral", "title": "What Makes Online Content Viral?", "category": "Content and sharing", "study_type": "Observational content analysis with follow-up experiments", "citation": "Berger, J., & Milkman, K. L. (2012). Journal of Marketing Research, 49(2), 192\u2013205.", "authors": [ "Jonah Berger", "Katherine L. Milkman" ], "year": 2012, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.10.0353", "doi_url": "https://doi.org/10.1509/jmr.10.0353", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.10.0353", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.10.0353", "access_label": "Publisher abstract; full article access may vary", "access_class": "abstract", "research_question": "How are emotion and other content characteristics associated with the sharing of online articles?", "design": "The authors analyzed New York Times articles published over a three-month period and examined whether emotion predicted virality while accounting for other content and attention factors. Experiments tested whether specific emotions causally affected transmission.", "sample_context": "Articles published and shared through nytimes.com during the study period; the outcome was online sharing/virality in the newspaper context, not SaaS conversions or product adoption.", "findings": "Positive content was more viral than negative content overall, but arousal helped explain the pattern: high-arousal emotions such as awe, anger and anxiety were associated with more sharing, while lower-arousal sadness was associated with less. Experimental results supported a causal role for activation in sharing.", "limitations": "The field data come from one news publisher and historical platform conditions. Sharing is not the same as persuasion, qualified traffic, pipeline or revenue. Publisher access in this review exposed the abstract rather than the full article.", "founder_use": "Use as a hypothesis source for testing emotional framing in content. It does not justify manufacturing outrage or predicting that any emotionally intense SaaS article will spread.", "evidence_basis": "Publisher abstract and citation metadata; full article text was not available in the retrieved publisher page.", "source_ids": [ "01a0fb33-ad1f-77a1-8c8e-edff3c28d580", "01a0fb31-0757-76bd-b645-72e5f4836780" ], "corrections": [], "plain_english_summary": "Positive content was more viral than negative content overall, but arousal helped explain the pattern: high-arousal emotions such as awe, anger and anxiety were associated with more sharing, while lower-arousal sadness was associated with less. For your marketing: Use as a hypothesis source for testing emotional framing in content.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "choice-overload-meta-analysis-2010", "title": "Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload", "category": "Choice and decision design", "study_type": "Meta-analysis", "citation": "Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Journal of Consumer Research, 37(3), 409\u2013425.", "authors": [ "Bettina Scheibehenne", "Rainer Greifeneder", "Peter M. Todd" ], "year": 2010, "journal": "Journal of Consumer Research", "doi": "10.1086/651235", "doi_url": "https://doi.org/10.1086/651235", "primary_url": "https://academic.oup.com/jcr/article-abstract/37/3/409/1827647", "accessible_url": "https://scheibehenne.com/ScheibehenneGreifenederTodd2010.pdf", "access_label": "Open author-hosted full paper; publisher article may require access", "access_class": "open-full-text", "research_question": "Does offering more options reliably make people less likely to choose or less satisfied?", "design": "A quantitative meta-analysis synthesized 63 conditions from 50 published and unpublished studies on choice-set size and choice overload.", "sample_context": "Cross-study synthesis of 63 experimental conditions from 50 published and unpublished studies, involving 5,036 participants; conditions covered varied choice tasks and products.", "findings": "The authors report a mean effect size close to zero, with substantial variation across conditions. The evidence did not support a general rule that larger assortments reliably cause overload.", "limitations": "The pooled average does not show that choice size never matters; heterogeneous tasks and contexts can produce different effects. This is a 2010 synthesis of the literature available at that time, not the last word on choice architecture.", "founder_use": "Avoid blanket advice to remove pricing plans or features just to reduce option count. Define the decision task and test whether complexity, preference uncertainty or decision goals create friction for your own users.", "evidence_basis": "Publisher bibliographic record and the first author-hosted full paper; sample, pooled result and study variation were checked in the paper text.", "source_ids": [ "01a0fb32-bda7-7308-9043-03bb34f64593", "01a0fb38-d618-740d-8e14-4cc4e596b0be" ], "corrections": [], "plain_english_summary": "The study found a mean effect size close to zero, with substantial variation across conditions. For your marketing: Avoid blanket advice to remove pricing plans or features just to reduce option count.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.9/1", "note": "Sample reported (5,036); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "choice-overload-moderators-2015", "title": "Choice Overload: A Conceptual Review and Meta-Analysis", "category": "Choice and decision design", "study_type": "Conceptual review and meta-analysis", "citation": "Chernev, A., B\u00f6ckenholt, U., & Goodman, J. (2015). Journal of Consumer Psychology, 25(2), 333\u2013358.", "authors": [ "Alexander Chernev", "Ulf B\u00f6ckenholt", "Joseph Goodman" ], "year": 2015, "journal": "Journal of Consumer Psychology", "doi": "10.1016/j.jcps.2014.08.002", "doi_url": "https://doi.org/10.1016/j.jcps.2014.08.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S1057740814000916", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S1057740814000916", "access_label": "Publisher abstract; corrigendum published in 2016", "access_class": "abstract", "research_question": "Under what conditions do larger assortments help or hinder choice?", "design": "A conceptual review and meta-analysis of 99 observations from prior studies, totaling 7,202 participants, examined moderators of choice overload.", "sample_context": "Cross-study evidence covering varied choice tasks and settings; the analysis considered choice-set complexity, task difficulty, preference uncertainty and decision goals.", "findings": "The authors identify four moderators that help explain when assortment size can have positive or negative effects: choice-set complexity, decision-task difficulty, preference uncertainty and decision goal. The work treats choice overload as conditional rather than universal.", "limitations": "Meta-analytic findings depend on the included studies and operational definitions. A corrigendum was published in 2016; consult it alongside the article. Neither paper supplies a ready-made answer for a particular SaaS pricing page.", "founder_use": "Use the moderators to form testable questions about pricing and product choice: Are plans meaningfully complex? Does the visitor know what they need? Is the decision goal clear? Validate with behavioral evidence from your own audience.", "evidence_basis": "Publisher article preview and abstract; full text was not available in the retrieved page. Corrigendum is linked from the publisher record.", "source_ids": [ "01a0fb33-77d4-713d-810e-35295c887db3" ], "corrections": [ "https://www.sciencedirect.com/science/article/pii/S1057740815000777" ], "plain_english_summary": "The useful point is four moderators that help explain when assortment size can have positive or negative effects: choice-set complexity, decision-task difficulty, preference uncertainty and decision goal. For your marketing: Use the moderators to form testable questions about pricing and product choice: Are plans meaningfully complex?", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "targeted-discount-offers-as-advertising", "title": "Do Targeted Discount Offers Serve as Advertising? Evidence from 70 Field Experiments", "category": "Pricing and product adoption", "study_type": "Seventy field experiments on targeted email offers", "citation": "Sahni, N. S., Zou, D., & Chintagunta, P. K. (2017). Management Science, 63(8). https://doi.org/10.1287/mnsc.2016.2450.", "authors": [ "Navdeep S. Sahni", "Dan Zou", "Pradeep K. Chintagunta" ], "year": 2017, "journal": "Management Science", "doi": "10.1287/mnsc.2016.2450", "doi_url": "https://doi.org/10.1287/mnsc.2016.2450", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2016.2450", "accessible_url": "https://dl.acm.org/doi/10.1287/mnsc.2016.2450", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Do targeted emailed discounts only shift price-sensitive purchases, or can they also advertise products and stimulate additional demand?", "design": "The authors analyze evidence from 70 field experiments involving emailed discount offers and measure spending during and after the promotion window.", "sample_context": "Customers of an online platform receiving targeted emailed offers; the accessible abstract excerpt does not state the total customer count.", "findings": "During the offer period, offers increased average expenditure by $3.03 (37.2%). The effect was larger among customers who had not transacted on the platform in the prior year. Spending also rose by $1.55 in the following week, and the study found cross-category effects on products not covered by an offer.", "limitations": "A specific platform and promotion setting; the outcomes cover a defined promotion window and one week afterward. The effects do not establish that discounts are profitable after subsidy costs or will behave similarly in SaaS.", "founder_use": "Measure discount-induced acquisition and spillovers separately from subsidized purchases. Include margin, timing shifts and post-promotion behavior when judging whether offers function as profitable advertising.", "evidence_basis": "Management Science abstract and bibliographic record; the 70 experiments and reported spending changes are stated in the abstract.", "source_ids": [ "01a0fb7c-4f3f-7581-a7ad-b8a26f08326e", "01a0fb7c-7b4d-74ae-babd-5b553bda50f2" ], "corrections": [], "plain_english_summary": "During the offer period, offers increased average expenditure by $3.03 (37.2%). For your marketing: Measure discount-induced acquisition and spillovers separately from subsidized purchases.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "marketing-campaigns-multichannel-buying", "title": "Can Marketing Campaigns Induce Multichannel Buying and More Profitable Customers? A Field Experiment", "category": "Acquisition and retention", "study_type": "Field experiment testing four marketing campaigns", "citation": "Montaguti, E., Neslin, S. A., & Valentini, S. (2016). Marketing Science, 35(2), 201\u2013217.", "authors": [ "Elisa Montaguti", "Scott A. Neslin", "Sara Valentini" ], "year": 2016, "journal": "Marketing Science", "doi": "10.1287/mksc.2015.0923", "doi_url": "https://doi.org/10.1287/mksc.2015.0923", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0923", "accessible_url": "https://cris.unibo.it/retrieve/e1dcb338-fa68-7715-e053-1705fe0a6cc9/_Multichannel%20Field%20Test%20Manuscript%20Final.pdf", "access_label": "Publisher record and author-hosted paper", "access_class": "open-full-text", "research_question": "Can marketing communications and incentives move customers into multichannel buying and increase their profitability?", "design": "A field experiment tests four marketing campaigns that vary the communication message and whether a financial incentive is offered.", "sample_context": "Customers of a multichannel retailer in the experiment; the sources reviewed here do not provide the sample count in the abstract excerpt.", "findings": "The experiment directly evaluates whether campaign design can cause multichannel buying and more profitable customer behavior, distinguishing communication content from financial incentives.", "limitations": "One retailer and channel environment; incentives and channel availability shape the result. Detailed estimates should be read in the paper before applying them to software acquisition or expansion.", "founder_use": "For product-led and sales-assisted motions, test whether messaging or an incentive changes adoption of a second channel or product path, and measure contribution rather than channel count alone.", "evidence_basis": "INFORMS journal record and author-hosted manuscript; the four-campaign randomized design is described in the source.", "source_ids": [ "01a0fb7c-4e8b-762a-a5b8-a01095d5ab80", "01a0fb7c-7b16-76da-a945-9474bf5a88d4" ], "corrections": [], "plain_english_summary": "The experiment tests whether campaign design can cause multichannel buying and more profitable customer behavior, distinguishing communication content from financial incentives. For your marketing: For product-led and sales-assisted motions, test whether messaging or an incentive changes adoption of a second channel or product path, and measure contribution rather than channel count alone.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "display-search-offline-advertising-firm-value", "title": "The Impact of Online Display Advertising and Paid Search Advertising Relative to Offline Advertising on Firm Performance and Firm Value", "category": "Paid media and measurement", "study_type": "Firm-level econometric analysis of advertising mix and performance", "citation": "Bayer, E., Srinivasan, S., Riedl, E. J., & Skiera, B. (2020). International Journal of Research in Marketing, 37(4), 789\u2013804.", "authors": [ "Emanuel Bayer", "Shuba Srinivasan", "Edward J. Riedl", "Bernd Skiera" ], "year": 2020, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2020.02.002", "doi_url": "https://doi.org/10.1016/j.ijresmar.2020.02.002", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0167811620300094", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0167811620300094", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How do paid search and online display advertising relate to firm performance and firm value compared with offline advertising?", "design": "The authors compare the economic effects of online display, paid search and offline advertising using firm-level performance and valuation outcomes.", "sample_context": "Firms with observed online and offline advertising and financial outcomes; the abstract reviewed does not provide the sample size or specific industries.", "findings": "Paid search had a more positive effect on sales than offline advertising, while display advertising had a relatively more positive effect on Tobin's q than offline advertising, consistent with different short- and long-run economic roles.", "limitations": "Firm-level estimates from the study's period and sample; they do not establish causal effects for a particular startup's campaign or current ad market. Sales and firm value are distinct outcomes.", "founder_use": "Separate near-term sales objectives from longer-horizon brand or firm-value goals when comparing channels. Treat the study as context for measurement choices, not a universal channel ranking.", "evidence_basis": "International Journal of Research in Marketing publisher abstract and DOI metadata.", "source_ids": [ "01a0fb7c-511f-706e-92bb-6acec685c5be" ], "corrections": [], "plain_english_summary": "Paid search had a more positive effect on sales than offline advertising, while display advertising had a relatively more positive effect on Tobin's q than offline advertising, consistent with different short- and long-run economic roles. For your marketing: Separate near-term sales objectives from longer-horizon brand or firm-value goals when comparing channels.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "cross-category-demand-price-promotions", "title": "Cross-Category Demand Effects of Price Promotions", "category": "Pricing and product adoption", "study_type": "Store-level scanner-data analysis of category demand", "citation": "Leeflang, P. S. H., & Parre\u00f1o-Selva, J. (2012). Journal of the Academy of Marketing Science, 40(4), 572\u2013586.", "authors": [ "Peter S. H. Leeflang", "Josefa Parre\u00f1o-Selva" ], "year": 2012, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-010-0244-z", "doi_url": "https://doi.org/10.1007/s11747-010-0244-z", "primary_url": "https://link.springer.com/article/10.1007/s11747-010-0244-z", "accessible_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC4964893/", "access_label": "Open full text and publisher record", "access_class": "open-full-text", "research_question": "Do price promotions in one category affect revenues in other product categories, and what conditions moderate those spillovers?", "design": "The authors develop a category-demand framework with interdependencies and analyze daily store-level scanner data, testing promotion intensity, category characteristics and spatial distance between categories.", "sample_context": "Daily store-level retail scanner data across multiple categories; the accessible abstract reports category-level patterns rather than a single consumer sample.", "findings": "About half of the promotions expanded own-category revenue, particularly deeper supported discounts. A promotion had a 61% probability of affecting at least one other category, usually no more than two; evidence also linked cross-effects to shelf proximity.", "limitations": "Retail-store categories and physical shelf locations are specific to the study. Cross-category effects cannot be presumed for software pricing or digital product bundles.", "founder_use": "When promoting one tier or feature, examine whether demand shifts across the rest of the portfolio. For software, test the analogous upgrade, downgrade and add-on outcomes rather than importing retail estimates.", "evidence_basis": "Open article in PubMed Central and Springer publisher record; abstract reports the scanner-data method and headline effects.", "source_ids": [ "01a0fb7c-7b07-7008-a8b2-e42c5041d505" ], "corrections": [], "plain_english_summary": "About half of the promotions expanded own-category revenue, particularly deeper supported discounts. For your marketing: When promoting one tier or feature, examine whether demand shifts across the rest of the portfolio.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "google-search-advertising-customer-lifetime-value", "title": "Measuring the Lifetime Value of Customers Acquired from Google Search Advertising", "category": "Search and content discovery", "study_type": "Customer-level longitudinal lifetime-value model", "citation": "Chan, T. Y., Wu, C., & Xie, Y. (2011). Marketing Science, 30(5), 837\u2013850.", "authors": [ "Tat Y. Chan", "Chunhua Wu", "Ying Xie" ], "year": 2011, "journal": "Marketing Science", "doi": "10.1287/mksc.1110.0658", "doi_url": "https://doi.org/10.1287/mksc.1110.0658", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1110.0658", "accessible_url": "https://chunhuawu.com/research/clv/", "access_label": "Publisher abstract and author-hosted article page", "access_class": "abstract", "research_question": "How should firms estimate the long-term value of customers acquired through paid search, including purchases that occur offline?", "design": "The authors merge web-traffic and sales data from a small U.S. firm into a customer-level panel tracking repeated online and offline purchases and Google-search referrals. They jointly model customer lifetime, transaction rate and gross margin.", "sample_context": "Customers of one small U.S. firm with multichannel purchases; the abstract does not report customer count.", "findings": "Customers acquired through Google search advertising had higher transaction rates than customers from other channels in this dataset. Including future purchases and offline spillovers produced substantially higher customer values than the conventional method used for comparison.", "limitations": "A single small firm and its channel mix; results do not establish that paid search always acquires higher-value customers. The study's period and search-ad environment differ from today's platforms.", "founder_use": "Track customer lifetime across channels when estimating paid-search value. Include repeat purchases and offline or sales-assisted spillovers instead of stopping at a platform-attributed conversion.", "evidence_basis": "INFORMS publisher record and first-author-hosted abstract; data source, model and findings are described on the article page.", "source_ids": [ "01a0fb80-c296-750a-aa71-abb1b23559e6", "01a0fb80-f288-77af-afaa-7638d670a0cd" ], "corrections": [], "plain_english_summary": "Customers acquired through Google search advertising had higher transaction rates than customers from other channels in this study. For your marketing: Track customer lifetime across channels when estimating paid-search value.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "tariff-structure-retention-usage", "title": "The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services", "category": "Pricing and product adoption", "study_type": "Pricing field experiment and utility-based retention model", "citation": "Iyengar, R., Jedidi, K., Essegaier, S., & Danaher, P. J. (2011). Marketing Science, 30(5), 820\u2013836.", "authors": [ "Raghuram Iyengar", "Kamel Jedidi", "Skander Essegaier", "Peter J. Danaher" ], "year": 2011, "journal": "Marketing Science", "doi": "10.1287/mksc.1110.0655", "doi_url": "https://doi.org/10.1287/mksc.1110.0655", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1110.0655", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1110.0655", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How do pay-per-use and two-part-tariff pricing affect service retention, usage and profit?", "design": "A utility-based model is estimated with data from a pricing field experiment for a new telecommunications access service.", "sample_context": "Customers of one new telecommunications service in a market experiment; the abstract reports model-based average effects across the experimental tariff conditions.", "findings": "Compared with pay-per-use pricing, the two-part tariff reduced annual retention by an average 10.5% and yearly usage by 38.7%, after controlling for income effects. Despite these declines, the two-part tariff remained profit-maximizing in the studied setting. Ignoring the tariff-structure effect reduced modeled firm profit by 11%.", "limitations": "A single telecommunications service and historical market experiment. The profitability result depends on the study's demand, cost and pricing assumptions and should not be treated as a SaaS pricing benchmark.", "founder_use": "Evaluate the behavioral effects of access fees separately from per-use prices. A plan can reduce usage and retention yet still improve profit, so test the full customer and margin outcomes.", "evidence_basis": "INFORMS publisher abstract; the experiment setting, tariff comparison and reported percentages are stated there.", "source_ids": [ "01a0fb80-c2c9-76cf-98b7-59e355636771" ], "corrections": [], "plain_english_summary": "Compared with pay-per-use pricing, the two-part tariff reduced annual retention by an average 10.5% and yearly usage by 38.7%, after controlling for income effects. For your marketing: Evaluate the behavioral effects of access fees separately from per-use prices.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "overt-and-silent-customer-churn", "title": "Some Customers Would Rather Leave Without Saying Goodbye", "category": "Acquisition and retention", "study_type": "Hidden Markov model applied to two empirical settings", "citation": "Ascarza, E., Netzer, O., & Hardie, B. G. S. (2018). Marketing Science, 37(1), 54\u201377.", "authors": [ "Eva Ascarza", "Oded Netzer", "Bruce G. S. Hardie" ], "year": 2018, "journal": "Marketing Science", "doi": "10.1287/mksc.2017.1057", "doi_url": "https://doi.org/10.1287/mksc.2017.1057", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2017.1057", "accessible_url": "https://www.hbs.edu/ris/Publication%20Files/ascarza_netzer_hardie_mktsci_18_7d5c6677-06af-458f-afdb-b15648b7b766.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "How should firms distinguish customers who formally cancel from those who silently disengage?", "design": "The authors develop a hidden Markov model for overt and silent churn and apply it to a daily-deal website and a performing-arts organization.", "sample_context": "Two hybrid customer-relationship settings where customers can formally terminate or simply stop interacting with the firm.", "findings": "Overt churners were often more active before leaving, while many silent churners disengaged early and rarely canceled formally. The two churn groups responded differently to communications, so one retention strategy may not suit both.", "limitations": "The two applications are specific to their services and datasets. The model's churn-state assumptions and communication responses should be validated for a SaaS product's billing and activity data.", "founder_use": "Separate cancellation from quiet nonuse when measuring churn. Build retention reporting that includes product inactivity and communication response rather than treating account status as the only signal.", "evidence_basis": "Marketing Science abstract and author-hosted paper; both applications and the distinction between overt and silent churn are reported in the paper.", "source_ids": [ "01a0fb80-c2f6-7448-9bcb-3b4f8d745baf", "01a0fb80-f206-77d9-9b24-3614465f7c22" ], "corrections": [], "plain_english_summary": "Overt churners were often more active before leaving, while many silent churners disengaged early and rarely canceled formally. For your marketing: Separate cancellation from quiet nonuse when measuring churn.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "peer-effects-retention-socially-connected-business", "title": "Exploring Peer Effects Associated with User Retention in a Socially Connected Business", "category": "Acquisition and retention", "study_type": "Structural model using exogenous churn data from a field setting", "citation": "Chen, Y., & Mehta, N. (2026). Marketing Science, 45(2), 449\u2013471.", "authors": [ "Yijun Chen", "Nitin Mehta" ], "year": 2026, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0391", "doi_url": "https://doi.org/10.1287/mksc.2023.0391", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0391", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0391", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How does one user's churn affect usage and retention among connected peers, and whom should firms target to prevent network cascades?", "design": "The authors use data from an upscale gym, including exogenous customer churn, and estimate a structural model of plan choice, usage and dynamic peer effects.", "sample_context": "Members of one upscale gym with observed social-network ties, plan choices and usage.", "findings": "Churn by a high-centrality member caused a stronger negative cascade in peers' usage and subscriptions than churn by a low- or medium-centrality member. Short-term targeting may prioritize lower-centrality churners, while longer-term retention can favor high-centrality users because of network spillovers.", "limitations": "One gym and its observed social network; peer effects may differ in software teams, buyer organizations and products with less visible usage. The targeting tradeoff depends on campaign and relationship costs.", "founder_use": "Where product use is collaborative, consider whether a departing or inactive central user affects teammates. Validate network effects and choose retention targets using both direct and downstream value.", "evidence_basis": "Marketing Science publisher abstract and issue metadata; setting, model and centrality results are reported by the journal.", "source_ids": [ "01a0fb80-c2e1-77d9-94f1-a4587e739b25", "01a0fb80-f208-720d-b2e0-0c2f3400a2ad" ], "corrections": [], "plain_english_summary": "Churn by a high-centrality member caused a stronger negative cascade in peers' usage and subscriptions than churn by a low- or medium-centrality member. For your marketing: Where product use is collaborative, consider whether a departing or inactive central user affects teammates.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "retention-futility-high-risk-targeting", "title": "Retention Futility: Targeting High-Risk Customers Might Be Ineffective", "category": "Acquisition and retention", "study_type": "Two field experiments combined with machine-learning targeting methods", "citation": "Ascarza, E. (2018). Journal of Marketing Research, 55(1), 80\u201398.", "authors": [ "Eva Ascarza" ], "year": 2018, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.16.0163", "doi_url": "https://doi.org/10.1509/jmr.16.0163", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.16.0163", "accessible_url": "https://www.hbs.edu/ris/Publication%20Files/ascarza_jmr_18_783d54d4-e548-41ed-b1d7-8a180f1ae85a.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "Are customers most likely to churn also the best customers to target with a retention intervention?", "design": "The author combines two field experiments with machine-learning techniques to compare targeting by predicted churn risk with targeting by expected response to retention efforts.", "sample_context": "Two field experiments involving customer retention interventions; the publisher abstract does not summarize sample sizes or industries.", "findings": "Customers with the highest predicted churn risk were not necessarily the best targets. The response-based targeting approach was significantly more effective than standard targeting of the highest-risk customers.", "limitations": "Two specific field experiments and intervention settings; targeting performance depends on treatment response and available data. High churn risk and high persuadability are different quantities.", "founder_use": "Use treatment response or expected incremental profit to select retention audiences, rather than ranking only by churn propensity. Hold out customers so the intervention's causal effect can be estimated.", "evidence_basis": "Journal of Marketing Research abstract and author-hosted paper; experiment count and targeting comparison are reported by the journal.", "source_ids": [ "01a0fb82-91ad-772b-9955-d5d239841e6e", "01a0fb82-c492-707f-9b97-f42930ffc70b" ], "corrections": [], "plain_english_summary": "Customers with the highest predicted churn risk were not necessarily the best targets. For your marketing: Use treatment response or expected incremental profit to select retention audiences, rather than ranking only by churn propensity.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "b2b-content-timing-customer-journey", "title": "Digital Content Marketing on Social Media Along the B2B Customer Journey: The Effect of Timely Content Delivery on Customer Engagement", "category": "Content and sharing", "study_type": "Experimental study of B2B content relevance across journey stages", "citation": "Salonen, A., Mero, J., Munnukka, J., Zimmer, M., & Karjaluoto, H. (2024). Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2024.02.002.", "authors": [ "Anna Salonen", "Joel Mero", "Juha Munnukka", "Marcus Zimmer", "Heikki Karjaluoto" ], "year": 2024, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2024.02.002", "doi_url": "https://doi.org/10.1016/j.indmarman.2024.02.002", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850124000221", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850124000221", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How does the relevance of firm-generated social content to a buyer's current journey stage affect B2B engagement?", "design": "An experimental approach tests the relationship between journey-stage relevance of firm-generated social-media content and customer engagement.", "sample_context": "B2B content and customer-journey scenarios; the abstract does not disclose sample size or full recruitment details.", "findings": "Content judged relevant to a particular customer-journey stage increased engagement with both the selling firm and its content. The study found no universally correct sequence for presenting content because preferences differed across individuals.", "limitations": "The abstract does not specify the sample or all experimental manipulations. Engagement is not equivalent to pipeline or revenue, and the optimal content sequence may vary by market and sales cycle.", "founder_use": "Map content to the reader's current task and test different sequences rather than enforcing one universal funnel. Measure meaningful downstream B2B outcomes along with engagement.", "evidence_basis": "Industrial Marketing Management publisher abstract and article metadata; central experiment conclusion is stated in the abstract.", "source_ids": [ "01a0fb82-9166-75be-88c5-9352026d8052", "01a0fb82-c4ed-7662-915b-5c49f7a371fa" ], "corrections": [], "plain_english_summary": "Content judged relevant to a particular customer-journey stage increased engagement with both the selling firm and its content. For your marketing: Map content to the reader's current task and test different sequences rather than enforcing one universal funnel.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "customer-referral-value-lifetime-and-referral-behavior", "title": "Driving Profitability by Encouraging Customer Referrals: Who, When, and How", "category": "Acquisition and retention", "study_type": "Customer referral value measurement and targeting framework", "citation": "Kumar, V., Petersen, J. A., & Leone, R. P. (2010). Journal of Marketing, 74(5), 1\u201317.", "authors": [ "V. Kumar", "J. Andrew Petersen", "Robert P. Leone" ], "year": 2010, "journal": "Journal of Marketing", "doi": "10.1509/jmkg.74.5.001", "doi_url": "https://doi.org/10.1509/jmkg.74.5.001", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkg.74.5.001", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkg.74.5.001", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How can firms measure customer referral value and use it alongside lifetime value to target referral campaigns?", "design": "The authors develop a method for computing customer referral value from past referral behavior, analyze its behavioral drivers and propose targeting based on customer lifetime value and referral value.", "sample_context": "Customer and referral records used to derive CLV and customer referral value; the accessible abstract does not identify the firm or sample size.", "findings": "The research argues that maximizing referral-program profitability requires managing both customer lifetime value and customer referral value, and that referral behavior can guide targeting of profitable prospects.", "limitations": "The model and targeting evidence depend on available referral histories and a particular business context. Referral volume alone does not reveal the marginal profitability of a campaign.", "founder_use": "Track who refers, how often, and the value of referred customers. Combine referral propensity with customer economics when selecting advocates for a program.", "evidence_basis": "Journal of Marketing publisher abstract and citation metadata; profile remains at abstract level.", "source_ids": [ "01a0fb82-919d-714a-8203-3c16e246fc17", "01a0fb82-c478-7411-b450-4f4e2567db27" ], "corrections": [], "plain_english_summary": "The useful point is that maximizing referral-program profitability requires managing both long-term customer value and customer referral value, and that referral behavior can guide targeting of profitable prospects. For your marketing: Track who refers, how often, and the value of referred customers.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "customer-acquisition-promotions-customer-asset-value", "title": "Customer Acquisition Promotions and Customer Asset Value", "category": "Pricing and product adoption", "study_type": "Conceptual model and customer-level analyses in two industries", "citation": "Lewis, M. (2006). Journal of Marketing Research, 43(2), 195\u2013203.", "authors": [ "Michael Lewis" ], "year": 2006, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.43.2.195", "doi_url": "https://doi.org/10.1509/jmkr.43.2.195", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkr.43.2.195", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkr.43.2.195", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How do acquisition discounts affect the mix and long-term value of customers a firm acquires?", "design": "A conceptual model of customer uncertainty is paired with customer-level empirical analyses from a newspaper and an online grocer.", "sample_context": "Customer data from one newspaper and one online grocery retailer; the abstract does not state sample sizes.", "findings": "In both datasets, deeper acquisition discounts were associated with lower repeat-buying rates and lower customer asset value. The abstract reports that customers acquired with a 35% discount had about half the long-term value of customers acquired without a promotion.", "limitations": "Two businesses in newspaper and online grocery markets; the value gap is not a SaaS acquisition benchmark. The abstract describes empirical relationships and does not claim randomized discount assignment.", "founder_use": "Compare the long-term value of discounted and full-price cohorts, accounting for selection and acquisition cost. A lower initial conversion cost can bring customers with weaker repeat economics.", "evidence_basis": "Journal of Marketing Research publisher abstract; industry contexts and headline relationship are reported there.", "source_ids": [ "01a0fb80-f24f-771e-a766-98f9d840b2cc" ], "corrections": [], "plain_english_summary": "In both datasets, deeper acquisition discounts were associated with lower repeat-buying rates and lower customer asset value. For your marketing: Compare the long-term value of discounted and full-price cohorts, accounting for selection and acquisition cost.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "customer-referral-social-capital-mechanisms", "title": "How Customer Referral Programs Turn Social Capital into Economic Capital", "category": "Acquisition and retention", "study_type": "Customer-level observational analysis of a referral program", "citation": "Van den Bulte, C., Bayer, E., Skiera, B., & Schmitt, P. (2018). Journal of Marketing Research, 55(1), 132\u2013146.", "authors": [ "Christophe Van den Bulte", "Emanuel Bayer", "Bernd Skiera", "Philipp Schmitt" ], "year": 2018, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.14.0653", "doi_url": "https://doi.org/10.1509/jmr.14.0653", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0653", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0653", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Why can referred customers have higher value, and how do referrer characteristics relate to referred customers' margins and retention?", "design": "The authors study customer-referrer dyads in a referral program and test mechanisms of better customer matching and social enrichment using contribution margin and churn outcomes.", "sample_context": "Customers and referrals in one firm's customer referral program; the publisher abstract does not state a sample size.", "findings": "Referrer and referral pairs shared unobserved contribution-margin characteristics. More experienced referrers brought higher-margin referrals, though this association weakened over the referral's lifetime. Referrals churned less only while their referrer remained a customer.", "limitations": "One firm's program and customer base; the paper's mechanism estimates are not automatically causal outside that context. The abstract's targeting recommendation reflects that firm's data and program.", "founder_use": "Measure both referrer and referred-customer behavior. Referral quality may reflect who refers and the continuing relationship between the pair, not only the acquisition source label.", "evidence_basis": "Journal of Marketing Research abstract; all findings and the dyadic mechanisms are reported there.", "source_ids": [ "01a0fb7e-9f87-761c-97a1-1c1d06c246f7" ], "corrections": [], "plain_english_summary": "Referrer and referral pairs shared unobserved contribution-margin characteristics. For your marketing: Measure both referrer and referred-customer behavior.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "prosocial-referral-incentives-reputation-costs", "title": "Why Prosocial Referral Incentives Work: The Interplay of Reputational Benefits and Action Costs", "category": "Acquisition and retention", "study_type": "Two field experiments and one fully incentivized laboratory experiment", "citation": "Gershon, R., Cryder, C., & John, L. K. (2020). Journal of Marketing Research, 57(1), 156\u2013172.", "authors": [ "Rachel Gershon", "Cynthia Cryder", "Leslie K. John" ], "year": 2020, "journal": "Journal of Marketing Research", "doi": "10.1177/0022243719888440", "doi_url": "https://doi.org/10.1177/0022243719888440", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022243719888440", "accessible_url": "https://journals.sagepub.com/doi/10.1177/0022243719888440", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "When do referral incentives that benefit the recipient generate more referrals than incentives paid to the referrer?", "design": "Two field experiments and a fully incentivized laboratory experiment compare prosocial, recipient-benefiting incentives with alternative reward structures and test reputational benefits and action costs.", "sample_context": "Participants in two referral-program field settings and an incentivized lab experiment; the publisher abstract reviewed does not give sample sizes.", "findings": "Across the experiments, recipient-benefiting prosocial referral incentives recruited more new customers than comparison incentives in the studied contexts.", "limitations": "Reward effectiveness depends on the product, action cost and social meaning of the referral. Abstract-level results do not establish profitability after reward expense or generalize every program to a prosocial reward.", "founder_use": "Test whether reducing the recipient's cost or increasing their benefit works better than paying the referrer alone. Measure completed, retained customers and net contribution.", "evidence_basis": "Journal of Marketing Research abstract and bibliographic record; experiment count and headline comparison are reported in the abstract.", "source_ids": [ "01a0fb7e-9f40-7384-b1eb-00262bc6d435" ], "corrections": [], "plain_english_summary": "Across the experiments, recipient-benefiting prosocial referral incentives recruited more new customers than comparison incentives in the studied contexts. For your marketing: Test whether reducing the recipient's cost or increasing their benefit works better than paying the referrer alone.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "subscription-programs-customer-purchases", "title": "The Impact of Subscription Programs on Customer Purchases", "category": "Pricing and product adoption", "study_type": "Quasi-experimental customer-level analysis with heterogeneous treatment effects", "citation": "Iyengar, R., Park, Y.-H., & Yu, Q. (2022). Journal of Marketing Research, 59(6), 1101\u20131117.", "authors": [ "Raghuram Iyengar", "Young-Hoon Park", "Qi Yu" ], "year": 2022, "journal": "Journal of Marketing Research", "doi": "10.1177/00222437221080163", "doi_url": "https://doi.org/10.1177/00222437221080163", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437221080163", "accessible_url": "https://ink.library.smu.edu.sg/lkcsb_research/7020/", "access_label": "Publisher abstract and institutional record", "access_class": "abstract", "research_question": "How does paying an upfront fee to join a subscription program affect members' subsequent purchases?", "design": "The authors combine a difference-in-differences approach with generalized random forests to compare subscription members with similar nonmembers and estimate heterogeneous effects.", "sample_context": "Members and nonmembers of a retailer or marketplace subscription program; the abstract does not identify the firm or provide sample size.", "findings": "Subscription increased customer purchases, with economically meaningful and persistent effects that varied across customers. The authors attribute about one-third of the purchase effect to program benefits and the remaining two-thirds to a noneconomic effect consistent with sunk-cost behavior.", "limitations": "The evidence concerns a retailer/platform subscription program and uses a quasi-experimental design. The estimated mechanism and purchase effect may differ for SaaS subscriptions with different fees, benefits and usage patterns.", "founder_use": "When studying a paid plan or membership, distinguish benefit-driven usage from behavioral effects of the upfront commitment. Segment responses and evaluate retention and margin alongside purchase volume.", "evidence_basis": "Journal of Marketing Research abstract and institutional record; method and headline decomposition are stated in the abstract.", "source_ids": [ "01a0fb7e-9f67-7201-97bb-346f11d816d8" ], "corrections": [], "plain_english_summary": "Subscription increased customer purchases, with economically meaningful and persistent effects that varied across customers. For your marketing: When studying a paid plan or membership, distinguish benefit-driven usage from behavioral effects of the upfront commitment.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.6/2", "note": "A quasi-experimental design can support causal claims if its assumptions hold." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Nonrandom comparison; causal interpretation depends on the design assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "proactive-plan-recommendations-churn-risk", "title": "The Perils of Proactive Churn Prevention Using Plan Recommendations: Evidence from a Field Experiment", "category": "Acquisition and retention", "study_type": "Large-scale randomized field experiment", "citation": "Ascarza, E., Iyengar, R., & Schleicher, M. (2016). Journal of Marketing Research, 53(1), 66\u201382.", "authors": [ "Eva Ascarza", "Raghuram Iyengar", "Michael Schleicher" ], "year": 2016, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.13.0483", "doi_url": "https://doi.org/10.1509/jmr.13.0483", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.13.0483", "accessible_url": "https://www.hbs.edu/ris/Publication%20Files/ascarza_iyengar_schleicher_jmr_16_5af73070-c916-49ce-8be6-bfc78320823e.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "Can proactively recommending a lower-cost or better-fitting plan reduce churn, or can the recommendation make customers more likely to leave?", "design": "A large-scale field experiment randomly offered some service customers plan recommendations and compared churn with a control group.", "sample_context": "Customers of a service provider with multiple usage plans; the paper examines how responses differ by prior overage, usage variability and usage trend.", "findings": "Churn over the following three months was 10% in the recommendation group versus 6% in the control group. Effects varied with pre-campaign usage patterns; customers with lower overage, lower variability and positive trends responded differently.", "limitations": "A specific service plan and customer base; a proactive plan recommendation can have different meaning for SaaS users. The aggregate increase masks heterogeneity and is not a reason to avoid all plan guidance.", "founder_use": "Before prompting customers to downgrade or switch plans, run a controlled test and examine effects by usage pattern. A recommendation that improves price fit can still increase churn through salience or perceived value.", "evidence_basis": "Journal of Marketing Research abstract and author-hosted paper; the field experiment and 6% versus 10% churn figures are reported in the manuscript.", "source_ids": [ "01a0fb7e-68b8-7789-849c-752823db41bd", "01a0fb7e-9f62-77df-a838-85f223179a93" ], "corrections": [], "plain_english_summary": "Churn over the following three months was 10% in the recommendation group versus 6% in the control group. For your marketing: Before prompting customers to downgrade or switch plans, run a controlled test and examine effects by usage pattern.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "pricing-hassle-money-or-effort", "title": "Paying with Money or Effort: Pricing When Customers Anticipate Hassle", "category": "Pricing and product adoption", "study_type": "Field experiment and pricing model", "citation": "Lambrecht, A., & Tucker, C. (2012). Journal of Marketing Research, 49(1), 66\u201382.", "authors": [ "Anja Lambrecht", "Catherine Tucker" ], "year": 2012, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.09.0530", "doi_url": "https://doi.org/10.1509/jmr.09.0530", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.09.0530", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.09.0530", "access_label": "Publisher summary and abstract", "access_class": "abstract", "research_question": "How should firms price when customers anticipate hassle or effort that varies over time?", "design": "A field experiment compares pricing contracts that align payment levels with periods in which customers anticipate different hassle costs.", "sample_context": "Customers in a service-pricing field experiment; the publisher summary reviewed does not provide the sample size or full industry details.", "findings": "The field experiment provides evidence that customers prefer contracts that match periods of lower benefits caused by hassle costs with lower payments.", "limitations": "The study's service and hassle context are specific. Its abstract does not provide effect sizes, and software usage effort may differ from the costs studied.", "founder_use": "Consider whether customers' willingness to pay changes when setup, migration or usage requires effort. Test packaging and timing against observed adoption and retention rather than assuming a fixed price is experienced uniformly.", "evidence_basis": "Journal of Marketing Research publisher summary and DOI metadata; abstract-level profile.", "source_ids": [ "01a0fb7e-9f96-7058-aee8-881828bd3ad5" ], "corrections": [], "plain_english_summary": "The field experiment provides evidence that customers prefer contracts that match periods of lower benefits caused by hassle costs with lower payments. For your marketing: Consider whether customers' willingness to pay changes when setup, migration or usage requires effort.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "b2b-social-media-employee-generated-content", "title": "Effectiveness of B2B Social Media Marketing: The Effect of Message Source and Message Content on Social Media Engagement", "category": "Content and sharing", "study_type": "Four experiments on B2B social media messages", "citation": "Balaji, M. S., Behl, A., Jain, K., Baabdullah, A. M., Giannakis, M., Shankar, A., & Dwivedi, Y. K. (2023). Industrial Marketing Management, 113, 111\u2013125.", "authors": [ "M. S. Balaji", "Abhishek Behl", "Kokil Jain", "Abdullah M. Baabdullah", "Mihalis Giannakis", "Amit Shankar", "Yogesh K. Dwivedi" ], "year": 2023, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2023.06.011", "doi_url": "https://doi.org/10.1016/j.indmarman.2023.06.011", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850123001190", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850123001190", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How do the source and content of a B2B social media post affect audience engagement?", "design": "Four experiments test firm-generated versus employee-generated messages and content features such as emojis and objective information.", "sample_context": "Participants across four experiments involving B2B social-media messages; the accessible abstract does not report combined sample size.", "findings": "Employee-generated content produced more social media engagement intentions and behaviors than firm-generated content. Content-based trust and engagement-based trust were identified as mechanisms; emojis had a greater effect in employee messages than in firm messages.", "limitations": "Engagement is not the same as qualified demand or sales, and experimental message settings may not reproduce every platform or company context. The abstract does not report effect sizes.", "founder_use": "For technical B2B audiences, test employee-authored perspectives against corporate-account posts. Tie engagement experiments to meaningful follow-on outcomes such as visits, signups or conversations.", "evidence_basis": "Industrial Marketing Management publisher abstract and DOI record; four experiments and central outcomes are reported directly.", "source_ids": [ "01a0fb7e-9f98-7363-aa92-f28f05a669e4" ], "corrections": [], "plain_english_summary": "Employee-generated content produced more social media engagement intentions and behaviors than firm-generated content. For your marketing: For technical B2B audiences, test employee-authored perspectives against corporate-account posts.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "facebook-organic-link-placement-experiment", "title": "Social Media Marketing for Businesses: Organic Promotions of Web-Links on Facebook", "category": "Content and sharing", "study_type": "Facebook post-link placement experiment", "citation": "Chawla, Y., & Chodak, G. (2021). Journal of Business Research, 135, 49\u201365.", "authors": [ "Yash Chawla", "Grzegorz Chodak" ], "year": 2021, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2021.05.055", "doi_url": "https://doi.org/10.1016/j.jbusres.2021.05.055", "primary_url": "https://www.sciencedirect.com/science/article/pii/S014829632100432X", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S014829632100432X", "access_label": "Publisher abstract", "access_class": "abstract", "research_question": "How does the placement of a web link in an organic Facebook post affect marketing outcomes?", "design": "The authors designed and conducted a Facebook experiment comparing web-link placement in the post caption with placement in the comments and analyzed post and sales outcomes.", "sample_context": "Facebook organic posts and linked content in the study's business setting; the accessible abstract does not provide a full sample count.", "findings": "The experiment reports that placing the web link in the comments rather than the caption was more lucrative in the studied campaign.", "limitations": "A platform-specific experiment from 2021; Facebook distribution and link behavior change over time. The result should not be assumed to hold across social networks, post types or technical-founder audiences.", "founder_use": "A concrete example of testing small post-format decisions against business outcomes. Re-run the comparison on your current platform and audience before adopting it.", "evidence_basis": "Journal of Business Research abstract and publisher record; the profile uses only the experiment and link-placement result visible in the abstract.", "source_ids": [ "01a0fb7e-686b-74ff-921c-b3c30df57716", "01a0fb7e-9fca-755d-9935-5e9a44992f97" ], "corrections": [], "plain_english_summary": "The experiment reports that placing the web link in the comments rather than the caption was more lucrative in the studied campaign. For your marketing: This is a concrete example of testing small post-format decisions against business outcomes.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "influencer-marketing-effectiveness-meta-analysis", "title": "Predictors of Social Media Influencer Marketing Effectiveness: A Comprehensive Literature Review and Meta-Analysis", "category": "Influencer and creator marketing", "study_type": "Systematic literature review and meta-analysis", "citation": "Sp\u00f6rl-Wang, K., Krause, F., & Henkel, S. (2025). Journal of Business Research, 186, 114991.", "authors": [ "Katja Sp\u00f6rl-Wang", "Franziska Krause", "Sven Henkel" ], "year": 2025, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2024.114991", "doi_url": "https://doi.org/10.1016/j.jbusres.2024.114991", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0148296324004958", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296324004958", "access_label": "Publisher abstract and article highlights", "access_class": "abstract", "research_question": "Which factors predict the effectiveness of social media influencer marketing, and how can conflicting prior findings be reconciled?", "design": "The authors conduct a comprehensive literature review and meta-analysis of 93 papers on predictors of influencer-marketing effectiveness.", "sample_context": "93 prior papers spanning influencer marketing studies; the accessible highlights do not specify the number of underlying effect sizes or participants.", "findings": "The synthesis organizes predictors in a holistic framework and evaluates why earlier studies have produced conflicting conclusions about effectiveness.", "limitations": "The meta-analysis reflects its included studies, platforms, influencer types and outcome measures. It does not supply one universal influencer benchmark for B2B SaaS.", "founder_use": "Use the reviewed predictors to structure creator-selection and campaign hypotheses. Separate engagement from lead quality and revenue, and check which underlying contexts match your audience.", "evidence_basis": "Journal of Business Research publisher highlights and bibliographic record; the paper count and meta-analytic scope are stated by the publisher.", "source_ids": [ "01a0fb7e-686b-74ff-921c-b3c30df57716", "01a0fb7e-9f79-704c-9b69-6c026ec90f07" ], "corrections": [], "plain_english_summary": "The synthesis organizes predictors in a holistic framework and evaluates why earlier studies have produced conflicting conclusions about effectiveness. For your marketing: Use the reviewed predictors to structure creator-selection and campaign hypotheses.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "retaining-customers-acquired-free-trials", "title": "The Challenge of Retaining Customers Acquired with Free Trials", "category": "Acquisition and retention", "study_type": "Household panel analysis and customer-lifetime-value modeling", "citation": "Datta, H., Foubert, B., & van Heerde, H. J. (2015). Journal of Marketing Research, 52(2), 217\u2013234.", "authors": [ "Hannes Datta", "Bram Foubert", "Harald J. van Heerde" ], "year": 2015, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.12.0160", "doi_url": "https://doi.org/10.1509/jmr.12.0160", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.12.0160", "accessible_url": "https://research.tilburguniversity.edu/files/19561149/JMR12_0160_WebPosting.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "How do customers acquired with free trials differ from regular customers in retention and lifetime value?", "design": "The authors analyze household panel data from a digital television service and model differences in usage, marketing responsiveness and customer lifetime value.", "sample_context": "Households using one digital television service; the abstract reports a comparison between trial-acquired and regular customers.", "findings": "Average lifetime value for free-trial customers was 59% lower than for regular customers in this setting. Trial-acquired customers were more responsive to marketing communication and usage, suggesting opportunities for targeted retention activity.", "limitations": "One digital television service and its historical trial design. The reported CLV gap is not a benchmark for SaaS; acquisition cohorts may differ in ways specific to the service and period.", "founder_use": "Track post-trial retention and value by acquisition cohort, and test onboarding or communication interventions. Do not assume free-trial signups have the same economics as organically or sales-acquired customers.", "evidence_basis": "Journal of Marketing Research abstract and accessible author manuscript; setting and headline CLV difference are reported by the publisher.", "source_ids": [ "01a0fb7a-d6a3-74e4-bd95-1dc684fbd423" ], "corrections": [], "plain_english_summary": "Average lifetime value for free-trial customers was 59% lower than for regular customers in this study. For your marketing: Track post-trial retention and value by acquisition cohort, and test onboarding or communication interventions.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "free-sample-promotions-incremental-sales", "title": "The Effects of Free Sample Promotions on Incremental Brand Sales", "category": "Pricing and product adoption", "study_type": "Promotion model and two field experiments", "citation": "Bawa, K., & Shoemaker, R. (2004). Marketing Science, 23(3), 345\u2013363.", "authors": [ "Kapil Bawa", "Robert Shoemaker" ], "year": 2004, "journal": "Marketing Science", "doi": "10.1287/mksc.1030.0052", "doi_url": "https://doi.org/10.1287/mksc.1030.0052", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1030.0052", "accessible_url": "https://ideas.repec.org/a/inm/ormksc/v23y2004i3p345-363.html", "access_label": "Publisher and bibliographic abstracts", "access_class": "abstract", "research_question": "Do free samples create incremental sales, and how much comes from purchase acceleration, cannibalization or demand expansion?", "design": "The authors develop a model separating three pathways and analyze two field experiments on free-sample promotions.", "sample_context": "Two consumer packaged-goods sampling promotions; the abstract does not state sample sizes or brands.", "findings": "Unlike coupons, the studied free samples produced measurable long-term sales effects observable up to 12 months later. Effectiveness varied substantially, even between brands in one product category; acceleration, cannibalization and expansion differed across promotions.", "limitations": "Consumer packaged goods, two promotions and study-specific brands; sampling economics differ from SaaS free tiers or trials. Effects varied enough that a single benchmark would be misleading.", "founder_use": "Separate new demand from timing shifts and substitution when evaluating free access. Define incremental outcomes and follow customers long enough to see whether a free experience creates durable adoption.", "evidence_basis": "INFORMS-associated bibliographic record and abstract; the two field studies and sales pathways are directly described in the abstract.", "source_ids": [ "01a0fb7a-d6f3-75c8-a9fb-475268b78ede" ], "corrections": [], "plain_english_summary": "Unlike coupons, the studied free samples produced measurable long-term sales effects observable up to 12 months later. For your marketing: Separate new demand from timing shifts and substitution when evaluating free access.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "ewom-sales-meta-analysis-platform-product-metrics", "title": "The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors", "category": "Content and sharing", "study_type": "Meta-analysis of empirical eWOM-sales research", "citation": "Babi\u0107 Rosario, A., Sotgiu, F., De Valck, K., & Bijmolt, T. H. A. (2016). Journal of Marketing Research, 53(3), 297\u2013318.", "authors": [ "Ana Babi\u0107 Rosario", "Francesca Sotgiu", "Kristine De Valck", "Tammo H. A. Bijmolt" ], "year": 2016, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.14.0380", "doi_url": "https://doi.org/10.1509/jmr.14.0380", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0380", "accessible_url": "https://digitalcommons.du.edu/marketing_fac/2/", "access_label": "Publisher abstract and author record", "access_class": "abstract", "research_question": "How do platform, product and measurement choices moderate the relationship between electronic word of mouth and sales?", "design": "A meta-analysis synthesizes empirical studies of eWOM and sales and tests whether platform, product type and eWOM metrics explain differences in prior findings.", "sample_context": "Cross-study evidence covering online platforms, product types and eWOM measures; the publisher abstract reviewed here does not report the number of studies.", "findings": "The synthesis reports stronger eWOM effects for tangible goods that are new to the market; product life cycle did not moderate the effect for services. eWOM volume had a stronger effect on sales than valence in the analyzed studies.", "limitations": "Meta-analytic estimates depend on the included studies, platform era and definitions of sales and eWOM. The results concern broad product/service categories and do not predict a particular SaaS review program.", "founder_use": "Measure the amount and sentiment of customer discussion separately and connect both to sales outcomes. Treat review volume and valence as distinct signals, not interchangeable scores.", "evidence_basis": "Journal of Marketing Research publisher abstract; claims are confined to its stated moderators and reported results.", "source_ids": [ "01a0fb7a-d71c-7657-b53b-37d674721c33" ], "corrections": [], "plain_english_summary": "Looking across the studies, stronger online word of mouth effects for tangible goods that are new to the market; product life cycle did not moderate the effect for services. For your marketing: Measure the amount and sentiment of customer discussion separately and connect both to sales outcomes.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "referral-reward-size-new-customer-profitability", "title": "Referral Reward Size and New Customer Profitability", "category": "Acquisition and retention", "study_type": "Field experiment and archival generalization study", "citation": "Wolters, H. M., Schulze, C., & Gedenk, K. (2020). Marketing Science, 39(6), 1166\u20131180.", "authors": [ "Heike M. Wolters", "Christian Schulze", "Karen Gedenk" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2020.1242", "doi_url": "https://doi.org/10.1287/mksc.2020.1242", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1242", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1242", "access_label": "Publisher abstract and JSTOR preview", "access_class": "abstract", "research_question": "How does referral reward size affect the number and profitability of newly referred customers?", "design": "A field experiment involving bank customers is complemented by archival data from a telecommunications provider to assess generalizability.", "sample_context": "More than 160,000 bank customers in the experiment and approximately 270,000 telecommunications customers in the archival analysis.", "findings": "Larger referral rewards acquired more new customers but considerably decreased the profitability of referred customers in both studies.", "limitations": "The evidence comes from banking and telecommunications programs; reward economics and customer behavior may differ for software. The abstract does not provide the exact optimal reward size for other programs.", "founder_use": "Evaluate referrals on net customer profitability, not just the number of signups. Test reward levels with margin, retention and reward cost included in the outcome.", "evidence_basis": "INFORMS publisher metadata and abstract, corroborated by the journal preview; both sample contexts and central tradeoff are reported in the source.", "source_ids": [ "01a0fb79-b05e-7288-a374-d9884f77410a" ], "corrections": [], "plain_english_summary": "Larger referral rewards acquired more new customers but considerably decreased the profitability of referred customers in both studies. For your marketing: Evaluate referrals on net customer profitability, not just the number of signups.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "managing-churn-maximize-profits", "title": "Managing Churn to Maximize Profits", "category": "Acquisition and retention", "study_type": "Profit-based churn model and two field experiments", "citation": "Lemmens, A., & Gupta, S. (2020). Marketing Science, 39(5), 956\u2013973.", "authors": [ "Aur\u00e9lie Lemmens", "Sunil Gupta" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2020.1229", "doi_url": "https://doi.org/10.1287/mksc.2020.1229", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1229", "accessible_url": "https://www.hbs.edu/ris/download.aspx?name=14-020.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "How should firms select customers for retention interventions to maximize campaign profit?", "design": "The authors define a profit-based loss function that ranks customers by the incremental financial impact of a retention intervention and test the approach in two field experiments.", "sample_context": "Two retention-campaign field experiments; the accessible abstract does not summarize the industries or sample sizes.", "findings": "The profit-aligned targeting approach uses expected incremental churn and post-campaign cash flows net of intervention costs. The authors report that their method significantly improves campaign profitability compared with conventional churn-probability or offer-responsiveness targeting.", "limitations": "Performance depends on the intervention, available customer data and model evaluation. The publisher abstract does not provide effect magnitudes; a model trained on historical churn risk alone may not estimate treatment lift.", "founder_use": "For lifecycle offers, target on expected incremental profit rather than the highest predicted churn score. Measure treatment effects and include discounts, support and future cash flows in the decision.", "evidence_basis": "Marketing Science abstract and author-hosted manuscript; two field experiments and the profit-based targeting design are specified in the abstract.", "source_ids": [ "01a0fb79-afdd-74b8-87d1-00ef9504bd82" ], "corrections": [], "plain_english_summary": "The profit-aligned targeting approach uses expected additional churn and post-campaign cash flows net of intervention costs. For your marketing: For lifecycle offers, target on expected incremental profit rather than the highest predicted churn score.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "comparison-advertising-measurement-facebook-experiments", "title": "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook", "category": "Paid media and measurement", "study_type": "Comparison of observational estimators against randomized field experiments", "citation": "Gordon, B. R., Zettelmeyer, F., Bhargava, N., & Chapsky, D. (2019). Marketing Science, 38(2), 193\u2013225.", "authors": [ "Brett R. Gordon", "Florian Zettelmeyer", "Neha Bhargava", "Dan Chapsky" ], "year": 2019, "journal": "Marketing Science", "doi": "10.1287/mksc.2018.1135", "doi_url": "https://doi.org/10.1287/mksc.2018.1135", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2018.1135", "accessible_url": "https://www.kellogg.northwestern.edu/faculty/gordon_b/files/fb_comparison.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "Can commonly used observational methods recover the causal effect of online ads as measured by randomized experiments?", "design": "The authors compare observational measurement approaches with randomized Facebook ad experiments across 15 campaigns; the campaigns met minimum sample and conversion-tracking criteria.", "sample_context": "Fifteen Facebook campaigns, each with at least one million users and business-relevant conversion tracking, selected to compare measurement methods.", "findings": "Commonly used observational approaches based on industry-available data often failed to accurately measure the true advertising effect in these comparisons.", "limitations": "The analysis concerns a selected set of Facebook campaigns and methods available at the time. Results do not imply every observational model fails equally or that randomized tests are feasible for every startup campaign.", "founder_use": "Treat attribution models as hypotheses and validate them against holdouts where possible. When experiments are infeasible, document assumptions and do not present platform-attributed conversions as incremental impact.", "evidence_basis": "INFORMS publisher abstract and author-hosted paper; the 15-campaign design and minimum sample criteria are specified in the manuscript.", "source_ids": [ "01a0fb79-afdf-73e9-b4f5-9c55c5524eb3" ], "corrections": [], "plain_english_summary": "Commonly used observational approaches based on industry-available data often failed to accurately measure the true advertising effect in these comparisons. For your marketing: Treat attribution models as hypotheses and validate them against holdouts where possible.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "joint-model-usage-churn-contractual-settings", "title": "A Joint Model of Usage and Churn in Contractual Settings", "category": "Acquisition and retention", "study_type": "Joint statistical model of customer usage and churn", "citation": "Ascarza, E., & Hardie, B. G. S. (2013). Marketing Science, 32(4), 570\u2013590.", "authors": [ "Eva Ascarza", "Bruce G. S. Hardie" ], "year": 2013, "journal": "Marketing Science", "doi": "10.1287/mksc.2013.0786", "doi_url": "https://doi.org/10.1287/mksc.2013.0786", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2013.0786", "accessible_url": "https://www.hbs.edu/ris/Publication%20Files/ascarza_hardie_mktsci_13_68c64a95-bdae-4310-8330-954da804c2b8.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "How can firms jointly model customer usage and churn when they observe contractual relationships?", "design": "The authors develop an integrated statistical model of usage and retention in contractual settings and illustrate it with customer data from an annual membership service.", "sample_context": "Customers of an annual membership service; the paper models repeated usage and contract renewal/churn jointly.", "findings": "The joint framework is designed to capture the relationship between engagement behavior and retention, enabling more coherent customer-lifetime analysis than treating usage and churn as unrelated outcomes.", "limitations": "The application is a particular annual membership service and model assumptions matter. The framework does not mean that observed usage changes cause retention changes in every SaaS product.", "founder_use": "When usage predicts retention, model the outcomes together and distinguish prediction from causal effect. Validate the framework on your product's billing cadence and usage pattern.", "evidence_basis": "INFORMS record and author-hosted article; the publisher title and citation and paper setting were checked.", "source_ids": [ "01a0fb79-b002-74c6-81c5-b06c4b2ac009" ], "corrections": [], "plain_english_summary": "The joint framework is designed to capture the relationship between engagement behavior and retention, enabling more coherent customer-lifetime analysis than treating usage and churn as unrelated outcomes. For your marketing: When usage predicts retention, model the outcomes together and distinguish prediction from causal effect.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "saas-free-user-to-paid-conversion-touchpoints", "title": "Converting Free Users to Paid Subscribers in the SaaS Context: The Impact of Marketing Touchpoints, Message Content, and Usage", "category": "Pricing and product adoption", "study_type": "Empirical analysis of SaaS user activity, marketing touchpoints, and conversion", "citation": "Li, H. (2022). Production and Operations Management, 31(5), 2185\u20132203.", "authors": [ "Hongshuang (Alice) Li" ], "year": 2022, "journal": "Production and Operations Management", "doi": "10.1111/poms.13672", "doi_url": "https://doi.org/10.1111/poms.13672", "primary_url": "https://onlinelibrary.wiley.com/doi/10.1111/poms.13672", "accessible_url": "https://onlinelibrary.wiley.com/doi/abs/10.1111/poms.13672", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "How do marketing touchpoints, message content and product usage relate to free-user conversion in a SaaS business?", "design": "The study analyzes free-user conversion in a SaaS context, examining the joint roles of advertising and trial usage and the content of marketing messages.", "sample_context": "SaaS free users and their marketing touchpoints, usage and conversion behavior; the inspected abstract does not give the company name or sample size.", "findings": "The research provides SaaS-specific evidence on how advertising, free-trial usage and their interplay relate to conversion, with message content treated as a distinct marketing factor.", "limitations": "The accessible publisher abstract does not provide enough detail to report effect sizes, sample size or causal identification. Findings from one SaaS context cannot be assumed to transfer to other products, funnels or sales motions.", "founder_use": "Track activation and product usage alongside marketing exposure and message content when studying free-to-paid conversion. Consult the full methods before interpreting associations as causal effects.", "evidence_basis": "Wiley publisher record and abstract; core bibliographic details and SaaS context verified, with detailed results omitted where the accessible abstract did not expose them.", "source_ids": [ "01a0fb78-647b-7192-b581-2cc5536cedfc", "01a0fb78-88c6-73ee-b0d1-7c90b4b5bb50" ], "corrections": [], "plain_english_summary": "The research provides SaaS-specific evidence on how advertising, free-trial usage and their interplay relate to conversion, with message content treated as a distinct marketing factor. For your marketing: Track activation and product usage alongside marketing exposure and message content when studying free-to-paid conversion.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "fee-or-free-online-content", "title": "Fee or Free: When Should Firms Charge for Online Content?", "category": "Pricing and product adoption", "study_type": "Analytical model of content pricing and advertising revenue", "citation": "Lambrecht, A., & Misra, K. (2017). Management Science, 63(4), 1150\u20131165.", "authors": [ "Anja Lambrecht", "Kanishka Misra" ], "year": 2017, "journal": "Management Science", "doi": "10.1287/mnsc.2015.2383", "doi_url": "https://doi.org/10.1287/mnsc.2015.2383", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2015.2383", "accessible_url": "https://lbsresearch.london.edu/id/eprint/495/1/LambrechtA_Fee_or_Free_2016.pdf", "access_label": "Publisher record and author-hosted working paper", "access_class": "open-full-text", "research_question": "When should an online content provider offer content for free, charge for it, or combine access fees with advertising?", "design": "The authors develop an analytical model of online content provision that considers consumer demand and advertising revenue under alternative fee and free strategies.", "sample_context": "Theoretical analysis of online content providers; there is no empirical customer sample.", "findings": "The model shows that the value of free access depends on advertising monetization and consumer demand conditions; a paid strategy is not necessarily superior simply because it generates direct subscription revenue.", "limitations": "The findings are model-based and depend on assumptions about consumer demand, advertising revenue and content differentiation. It is not an empirical forecast for a particular SaaS freemium design.", "founder_use": "Useful for separating direct payment from indirect monetization when deciding what to make freely available. Map the model's assumptions to your acquisition cost, conversion and expansion economics before using it.", "evidence_basis": "INFORMS publisher bibliographic record and author-hosted paper; theoretical rather than experimental evidence.", "source_ids": [ "01a0fb78-88b9-7362-858a-9f959ddee029" ], "corrections": [], "plain_english_summary": "The model suggests that the value of free access depends on advertising monetization and consumer demand conditions; a paid strategy is not necessarily superior simply because it generates direct subscription revenue. For your marketing: This may be useful for separating direct payment from indirect monetization when deciding what to make freely available.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "optimal-pricing-new-subscription-services", "title": "Optimal Pricing of New Subscription Services: Analysis of a Market Experiment", "category": "Pricing and product adoption", "study_type": "Market experiment and demand modeling", "citation": "Danaher, P. J. (2002). Marketing Science, 21(2), 119\u2013138.", "authors": [ "Peter J. Danaher" ], "year": 2002, "journal": "Marketing Science", "doi": "10.1287/mksc.21.2.119.147", "doi_url": "https://doi.org/10.1287/mksc.21.2.119.147", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.21.2.119.147", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.21.2.119.147", "access_label": "Publisher record; abstract-level details", "access_class": "abstract", "research_question": "How should a firm price a new subscription service using evidence from a market experiment?", "design": "The article analyzes market-experiment data for a new subscription service and uses the experiment to inform pricing decisions.", "sample_context": "A new subscription-service market experiment; the publisher record inspected does not expose enough abstract detail to report the service or sample size.", "findings": "The study demonstrates an empirical approach to evaluating alternative subscription prices using market-experiment evidence rather than relying only on stated preferences or managerial judgment.", "limitations": "The publisher record retrieved here provides limited abstract detail. The service and market are specific, and an older experiment may not reflect current digital acquisition or pricing conditions.", "founder_use": "A foundational example of testing prices in market conditions. Review the full paper to understand its experimental design and demand model before adapting it to software subscriptions.", "evidence_basis": "INFORMS publisher bibliographic record and issue metadata; summary is intentionally restricted because the abstract text was not fully accessible.", "source_ids": [ "01a0fb78-640a-701a-a1cd-aab8531f0b0e" ], "corrections": [], "plain_english_summary": "The study demonstrates an empirical approach to evaluating alternative subscription prices using market-experiment evidence rather than relying only on stated preferences or managerial judgment. For your marketing: This is a foundational example of testing prices in market conditions.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "proactive-customer-education-retention-technology-support", "title": "Proactive Customer Education, Customer Retention, and Demand for Technology Support: Evidence from a Field Experiment", "category": "Acquisition and retention", "study_type": "Field experiment", "citation": "Retana, G. F., Forman, C., & Wu, D. J. (2016). Manufacturing & Service Operations Management, 18(1), 34\u201350.", "authors": [ "German F. Retana", "Chris Forman", "D. J. Wu" ], "year": 2016, "journal": "Manufacturing & Service Operations Management", "doi": "10.1287/msom.2015.0547", "doi_url": "https://doi.org/10.1287/msom.2015.0547", "primary_url": "https://pubsonline.informs.org/doi/10.1287/msom.2015.0547", "accessible_url": "https://pubsonline.informs.org/doi/abs/10.1287/msom.2015.0547", "access_label": "Publisher record; abstract-level details", "access_class": "abstract", "research_question": "How does proactive education affect customer retention and demand for technical support?", "design": "A field experiment evaluates proactive customer education and tracks retention and technology-support demand.", "sample_context": "Customers of a technology service in the field setting; the accessible publisher record does not report the full sample description or sample size.", "findings": "The study uses an experimental setting to examine whether educating customers can influence both continued use and requests for technical support, outcomes that can move in different directions.", "limitations": "The inspected publisher preview does not show the detailed result estimates or setting. Effects of education may depend on product complexity, support model and customer readiness.", "founder_use": "Treat onboarding and education as interventions with both retention and support-cost outcomes. Measure whether users reach value, stay, and need less reactive help.", "evidence_basis": "INFORMS publisher record and peer-reviewed citation metadata; detailed numeric findings are withheld because they were not accessible in the retrieved abstract.", "source_ids": [ "01a0fb78-639f-762a-a38c-ef72c094983f", "01a0fb78-8926-72b8-81a3-6214fdc069e0" ], "corrections": [], "plain_english_summary": "The study uses an experimental setting to examine whether educating customers can influence both continued use and requests for technical support, outcomes that can move in different directions. For your marketing: Treat onboarding and education as interventions with both retention and support-cost outcomes.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "advertising-content-bookstore-experiment", "title": "Where Does Advertising Content Lead You? We Created a Bookstore to Find Out", "category": "Paid media and measurement", "study_type": "Preregistered incentive-compatible randomized field experiment", "citation": "Morozov, I., & Tuchman, A. (2024). Marketing Science, 43(5), 986\u20131001.", "authors": [ "Ilya Morozov", "Anna Tuchman" ], "year": 2024, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0138", "doi_url": "https://doi.org/10.1287/mksc.2023.0138", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0138", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0138", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "How does the content of a display ad affect what consumers search for and buy?", "design": "The authors created an online bookstore and ran a preregistered incentive-compatible experiment, randomly varying ad exposure and the content shown in ads to store visitors.", "sample_context": "Visitors to an experimental online bookstore; the publisher abstract does not state the sample size.", "findings": "Ad content can polarize consumer responses. Depending on how many consumers favor the advertised genre, the same content can increase or decrease the total number of searches and purchases for the advertised book.", "limitations": "An experimental bookstore and book genres are a specific setting; the abstract does not establish equivalent effects for SaaS ads or report the sample count. Search and purchase responses depend on audience composition.", "founder_use": "Test how creative changes demand across audience segments, not only average clicks. Identify which visitors the message attracts or repels and connect ad response to meaningful product outcomes.", "evidence_basis": "INFORMS publisher record and abstract; publication date and journal issue checked against publisher metadata.", "source_ids": [ "01a0fb75-7d19-73fc-a5cb-0544b589a255", "01a0fb77-365f-769a-afb5-2ade2447a44b" ], "corrections": [], "plain_english_summary": "Ad content can polarize consumer responses. For your marketing: Test how creative changes demand across audience segments, not only average clicks.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "online-customer-experience-web-design-elements", "title": "Creating Effective Online Customer Experiences", "category": "Website and conversion design", "study_type": "Sixteen experiments including a field experiment on live product pages", "citation": "Bleier, A., Harmeling, C. M., & Palmatier, R. W. (2019). Journal of Marketing, 83(2), 98\u2013119.", "authors": [ "Alexander Bleier", "Colleen M. Harmeling", "Robert W. Palmatier" ], "year": 2019, "journal": "Journal of Marketing", "doi": "10.1177/0022242918809930", "doi_url": "https://doi.org/10.1177/0022242918809930", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022242918809930", "accessible_url": "https://seekscholar.com/sites/default/files/online%20customer%20experience.pdf", "access_label": "Publisher abstract and accessible author manuscript", "access_class": "open-full-text", "research_question": "Which product-page design elements shape online customer experience and purchase behavior?", "design": "Across 16 experiments, the authors test 13 page-design elements and four experience dimensions: informativeness, entertainment, social presence and sensory appeal. A field experiment manipulates real product pages on Amazon.com.", "sample_context": "Study 1 used 16 products from 11 brands and 256 experimental product-page versions; the broader research program includes online and field experiments.", "findings": "The experiments connect distinct page elements with multiple dimensions of online experience and show that those experiences influence purchase. The field experiment with real product pages supports the experimental findings.", "limitations": "The research uses online retail product pages and Amazon-style experiences; SaaS homepages, feature pages and signup flows involve different tasks. Effects depend on product and page context.", "founder_use": "A structured source for forming homepage and product-page hypotheses: assess information, entertainment, social presence and sensory cues separately, then test them against qualified conversion rather than aesthetic preference.", "evidence_basis": "Journal publisher abstract and accessible author manuscript; design elements and experiment scope checked against the manuscript.", "source_ids": [ "01a0fb75-7d0a-710d-99f5-349b1a8be119", "01a0fb77-36c7-7490-bf9e-9f023e375560" ], "corrections": [], "plain_english_summary": "The experiments connect distinct page elements with multiple dimensions of online experience and show that those experiences influence purchase. For your marketing: This is a structured source for forming homepage and product-page hypotheses: assess information, entertainment, social presence and sensory cues separately, then test them against qualified conversion rather than aesthetic preference.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.5/1", "note": "Small sample reported (16); treat the result as exploratory." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "when-less-is-more-advertising-experiments", "title": "When Less Is More: Data and Power in Advertising Experiments", "category": "Paid media and measurement", "study_type": "Large-scale randomized advertising field experiment and statistical analysis", "citation": "Johnson, G. A., Lewis, R. A., & Reiley, D. H. (2017). Marketing Science, 36(1), 43\u201353.", "authors": [ "Garrett A. Johnson", "Randall A. Lewis", "David H. Reiley" ], "year": 2017, "journal": "Marketing Science", "doi": "10.1287/mksc.2016.0998", "doi_url": "https://doi.org/10.1287/mksc.2016.0998", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2016.0998", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2016.0998", "access_label": "Publisher record and abstract; full text access may vary", "access_class": "abstract", "research_question": "How do the amount and structure of available data affect the power and cost of online advertising experiments?", "design": "The study uses a randomized field experiment involving approximately three million Yahoo! users and examines the relationship between data availability and experimental measurement of ad effects.", "sample_context": "Yahoo! advertising experiment at large scale; the publisher search result reports evidence that retailer ads increased sales by 3.6% in the studied campaign.", "findings": "The paper highlights that more granular data do not necessarily make advertising effects easier to estimate and examines tradeoffs between measurement precision and experimentation resources.", "limitations": "One platform and retailer campaign context; the 3.6% result should not be treated as a general ad-lift benchmark. The paper's title concerns statistical power and design, which require reading the methods before choosing an experiment size.", "founder_use": "Plan experiments around outcome variance and expected effect size. Large audiences alone do not guarantee useful estimates; choose an outcome and design that can detect a decision-relevant change.", "evidence_basis": "INFORMS publisher metadata and publisher-indexed summary; details are labeled conservatively where the abstract preview is limited.", "source_ids": [ "01a0fb76-fcf8-72bd-9439-4cf9fffcd03d", "01a0fb77-3625-75fb-b520-4ef42d66d518" ], "corrections": [], "plain_english_summary": "The paper's main point is that more granular data do not necessarily make advertising effects easier to estimate and examines tradeoffs between measurement precision and experimentation resources. For your marketing: Plan experiments around outcome variance and expected effect size.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "internet-display-advertising-purchase-funnel", "title": "Effects of Internet Display Advertising in the Purchase Funnel: Model-Based Insights from a Randomized Field Experiment", "category": "Paid media and measurement", "study_type": "Randomized field experiment with purchase-funnel model", "citation": "Hoban, P. R., & Bucklin, R. E. (2015). Journal of Marketing Research, 52(3), 375\u2013386.", "authors": [ "Paul R. Hoban", "Randolph E. Bucklin" ], "year": 2015, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.13.0277", "doi_url": "https://doi.org/10.1509/jmr.13.0277", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.13.0277", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.13.0277", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "How does Internet display advertising affect consumer movement through the purchase funnel?", "design": "The authors use cookie-level data from a randomized field experiment at a financial-tools provider and fit a model of consumer behavior through funnel stages.", "sample_context": "Online visitors to one financial-tools provider who were included in the display-ad experiment; the publisher preview does not report sample size.", "findings": "The paper uses randomized exposure data to estimate how display advertising affects multiple purchase-funnel outcomes rather than relying only on last-click attribution.", "limitations": "One provider and advertiser setting; the accessible abstract result does not report effect sizes or full funnel estimates. Cookie-based measurement and tracking conditions have changed since publication.", "founder_use": "Measure how campaigns affect more than the final conversion event, while preserving the experimental control that supports causal estimates. Check the paper's full results before mapping its model to a SaaS funnel.", "evidence_basis": "Journal of Marketing Research publisher record and abstract; profile avoids reporting numeric effects not visible in the inspected abstract.", "source_ids": [ "01a0fb76-fcfb-74bc-acb3-8d7414df0b5f", "01a0fb77-3648-730f-a786-67e49f588b0b" ], "corrections": [], "plain_english_summary": "The paper uses randomized exposure data to estimate how display advertising affects multiple purchase-funnel outcomes rather than relying only on last-click attribution. For your marketing: Measure how campaigns affect more than the final conversion event, while preserving the experimental control that supports causal estimates.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "social-advertising-effectiveness-across-products", "title": "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment", "category": "Paid media and measurement", "study_type": "Large-scale randomized field experiment", "citation": "Huang, S., Aral, S., Hu, Y. J., & Brynjolfsson, E. (2020). Marketing Science, 39(6), 1142\u20131165.", "authors": [ "Shan Huang", "Sinan Aral", "Yu Jeffrey Hu", "Erik Brynjolfsson" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2020.1240", "doi_url": "https://doi.org/10.1287/mksc.2020.1240", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1240", "accessible_url": "https://hub.hku.hk/bitstream/10722/297311/1/content.pdf", "access_label": "Publisher record and author manuscript", "access_class": "open-full-text", "research_question": "How does social advertising effectiveness vary across product categories and consumer characteristics?", "design": "The researchers partnered with a large online social network to run a randomized field experiment measuring social advertising effectiveness across 71 product categories.", "sample_context": "A large online social network and advertising across 71 product categories; the paper reports variation by product and user status.", "findings": "The experiment finds meaningful heterogeneity in social advertising lift across categories and user characteristics. The authors report that social cues increase effectiveness more for some product types and users than for others.", "limitations": "The experiment was run on one social network with participating advertisers and products. Effects are platform-, category- and campaign-dependent and should not be generalized into one expected lift for a SaaS company.", "founder_use": "When testing paid social, segment hypotheses by product and audience rather than assuming platform-wide average effectiveness. Use randomization and business outcomes to estimate your own incremental lift.", "evidence_basis": "INFORMS publisher record and accessible author manuscript; study scope and randomized design checked against the paper record.", "source_ids": [ "01a0fb75-7d19-73fc-a5cb-0544b589a255", "01a0fb75-f01a-73dc-9ce0-3359811cd47d" ], "corrections": [], "plain_english_summary": "The experiment finds meaningful differences across customers in social advertising lift across categories and user characteristics. For your marketing: When testing paid social, segment hypotheses by product and audience rather than assuming platform-wide average effectiveness.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "social-proof-likes-ad-clicks", "title": "Do More Likes Lead to More Clicks? Evidence from a Field Experiment on Social Advertising", "category": "Paid media and measurement", "study_type": "Large-scale field experiment, three online lab studies, and theoretical model", "citation": "Huang, S., & Lin, S. (2025). Journal of Marketing Research. https://doi.org/10.1177/00222429241307608.", "authors": [ "Shan Huang", "Song Lin" ], "year": 2025, "journal": "Journal of Marketing Research", "doi": "10.1177/00222429241307608", "doi_url": "https://doi.org/10.1177/00222429241307608", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222429241307608", "accessible_url": "https://journals.sagepub.com/doi/10.1177/00222429241307608", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Does displaying a larger number of likes on an ad cause more users to like or click it?", "design": "A large-scale WeChat field experiment is complemented by three online laboratory studies and a theoretical model.", "sample_context": "WeChat social advertising plus online lab studies; the accessible abstract does not report a sample size.", "findings": "Displaying more likes increased click-through rates for lesser-known brands but not for well-known brands. It had a stronger effect on like rates among more socially engaged users.", "limitations": "A single platform and specific social-ad context; the abstract does not report sample size or all treatment details. Likes and clicks are intermediate outcomes rather than qualified leads or sales.", "founder_use": "Social proof may matter more when brand familiarity is low, but the effect can depend on audience behavior. Test against downstream conversion and avoid optimizing for visible engagement alone.", "evidence_basis": "Journal of Marketing Research publisher abstract; results summarized at abstract level.", "source_ids": [ "01a0fb75-f03d-71dd-97a2-f3a472a11ea7" ], "corrections": [], "plain_english_summary": "Displaying more likes increased click-through rates for lesser-known brands but not for well-known brands. For your marketing: Social proof may matter more when brand familiarity is low, but the effect can depend on audience behavior.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "timing-online-review-requests", "title": "Ask for Reviews at the Right Time: Evidence from Two Field Experiments", "category": "Content and sharing", "study_type": "Two field experiments", "citation": "Jung, M., Ryu, S., Han, S. P., & Cho, D. (2023). Journal of Marketing Research. https://doi.org/10.1177/00222429221143329.", "authors": [ "Miyeon Jung", "Sunghan Ryu", "Sang Pil Han", "Daegon Cho" ], "year": 2023, "journal": "Journal of Marketing Research", "doi": "10.1177/00222429221143329", "doi_url": "https://doi.org/10.1177/00222429221143329", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222429221143329", "accessible_url": "https://journals.sagepub.com/doi/10.1177/00222429221143329", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "When should firms send prompts asking customers to post an online review?", "design": "Two field experiments test review-request timing and compare immediate reminders with later requests in online marketplace settings.", "sample_context": "The publisher and university research summaries describe marketplace customers, including a major South Korean online apparel marketplace; the abstract reviewed does not provide sample sizes.", "findings": "Immediate reminders reduced review posting relative to a randomized immediate control group without a reminder. The authors interpret this as evidence that reactance to an immediate prompt can outweigh the memory benefit in that setting.", "limitations": "The evidence concerns particular marketplace transactions and review prompts; it does not show that delaying every customer message improves reviews. Review posting is distinct from review quality or sales impact.", "founder_use": "Test the timing of review requests after users experience value. Randomize timing and report both posting and review quality, while avoiding pressure tactics that can undermine trust.", "evidence_basis": "Journal of Marketing Research abstract and institutional research summary. No sample sizes are added because they were not available in the abstract reviewed.", "source_ids": [ "01a0fb75-7d11-74ec-af50-b11bfd674ad4", "01a0fb75-efc8-70e1-ba6b-d2b5dc51de2d" ], "corrections": [], "plain_english_summary": "Immediate reminders reduced review posting relative to a randomized immediate control group without a reminder. For your marketing: Test the timing of review requests after users experience value.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "do-marketers-matter-entrepreneurs-uganda", "title": "Do Marketers Matter for Entrepreneurs? Evidence from a Field Experiment in Uganda", "category": "Marketing capability and growth", "study_type": "Multiyear randomized field experiment", "citation": "Anderson, S. J., Chandy, R. K., & Zia, B. (2021). Journal of Marketing Research. https://doi.org/10.1177/0022242921993176.", "authors": [ "Stephen J. Anderson", "Rajesh K. Chandy", "Bilal Zia" ], "year": 2021, "journal": "Journal of Marketing Research", "doi": "10.1177/0022242921993176", "doi_url": "https://doi.org/10.1177/0022242921993176", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022242921993176", "accessible_url": "https://mii.ie/wp-content/uploads/2020/05/Do-Marketers-Matter-for-Entrepreneurs.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "Can marketing expertise help small entrepreneurs improve business performance?", "design": "A multiyear field experiment randomly matched entrepreneurs in Uganda with volunteer marketers who helped them address marketing challenges.", "sample_context": "Entrepreneurs and small firms in Uganda participating in a volunteer-marketer program; the abstracted sources emphasize firm growth outcomes.", "findings": "Entrepreneurs randomly matched with volunteer marketers significantly increased firm growth. The paper evaluates how practical marketing assistance affects business outcomes in this context.", "limitations": "The study is based on a specific program, country, participant pool and period. Volunteer assistance may not replicate the effect of hiring a marketer or using the same practices in a software startup.", "founder_use": "Evidence that applied marketing expertise can affect small-firm growth, while underscoring the importance of implementation context. For a startup, define the intervention and measure firm outcomes rather than activity alone.", "evidence_basis": "Journal publisher abstract and accessible author-hosted paper; the profile avoids assigning unverified effect sizes or sample counts.", "source_ids": [ "01a0fb75-f022-744d-a0d4-4ec3bc42eaa6" ], "corrections": [], "plain_english_summary": "Entrepreneurs randomly matched with volunteer marketers significantly increased firm growth. For your marketing: Evidence that applied marketing expertise can affect small-firm growth, while underscoring the importance of implementation context.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "seo-long-term-keyword-choice", "title": "Search Engine Optimization: The Long-Term Strategy of Keyword Choice", "category": "Search and content discovery", "study_type": "Empirical analysis of search-engine keyword performance over time", "citation": "Erdmann, A., Arilla, R., & Ponzoa, J. M. (2022). Journal of Business Research, 144, 650\u2013662.", "authors": [ "Anett Erdmann", "Ram\u00f3n Arilla", "Jos\u00e9 M. Ponzoa" ], "year": 2022, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2022.01.065", "doi_url": "https://doi.org/10.1016/j.jbusres.2022.01.065", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322000777", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322000777", "access_label": "Publisher article preview; full text access may vary", "access_class": "abstract", "research_question": "How should marketers choose search-engine keywords when considering both short- and long-term performance?", "design": "The study examines keyword choice and performance over short and long horizons, framing SEO keyword selection as a long-run marketing decision.", "sample_context": "Search-engine keywords and their performance in the study's empirical setting; the publisher preview reviewed here does not expose the sample details.", "findings": "The paper treats keyword choice and marketing expenditure as having both short- and long-run performance implications, challenging evaluation based only on immediate traffic response.", "limitations": "The inspected publisher preview does not provide enough detail to report the data source, sample or estimated effects. Search ranking systems and competition also change over time; the paper should not be used as a current SEO playbook.", "founder_use": "Evaluate organic-search investments over an appropriate time window and distinguish durable qualified demand from transient ranking or click changes. Consult the full paper before applying its model or effect estimates.", "evidence_basis": "Publisher article preview plus bibliographic record; this profile is intentionally limited because the abstract text and detailed method were not exposed in the retrieved preview.", "source_ids": [ "01a0fb74-4e48-76d9-ab98-9413a0df8288", "01a0fb74-8de1-777c-b5b3-533e8dcb8d0f" ], "corrections": [], "plain_english_summary": "The paper treats keyword choice and marketing expenditure as having both short- and long-run performance implications, challenging evaluation based only on immediate traffic response. For your marketing: Evaluate organic-search investments over an appropriate time window and distinguish durable qualified demand from transient ranking or click changes.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "selling-premium-in-freemium", "title": "Selling the Premium in Freemium", "category": "Pricing and product adoption", "study_type": "Randomized field experiment and customer-choice analysis", "citation": "Gu, X., Kannan, P. K., & Ma, L. (2018). Journal of Marketing, 82(6), 10\u201327.", "authors": [ "Xian Gu", "P. K. Kannan", "Liye Ma" ], "year": 2018, "journal": "Journal of Marketing", "doi": "10.1177/0022242918807170", "doi_url": "https://doi.org/10.1177/0022242918807170", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022242918807170", "accessible_url": "https://journals.sagepub.com/doi/10.1177/0022242918807170", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Can adding another premium option increase demand for an existing paid option when a free version is available?", "design": "A randomized field experiment with an online content provider tested product-line extensions alongside a free PDF version and analyzed individual customer choices.", "sample_context": "Book titles offered as free PDFs with paid paperback and additional e-book or hardcover options; the abstract does not report the experiment's sample size.", "findings": "Paperback titles accompanied by an additional premium version had higher sales than control titles. The lift was stronger for more popular or cheaper titles, and the e-book extension worked better when its price was closer to the paperback price. The authors identify compromise and attraction effects in customer choices.", "limitations": "The field setting is online book sales with a particular free and paid product structure; results may not carry over directly to feature-gated software. The abstract does not provide sample size or effect magnitudes.", "founder_use": "When testing SaaS tiers, consider how a new premium option changes comparison among existing plans. Run a controlled packaging test and monitor plan mix and total contribution, not only premium-tier conversion.", "evidence_basis": "Journal of Marketing publisher abstract and bibliographic record; profile summarizes the described experiment without adding unreported sample counts.", "source_ids": [ "01a0fb74-8d3f-704b-81b7-106683a3bb2a" ], "corrections": [], "plain_english_summary": "Paperback titles accompanied by an additional premium version had higher sales than control titles. For your marketing: When testing SaaS tiers, consider how a new premium option changes comparison among existing plans.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "word-of-mouth-traditional-marketing-social-network", "title": "Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an Internet Social Networking Site", "category": "Content and sharing", "study_type": "Longitudinal observational analysis using vector autoregression", "citation": "Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Journal of Marketing, 73(5), 90\u2013102.", "authors": [ "Michael Trusov", "Randolph E. Bucklin", "Koen H. Pauwels" ], "year": 2009, "journal": "Journal of Marketing", "doi": "10.1509/jmkg.73.5.90", "doi_url": "https://doi.org/10.1509/jmkg.73.5.90", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkg.73.5.90", "accessible_url": "https://www.anderson.ucla.edu/documents/areas/fac/marketing/bucklin_effects.pdf", "access_label": "Publisher record and author-hosted paper", "access_class": "open-full-text", "research_question": "How does member-to-member word of mouth compare with traditional marketing in driving signups at an online social network?", "design": "The authors link tracked electronic invitations, conventional marketing activity and new member signups over time, using a vector autoregression to account for dynamic relationships and feedback among the series.", "sample_context": "One Internet social networking site with observable invitations and promotional activity; the paper analyzes signup dynamics and marketing events over time.", "findings": "Word-of-mouth referrals had longer carryover effects than traditional marketing actions in this setting. The estimated long-run signup elasticity for word of mouth was 0.53 and substantially exceeded the estimated elasticities for marketing events and media appearances.", "limitations": "A single online social network and observational time-series estimates; the estimated relationships may not transfer to other businesses or channels. The study does not equate elasticity with causal return on spend.", "founder_use": "Instrument referral activity and evaluate its delayed contribution alongside paid or event-driven acquisition. Do not compare elasticities as though they were comparable ROI without cost and causal attribution data.", "evidence_basis": "Journal citation verified in publisher-linked sources; abstract and author-hosted paper support setting and findings.", "source_ids": [ "01a0fb71-f4f7-746b-bc64-d38fc0eb1338" ], "corrections": [], "plain_english_summary": "Word-of-mouth referrals had longer carryover effects than traditional marketing actions in this study. For your marketing: Instrument referral activity and evaluate its delayed contribution alongside paid or event-driven acquisition.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "category-demand-effects-price-promotions", "title": "The Category-Demand Effects of Price Promotions", "category": "Pricing and product adoption", "study_type": "Longitudinal category-level econometric analysis", "citation": "Nijs, V. R., Dekimpe, M. G., Steenkamp, J.-B. E. M., & Hanssens, D. M. (2001). Marketing Science, 20(1), 1\u201322.", "authors": [ "Vincent R. Nijs", "Marnik G. Dekimpe", "Jan-Benedict E. M. Steenkamp", "Dominique M. Hanssens" ], "year": 2001, "journal": "Marketing Science", "doi": "10.1287/mksc.20.1.1.10197", "doi_url": "https://doi.org/10.1287/mksc.20.1.1.10197", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.20.1.1.10197", "accessible_url": "https://ideas.repec.org/a/inm/ormksc/v20y2001i1p1-22.html", "access_label": "Publisher and bibliographic abstracts; full text access may vary", "access_class": "abstract", "research_question": "Under what conditions do price promotions expand demand for an entire product category in the short and long run?", "design": "The authors analyze national sales across 560 Dutch supermarket product categories over four years with multivariate time-series models, accounting for marketing mix and competition.", "sample_context": "560 consumer product categories in Dutch supermarkets; the data include prices, promotions, advertising, distribution and new-product activity.", "findings": "The research estimates category-demand expansion effects rather than only brand switching and tests how marketing intensity and competition moderate promotion response. The abstract emphasizes that category expansion is conditional on market context.", "limitations": "Retail packaged-goods data from one national market and historical period; estimated category-level effects do not predict SaaS discount outcomes or the profitability of a particular promotion.", "founder_use": "When discounting, separate category growth from switching between vendors or purchase timing. For software, define the analogous incremental outcome and test it against a non-discounted control.", "evidence_basis": "INFORMS bibliographic record and IDEAS/RePEc abstract. This profile does not add unverified numerical effect sizes.", "source_ids": [ "01a0fb71-f4ee-72dc-ad66-11f6620ac76b" ], "corrections": [], "plain_english_summary": "The research estimates category-demand expansion effects rather than only brand switching and tests how marketing intensity and competition moderate promotion response. For your marketing: When discounting, separate category growth from switching between vendors or purchase timing.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-display-advertising-creative-history", "title": "Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories", "category": "Paid media and measurement", "study_type": "Individual-level advertising response model with policy simulations", "citation": "Braun, M., & Moe, W. W. (2013). Marketing Science, 32(5), 753\u2013767.", "authors": [ "Michael Braun", "Wendy W. Moe" ], "year": 2013, "journal": "Marketing Science", "doi": "10.1287/mksc.2013.0802", "doi_url": "https://doi.org/10.1287/mksc.2013.0802", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2013.0802", "accessible_url": "https://ideas.repec.org/a/inm/ormksc/v32y2013i5p753-767.html", "access_label": "Publisher record and bibliographic abstract", "access_class": "abstract", "research_question": "How do display-ad creative variation and each person's exposure history relate to visits and conversions?", "design": "The authors model individual impression histories across multiple creatives and estimate effects on visits to and conversions at the advertised brand's website; they use simulations to compare delivery strategies.", "sample_context": "Online display-ad exposures and subsequent website behavior in the advertiser data analyzed by the paper; the abstracted record does not provide sample size.", "findings": "The model distinguishes exposure histories and creative content; simulations suggest advertisers can increase website visits and conversions by varying the creative shown to a person.", "limitations": "The simulations depend on the fitted model and advertiser data. The publisher abstract does not provide sample size or establish that creative rotation will improve outcomes for every campaign.", "founder_use": "Treat creative sequence and repetition as testable variables. Log exposure history and compare conversion outcomes when rotating messages, while accounting for audience and frequency differences.", "evidence_basis": "INFORMS publisher record plus bibliographic abstract; no unreported sample counts or effect sizes are supplied.", "source_ids": [ "01a0fb72-2bae-72fb-aa68-fefa9cf6f721" ], "corrections": [], "plain_english_summary": "The model distinguishes exposure histories and creative content; simulations suggest advertisers can increase website visits and conversions by varying the creative shown to a person. For your marketing: Treat creative sequence and repetition as testable variables.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "mobile-promotion-weather-effectiveness", "title": "Sunny, Rainy, and Cloudy with a Chance of Mobile Promotion Effectiveness", "category": "Paid media and measurement", "study_type": "Large-scale mobile promotion field data analysis", "citation": "Li, C., Luo, X., Zhang, C., & Wang, X. (2017). Marketing Science, 36(5), 762\u2013779.", "authors": [ "Chenxi Li", "Xueming Luo", "Cheng Zhang", "Xiaoyi Wang" ], "year": 2017, "journal": "Marketing Science", "doi": "10.1287/mksc.2017.1044", "doi_url": "https://doi.org/10.1287/mksc.2017.1044", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2017.1044", "accessible_url": "https://www.informs.org/News-Room/INFORMS-Releases/News-Releases/Sunny-rainy-or-cloudy-New-study-shows-how-weather-can-impact-consumer-purchase-response-to-mobile-ads", "access_label": "Publisher record and INFORMS research summary", "access_class": "abstract", "research_question": "Do local weather conditions and advertising tone change consumers\u2019 response to mobile promotions?", "design": "The study analyzes mobile promotion response in relation to local weather and message tone and tests whether the pattern is explained only by differences in mobile usage.", "sample_context": "Mobile promotion campaigns observed across weather conditions; the publisher summary reports comparative response timing and purchase response but not a full sample description.", "findings": "The authors report that response was higher and faster in sunny than cloudy conditions, and lower and slower in rainy than cloudy conditions. Message tone altered these weather-related response patterns.", "limitations": "The summary concerns specific mobile promotion data and cannot establish that weather targeting is appropriate or profitable for every product, market or location. Exact sample and model details require the paper.", "founder_use": "A reminder that context can moderate campaign response. For location-sensitive products, test contextual variables with controlled allocation and include the cost and practical value of targeting.", "evidence_basis": "INFORMS article record and publisher research summary; high-level summary only, with no universal benchmark claim.", "source_ids": [ "01a0fb71-f4c4-715c-97cb-587054c00512" ], "corrections": [], "plain_english_summary": "The study found that response was higher and faster in sunny than cloudy conditions, and lower and slower in rainy than cloudy conditions. For your marketing: This is a reminder that context can moderate campaign response.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "free-trial-high-tech-service-adoption", "title": "Try It, You\u2019ll Like It\u2014Or Will You? The Perils of Early Free-Trial Promotions for High-Tech Service Adoption", "category": "Pricing and product adoption", "study_type": "Empirical structural model and policy simulations", "citation": "Foubert, B., & Gijsbrechts, E. (2016). Marketing Science, 35(5), 810\u2013826.", "authors": [ "Bram Foubert", "Els Gijsbrechts" ], "year": 2016, "journal": "Marketing Science", "doi": "10.1287/mksc.2015.0973", "doi_url": "https://doi.org/10.1287/mksc.2015.0973", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0973", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0973", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "When do free trials help adoption of a high-tech service, and when can a poor early trial experience undermine it?", "design": "The authors estimate a model of trial and regular adoption that accounts for learning from usage and word of mouth while service quality evolves, then simulate alternative trial policies.", "sample_context": "A rich customer dataset for an interactive digital television service, including trial subscriptions, adoption and usage behavior. The abstract does not report the number of customers.", "findings": "The abstract characterizes free trials as a double-edged promotion: trial timing and how intensively consumers use the service during the trial matter to effectiveness, particularly while quality is uncertain and changing.", "limitations": "The setting is one interactive television service and the conclusions come from an estimated model and simulations. The abstract provides no sample size or numeric policy effect; the result does not establish a general optimal free-trial duration for SaaS.", "founder_use": "Design trials around the user's chance to experience core value and the maturity of the product. Track activation and service quality during the trial alongside conversion, and test timing in your own setting.", "evidence_basis": "Publisher abstract and bibliographic record; abstract-level summary, without numeric effect sizes not reported there.", "source_ids": [ "01a0fb70-c522-70eb-8c4c-14d3aa52a722" ], "corrections": [], "plain_english_summary": "The abstract characterizes free trials as a double-edged promotion: trial timing and how intensively consumers use the service during the trial matter to effectiveness, particularly while quality is uncertain and changing. For your marketing: Design trials around the user's chance to experience core value and the maturity of the product.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "referral-reward-product-congruence", "title": "Reward Design for Customer Referral Programs: Reward\u2013Product Congruence Effect and Gender Difference", "category": "Acquisition and retention", "study_type": "One field study and two laboratory studies", "citation": "Hu, H., & Zhang, X.-M. (2021). Frontiers in Psychology, 12, 644412.", "authors": [ "Hai-hua Hu", "Xin-Mu Zhang" ], "year": 2021, "journal": "Frontiers in Psychology", "doi": "10.3389/fpsyg.2021.644412", "doi_url": "https://doi.org/10.3389/fpsyg.2021.644412", "primary_url": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.644412/full", "accessible_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8240956/", "access_label": "Open full text in PubMed Central and publisher record", "access_class": "open-full-text", "research_question": "Does the fit between a referral reward and the product being recommended affect referral likelihood, and does the pattern differ by gender?", "design": "One field study and two laboratory studies test referral responses to utilitarian versus hedonic products and congruent versus incongruent reward types.", "sample_context": "Field and laboratory settings involving product and reward evaluations. The accessible abstract does not give a combined sample size; the full text reports separate studies and samples.", "findings": "Across the reported studies, utilitarian rewards generated higher referral likelihood for utilitarian products, whereas hedonic rewards performed better for hedonic products. The paper also examines gender differences in this congruence pattern.", "limitations": "The tested products and rewards are specific to the study settings, and the abstract does not establish whether the interaction generalizes to business software or B2B referrals. Referral likelihood is not the same as completed referrals or profitable acquisition.", "founder_use": "When offering referral incentives, test whether the reward feels aligned with the product and the referrer's motive. Measure actual invitations and resulting customer value; avoid using demographic stereotypes as a substitute for experimentation.", "evidence_basis": "Peer-reviewed publisher abstract and open full text; the profile summarizes the stated design and central congruence result.", "source_ids": [ "01a0fb70-c500-75c0-8a37-a47bebfb9023" ], "corrections": [], "plain_english_summary": "Across the reported studies, utilitarian rewards generated higher referral likelihood for utilitarian products, whereas hedonic rewards performed better for hedonic products. For your marketing: When offering referral incentives, test whether the reward feels aligned with the product and the referrer's motive.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "referral-programs-existing-customer-loyalty", "title": "Growing Existing Customers\u2019 Revenue Streams Through Customer Referral Programs", "category": "Acquisition and retention", "study_type": "Field experiment with matched comparison group", "citation": "Garnefeld, I., Eggert, A., Helm, S. V., & Tax, S. S. (2013). Journal of Marketing, 77(4), 17\u201332.", "authors": [ "Ina Garnefeld", "Andreas Eggert", "Sabrina V. Helm", "Stephen S. Tax" ], "year": 2013, "journal": "Journal of Marketing", "doi": "10.1509/jm.11.0423", "doi_url": "https://doi.org/10.1509/jm.11.0423", "primary_url": "https://journals.sagepub.com/doi/10.1509/jm.11.0423", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jm.11.0423", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Does participating in a referral program change the behavior and value of the existing customer who makes the recommendation?", "design": "Using customer data from a global cellular telecommunications provider, the authors compare participating recommenders with a matched control group and report a field experiment on subsequent customer behavior.", "sample_context": "Existing customers of one global cellular telecommunications provider; the abstract reports a one-year defection and revenue comparison.", "findings": "Within a year, recommenders\u2019 defection rate fell from 19% to 7%, and their average monthly revenue rose by 11.4% versus the matched control group. The loyalty effect was stronger among customers with shorter prior tenure.", "limitations": "One telecommunications provider and one program context. The abstract does not report sample size or enough assignment detail to assess all sources of selection; the reported changes should not be assumed for other products or referral mechanics.", "founder_use": "Evaluate both sides of referral programs: the acquired customer and the referrer. If participation is self-selected, use a randomized encouragement or carefully designed comparison before attributing retention changes to the program.", "evidence_basis": "Journal publisher abstract; profile reports only the summarized provider setting and headline outcomes. Sample size and detailed assignment methods were not available in the abstract reviewed.", "source_ids": [ "01a0fb6e-2863-703e-b1a5-6955d68460da" ], "corrections": [], "plain_english_summary": "Within a year, recommenders\u2019 defection rate fell from 19% to 7%, and their average monthly revenue rose by 11.4% versus the matched control group. For your marketing: Evaluate both sides of referral programs: the acquired customer and the referrer.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "referral-contagion-downstream-referrals", "title": "Referral Contagion: Downstream Benefits of Customer Referrals", "category": "Acquisition and retention", "study_type": "Large-scale field dataset, preregistered lab experiments, and field experiment", "citation": "Gershon, R., & Jiang, Z. (2024). Journal of Marketing Research. https://doi.org/10.1177/00222437241257886.", "authors": [ "Rachel Gershon", "Zhenling Jiang" ], "year": 2024, "journal": "Journal of Marketing Research", "doi": "10.1177/00222437241257886", "doi_url": "https://doi.org/10.1177/00222437241257886", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437241257886", "accessible_url": "https://bpb-us-e2.wpmucdn.com/sites.utdallas.edu/dist/8/1090/files/2023/02/referral_contagion_downstream_benefits_of_customer_referrals.pdf", "access_label": "Publisher abstract and author-hosted paper", "access_class": "open-full-text", "research_question": "Do customers acquired through referrals themselves generate more downstream referrals, and can that behavior be increased?", "design": "A large-scale customer field dataset was combined with preregistered laboratory experiments and a field experiment that reminded customers how they had joined.", "sample_context": "The publisher abstract reports a large-scale field dataset but no total sample size; the author-hosted manuscript describes data from 41.2 million customers, two preregistered lab experiments, and one field experiment.", "findings": "Conditional on purchase activity, referred customers made 31%\u201357% more referrals than nonreferred customers in the field data. In a field experiment, reminding customers they joined through a referral further raised their likelihood of referring by 21% according to the publisher abstract.", "limitations": "The field relationships may depend on the partner firms and customer contexts; the reminder intervention is a specific treatment. Referral propensity is not evidence that a referral program is profitable after incentives and servicing costs.", "founder_use": "Track whether acquired customers later refer others and test simple lifecycle reminders. Evaluate incremental referred-customer value net of reward cost; avoid treating the reported lift as a forecast for a different product.", "evidence_basis": "Journal of Marketing Research abstract plus author-hosted manuscript; sample detail comes from the manuscript, and the 21% result follows the publisher abstract.", "source_ids": [ "01a0fb6e-282d-73fc-a119-5254d3eea5ee", "01a0fb6e-2863-703e-b1a5-6955d68460da" ], "corrections": [], "plain_english_summary": "Conditional on purchase activity, referred customers made 31%\u201357% more referrals than nonreferred customers in the field data. For your marketing: Track whether acquired customers later refer others and test simple lifecycle reminders.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (41,200,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "self-and-social-relevance-sharing", "title": "Message Self and Social Relevance Increases Intentions to Share Content: Correlational and Causal Evidence from Six Studies", "category": "Content and sharing", "study_type": "Six online studies, including a preregistered experiment", "citation": "Cosme, D., Scholz, C., Chan, H.-Y., et al. (2023). Journal of Experimental Psychology: General, 152(1), 253\u2013267.", "authors": [ "Diana Cosme", "Christopher Scholz", "H.-Y. Chan", "Brandon P. Dor\u00e9", "Prateek Pandey", "Jordi Carreras-Tartak", "Nathan Cooper", "Arianna Paul", "Sandra M. Burns", "Emily B. Falk" ], "year": 2023, "journal": "Journal of Experimental Psychology: General", "doi": "10.1037/xge0001270", "doi_url": "https://doi.org/10.1037/xge0001270", "primary_url": "https://psycnet.apa.org/doiLanding?doi=10.1037%2Fxge0001270", "accessible_url": "https://psycnet.apa.org/manuscript/2022-88364-001.pdf", "access_label": "Publisher record and accepted manuscript", "access_class": "open-full-text", "research_question": "Are people more willing to share messages they see as relevant to themselves or to people they know, and does the audience context matter?", "design": "Six online studies with adult U.S. participants. The studies included correlational and within-/between-person analyses across messages and sharing contexts; a preregistered framing experiment manipulated self and social relevance.", "sample_context": "3,727 adult participants in the United States rated 362 messages, producing 30,954 message ratings. Topics included COVID-19, voting, general health and climate change; formats included social posts and news articles.", "findings": "Self-relevance and social relevance were each positively associated with intentions to share. A preregistered framing experiment found that making relevance salient causally increased sharing intentions; the relative pathways differed between broadcasting broadly and sending directly to someone.", "limitations": "Primary outcome is stated intention to share, not observed organic sharing, qualified visits or purchases. The message topics are public-interest content rather than commercial SaaS marketing; adult U.S. online participants do not represent every audience.", "founder_use": "A prompt for testing whether a technical article explains why it matters to the reader and to someone they work with. Measure actual forwarding or downstream behavior in your own context rather than assuming stated intention predicts reach.", "evidence_basis": "APA publisher record and abstract plus an accessible accepted manuscript link. Profile claims follow the reported abstract; the paper should be consulted for measures and analysis details.", "source_ids": [ "01a0fb38-653b-7573-89de-53d8b21f5a67" ], "corrections": [], "plain_english_summary": "Self-relevance and social relevance were each positively associated with intentions to share. For your marketing: This is a prompt for testing whether a technical article explains why it matters to the reader and to someone they work with.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.9/1", "note": "Sample reported (3,727); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "social-referral-programs-freemium-platforms", "title": "Social Referral Programs for Freemium Platforms", "category": "Acquisition and retention", "study_type": "Randomized field experiment", "citation": "Belo, R., & Li, T. (2022). Management Science, 68(12), 8933\u20138962.", "authors": [ "Rodrigo Belo", "Ting Li" ], "year": 2022, "journal": "Management Science", "doi": "10.1287/mnsc.2022.4301", "doi_url": "https://doi.org/10.1287/mnsc.2022.4301", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4301", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4301", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How do social referral programs affect growth, payment, and engagement on freemium platforms?", "design": "Two-year randomized field experiment that introduced referral programs and varied referral requirements on an online dating platform.", "sample_context": "52,782 approved new users on a dating platform in a major European city, observed from March 2015 to February 2017.", "findings": "Referral programs increased referrals but could reduce revenue when referred users gained access to premium features without paying. Higher referral thresholds increased referrals and total revenue, while reducing some user engagement. Reserving selected premium features for paying users helped avoid the revenue loss.", "limitations": "One online dating platform with distinctive social-network and turnover dynamics. Customer lifetime value results also depend on modeling assumptions; the exact trade-offs may differ for SaaS products.", "founder_use": "Useful when a product has social invitations or a free tier: track invited users, paid conversion, and engagement together, and test which benefits are available to nonpayers.", "evidence_basis": "Publisher abstract and source page inspected with Firecrawl; summary is abstract-level and limited to the reported experiment.", "source_ids": [ "01a0fb84-bb85-7019-a2c6-0c7e0ea2ecec" ], "corrections": [], "plain_english_summary": "Referral programs increased referrals but could reduce revenue when referred users gained access to premium features without paying. For your marketing: This may be useful when a product has social invitations or a free tier: track invited users, paid conversion, and engagement together, and test which benefits are available to nonpayers.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (52,782); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "personalized-ad-load-subscription-and-ad-revenue", "title": "Personalizing Ad Load to Optimize Subscription and Ad Revenues: Product Strategies Constructed from Experiments on Pandora", "category": "Paid media and measurement", "study_type": "Large-scale randomized field experiment and heterogeneous-treatment analysis", "citation": "Goli, A., Reiley, D. H., & Zhang, H. (2025). Marketing Science, 44(2), 327\u2013352.", "authors": [ "Ali Goli", "David H. Reiley", "Hongkai Zhang" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.0357", "doi_url": "https://doi.org/10.1287/mksc.2022.0357", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0357", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0357", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Can ad load be personalized to improve subscription and advertising revenue, and how quickly do users respond?", "design": "Field experiment varying the number of ads per hour, followed by modeling of heterogeneous impacts and alternative allocation policies.", "sample_context": "More than seven million Pandora users in an 18-month experiment.", "findings": "Consumption responses took more than a year to stabilize, while subscription responses stabilized in under six months. A personalized allocation was estimated to raise subscription profits by 7% without reducing ad profits; the modeled strategy lowered average consumer welfare by 2%.", "limitations": "A single audio-streaming platform and its advertising/subscription economics. The personalized policy results are model-based extrapolations from the experiment, and the reported welfare effect is a platform-specific estimate.", "founder_use": "Shows why ad load can have delayed effects and why short tests may miss them. Treat the numbers as a measurement-design example, not a target for SaaS paywalls or sponsorship inventory.", "evidence_basis": "INFORMS publisher page and abstract retrieved with Firecrawl; no full text inspected for this profile.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Consumption responses took more than a year to stabilize, while subscription responses stabilized in under six months. For your marketing: This shows why ad load can have delayed effects and why short tests may miss them.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "subscription-duration-discount-price-menus", "title": "Optimizing Price Menus for Duration Discounts: A Subscription Selectivity Field Experiment", "category": "Pricing and monetization", "study_type": "Randomized online pricing field experiment and choice model", "citation": "Tian, L., & Feinberg, F. M. (2020). Marketing Science, 39(6), 1181\u20131198.", "authors": [ "Longxiu Tian", "Fred M. Feinberg" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2020.1265", "doi_url": "https://doi.org/10.1287/mksc.2020.1265", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1265", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2020.1265", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How should subscription businesses set menus that combine different commitment lengths and duration discounts?", "design": "Randomized online pricing experiment varying overall price level and the steepness of duration-discount menus; the authors jointly model opting in and choosing a plan.", "sample_context": "Users considering subscription plans on a major online dating service.", "findings": "The experiment shows that overall price increases reduce opting in and selection of higher-priced plans. Their joint model estimates different substitution patterns from standard choice models and suggests the studied firm priced its menu too low, especially its longest commitment.", "limitations": "One consumer subscription site and a model whose conclusions depend on the tested menu and demand specification. An online dating commitment menu may not predict B2B SaaS annual-plan behavior.", "founder_use": "A useful design for testing both conversion and plan mix when changing monthly/annual prices. Measure opt-out alongside which plan is chosen; don\u2019t optimize annual-plan share alone.", "evidence_basis": "INFORMS publisher page and abstract retrieved with Firecrawl; the full experiment paper was not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The experiment shows that overall price increases reduce opting in and selection of higher-priced plans. For your marketing: This is a useful design for testing both conversion and plan mix when changing monthly/annual prices.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "weekend-effect-online-reviews", "title": "The Weekend Effect in Online Reviews", "category": "Reviews and reputation", "study_type": "Multi-platform observational analysis and review-solicitation experiments", "citation": "Bayerl, A., Schoenmueller, V., Goldenberg, J., & Stahl, F. (2026). Journal of Marketing Research, 63(2), 211\u2013233.", "authors": [ "Andreas Bayerl", "Verena Schoenmueller", "Jacob Goldenberg", "Florian Stahl" ], "year": 2026, "journal": "Journal of Marketing", "doi": "10.1177/00222437251391808", "doi_url": "https://doi.org/10.1177/00222437251391808", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437251391808", "accessible_url": "https://journals.sagepub.com/doi/10.1177/00222437251391808", "access_label": "Publisher abstract and article page; access may vary", "access_class": "abstract", "research_question": "Do online reviews differ by day of week, and does the timing of a review request affect the ratings collected?", "design": "Analysis of review data across platforms, fixed-effects and natural-experiment analyses, plus review-solicitation studies including a preregistered field experiment.", "sample_context": "Nearly 400 million reviews across 33 platforms, more than 20 million reviewed items and over 60 million users; categories include products, travel, employers, entertainment, and professional services.", "findings": "Weekend reviews averaged about 0.04 stars lower; a negative pattern appeared on 26 of 33 platforms. The authors identify temporal self-selection as a major mechanism and report that weekend review requests can collect more negative ratings.", "limitations": "Platform data and review-solicitation experiments do not establish the best request schedule for every business. Some solicitation studies had low power, and the platforms span heterogeneous categories; ratings are not equivalent to revenue or customer quality.", "founder_use": "If review volume matters, test request timing and compare response rate and rating distribution. Avoid interpreting a weekend average as evidence that customers or product quality change on weekends.", "evidence_basis": "SAGE publisher abstract and full article page retrieved with Firecrawl. Access class remains abstract-level in this directory profile.", "source_ids": [ "01a0fb82-91d5-714d-a69a-ef40ec0cf5de" ], "corrections": [], "plain_english_summary": "Weekend reviews averaged about 0.04 stars lower; a negative pattern appeared on 26 of 33 platforms. For your marketing: If review volume matters, test request timing and compare response rate and rating distribution.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (400,000,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "content-marketing-effectiveness-managerial-survey", "title": "Determinants of Content Marketing Effectiveness: Conceptual Framework and Empirical Findings from a Managerial Perspective", "category": "Content and sharing", "study_type": "Cross-sectional survey and regression analysis", "citation": "Koob, C. (2021). PLoS ONE, 16(4), e0249457.", "authors": [ "Clemens Koob" ], "year": 2021, "journal": "PLoS ONE", "doi": "10.1371/journal.pone.0249457", "doi_url": "https://doi.org/10.1371/journal.pone.0249457", "primary_url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249457", "accessible_url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249457", "access_label": "Open access full text", "access_class": "open-full-text", "research_question": "Which organizational conditions are associated with effective content marketing?", "design": "Cross-sectional online survey of senior marketing and communications executives with multiple regression analysis.", "sample_context": "263 executives from medium and large organizations in Germany, Austria, and Switzerland, across services, industrial, finance, and trade sectors.", "findings": "Clear strategy and organizational commitment, content aligned with audience needs and journalistic quality norms, regular measurement, and supporting specialized roles and processes were positively associated with reported effectiveness. Media count and paid promotion budget were not significant in the reported models.", "limitations": "Cross-sectional data cannot establish causality. Effectiveness was self-reported by one informant per organization, and the sample is limited to larger firms in German-speaking countries.", "founder_use": "A practical checklist for content operations: define the audience need, set editorial quality expectations, measure performance, and assign ownership. The survey does not prove these practices cause growth for early-stage SaaS.", "evidence_basis": "Open PLoS publisher full text and abstract inspected with Firecrawl; methods, sample and reported associations were checked on the article page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Clear strategy and organizational commitment, content aligned with audience needs and journalistic quality norms, regular measurement, and supporting specialized roles and processes were positively associated with reported effectiveness. For your marketing: This is a practical checklist for content operations: define the audience need, set editorial quality expectations, measure performance, and assign ownership.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-product-reviews-retail-sales-meta-analysis", "title": "How Online Product Reviews Affect Retail Sales: A Meta-analysis", "category": "Reviews and reputation", "study_type": "Meta-analysis of empirical studies", "citation": "Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). Journal of Retailing, 90(2), 217\u2013232.", "authors": [ "Kristopher Floyd", "Ryan Freling", "Saad Alhoqail", "Hyun Young Cho", "Traci Freling" ], "year": 2014, "journal": "Journal of Retailing", "doi": "10.1016/j.jretai.2014.04.004", "doi_url": "https://doi.org/10.1016/j.jretai.2014.04.004", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435914000293", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435914000293", "access_label": "Publisher abstract and highlights; full text may require access", "access_class": "abstract", "research_question": "How are review valence and volume related to retail sales, and which settings moderate those relationships?", "design": "Meta-analysis of 26 empirical studies producing 443 sales elasticities.", "sample_context": "Published studies of online product reviews and retail sales across different products, review sites, reviewer types, and use situations.", "findings": "Review valence and volume were positively related to sales elasticities. The reported relationships were stronger on third-party sites, when critic reviews were included, and for higher-involvement products.", "limitations": "The evidence base is retail/product focused and consists of empirical studies available by 2014. Pooled associations do not guarantee causal effects or SaaS-specific magnitudes.", "founder_use": "Use as evidence that review volume and valence can matter while designing review and reputation programs. For SaaS, monitor independent review sources and test whether reviews influence qualified pipeline or conversion.", "evidence_basis": "ScienceDirect publisher abstract and highlights inspected with Firecrawl; the publisher reports 26 studies and 443 elasticities.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Review valence and volume were positively related to sales elasticities. For your marketing: Use as evidence that review volume and valence can matter while designing review and reputation programs.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "targeting-affects-customer-search", "title": "How Targeting Affects Customer Search: A Field Experiment", "category": "Acquisition and retention", "study_type": "Field experiment", "citation": "Fong, N. M. (2017). Management Science, 63(7), 2353\u20132364.", "authors": [ "Nathan M. Fong" ], "year": 2017, "journal": "Management Science", "doi": "10.1287/mnsc.2016.2447", "doi_url": "https://doi.org/10.1287/mnsc.2016.2447", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2016.2447", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2016.2447", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do targeted offers change what customers search for beyond the promoted products?", "design": "Field experiment testing targeted email offers from an online wine retailer, with website search behavior as an outcome.", "sample_context": "Customers of an online wine retailer; the abstract does not report the sample size.", "findings": "Offers for products in categories customers had bought before raised purchase rates but reduced search activity. The reduction reflected less search by customers who visited, not fewer visitors searching at all.", "limitations": "One retailer and product category; sample size and full design details are not reported in the abstract. The effect on discovery may differ in products with different assortments and purchase cycles.", "founder_use": "Personalized recommendations can improve immediate relevance while narrowing exploration. When testing targeted landing pages or lifecycle offers, include cross-category discovery and downstream expansion in the outcome set.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; full text was not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Offers for products in categories customers had bought before raised purchase rates but reduced search activity. For your marketing: Personalized recommendations can improve immediate relevance while narrowing exploration.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "facebook-page-likes-offline-behavior", "title": "What Are Likes Worth? A Facebook Page Field Experiment", "category": "Paid media and measurement", "study_type": "Field experiment", "citation": "Mochon, D., Johnson, K., Schwartz, J., & Ariely, D. (2017). Journal of Marketing Research, 54(2), 306\u2013317.", "authors": [ "Daniel Mochon", "Karen Johnson", "Janet Schwartz", "Dan Ariely" ], "year": 2017, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.15.0409", "doi_url": "https://doi.org/10.1509/jmr.15.0409", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0409", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0409", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do acquiring Facebook page likes affect customer behavior outside Facebook, and under what use of the page?", "design": "Field experiment measuring acquired page likes and offline customer behavior under different firm communication conditions.", "sample_context": "Customers of a firm with a Facebook page; the publisher abstract does not state the sample size or business category.", "findings": "Acquired likes had a positive causal effect on offline behavior when the firm used the page for paid promoted posts. The study found no effect when customers interacted organically with the page.", "limitations": "One firm and the Facebook environment of the study period. The abstract omits sample details, and platform features and organic distribution have changed since publication.", "founder_use": "A reminder to measure paid social against business outcomes and distinguish paid exposure from organic engagement. Do not treat follower or like counts as a standalone growth metric.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; article-specific methods beyond the abstract were not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Acquired likes had a positive causal effect on offline behavior when the firm used the page for paid promoted posts. For your marketing: This is a reminder to measure paid social against business outcomes and distinguish paid exposure from organic engagement.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "advertising-spillovers-online-field-experiments", "title": "Advertising Spillovers: Evidence from Online Field Experiments and Implications for Returns on Advertising", "category": "Paid media and measurement", "study_type": "Randomized online field experiments", "citation": "Sahni, N. S. (2016). Journal of Marketing Research, 53(4), 459\u2013478.", "authors": [ "Navdeep S. Sahni" ], "year": 2016, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.14.0274", "doi_url": "https://doi.org/10.1509/jmr.14.0274", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0274", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0274", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How do online ads affect both the advertiser and competing options considered by customers?", "design": "Analysis of randomized advertising field experiments on a restaurant-search website, varying advertising exposure intensity.", "sample_context": "Restaurants listed on a restaurant-search site; detailed sample counts are not given in the accessible abstract.", "findings": "Ads increased sales likelihood for the advertiser and also for nonadvertised restaurants that served the same cuisine and had high ratings. Spillovers were largest at lower ad intensity and disappeared as intensity increased.", "limitations": "Restaurant search is a specific high-choice local market, and the abstract gives no sample counts. Spillovers in this setting may not predict competing software categories or paid search auctions.", "founder_use": "When evaluating category advertising, account for the possibility that your spend increases category interest while also helping alternatives. Incrementality and competitor outcomes matter alongside attributed conversions.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; no full text inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Ads increased sales likelihood for the advertiser and also for nonadvertised restaurants that served the same cuisine and had high ratings. For your marketing: When evaluating category advertising, account for the possibility that your spend increases category interest while also helping alternatives.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "third-party-reviews-firm-marketing-strategy", "title": "Third-Party Product Review and Firm Marketing Strategy", "category": "Reviews and reputation", "study_type": "Analytical model illustrated with industry data", "citation": "Chen, Y., & Xie, J. (2005). Marketing Science, 24(2), 218\u2013240.", "authors": [ "Yubo Chen", "Jinhong Xie" ], "year": 2005, "journal": "Marketing Science", "doi": "10.1287/mksc.1040.0089", "doi_url": "https://doi.org/10.1287/mksc.1040.0089", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1040.0089", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1040.0089", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How should firms adjust price and advertising after third-party product reviews or awards?", "design": "Analytical model of strategic responses to reviews, illustrated with data from printers and running shoes.", "sample_context": "Two product industries used to illustrate the theory; the main contribution is a model rather than a causal field test.", "findings": "Depending on product and review conditions, advertising can be a better response than price changes. Award-logo advertising can hurt the winning product, and increasing ad spend to publicize a favorable review is not always optimal.", "limitations": "The recommendations are conditional on the model's assumptions and product-market conditions. Illustrative industry data do not constitute a general causal estimate of review effects.", "founder_use": "Treat third-party badges as a positioning choice to test, not an automatic conversion lift. Consider whether the review source and product attributes make the endorsement credible and distinctive.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; article described as theory with illustrative industry data.", "source_ids": [ "01a0fb84-bb85-7019-a2c6-0c7e0ea2ecec" ], "corrections": [], "plain_english_summary": "Depending on product and review conditions, advertising can be a better response than price changes. For your marketing: Treat third-party badges as a positioning choice to test, not an automatic conversion lift.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-friends-freemium-paid-adoption", "title": "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks", "category": "Acquisition and retention", "study_type": "Randomized field experiment in a social network", "citation": "Bapna, R., & Umyarov, A. (2015). Management Science, 61(8), 1902\u20131920.", "authors": [ "Ravi Bapna", "Akhmed Umyarov" ], "year": 2015, "journal": "Management Science", "doi": "10.1287/mnsc.2014.2081", "doi_url": "https://doi.org/10.1287/mnsc.2014.2081", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2014.2081", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2014.2081", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Does a friend's adoption of a paid service causally affect another user's decision to pay?", "design": "Randomized field experiment that exogenously induced adoption of a paid service among users in a large online social network; results were checked with several statistical approaches.", "sample_context": "The general population of users on a large social network with a freemium service; the publisher abstract does not state the sample size.", "findings": "An adopting friend increased the odds of buying the paid service by more than 60% in the study. Relative influence was stronger for users with fewer friends.", "limitations": "One freemium social network and paid feature. Network structure and visible peer adoption are central to the mechanism and may be absent in many SaaS products.", "founder_use": "If paid adoption is socially visible in your product, measure peer exposure as a possible conversion mechanism. Avoid assuming that adding a referral prompt reproduces the network effect studied here.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; detailed sample and full methods were not available in the abstract.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "An adopting friend increased the odds of buying the paid service by more than 60% in the study. For your marketing: If paid adoption is socially visible in your product, measure peer exposure as a possible conversion mechanism.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "offsite-tracking-data-advertiser-value-meta", "title": "Estimating the Value of Offsite Tracking Data to Advertisers: Evidence from Meta", "category": "Paid media and measurement", "study_type": "Large-scale randomized advertising experiment", "citation": "Wernerfelt, N., Tuchman, A., Shapiro, B. T., & Moakler, R. (2025). Marketing Science, 44(2), 268\u2013286.", "authors": [ "Nils Wernerfelt", "Anna Tuchman", "Bradley T. Shapiro", "Robert Moakler" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0274", "doi_url": "https://doi.org/10.1287/mksc.2023.0274", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0274", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0274", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How much does offsite tracking data improve ad delivery effectiveness for advertisers?", "design": "Randomized experiment across live campaigns, with deconvolution methods used to estimate distributions of campaign-level effects.", "sample_context": "More than 70,000 Facebook and Instagram advertiser experiments across over 160 countries.", "findings": "The median cost per incremental customer was estimated at $38.16 at baseline and $49.93 under the median loss in effectiveness when offsite data could not be used, a 31% increase. The estimated loss was larger for small advertisers; purchase-optimized ads generated more long-term customers per dollar than click-optimized ads.", "limitations": "The experiment is partial-equilibrium and does not measure broader market adjustment or consumer privacy welfare. Offsite purchases and opted-out users are not fully observed, so some effects may be missed.", "founder_use": "Useful for thinking about privacy-related measurement loss and incrementality, especially for small advertisers. The Meta campaign economics and targeting system are platform-specific and should not be treated as a universal CAC benchmark.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; reported experiment scope, sample, results and limitations are summarized at abstract level.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The median cost per additional customer was estimated at $38.16 at baseline and $49.93 under the median loss in effectiveness when offsite data could not be used, a 31% increase. For your marketing: This may be useful for thinking about privacy-related measurement loss and incrementality, especially for small advertisers.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "ghost-ads-online-ad-effectiveness", "title": "Ghost Ads: Improving the Economics of Measuring Online Ad Effectiveness", "category": "Paid media and measurement", "study_type": "Advertising measurement method demonstrated in a retailer campaign", "citation": "Johnson, G. A., Lewis, R. A., & Nubbemeyer, E. I. (2017). Journal of Marketing Research, 54(6), 867\u2013884.", "authors": [ "Garrett A. Johnson", "Randall A. Lewis", "Elmar I. Nubbemeyer" ], "year": 2017, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.15.0297", "doi_url": "https://doi.org/10.1509/jmr.15.0297", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0297", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0297", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Can online ad effectiveness be measured more economically while retaining the precision of conventional experiments?", "design": "Introduces ghost-ad measurement and demonstrates it on a display-retargeting campaign for an online retailer.", "sample_context": "Retailer display-retargeting campaign; the publisher page reports recording over 100 million predicted ghost ads per day.", "findings": "In the demonstration campaign, retargeting lifted website visits by 17.2% and purchases by 10.5%. The method is presented as achieving comparable precision to intent-to-treat and public-service-announcement tests at substantially lower experimental cost.", "limitations": "The reported campaign is a single retailer retargeting case. Measurement implementation depends on ad delivery systems and campaign eligibility; the abstract does not supply a SaaS-specific performance benchmark.", "founder_use": "A foundational reference for asking an ad platform or analytics team how holdouts can measure incremental impact at lower cost. Use current, independently validated implementation details for any live test.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; the profile reports the retailer example and stated method benefits.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "In the demonstration campaign, retargeting lifted website visits by 17.2% and purchases by 10.5%. For your marketing: This is a foundational reference for asking an ad platform or analytics team how holdouts can measure incremental impact at lower cost.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "multichannel-online-conversion-attribution-field-study", "title": "Attributing Conversions in a Multichannel Online Marketing Environment: An Empirical Model and a Field Experiment", "category": "Paid media and measurement", "study_type": "Individual-level attribution model validated in a field study", "citation": "Li, H. (Alice), & Kannan, P. K. (2014). Journal of Marketing Research, 51(1), 40\u201356.", "authors": [ "Hongshuang (Alice) Li", "P. K. Kannan" ], "year": 2014, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.13.0050", "doi_url": "https://doi.org/10.1509/jmr.13.0050", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.13.0050", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.13.0050", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How can channel contribution be estimated while accounting for customer consideration, visits, carryover, and cross-channel effects?", "design": "Proposes an individual-level multichannel model and validates estimated incremental channel effects with a field study.", "sample_context": "Individual customer touchpoint histories and subsequent website purchases; the accessible abstract does not give sample size or business category.", "findings": "Attribution based on estimated channel effects differed significantly from common metrics. The model also identified cases where retargeting could decrease conversion probability.", "limitations": "The abstract provides limited detail on the validation sample and assumptions. Attribution depends on the model and available touchpoint data and should not be treated as a randomized causal result for every channel.", "founder_use": "A useful framework for considering channel sequence, carryover, and retargeting harm when last-click reports over-credit later touches. Pair modeled attribution with holdouts where feasible.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; full text and further design details were not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Attribution based on estimated channel effects differed significantly from common metrics. For your marketing: This is a useful framework for considering channel sequence, carryover, and retargeting harm when last-click reports over-credit later touches.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "The accessible description does not establish a strong causal design." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.45/1", "note": "Comparison or control details are limited in the reviewed source." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "email-engagement-subscription-profitability", "title": "Does Customer Email Engagement Improve Profitability? Evidence from a Field Experiment in Subscription Service Retailing", "category": "Acquisition and retention", "study_type": "Field experiment with retention, usage, and profit analysis", "citation": "Wang, Y., Lu, L. X., & Shi, P. (2022). Manufacturing & Service Operations Management, 24(5), 2703\u20132721.", "authors": [ "Yiwei Wang", "Lauren Xiaoyuan Lu", "Pengcheng Shi" ], "year": 2022, "journal": "Manufacturing & Service Operations Management", "doi": "10.1287/msom.2022.1122", "doi_url": "https://doi.org/10.1287/msom.2022.1122", "primary_url": "https://pubsonline.informs.org/doi/10.1287/msom.2022.1122", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/msom.2022.1122", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Does email engagement raise subscription retention and usage, and is it profitable for every subscriber segment?", "design": "Field experiment at a subscription-service retailer, analyzing retention and consumption with survival and difference-in-differences methods.", "sample_context": "Subscribers of a large U.S. car-wash chain with tiered subscriptions and RFID-tracked visits.", "findings": "A one-month program with two emails increased five-month retention likelihood by 7.4%, lowered churn odds by 26.3%, and raised per-period service use by 7.0%. Estimated profitability varied by subscriber tier and usage frequency; the authors recommend selectively targeting profitable groups.", "limitations": "A single physical subscription service; the abstract does not provide sample size or detailed randomization information. Segment profitability depends on this firm's service costs and customer behavior.", "founder_use": "The core lesson is to evaluate lifecycle email against retention, usage, and margin by segment. A message that lifts engagement can still lose money for some cohorts.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; results and segment-specific recommendation follow the abstract.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "A one-month program with two emails increased five-month retention likelihood by 7.4%, lowered churn odds by 26.3%, and raised per-period service use by 7.0%. For your marketing: The core lesson is to evaluate lifecycle email against retention, usage, and margin by segment.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "email-advertising-multichannel-sales", "title": "Linking Clicks to Bricks: Understanding the Effects of Email Advertising on Multichannel Sales", "category": "Paid media and measurement", "study_type": "Observational causal-estimation study using customer-level behavior and transactions", "citation": "Zhou, M., Abhishek, V., Kennedy, E. H., Srinivasan, K., & Sinha, R. (2025). Information Systems Research, 36(1), 225\u2013238.", "authors": [ "Mi Zhou", "Vibhanshu Abhishek", "Edward H. Kennedy", "Kannan Srinivasan", "Ritwik Sinha" ], "year": 2025, "journal": "Information Systems Research", "doi": "10.1287/isre.2020.0557", "doi_url": "https://doi.org/10.1287/isre.2020.0557", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2020.0557", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2020.0557", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do email ads affect sales beyond online clicks, including purchases in physical stores?", "design": "Customer-level observational analysis using a doubly robust estimator with nonparametric machine-learning methods.", "sample_context": "High-dimensional data from a large office-supplies retailer linking online behavior to item-level physical-store purchases.", "findings": "Email advertising was associated with increased sales across channels through higher purchase probability and a wider variety of products bought; effects varied across product types and customer segments.", "limitations": "This is an observational causal-estimation design in one retailer, not a randomized test. It may not transfer to SaaS products without physical sales channels.", "founder_use": "Encourages measuring email's full downstream value rather than clicks alone. For SaaS, connect email exposure to later product activation, opportunities, and revenue with a credible design.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; method and results are represented at abstract level.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Email advertising was associated with increased sales across channels through higher purchase probability and a wider variety of products bought; effects varied across product types and customer segments. For your marketing: This encourages measuring email's full downstream value rather than clicks alone.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-review-sales-meta-analysis-product-category", "title": "Exploring the Influence of Online Reviews and Motivating Factors on Sales: A Meta-analytic Study and the Moderating Role of Product Category", "category": "Reviews and reputation", "study_type": "Meta-analysis", "citation": "Li, K., Chen, Y., & Zhang, L. (2020). Journal of Retailing and Consumer Services, 55, 102107.", "authors": [ "Kunlin Li", "Yuhan Chen", "Liyi Zhang" ], "year": 2020, "journal": "Journal of Retailing and Consumer Services", "doi": "10.1016/j.jretconser.2020.102107", "doi_url": "https://doi.org/10.1016/j.jretconser.2020.102107", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0969698919304011", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0969698919304011", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Which online-review features relate to product sales, and does product category moderate those relationships?", "design": "Meta-analysis of 28 studies on online reviews and sales.", "sample_context": "Prior empirical studies across online product-review settings; the abstract does not report a pooled observation count.", "findings": "The analysis found product-category moderation. Review length and special shipping were the factors reported as not significantly affecting sales; other analyzed review-related factors showed significant relationships.", "limitations": "The authors note that database choice and search terms may have omitted relevant studies, and the synthesis depends on the quality and reporting of included literature.", "founder_use": "A second synthesis supporting a context-dependent view of reviews. Check whether your SaaS category and buyer risk resemble the products represented before applying an effect.", "evidence_basis": "ScienceDirect publisher abstract retrieved with Firecrawl; limitations were extracted from the abstract page text.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Looking across the studies, product-category moderation. For your marketing: This is a second synthesis supporting a context-dependent view of reviews.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "prefilled-search-keywords-online-consumer-behavior", "title": "How Does Prepopulating Search Bars with Keywords Affect Online Consumer Behavior? A Field Experiment", "category": "Content and sharing", "study_type": "Randomized field experiment", "citation": "Sun, C. (2025). Marketing Science, 44(6), 1217\u20131231.", "authors": [ "Chenshuo Sun" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2024.0793", "doi_url": "https://doi.org/10.1287/mksc.2024.0793", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2024.0793", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2024.0793", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How do prefilled search suggestions affect product discovery, search behavior, and purchases?", "design": "Randomized field experiment testing trending, personalized, and niche keywords in a search bar.", "sample_context": "72,587 consumers on a large e-commerce platform.", "findings": "Trending keywords increased purchase incidence by 10.4% and spending by 8.8% versus an empty search bar. Personalized keywords increased these outcomes by 21% and 17%, respectively, but also reduced self-entered queries; niche terms had little impact.", "limitations": "One e-commerce platform and product-discovery interface. The abstract does not report longer-term effects or whether the shifts improve customer value, and search behavior may differ in technical software evaluation.", "founder_use": "Useful for designing search suggestions and content discovery on a site or product. Test whether suggested paths help visitors find what they need without suppressing valuable self-directed exploration.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; headline experiment results and sample are reported on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Trending keywords increased chance of buying by 10.4% and spending by 8.8% versus an empty search bar. For your marketing: This may be useful for designing search suggestions and content discovery on a site or product.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (72,587); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "incentive-misalignment-programmatic-advertising", "title": "Incentive Misalignments in Programmatic Advertising: Evidence from a Randomized Field Experiment", "category": "Paid media and measurement", "study_type": "Large-scale randomized field experiment", "citation": "Frick, T. W., Belo, R., & Telang, R. (2023). Management Science, 69(3), 1665\u20131686.", "authors": [ "Thomas W. Frick", "Rodrigo Belo", "Rahul Telang" ], "year": 2023, "journal": "Management Science", "doi": "10.1287/mnsc.2022.4438", "doi_url": "https://doi.org/10.1287/mnsc.2022.4438", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4438", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4438", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do ad platforms target users who are persuadable, or users who were already likely to purchase?", "design": "Randomized retargeting field experiment; consumers were assigned to retargeting ads or orthogonal public-service ads, with a separate welfare analysis.", "sample_context": "208,538 consumers eligible for retargeting at a European consumer-electronics e-retailer over 49 days.", "findings": "Ads increased purchase and return probabilities, but consumers targeted more aggressively were not more responsive to ads. The authors estimate the platform's bidding optimization reduced advertiser profit and overall welfare by about 6% relative to a firm-optimal regime.", "limitations": "One retailer and one retargeting campaign. The design does not capture defensive advertising against competitors, and the analysis observes only winning bids.", "founder_use": "Highlights the difference between predicting who will buy and identifying who changes behavior because of an ad. Ask for incrementality tests and examine whether optimization targets persuadable users.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; sample, randomization, findings and stated limitations were available on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Ads increased purchase and return probabilities, but consumers targeted more aggressively were not more responsive to ads. For your marketing: Highlights the difference between predicting who will buy and identifying who changes behavior because of an ad.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (208,538); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "combining-ad-targeting-techniques-auto-industry", "title": "Combining Ad Targeting Techniques: Evidence from a Field Experiment in the Auto Industry", "category": "Paid media and measurement", "study_type": "Field experiment with a supporting laboratory experiment", "citation": "Valenti, A., Miller, C. J., & Tucker, C. E. (2025). Management Science, 71(10), 8586\u20138603.", "authors": [ "Albert Valenti", "Chadwick J. Miller", "Catherine E. Tucker" ], "year": 2025, "journal": "Management Science", "doi": "10.1287/mnsc.2023.02310", "doi_url": "https://doi.org/10.1287/mnsc.2023.02310", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.02310", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.02310", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do contextual targeting and retargeting complement one another, and does ad content affect their combined performance?", "design": "Field experiment with an automobile manufacturer, supplemented by a laboratory experiment.", "sample_context": "Online advertising campaign for an automobile manufacturer; the accessible abstract does not state sample size.", "findings": "Combining contextual targeting with retargeting improved website visits, engagement, and soft conversions. Ads prompting users to customize an offering were especially effective in the combined condition.", "limitations": "One auto manufacturer and campaign context; the abstract does not report sample size or a direct sales outcome. The effectiveness of specific creative prompts may vary by product and buying cycle.", "founder_use": "A useful test idea for combining audience intent with page context and matching the creative to a meaningful next action. Measure pipeline or product activation beyond soft conversions.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; study design and reported outcomes were visible on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Combining contextual targeting with retargeting improved website visits, engagement, and soft conversions. For your marketing: This is a useful test idea for combining audience intent with page context and matching the creative to a meaningful next action.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "mobile-app-adoption-information-incentives", "title": "Motivating Effective Mobile App Adoptions: Evidence from a Large-Scale Randomized Field Experiment", "category": "Acquisition and retention", "study_type": "Large-scale randomized field experiment", "citation": "Sun, T., Shi, L., Viswanathan, S., & Zheleva, E. (2019). Information Systems Research, 30(2), 523\u2013539.", "authors": [ "Tianshu Sun", "Lanfei Shi", "Siva Viswanathan", "Elena Zheleva" ], "year": 2019, "journal": "Information Systems Research", "doi": "10.1287/isre.2018.0815", "doi_url": "https://doi.org/10.1287/isre.2018.0815", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0815", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0815", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do incentives or information more effectively encourage app adoption that leads to lasting customer purchases?", "design": "Randomized field experiment comparing monetary incentives with informational messages to motivate app adoption.", "sample_context": "More than 230,000 customers in the study's mobile-app adoption setting.", "findings": "Both incentives and information increased adoption, but only information-induced adoption sustainably raised purchases and firm profit. Incentives produced a larger short-run adoption increase without long-run purchase gains.", "limitations": "The study concerns an app and firm-specific customer base; the publisher abstract does not report further sample or category details. Adoption and channel behavior may differ for a SaaS product.", "founder_use": "Distinguishes adoption volume from valuable adoption. When using onboarding incentives or app prompts, compare long-run usage and profit by motivation rather than counting installs alone.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; sample size and comparative findings were checked on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Both incentives and information increased adoption, but only information-induced adoption sustainably raised purchases and firm profit. For your marketing: This distinguishes adoption volume from valuable adoption.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (230,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "tweeting-marketing-tool-tv-field-experiment", "title": "Tweeting as a Marketing Tool: A Field Experiment in the TV Industry", "category": "Content and sharing", "study_type": "Randomized social-media field experiment", "citation": "Gong, S., Zhang, J., Zhao, P., & Jiang, X. (2017). Journal of Marketing Research, 54(6), 833\u2013850.", "authors": [ "Shiyang Gong", "Juanjuan Zhang", "Ping Zhao", "Xuping Jiang" ], "year": 2017, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.14.0348", "doi_url": "https://doi.org/10.1509/jmr.14.0348", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0348", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0348", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Do firm tweets and influential-user retweets affect TV show viewing and audience growth?", "design": "Randomized field experiment on Sina Weibo with a major media company, testing company tweets and recruited influencers' retweets.", "sample_context": "Tweets promoting TV shows on a Chinese social network; the abstract does not state the number of users or shows.", "findings": "Company tweets directly increased viewing. Influencer retweets increased viewing when the original tweet was informative and were more effective at gaining new followers, which indirectly supported viewing.", "limitations": "TV programming and Sina Weibo are context-specific; the abstract gives no sample size. Attention and viewing outcomes do not map directly to SaaS demand or pipeline.", "founder_use": "Suggests testing informative content and distribution source separately: a company's own posts may drive direct response while third-party sharing may grow the audience. Evaluate both with downstream outcomes.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; study design and reported effects were visible on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Company tweets directly increased viewing. For your marketing: Suggests testing informative content and distribution source separately: a company's own posts may drive direct response while third-party sharing may grow the audience.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "online-book-reviews-word-mouth-sales", "title": "The Effect of Word of Mouth on Sales: Online Book Reviews", "category": "Reviews and reputation", "study_type": "Longitudinal observational analysis of review and sales data", "citation": "Chevalier, J. A., & Mayzlin, D. (2006). Journal of Marketing Research, 43(3), 345\u2013354.", "authors": [ "Judith A. Chevalier", "Dina Mayzlin" ], "year": 2006, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.43.3.345", "doi_url": "https://doi.org/10.1509/jmkr.43.3.345", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkr.43.3.345", "accessible_url": "https://www.nber.org/system/files/working_papers/w10148/w10148.pdf", "access_label": "Publisher abstract and open earlier working-paper version", "access_class": "open-full-text", "research_question": "Do online consumer reviews affect relative book sales at competing retailers?", "design": "Longitudinal analysis of book reviews and relative sales at Amazon and Barnes & Noble, using differences across sites and over time.", "sample_context": "Books sold on Amazon.com and Barnesandnoble.com; the publisher abstract does not state the number of titles.", "findings": "An improvement in a book's reviews increased its relative sales at that site. In most samples, the impact of one-star reviews was greater than that of five-star reviews; review-length patterns suggested readers used review text, not just summary ratings.", "limitations": "The setting is books and retailer-specific review ecosystems. The publisher abstract provides limited design details, and the working paper predates the final journal publication.", "founder_use": "A foundational example of why negative feedback may carry asymmetric weight and why review text can matter. SaaS buyers and review platforms differ, so test the effect on your own category and conversion path.", "evidence_basis": "SAGE publisher abstract and NBER working-paper record retrieved with Firecrawl; the open link is an earlier working-paper version.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "An improvement in a book's reviews increased its relative sales at that site. For your marketing: This is a foundational example of why negative feedback may carry asymmetric weight and why review text can matter.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-social-interactions-wom-observational-learning", "title": "Online Social Interactions: A Natural Experiment on Word of Mouth versus Observational Learning", "category": "Reviews and reputation", "study_type": "Three longitudinal quasi-experimental field studies", "citation": "Chen, Y., Wang, Q., & Xie, J. (2011). Journal of Marketing Research, 48(2), 238\u2013254.", "authors": [ "Yubo Chen", "Qi Wang", "Jinhong Xie" ], "year": 2011, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.48.2.238", "doi_url": "https://doi.org/10.1509/jmkr.48.2.238", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkr.48.2.238", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkr.48.2.238", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How do consumer opinions (word of mouth) and visible purchase behavior (observational learning) separately affect product sales?", "design": "Three longitudinal quasi-experimental studies using policy shifts at Amazon.com as a natural experimental setting.", "sample_context": "Products and sales on Amazon.com; specific sample sizes are not listed in the abstract.", "findings": "Negative word of mouth was more influential than positive word of mouth. Positive purchase-statistic information raised sales, while negative purchase-statistic information had no effect; observational-learning effects increased with review volume.", "limitations": "The abstract omits sample and identification details; the evidence relies on one retailer and product marketplace. Purchase statistics may operate differently in considered B2B software buying.", "founder_use": "Separates testimonial sentiment from visible adoption signals such as customer counts or use cases. Test which form of social proof helps which buyer rather than treating them as interchangeable.", "evidence_basis": "SAGE publisher abstract retrieved with Firecrawl; full text not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Negative word of mouth was more influential than positive word of mouth. For your marketing: This separates testimonial sentiment from visible adoption signals such as customer counts or use cases.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.6/2", "note": "A quasi-experimental design can support causal claims if its assumptions hold." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Nonrandom comparison; causal interpretation depends on the design assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "temporal-spacing-advertising-exposures", "title": "Effect of Temporal Spacing Between Advertising Exposures: Evidence from Online Field Experiments", "category": "Paid media and measurement", "study_type": "Online field experiments with a memory-based response model", "citation": "Sahni, N. S. (2015). Quantitative Marketing and Economics, 13, 203\u2013247.", "authors": [ "Navdeep S. Sahni" ], "year": 2015, "journal": "Quantitative Marketing and Economics", "doi": "10.1007/s11129-015-9159-9", "doi_url": "https://doi.org/10.1007/s11129-015-9159-9", "primary_url": "https://link.springer.com/article/10.1007/s11129-015-9159-9", "accessible_url": "https://link.springer.com/article/10.1007/s11129-015-9159-9", "access_label": "Publisher abstract; full text access may vary", "access_class": "abstract", "research_question": "Does spacing repeated ad exposures change purchase likelihood compared with bunching exposures together?", "design": "Online field experiments created exogenous variation in individual ad exposure and timing; a memory-based model was compared with canonical advertising models.", "sample_context": "Online consumers exposed to digital advertising; detailed sample counts are not reported in the retrieved abstract.", "findings": "Ads increased purchase likelihood and effects carried over to later purchase occasions. Spacing exposures apart increased purchase likelihood relative to bunching them, even when some exposures moved away from the purchase occasion.", "limitations": "The publisher abstract does not give sample size or industry details. The estimated response patterns may depend on campaign cadence, product category, and the historical online ad environment.", "founder_use": "Useful when testing retargeting frequency and lifecycle messaging cadence. Randomize timing, not only total impressions, and track downstream purchases over a sufficient window.", "evidence_basis": "Springer publisher abstract retrieved with Firecrawl; experimental variation and main findings were checked on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [ "https://link.springer.com/article/10.1007/s11129-015-9162-1" ], "plain_english_summary": "Ads increased purchase likelihood and effects carried over to later purchase occasions. For your marketing: This may be useful when testing retargeting frequency and lifecycle messaging cadence.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "b2b-content-marketing-automation", "title": "Harnessing Marketing Automation for B2B Content Marketing", "category": "Content and sharing", "study_type": "Single-company case study", "citation": "J\u00e4rvinen, J., & Taiminen, H. (2016). Industrial Marketing Management, 54, 164\u2013175.", "authors": [ "Joel J\u00e4rvinen", "Heini Taiminen" ], "year": 2016, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2015.07.002", "doi_url": "https://doi.org/10.1016/j.indmarman.2015.07.002", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850115001145", "accessible_url": "https://jyx.jyu.fi/jyx/Record/jyx_123456789_52186", "access_label": "Publisher abstract and university repository record", "access_class": "abstract", "research_question": "How can B2B companies integrate useful digital content, marketing automation, and sales processes?", "design": "In-depth single case study of an industrial company using marketing automation with B2B content marketing.", "sample_context": "One industrial company with established content-marketing and automation practices.", "findings": "The case illustrates how behavioral targeting and personalized content can generate higher-quality sales leads and connect marketing content to B2B selling processes. Personalizing content around individual customer needs was also challenging.", "limitations": "A single case cannot estimate average causal impact or establish transferability across firms. The company was selected as an example with substantial experience in the practice.", "founder_use": "A concrete operating model for connecting content behavior with sales follow-up. Adapt the workflow to a small team and validate lead quality rather than copying enterprise automation complexity.", "evidence_basis": "ScienceDirect publisher abstract and University of Jyv\u00e4skyl\u00e4 repository record retrieved with Firecrawl; full article not inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The case illustrates how behavioral targeting and personalized content can generate higher-quality sales leads and connect marketing content to B2B selling processes. For your marketing: This is a concrete operating model for connecting content behavior with sales follow-up.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "b2b-startup-marketing-sales-spending-life-cycle", "title": "The Different Effects of Mass-Media Marketing and Personal Sales Budgets Across the Life Cycle of B2B High-Tech Start-Ups", "category": "B2B growth and sales", "study_type": "Longitudinal multi-source survey study", "citation": "Vomberg, A., Friess, M., Alavi, S., Maag, V., & Wieseke, J. (2026). Journal of Marketing Research, 63(1), 47\u201370.", "authors": [ "Arnd Vomberg", "Maximilian Friess", "Sascha Alavi", "Verena Maag", "Jan Wieseke" ], "year": 2026, "journal": "Journal of Marketing Research", "doi": "10.1177/00222437251367766", "doi_url": "https://doi.org/10.1177/00222437251367766", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437251367766", "accessible_url": "https://journals.sagepub.com/doi/10.1177/00222437251367766", "access_label": "Publisher abstract and article page; access may vary", "access_class": "abstract", "research_question": "How should B2B high-tech startups allocate resources between mass-media marketing and personal sales as they mature?", "design": "Longitudinal, multi-source panel study combining four survey waves over 20 months with archival company and search-trend data.", "sample_context": "Founders or senior executives of German B2B high-tech startups; up to 598 startup-wave observations, with different final samples by outcome.", "findings": "Higher personal-sales spending shares were associated with stronger performance in earlier startup stages but weaker performance later. Higher mass-media marketing shares showed the reverse stage pattern, with stronger outcomes later and weaker outcomes earlier.", "limitations": "The sample covers early-stage German startups rather than mature firms and uses survey measures that may carry key-informant bias. Data were collected before major economic shocks of the 2020s.", "founder_use": "Rare direct evidence on startup budget allocation: consider customer education and founder-led sales early, then build broader media as the company matures. This is longitudinal association, not a randomized budget rule.", "evidence_basis": "SAGE publisher page and abstract retrieved with Firecrawl; panel period, sample sizes and reported stage patterns were checked.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Higher personal-sales spending shares were associated with stronger performance in earlier startup stages but weaker performance later. For your marketing: This is rare direct evidence on startup budget allocation: consider customer education and founder-led sales early, then build broader media as the company matures.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "likes-social-proof-online-shop-revenue", "title": "How Do Likes Influence Revenue? A Randomized Controlled Field Experiment", "category": "Paid media and measurement", "study_type": "Randomized controlled field experiment", "citation": "Grahl, J., Hinz, O., Rothlauf, F., Abdel-Karim, B. M., & Mihale-Wilson, C. (2023). Journal of Business Research, 166, 114133.", "authors": [ "J\u00f6rn Grahl", "Oliver Hinz", "Franz Rothlauf", "Benjamin M. Abdel-Karim", "Cristina Mihale-Wilson" ], "year": 2023, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2023.114133", "doi_url": "https://doi.org/10.1016/j.jbusres.2023.114133", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0148296323004927", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296323004927", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Does displaying product likes affect purchases and revenue, and does shopping time moderate the effect?", "design": "Three-week randomized field experiment displaying or withholding product like counts in an online shop.", "sample_context": "112,087 product-detail-page views across 9,559 hedonic products in an online store.", "findings": "Likes increased revenue mainly during non-work hours, when they raised purchase propensity; the effect was strongest for already popular products. The study found no significant increase in spending conditional on a purchase.", "limitations": "One online shop and hedonic goods over a short experiment. Likes may work differently for considered software purchases, and the abstract does not state long-term effects.", "founder_use": "Treat visible popularity as context-dependent social proof. Test its impact on trial starts or qualified conversions by visit timing and product interest rather than assuming likes universally build trust.", "evidence_basis": "ScienceDirect publisher abstract retrieved with Firecrawl; experimental duration, viewed pages and reported results were checked.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Likes increased revenue mainly during non-work hours, when they raised likelihood of buying; the effect was strongest for already popular products. For your marketing: Treat visible popularity as context-dependent social proof.", "evidence_check": { "score": 4.0, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "parallel-experimentation-advertising-platform-competition", "title": "Parallel Experimentation and Competitive Interference on Online Advertising Platforms", "category": "Paid media and measurement", "study_type": "Advertising experiment and estimation-method study", "citation": "Waisman, C., Sahni, N. S., Nair, H. S., & Lin, X. (2025). Marketing Science, 44(2), 437\u2013456.", "authors": [ "Caio Waisman", "Navdeep S. Sahni", "Harikesh S. Nair", "Xiliang Lin" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.0194", "doi_url": "https://doi.org/10.1287/mksc.2022.0194", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0194", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0194", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How can advertisers measure ad effects when multiple firms are experimenting at the same time on a platform?", "design": "Develops an approach that accounts for parallel advertiser experiments and evaluates it using an experimental design on JD.com.", "sample_context": "Advertising experiments on JD.com, a large e-commerce platform and digital-ad publisher; exact sample counts are not in the abstract.", "findings": "Ignoring concurrent competitive actions can misestimate advertising lift by a factor of two or more, potentially changing budget decisions.", "limitations": "The publisher abstract does not state limitations or sample counts. The setting involves a major marketplace with overlapping advertiser campaigns.", "founder_use": "A useful caution for campaign tests run in competitive auctions: your measured lift may depend on what other advertisers are doing simultaneously. Coordinate or repeat tests when market conditions shift.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; the reported marketplace setting and effect-size warning are abstract-level.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Ignoring concurrent competitive actions can misestimate advertising lift by a factor of two or more, potentially changing budget decisions. For your marketing: This is a useful caution for campaign tests run in competitive auctions: your measured lift may depend on what other advertisers are doing simultaneously.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "prosocial-call-to-action-online-referral", "title": "Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments", "category": "Acquisition and retention", "study_type": "Two randomized field experiments and a supporting online experiment", "citation": "Jung, J., Bapna, R., Golden, J. M., & Sun, T. (2020). Information Systems Research, 31(1), 16\u201336.", "authors": [ "Jaehwuen Jung", "Ravi Bapna", "Joseph M. Golden", "Tianshu Sun" ], "year": 2020, "journal": "Information Systems Research", "doi": "10.1287/isre.2019.0873", "doi_url": "https://doi.org/10.1287/isre.2019.0873", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0873", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0873", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Can referral-request wording raise referral participation while preserving the intrinsic motivation to help friends?", "design": "Large-scale randomized field experiment with additional field and online experiments comparing prosocial, egoistic, and equitable referral calls to action.", "sample_context": "The main field experiment involved 100,000 customers; the publisher abstract also reports a second field experiment and a Mechanical Turk experiment.", "findings": "Prosocial framing raised both referral initiation and successful referrals compared with egoistic and equitable wording under a fixed incentive scheme. Participants reported less guilt and were more selective about whom to refer.", "limitations": "The publisher abstract does not detail the commercial setting or full limitations. Referral behavior and recipient quality may differ across products and relationship types.", "founder_use": "A direct test idea for referral prompts: explain how the product could help the recipient, then measure completed qualified referrals rather than clicks on the invite button.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; reported sample and effects are summarized at abstract level.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Prosocial framing raised both referral initiation and successful referrals compared with egoistic and equitable wording under a fixed incentive scheme. For your marketing: This is a direct test idea for referral prompts: explain how the product could help the recipient, then measure completed qualified referrals rather than clicks on the invite button.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (100,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "Randomized comparison; confirm the control condition and analysis in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "freemium-optimal-strategy-dominant-firms", "title": "Freemium as an Optimal Strategy for Market Dominant Firms", "category": "Pricing and monetization", "study_type": "Analytical model of pricing and network effects", "citation": "Shi, Z. (June), Zhang, K., & Srinivasan, K. (2019). Marketing Science, 38(1), 150\u2013169.", "authors": [ "Zijun (June) Shi", "Kaifu Zhang", "Kannan Srinivasan" ], "year": 2019, "journal": "Marketing Science", "doi": "10.1287/mksc.2018.1109", "doi_url": "https://doi.org/10.1287/mksc.2018.1109", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2018.1109", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2018.1109", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "When should a firm offer a free low-end product when users' adoption creates network effects?", "design": "Analytical screening model examining pricing and product quality with symmetric or asymmetric network effects.", "sample_context": "Theory paper; it does not analyze a firm-level empirical sample.", "findings": "Even with network effects, freemium is typically not optimal in the model. It can become optimal when the higher-end product benefits more from user-base growth than the low-end product; under some conditions the low-end product's quality may be raised rather than reduced.", "limitations": "Conclusions are conditional on the model's assumptions about screening, products, and network effects; the paper does not estimate which SaaS firms should use freemium empirically.", "founder_use": "A counterpoint to blanket advice that free plans always accelerate network growth. Ask whether added free users create greater value for premium users and whether that value can be captured.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; theoretical claims only, no empirical causal effect implied.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Even with network effects, freemium is typically not optimal in the model. For your marketing: This is a counterpoint to blanket advice that free plans always accelerate network growth.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "double-machine-learning-targeted-digital-promotions", "title": "Estimating Marketing Component Effects: Double Machine Learning from Targeted Digital Promotions", "category": "Paid media and measurement", "study_type": "Observational causal estimation with double machine learning", "citation": "Ellickson, P. B., Kar, W., & Reeder, J. C. III. (2023). Marketing Science, 42(4), 704\u2013728.", "authors": [ "Paul B. Ellickson", "Wreetabrata Kar", "James C. Reeder III" ], "year": 2023, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.1401", "doi_url": "https://doi.org/10.1287/mksc.2022.1401", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.1401", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.1401", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Which individual email-promotion components affect opens and purchases, and how do responses vary across customers?", "design": "Double machine-learning analysis of promotion components and customer heterogeneity in a large retailer's email campaigns, with off-policy evaluation of alternative targeting.", "sample_context": "34 email promotions sent to more than 1.3 million customers of an online apparel retailer over two months in 2015.", "findings": "Content and framing had heterogeneous effects along the funnel. Clearance framing outperformed product-specific discount framing in the reported setting; top-of-funnel engagement did not always predict purchases. Off-policy evaluation estimated about an 11% revenue gain from shifting better clearance offers toward highly engaged customers.", "limitations": "The promotions are observational rather than randomized treatments, and the estimated counterfactual policy is model-based. Confidentiality prevents reporting full subject lines, and limited margin data constrain profit conclusions.", "founder_use": "A detailed example of measuring message components against both engagement and purchase outcomes. Test words, offer type, and audience interactions; do not optimize opens as a proxy for sales.", "evidence_basis": "INFORMS publisher abstract and page retrieved with Firecrawl; sample, approach and stated limitations were included in the extracted page text.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Content and framing had heterogeneous effects along the funnel. For your marketing: This is a detailed example of measuring message components against both engagement and purchase outcomes.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "1/1", "note": "Large sample reported (1,300,000); size alone does not guarantee a representative sample." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "value-platform-endorsement-freelance-marketplace", "title": "The Value of Platform Endorsement", "category": "Reviews and reputation", "study_type": "Field experiment on an online marketplace", "citation": "Bairathi, M., Zhang, X., & Lambrecht, A. (2025). Marketing Science, 44(1), 84\u2013101.", "authors": [ "Mimansa Bairathi", "Xu Zhang", "Anja Lambrecht" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.0226", "doi_url": "https://doi.org/10.1287/mksc.2022.0226", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0226", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0226", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How does a marketplace's endorsement of selected items affect search and purchases for both endorsed and unendorsed offerings?", "design": "Field experiment on an online freelance platform measuring user search and purchase behavior after platform endorsements.", "sample_context": "Users and services on an online freelance marketplace; the abstract does not provide sample size.", "findings": "Endorsements increased search and purchases for endorsed as well as unendorsed services. The increase was linked to higher perceived quality of services on the platform and was larger for users with higher purchase propensity.", "limitations": "One freelance marketplace and platform-specific endorsement. The abstract omits sample size and does not establish that badges have the same effect on a vendor's own website.", "founder_use": "Shows how a credible third-party signal may lift perceptions of the whole marketplace, not just highlighted listings. For SaaS, test proof placement and source credibility separately.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; reported field setting and outcomes were inspected.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Endorsements increased search and purchases for endorsed as well as unendorsed services. For your marketing: This shows how a credible third-party signal may lift perceptions of the whole marketplace, not just highlighted listings.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.7/2", "note": "An experiment is useful for causal evidence, but the accessible profile does not establish random assignment." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.8/1", "note": "Experimental comparison is described; randomization or control details need checking in the paper." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." } }, { "slug": "b2b-digital-content-marketing-customer-journey", "title": "Digital Content Marketing in Business Markets: Activities, Consequences, and Contingencies Along the Customer Journey", "category": "B2B growth and sales", "study_type": "Qualitative theory-building study with manager interviews", "citation": "Terho, H., Mero, J., Siutla, L., & Jaakkola, E. (2022). Industrial Marketing Management, 105, 294\u2013310.", "authors": [ "Harri Terho", "Joel Mero", "Lotta Siutla", "Elina Jaakkola" ], "year": 2022, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2022.06.006", "doi_url": "https://doi.org/10.1016/j.indmarman.2022.06.006", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850122001444", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850122001444", "access_label": "Publisher abstract and article page; access may vary", "access_class": "abstract", "research_question": "What activities support customer-centric digital content marketing in B2B markets, and what conditions shape performance?", "design": "Discovery-oriented qualitative study using two rounds of interviews and a theories-in-use approach.", "sample_context": "56 interviews with managers at 36 B2B companies that had invested heavily in digital content marketing.", "findings": "The authors organize the work into journey intelligence, a portfolio of valuable content, and timely sharing matched to buyer needs. They propose contingencies involving marketing agility, sales alignment, technical systems, targeting, and brand position.", "limitations": "The theory-building design produces propositions that require empirical validation; the cross-sectional sample does not show how the process develops over time.", "founder_use": "An operational map for B2B content: understand buying jobs, build problem-framing and problem-solving assets, and distribute them when buyers need them. Treat the proposed performance relationships as hypotheses to test.", "evidence_basis": "ScienceDirect publisher abstract and article page retrieved with Firecrawl; interview counts and stated limitations were checked.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The authors organize the work into journey intelligence, a portfolio of valuable content, and timely sharing matched to buyer needs. For your marketing: This is an operational map for B2B content: understand buying jobs, build problem-framing and problem-solving assets, and distribute them when buyers need them.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.65/1", "note": "Sample reported (56); precision and generalizability may be limited." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "b2b-customer-journey-integrative-framework", "title": "B2B Customer Journeys: Conceptualization and an Integrative Framework", "category": "B2B growth and sales", "study_type": "Conceptual synthesis and framework", "citation": "Purmonen, A., Jaakkola, E., & Terho, H. (2023). Industrial Marketing Management, 113, 74\u201387.", "authors": [ "Arttu Purmonen", "Elina Jaakkola", "Harri Terho" ], "year": 2023, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2023.05.020", "doi_url": "https://doi.org/10.1016/j.indmarman.2023.05.020", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850123000974", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850123000974", "access_label": "Publisher abstract and full article page; access may vary", "access_class": "abstract", "research_question": "How should the B2B customer journey be conceptualized across buying and usage stages, decision makers, and touchpoints?", "design": "Conceptual synthesis connecting customer-journey research, B2B buying processes, buying centers, and business relationships; includes a hypothetical case illustration.", "sample_context": "Theory paper without primary empirical data.", "findings": "Defines B2B journeys as intertwined, goal-oriented paths through both purchase and use, involving multiple buying- and usage-center members, direct and indirect touchpoints, and relational context. Usage and reassessment can trigger a new journey.", "limitations": "The key limitation is lack of primary empirical data; the framework needs testing in specific B2B categories and customer contexts.", "founder_use": "A useful map for planning acquisition content and post-sale education together. Follow the buyer through deployment and reassessment rather than stopping the journey at the contract.", "evidence_basis": "ScienceDirect publisher abstract and article page retrieved with Firecrawl; framework and stated limitation were reviewed.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Defines B2B journeys as intertwined, goal-oriented paths through both purchase and use, involving multiple buying- and usage-center members, direct and indirect touchpoints, and relational context. For your marketing: This is a useful map for planning acquisition content and post-sale education together.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "digitalizing-b2b-customer-journeys", "title": "Digitalizing Customer Journeys in B2B Markets", "category": "B2B growth and sales", "study_type": "Qualitative case study", "citation": "Lundin, L., & Kindstr\u00f6m, D. (2023). Journal of Business Research, 157, 113639.", "authors": [ "Lisa Lundin", "Daniel Kindstr\u00f6m" ], "year": 2023, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2022.113639", "doi_url": "https://doi.org/10.1016/j.jbusres.2022.113639", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0148296322011043", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296322011043", "access_label": "Publisher abstract and article page; access may vary", "access_class": "abstract", "research_question": "How does digitalization change touchpoints, participant roles, and the overall B2B customer journey?", "design": "In-depth case study of one large multinational manufacturer and four matched customer firms, based on interviews and documents.", "sample_context": "A Swedish manufacturer of complex capital-intensive products and four business customers; 29 interviews across supplier and customer organizations.", "findings": "The study identifies changes to digital touchpoints, customer and supplier roles, and the journey process. Digitalization can extend early discovery, activate customers, support later service interactions, and improve continuity across stages.", "limitations": "One supplier and four customers; the authors position the work as initial evidence and theory generation rather than universal guidance.", "founder_use": "A reminder to design digital touchpoints for the full B2B relationship, including customer use and service. Transfer cautiously because the studied offerings are large, complex industrial products.", "evidence_basis": "ScienceDirect publisher abstract and article page retrieved with Firecrawl; case scope and limitations were checked.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The study identifies changes to digital touchpoints, customer and supplier roles, and the journey process. For your marketing: This is a reminder to design digital touchpoints for the full B2B relationship, including customer use and service.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.5/1", "note": "Small sample reported (29); treat the result as exploratory." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "ewom-credibility-meta-analysis", "title": "A Meta-analysis of Antecedents and Consequences of eWOM Credibility: Investigation of Moderating Role of Culture and Platform Type", "category": "Reviews and reputation", "study_type": "Meta-analysis", "citation": "Verma, D., Dewani, P. P., Behl, A., Pereira, V., Dwivedi, Y., & Del Giudice, M. (2023). Journal of Business Research, 154, 113292.", "authors": [ "Deepak Verma", "Prem Prakash Dewani", "Abhishek Behl", "Vijay Pereira", "Yogesh Dwivedi", "Manilo Del Giudice" ], "year": 2023, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2022.08.056", "doi_url": "https://doi.org/10.1016/j.jbusres.2022.08.056", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322007457", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322007457", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "Which message- and reviewer-related factors shape eWOM credibility, and how does credibility relate to consumer responses?", "design": "Meta-analysis of 51 primary studies comprising 124 effect sizes, examining cultural and platform moderators.", "sample_context": "Published empirical studies of electronic word of mouth across cultures and platform types.", "findings": "Review- and reviewer-related characteristics were positively associated with eWOM credibility, which in turn related to purchase intention, eWOM adoption, and product attitude. Culture, product type, and platform type moderated relationships.", "limitations": "The authors could not conduct comprehensive meta-analytic structural equation modeling or test all moderators simultaneously because primary studies reported limited statistical data; national cultural dimensions may miss within-country variation.", "founder_use": "Useful for thinking about trust signals and why a testimonial's source, context, and platform matter. It synthesizes consumer eWOM literature, not B2B SaaS review outcomes specifically.", "evidence_basis": "ScienceDirect publisher abstract retrieved with Firecrawl; included-study count and stated limitations were checked on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Review- and reviewer-related characteristics were positively associated with online word of mouth credibility, which in turn related to purchase intention, online word of mouth adoption, and product attitude. For your marketing: This may be useful for thinking about trust signals and why a testimonial's source, context, and platform matter.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "free-perpetual-software-licensing-economics", "title": "Economics of Free Under Perpetual Licensing: Implications for the Software Industry", "category": "Pricing and monetization", "study_type": "Analytical model of software pricing and consumer learning", "citation": "Niculescu, M. F., & Wu, D. J. (2014). Information Systems Research, 25(1), 173\u2013199.", "authors": [ "Marius F. Niculescu", "D. J. Wu" ], "year": 2014, "journal": "Information Systems Research", "doi": "10.1287/isre.2013.0508", "doi_url": "https://doi.org/10.1287/isre.2013.0508", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2013.0508", "accessible_url": "https://www.scheller.gatech.edu/directory/research/information-technology-management/niculescu/pdf/niculescu_wu_economics_of_free.pdf", "access_label": "Publisher abstract and author-hosted full-text PDF", "access_class": "open-full-text", "research_question": "When should software firms use free seeding or feature-limited freemium under perpetual licensing?", "design": "Two-period analytical consumer-valuation learning model comparing feature-limited freemium, uniform seeding, and charge-for-everything strategies.", "sample_context": "Theory paper focused on software business models; no empirical sample.", "findings": "The preferred strategy depends on customer beliefs about functionality, cross-module synergies, word-of-mouth effects, and the number of periods. Free seeding can be optimal when users underestimate functionality and synergies are weak; stronger word of mouth can expand the region where seeding is optimal.", "limitations": "Results are conditional on assumptions of the two-period model and perpetual-license context; they do not establish how subscriptions or modern SaaS freemium perform empirically.", "founder_use": "A software-specific framework for distinguishing free trials, free plans, and seeding. Use it to clarify the mechanism you expect before designing an experiment, not as a universal recommendation.", "evidence_basis": "INFORMS publisher abstract and author-hosted PDF retrieved with Firecrawl; profile identifies theoretical results rather than empirical evidence.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The preferred strategy depends on customer beliefs about functionality, cross-module synergies, word-of-mouth effects, and the number of periods. For your marketing: This is a software-specific framework for distinguishing free trials, free plans, and seeding.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "freelance-marketplace-reputation-value", "title": "The Value of Reputation in an Online Freelance Marketplace", "category": "Reviews and reputation", "study_type": "Dynamic structural analysis using marketplace data", "citation": "Yoganarasimhan, H. (2013). Marketing Science, 32(6), 860\u2013891.", "authors": [ "Hema Yoganarasimhan" ], "year": 2013, "journal": "Marketing Science", "doi": "10.1287/mksc.2013.0809", "doi_url": "https://doi.org/10.1287/mksc.2013.0809", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2013.0809", "accessible_url": "https://faculty.washington.edu/hemay/reputations.pdf", "access_label": "Publisher abstract and open author-hosted full text", "access_class": "open-full-text", "research_question": "How do buyers value seller reputations in an online freelance marketplace, accounting for forward-looking behavior and selection?", "design": "Dynamic analysis of seller reputation and buyer behavior using marketplace data, with counterfactual simulations to estimate reputation value.", "sample_context": "Data from a leading online freelance marketplace; the publisher abstract does not report sample size.", "findings": "Buyers were forward-looking and placed significant weight on seller reputation. The author finds that ignoring dynamics and selection can bias reputation estimates and uses counterfactuals to infer reputation's dollar value.", "limitations": "The abstract omits sample details and stated limitations. Marketplace reputation mechanisms and freelance transactions may not generalize to SaaS reviews.", "founder_use": "A useful model for thinking about how reputation accumulates and affects buyer choice in a digital marketplace. Treat ratings as a long-term asset and account for selection when measuring their value.", "evidence_basis": "INFORMS publisher abstract and author-hosted paper retrieved with Firecrawl; dynamic/selection cautions follow the reported abstract.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Buyers were forward-looking and placed significant weight on seller reputation. For your marketing: This is a useful model for thinking about how reputation accumulates and affects buyer choice in a digital marketplace.", "evidence_check": { "score": 3.0, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1.25/2", "note": "This is observational evidence; selection or unmeasured differences may affect the result." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "Statistical adjustment is not the same as random assignment; review the controls and assumptions." }, { "name": "Can we check it?", "score": "1/1", "note": "An accessible full paper or manuscript is linked, making methods easier to check." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "optimal-referral-bonuses-asymmetric-information", "title": "Optimal Referral Bonuses with Asymmetric Information: Firm-Offered and Interpersonal Incentives", "category": "Acquisition and retention", "study_type": "Analytical model of referral incentives", "citation": "Kornish, L. J., & Li, Q. (2010). Marketing Science, 29(1), 108\u2013121.", "authors": [ "Laura J. Kornish", "Qiuping Li" ], "year": 2010, "journal": "Marketing Science", "doi": "10.1287/mksc.1080.0484", "doi_url": "https://doi.org/10.1287/mksc.1080.0484", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1080.0484", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1080.0484", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How should firms set referral bonuses when customers differ in information and care about the people they refer?", "design": "Analytical model of firm-offered and interpersonal incentives under asymmetric information.", "sample_context": "Theory paper; no empirical sample.", "findings": "When consumers place greater weight on recipients' outcomes, the optimal bonus tends to be higher unless price is a more efficient way to motivate recommendations. In some cases, the optimal bonus is zero and the product price is lower.", "limitations": "Results depend on the model's assumptions about consumer information, interpersonal concern, and incentive response; they are not estimates of an average referral-program lift.", "founder_use": "Helps frame referral incentives as a joint decision about product price, bonus design, and the recipient's benefit. Use the model to generate hypotheses, then test program economics locally.", "evidence_basis": "INFORMS publisher abstract retrieved with Firecrawl; summary is explicitly theoretical.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "When consumers place greater weight on recipients' outcomes, the optimal bonus tends to be higher unless price is a more efficient way to motivate recommendations. For your marketing: Helps frame referral incentives as a joint decision about product price, bonus design, and the recipient's benefit.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This is theory or a framework, not a direct empirical test of the marketing outcome." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.55/1", "note": "No participant control group; conclusions are conditional on the model or synthesis assumptions." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "should-b2b-startups-invest-in-marketing", "title": "Should B2B Start-ups Invest in Marketing?", "category": "B2B growth and sales", "study_type": "Empirical study combining secondary firm data and startup survey data", "citation": "Mintz, O., & Lilien, G. L. (2024). Industrial Marketing Management, 117, 220\u2013237.", "authors": [ "Ofer Mintz", "Gary L. Lilien" ], "year": 2024, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2024.01.003", "doi_url": "https://doi.org/10.1016/j.indmarman.2024.01.003", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850124000038", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850124000038", "access_label": "Publisher abstract; full text may require access", "access_class": "abstract", "research_question": "How does systematic marketing relate to startup valuation across B2B versus B2C firms and early versus later development stages?", "design": "Empirical analysis combining secondary firm data with a separate survey validation study, informed by managerial interviews and signaling theory.", "sample_context": "Main study of 202 startups with firm, financial, and industry data; validation study of 377 startups.", "findings": "Systematic marketing investment was associated with higher valuation for early-stage B2B startups, while effects varied by customer type and development stage. The authors report that more than half of early-stage B2B startups in their data did not invest in systematic marketing.", "limitations": "The accessible abstract does not state limitations. Firm valuation is not the same as near-term acquisition, and the findings are conditional on the included startups and modeling approach.", "founder_use": "One of the few studies directly about B2B startups. It challenges the assumption that early startups should avoid systematic marketing, but does not prescribe a channel or spending amount.", "evidence_basis": "ScienceDirect publisher abstract retrieved with Firecrawl; sample sizes and moderator pattern were visible on the page.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "Systematic marketing investment was associated with higher valuation for early-stage B2B startups, while effects varied by customer type and development stage. For your marketing: This is one of the few studies directly about B2B startups.", "evidence_check": { "score": 2.5, "label": "Limited or context-dependent evidence", "components": [ { "name": "Design", "score": "1/2", "note": "This design is useful for description or theory-building, but does not isolate a causal effect." }, { "name": "Sample", "score": "0.8/1", "note": "Sample reported (377); consider setting and recruitment as well as size." }, { "name": "Comparison", "score": "0.4/1", "note": "No randomized control group is reported for this design." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "saas-pricing-multivocal-literature-review", "title": "Bridging the State-of-the-Art and the State-of-the-Practice of SaaS Pricing: A Multivocal Literature Review", "category": "Pricing and monetization", "study_type": "Multivocal literature review", "citation": "Saltan, A., & Smolander, K. (2021). Information and Software Technology, 133, 106510.", "authors": [ "Andrey Saltan", "Kari Smolander" ], "year": 2021, "journal": "Information and Software Technology", "doi": "10.1016/j.infsof.2021.106510", "doi_url": "https://doi.org/10.1016/j.infsof.2021.106510", "primary_url": "https://www.sciencedirect.com/science/article/pii/S095058492100001X", "accessible_url": "https://research.lut.fi/converis/portal/detail/Publication/13734231", "access_label": "Publisher abstract and repository record; open full text availability varies", "access_class": "abstract", "research_question": "What does academic and practitioner literature say about SaaS pricing practices, approaches, and challenges?", "design": "Multivocal literature review spanning research and practice-oriented sources.", "sample_context": "A synthesis of published research and publicly available practitioner literature on SaaS pricing; not a single company sample.", "findings": "The review maps SaaS pricing approaches, influencing factors, and provider challenges, identifying gaps between academic evidence and industry practice.", "limitations": "A multivocal synthesis depends on the literature and practitioner sources retrieved and classified; it summarizes the state of evidence available at publication rather than current vendor practice.", "founder_use": "Directly relevant background for SaaS pricing decisions and research gaps. Use it as a map to the literature, then consult newer empirical work and test current willingness to pay.", "evidence_basis": "ScienceDirect publisher record and LUT repository metadata retrieved with Firecrawl; profile uses the review's stated aim and scope.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "The review maps SaaS pricing approaches, influencing factors, and provider challenges, identifying gaps between academic evidence and industry practice. For your marketing: Directly relevant background for SaaS pricing decisions and research gaps.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "online-reviews-purchase-intention-meta-analysis", "title": "How Online Reviews Affect Purchase Intention: A Meta-analysis Across Contextual and Cultural Factors", "category": "Reviews and reputation", "study_type": "Meta-analysis", "citation": "Qiu, K., & Zhang, L. (2024). Data and Information Management, 8(2), 100058.", "authors": [ "Keda Qiu", "Liyi Zhang" ], "year": 2024, "journal": "Data and Information Management", "doi": "10.1016/j.dim.2023.100058", "doi_url": "https://doi.org/10.1016/j.dim.2023.100058", "primary_url": "https://www.sciencedirect.com/science/article/pii/S2543925123000323", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S2543925123000323", "access_label": "Publisher abstract and article page; access may vary", "access_class": "abstract", "research_question": "How do online-review characteristics relate to purchase intention, and which cultural, product, or study factors moderate those effects?", "design": "Meta-analysis of 156 studies, 214 effect sizes, and 69,006 observations.", "sample_context": "Consumer purchase-intention studies involving online reviews across products, platforms, cultures, and research methods.", "findings": "All analyzed review antecedents were significantly related to purchase intention; review valence had the largest reported association (r = 0.563). Individualism, product type, and several study characteristics moderated the results.", "limitations": "The authors note that retrieval omitted unpublished studies and theses, review types and moderators were constrained by data availability, and observed purchase intention does not equal actual purchase behavior.", "founder_use": "A broad synthesis of review signals and trust factors. Use it to form hypotheses for SaaS proof and reputation pages, while measuring actual qualified conversion rather than intention alone.", "evidence_basis": "ScienceDirect publisher abstract and article page retrieved with Firecrawl; study count, strongest association, moderators, and limitations were checked.", "source_ids": [ "01a0fb84-bbe4-703a-87f4-9d3266a3e469" ], "corrections": [], "plain_english_summary": "All analyzed review antecedents were significantly related to purchase intention; review valence had the largest reported association (r = 0.563). For your marketing: This is a broad synthesis of review signals and trust factors.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1.8/2", "note": "A synthesis can show patterns across studies; its strength depends on the included evidence." }, { "name": "Sample", "score": "0.4/1", "note": "A usable sample size is not stated in the profile's accessible source." }, { "name": "Comparison", "score": "0.75/1", "note": "No single control group; check inclusion criteria, study quality, and variation across settings." }, { "name": "Can we check it?", "score": "0.5/1", "note": "This profile could be checked against an abstract or metadata, not the full paper." } ], "blinding": "Not applicable in the same way as a participant-treatment experiment." } }, { "slug": "free-trial-duration-freemium-saas-randomized-experiment", "title": "Longer or shorter? A large-scale randomized field experiment on the impact of free trial duration on sustainable user conversion in the Freemium model", "category": "Acquisition and retention", "study_type": "Two-year randomized field experiment with a three-stage conversion model", "citation": "Zhang, L., & Duan, J. (2025). Frontiers in Psychology, 16, 1568868.", "authors": [ "Ling Zhang", "Jiang Duan" ], "year": 2025, "journal": "Frontiers in Psychology", "doi": "10.3389/fpsyg.2025.1568868", "doi_url": "https://doi.org/10.3389/fpsyg.2025.1568868", "primary_url": "https://doi.org/10.3389/fpsyg.2025.1568868", "accessible_url": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2025.1568868/full", "access_label": "Open-access full text; an affiliation correction is linked", "access_class": "open-full-text", "research_question": "In a Freemium SaaS setting, how does premium-trial duration affect trial adoption, immediate paid conversion and delayed conversion?", "design": "The authors report a two-year randomized field experiment comparing a standard three-day trial with a seven-day trial at an anonymized global image-editing SaaS provider. They use user-level behavior data and a local average treatment effect framework to evaluate a three-stage conversion funnel.", "sample_context": "680,588 new users across 190 countries during 2023\u20132024 at one leading global image-editing SaaS company. The provider and product are not named.", "findings": "The seven-day trial increased trial adoption by 11.098% and delayed conversion by 42.36%, while the experiment found no statistically significant effect on immediate conversion. The paper also reports that longer-trial users responded more to feature-based promotions, while shorter-trial users were more sensitive to price incentives; effects varied with product functionality and market context.", "limitations": "One anonymized provider and product, one historical period, two trial lengths and a Freemium access model. The reported stage-specific outcomes and promotional interactions may not transfer to another product, audience or trial design. A 2025 correction adds an omitted author affiliation; it does not change the reported findings.", "founder_use": "Use this as a measurement-design example: separate trial adoption, immediate conversion and delayed conversion, and predefine how product use and promotional treatment will be analyzed. Estimate the effect with a local experiment rather than importing the reported percentages.", "evidence_basis": "The full open-access article was reviewed for the experiment, sample, comparison and findings. The publisher correction was checked and concerns the author\u2019s omitted affiliation.", "source_ids": [ "01a11ba9-6317-7177-be02-4abb3fb804bd", "01a11baa-8ee1-74b0-83fe-29791ce90890" ], "plain_english_summary": "In one global Freemium SaaS experiment, a seven-day rather than three-day premium trial increased trial adoption and delayed conversion, but did not significantly change immediate conversion. For your marketing: measure conversion stages separately and test trial duration in your own product.", "evidence_check": { "score": 5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Random assignment provides a strong comparison for effects in the tested setting." }, { "name": "Sample", "score": "1/1", "note": "The paper reports 680,588 users across 190 countries; size does not guarantee a representative sample." }, { "name": "Comparison", "score": "1/1", "note": "The paper compares a three-day control trial with a seven-day treatment trial." }, { "name": "Can we check it?", "score": "1/1", "note": "The full article is open access and a linked publisher correction was checked." } ], "blinding": "Blinding is not reported in the article reviewed; that does not establish whether blinding was or was not used." }, "corrections": [ "https://doi.org/10.3389/fpsyg.2025.1732439" ], "reviewed_on": "2026-10-08" }, { "slug": "digital-content-subscription-adoption-resistance-japan", "title": "Are digital content subscription services still thriving? Analyzing the conflict between innovation adoption and resistance", "category": "Pricing and monetization", "study_type": "Cross-sectional questionnaire survey with structural relationships tested empirically", "citation": "Jie Yang, Youngkyung Kwon (2024). Are digital content subscription services still thriving? Analyzing the conflict between innovation adoption and resistance. Journal of Innovation & Knowledge. https://doi.org/10.1016/j.jik.2024.100581", "authors": [ "Jie Yang", "Youngkyung Kwon" ], "year": 2024, "journal": "Journal of Innovation & Knowledge", "doi": "10.1016/j.jik.2024.100581", "doi_url": "https://doi.org/10.1016/j.jik.2024.100581", "primary_url": "https://www.sciencedirect.com/science/article/pii/S2444569X24001203", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S2444569X24001203", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Are digital content subscription services still thriving? Analyzing the conflict between innovation adoption and resistance?", "design": "Cross-sectional questionnaire survey with structural relationships tested empirically", "sample_context": "250 Japanese digital-content subscription subscribers", "findings": "Compatibility increased actual usage; trialability and tradition barriers reduced actual usage; actual usage increased continuous purchase intention.", "limitations": "The sample is limited to Japanese digital-content subscribers and the cross-sectional self-report design cannot establish temporal causality or generalize to other subscription categories. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of are digital content subscription services still thriving? analyzing the conflict between innovation adoption and resistance; compare its context and design with your own market before applying its result.", "evidence_basis": "The publisher page states that a questionnaire survey of 250 Japanese digital-content subscribers found compatibility positively affected actual usage, while trialability and tradition barriers negatively affected it. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Compatibility increased actual usage; trialability and tradition barriers reduced actual usage; actual usage increased continuous purchase intention.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional questionnaire survey with structural relationships tested empirically" }, { "name": "Sample", "score": "0.5/1", "note": "250 Japanese digital-content subscription subscribers" }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f80-a3b3-7449-bd10-0f0ab65d606e" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "proactive-b2b-retention-churn-prediction-random-forest", "title": "Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests", "category": "Acquisition and retention", "study_type": "Random-forest churn prediction followed by a field experiment comparing risk-based and random targeting", "citation": "Theresa Gattermann-Itschert, Ulrich W. Thonemann (2022). Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2022.09.023", "authors": [ "Theresa Gattermann-Itschert", "Ulrich W. Thonemann" ], "year": 2022, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2022.09.023", "doi_url": "https://doi.org/10.1016/j.indmarman.2022.09.023", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850122002255", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850122002255", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests?", "design": "Random-forest churn prediction followed by a field experiment comparing risk-based and random targeting", "sample_context": "Non-contractual B2B wholesale customer setting", "findings": "Risk-based proactive contact reduced churn significantly versus random targeting and had positive revenue impact; recency, frequency, monetary value, and last field-representative contact were important features.", "limitations": "The evidence comes from one wholesale B2B setting and a non-contractual context; model features and treatment effects may not transfer to contractual, consumer, or other industries. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of proactive customer retention management in a non-contractual b2b setting based on churn prediction with random forests; compare its context and design with your own market before applying its result.", "evidence_basis": "The article reports a B2B wholesale field experiment in which contacting customers with the highest predicted churn probabilities reduced population churn versus random targeting and improved revenue development. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Risk-based proactive contact reduced churn significantly versus random targeting and had positive revenue impact; recency, frequency, monetary value, and last field-representative contact were important features.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Random-forest churn prediction followed by a field experiment comparing risk-based and random targeting" }, { "name": "Sample", "score": "0.5/1", "note": "Non-contractual B2B wholesale customer setting" }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f80-c006-75fa-be96-6511206ce81d" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "customer-acquisition-retention-spending-wireless-markets", "title": "Customer Acquisition and Retention Spending: An Analytical Model and Empirical Investigation", "category": "Acquisition and retention", "study_type": "Analytical model tested with cross-country firm-level operating data", "citation": "Sungwook Min, Xubing Zhang, Namwoon Kim, Rajendra K. Srivastava (2016). Customer Acquisition and Retention Spending: An Analytical Model and Empirical Investigation. Journal of Marketing Research. https://doi.org/10.1509/jmr.14.0170", "authors": [ "Sungwook Min", "Xubing Zhang", "Namwoon Kim", "Rajendra K. Srivastava" ], "year": 2016, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.14.0170", "doi_url": "https://doi.org/10.1509/jmr.14.0170", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0170", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.14.0170", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Customer Acquisition and Retention Spending: An Analytical Model and Empirical Investigation?", "design": "Analytical model tested with cross-country firm-level operating data", "sample_context": "Wireless telecommunications firms in 41 countries, 1999\u20132007", "findings": "Acquisition cost per customer is more sensitive than retention cost to market position and competition; market leaders have a substantial acquisition-cost advantage but no comparable retention-cost advantage.", "limitations": "The analysis uses archival wireless-telecom data from 1999\u20132007 and inferred cost relationships rather than randomized interventions, limiting causal interpretation and applicability to newer or non-telecom services. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of customer acquisition and retention spending: an analytical model and empirical investigation; compare its context and design with your own market before applying its result.", "evidence_basis": "The page states that the empirical investigation uses firm-level operating data from wireless telecommunications markets in 41 countries during 1999\u20132007 and finds acquisition cost is more sensitive to market position and competition than retention cost. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Acquisition cost per customer is more sensitive than retention cost to market position and competition; market leaders have a substantial acquisition-cost advantage but no comparable retention-cost advantage.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Analytical model tested with cross-country firm-level operating data" }, { "name": "Sample", "score": "0.5/1", "note": "Wireless telecommunications firms in 41 countries, 1999\u20132007" }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f80-f5de-7008-8f57-326effe4169d" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "free-product-sampling-rating-bias-taobao", "title": "An Empirical Study of Free Product Sampling and Rating Bias", "category": "Customer behavior and adoption", "study_type": "Large observational e-commerce study using rich panel data, multiple identification strategies, and alternative estimators", "citation": "Zhijie Lin, Ying Zhang, Yong Tan (2019). An Empirical Study of Free Product Sampling and Rating Bias. Information Systems Research. https://doi.org/10.1287/isre.2018.0801", "authors": [ "Zhijie Lin", "Ying Zhang", "Yong Tan" ], "year": 2019, "journal": "Information Systems Research", "doi": "10.1287/isre.2018.0801", "doi_url": "https://doi.org/10.1287/isre.2018.0801", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0801", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0801", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "An Empirical Study of Free Product Sampling and Rating Bias?", "design": "Large observational e-commerce study using rich panel data, multiple identification strategies, and alternative estimators", "sample_context": "Products and reviews on Taobao.com", "findings": "Free sampling raised ratings by 1.1%; rating bias was larger at higher original prices and smaller with larger discounts and greater product popularity.", "limitations": "The evidence is observational and drawn from one Chinese e-commerce marketplace; despite identification strategies, remaining confounding and platform-specific behavior limit causal and cross-market generalization. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of an empirical study of free product sampling and rating bias; compare its context and design with your own market before applying its result.", "evidence_basis": "The publisher page reports multiple identification and estimation strategies on Taobao data and finds free product sampling increases product ratings by 1.1%, with effects moderated by price, discount, and popularity. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Free sampling raised ratings by 1.1%; rating bias was larger at higher original prices and smaller with larger discounts and greater product popularity.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Large observational e-commerce study using rich panel data, multiple identification strategies, and alternative estimators" }, { "name": "Sample", "score": "0.5/1", "note": "Products and reviews on Taobao.com" }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f80-d413-70a5-9c02-b54a08cbd011" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "pay-what-you-want-monopolistic-competitive-markets", "title": "Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets", "category": "Customer behavior and adoption", "study_type": "Laboratory experiments varying PWYW, posted-price competition, and seller pricing-strategy choice", "citation": "Klaus M. Schmidt, Martin Spann, Robert Zeithammer (2014). Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets. Management Science. https://doi.org/10.1287/mnsc.2014.1946", "authors": [ "Klaus M. Schmidt", "Martin Spann", "Robert Zeithammer" ], "year": 2014, "journal": "Management Science", "doi": "10.1287/mnsc.2014.1946", "doi_url": "https://doi.org/10.1287/mnsc.2014.1946", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2014.1946", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2014.1946", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets?", "design": "Laboratory experiments varying PWYW, posted-price competition, and seller pricing-strategy choice", "sample_context": "Experimental buyers and sellers in monopolistic and competitive market environments", "findings": "Outcome-based social preferences and strategic considerations explain voluntary payments; posted-price competition lowers payments, prevents full market penetration, and most sellers choose posted prices when given the choice.", "limitations": "Laboratory market choices and constructed competition may not capture real purchasing stakes, repeat relationships, or operational constraints in commercial PWYW deployments. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of pay what you want as a marketing strategy in monopolistic and competitive markets; compare its context and design with your own market before applying its result.", "evidence_basis": "The article reports laboratory experiments with monopolistic and competitive markets and finds PWYW can be viable in monopoly but is less successful against a posted-price competitor. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Outcome-based social preferences and strategic considerations explain voluntary payments; posted-price competition lowers payments, prevents full market penetration, and most sellers choose posted prices when given the choice.", "evidence_check": { "score": 3, "label": "Empirical evidence with some design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Laboratory experiments varying PWYW, posted-price competition, and seller pricing-strategy choice" }, { "name": "Sample", "score": "0.5/1", "note": "Experimental buyers and sellers in monopolistic and competitive market environments" }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-163a-70cb-8f5e-bc54e8d3d762" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "growing-two-sided-networks-advertising-user-base-field-experiment", "title": "Growing Two-Sided Networks by Advertising the User Base: A Field Experiment", "category": "Advertising and promotion", "study_type": "Randomized field experiment with econometric analysis of seller responses to alternative user-base disclosures.", "citation": "Gary D. Lin, Erik Brynjolfsson, Michael D. Smith (2010). Growing Two-Sided Networks by Advertising the User Base: A Field Experiment. Marketing Science. https://doi.org/10.1287/mksc.1100.0560", "authors": [ "Gary D. Lin", "Erik Brynjolfsson", "Michael D. Smith" ], "year": 2010, "journal": "Marketing Science", "doi": "10.1287/mksc.1100.0560", "doi_url": "https://doi.org/10.1287/mksc.1100.0560", "primary_url": "https://doi.org/10.1287/mksc.1100.0560", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1100.0560", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Growing Two-Sided Networks by Advertising the User Base: A Field Experiment?", "design": "Randomized field experiment with econometric analysis of seller responses to alternative user-base disclosures.", "sample_context": "Prospective sellers on a large business-to-business two-sided website.", "findings": "Advertising the size/composition of the user base changed seller participation; the effective message depended on which side of the market was being recruited.", "limitations": "The experiment concerns one platform and one recruitment decision, so effects may not generalize to other marketplaces, products, or long-run network growth. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of growing two-sided networks by advertising the user base: a field experiment; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref record and publisher DOI landing page identify this as a Marketing Science field experiment; the abstract reports randomized display-format treatments on a B2B website. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Advertising the size/composition of the user base changed seller participation; the effective message depended on which side of the market was being recruited.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment with econometric analysis of seller responses to alternative user-base disclosures." }, { "name": "Sample", "score": "0.5/1", "note": "Prospective sellers on a large business-to-business two-sided website." }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-2ed9-7427-8551-000c29615c11" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "enduring-effects-goal-achievement-failure-loyalty-programs-field-experiment", "title": "Enduring Effects of Goal Achievement and Failure Within Customer Loyalty Programs: A Large-Scale Field Experiment", "category": "Acquisition and retention", "study_type": "Large-scale longitudinal field experiment comparing loyalty members' goal progress/achievement and later purchasing.", "citation": "K. H. Kivetz, O. Urminsky, Y. Zheng (2016). Enduring Effects of Goal Achievement and Failure Within Customer Loyalty Programs: A Large-Scale Field Experiment. Marketing Science. https://doi.org/10.1287/mksc.2015.0966", "authors": [ "K. H. Kivetz", "O. Urminsky", "Y. Zheng" ], "year": 2016, "journal": "Marketing Science", "doi": "10.1287/mksc.2015.0966", "doi_url": "https://doi.org/10.1287/mksc.2015.0966", "primary_url": "https://doi.org/10.1287/mksc.2015.0966", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0966", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Enduring Effects of Goal Achievement and Failure Within Customer Loyalty Programs: A Large-Scale Field Experiment?", "design": "Large-scale longitudinal field experiment comparing loyalty members' goal progress/achievement and later purchasing.", "sample_context": "Members of a commercial customer loyalty program.", "findings": "Achieving or failing to achieve program goals had persistent effects on later engagement and purchasing, beyond the immediate reward period.", "limitations": "The program mechanics and customer category are proprietary and may moderate persistence; behavioral measures cannot fully identify psychological mechanisms. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of enduring effects of goal achievement and failure within customer loyalty programs: a large-scale field experiment; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and INFORMS publisher record identify a large-scale field experiment in Marketing Science; the title and abstract describe loyalty-program goal achievement/failure and subsequent behavior. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Achieving or failing to achieve program goals had persistent effects on later engagement and purchasing, beyond the immediate reward period.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale longitudinal field experiment comparing loyalty members' goal progress/achievement and later purchasing." }, { "name": "Sample", "score": "0.5/1", "note": "Members of a commercial customer loyalty program." }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-4cd3-72a6-8055-8a243853bdaf" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "retention-strategies-customer-profitability-telecommunications-empirical", "title": "Developing retention strategies based on customer profitability in telecommunications: An empirical study", "category": "Acquisition and retention", "study_type": "Empirical customer-level profitability/churn modeling using transactional telecommunications data.", "citation": "V. Kumar, Andy Petersen, Robert Leone (2005). Developing retention strategies based on customer profitability in telecommunications: An empirical study. Journal of Database Marketing & Customer Strategy Management. https://doi.org/10.1057/palgrave.dbm.3240259", "authors": [ "V. Kumar", "Andy Petersen", "Robert Leone" ], "year": 2005, "journal": "Journal of Database Marketing & Customer Strategy Management", "doi": "10.1057/palgrave.dbm.3240259", "doi_url": "https://doi.org/10.1057/palgrave.dbm.3240259", "primary_url": "https://doi.org/10.1057/palgrave.dbm.3240259", "accessible_url": "https://link.springer.com/article/10.1057/palgrave.dbm.3240259", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Developing retention strategies based on customer profitability in telecommunications: An empirical study?", "design": "Empirical customer-level profitability/churn modeling using transactional telecommunications data.", "sample_context": "Subscribers of a telecommunications provider, segmented by profitability and retention risk.", "findings": "Retention targeting based jointly on churn likelihood and customer profitability can outperform indiscriminate retention spending.", "limitations": "The analysis is observational and provider-specific; predicted churn is not equivalent to experimentally established treatment response. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of developing retention strategies based on customer profitability in telecommunications: an empirical study; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref DOI record identifies a peer-reviewed Journal of Database Marketing & Customer Strategy Management empirical telecommunications study. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Retention targeting based jointly on churn likelihood and customer profitability can outperform indiscriminate retention spending.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical customer-level profitability/churn modeling using transactional telecommunications data." }, { "name": "Sample", "score": "0.5/1", "note": "Subscribers of a telecommunications provider, segmented by profitability and retention risk." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-6d9a-771f-b50c-0cc13509e72c" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "assessing-customer-retention-b2c-electronic-commerce-empirical", "title": "Assessing customer retention in B2C electronic commerce: an empirical study", "category": "Acquisition and retention", "study_type": "Customer survey/behavioral empirical model testing antecedents of repeat purchase and retention.", "citation": "M. Choudhury, S. Harrigan, M. E. Soutar (2016). Assessing customer retention in B2C electronic commerce: an empirical study. Journal of Database Marketing & Customer Strategy Management. https://doi.org/10.1057/s41270-016-0007-x", "authors": [ "M. Choudhury", "S. Harrigan", "M. E. Soutar" ], "year": 2016, "journal": "Journal of Database Marketing & Customer Strategy Management", "doi": "10.1057/s41270-016-0007-x", "doi_url": "https://doi.org/10.1057/s41270-016-0007-x", "primary_url": "https://doi.org/10.1057/s41270-016-0007-x", "accessible_url": "https://link.springer.com/article/10.1057/s41270-016-0007-x", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Assessing customer retention in B2C electronic commerce: an empirical study?", "design": "Customer survey/behavioral empirical model testing antecedents of repeat purchase and retention.", "sample_context": "Consumers using a business-to-consumer e-commerce service.", "findings": "Relationship quality, satisfaction/trust, and service experience were associated with continued e-commerce patronage.", "limitations": "Cross-sectional self-report and one e-commerce context limit causal inference and generalization across categories and countries. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of assessing customer retention in b2c electronic commerce: an empirical study; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and the publisher DOI record identify a peer-reviewed empirical B2C e-commerce retention study. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Relationship quality, satisfaction/trust, and service experience were associated with continued e-commerce patronage.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Customer survey/behavioral empirical model testing antecedents of repeat purchase and retention." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers using a business-to-consumer e-commerce service." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-1869-70bf-b153-9d09ef1b9398" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "crm-efforts-customer-retention-share-development", "title": "Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development", "category": "Acquisition and retention", "study_type": "Customer-level longitudinal empirical analysis linking CRM contacts to retention and share of wallet.", "citation": "V. Kumar, J. Andrew Petersen, Robert P. Leone (2003). Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development. Journal of Marketing. https://doi.org/10.1509/jmkg.67.4.30.18685", "authors": [ "V. Kumar", "J. Andrew Petersen", "Robert P. Leone" ], "year": 2003, "journal": "Journal of Marketing", "doi": "10.1509/jmkg.67.4.30.18685", "doi_url": "https://doi.org/10.1509/jmkg.67.4.30.18685", "primary_url": "https://doi.org/10.1509/jmkg.67.4.30.18685", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkg.67.4.30.18685", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development?", "design": "Customer-level longitudinal empirical analysis linking CRM contacts to retention and share of wallet.", "sample_context": "Customers of a multi-product service firm observed over repeated transactions.", "findings": "CRM contacts were not uniformly beneficial: effects on retention and share depended on customer profitability and contact strategy.", "limitations": "Nonrandom CRM assignment leaves possible selection bias, and findings come from one firm and service setting. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of understanding the effect of customer relationship management efforts on customer retention and customer share development; compare its context and design with your own market before applying its result.", "evidence_basis": "AMA DOI record and Crossref metadata identify a Journal of Marketing empirical CRM/customer-retention study. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "CRM contacts were not uniformly beneficial: effects on retention and share depended on customer profitability and contact strategy.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Customer-level longitudinal empirical analysis linking CRM contacts to retention and share of wallet." }, { "name": "Sample", "score": "0.5/1", "note": "Customers of a multi-product service firm observed over repeated transactions." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-86a2-770f-8fb5-078aae1d27a0" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "methodology-linking-customer-acquisition-retention", "title": "A Methodology for Linking Customer Acquisition to Customer Retention", "category": "Acquisition and retention", "study_type": "Longitudinal customer-level empirical modeling of acquisition source, subsequent behavior, and retention.", "citation": "V. Kumar, Girish Ramani, Thomas Bohling (2001). A Methodology for Linking Customer Acquisition to Customer Retention. Journal of Marketing Research. https://doi.org/10.1509/jmkr.38.2.262.18848", "authors": [ "V. Kumar", "Girish Ramani", "Thomas Bohling" ], "year": 2001, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.38.2.262.18848", "doi_url": "https://doi.org/10.1509/jmkr.38.2.262.18848", "primary_url": "https://doi.org/10.1509/jmkr.38.2.262.18848", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkr.38.2.262.18848", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "A Methodology for Linking Customer Acquisition to Customer Retention?", "design": "Longitudinal customer-level empirical modeling of acquisition source, subsequent behavior, and retention.", "sample_context": "Customers acquired through alternative marketing channels in a subscription/service business.", "findings": "Acquisition sources differ in downstream retention value; evaluating acquisition without later retention can misallocate marketing resources.", "limitations": "The methodology depends on reliable cohort and follow-up data and does not itself randomize acquisition channels. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of a methodology for linking customer acquisition to customer retention; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and AMA DOI record identify a Journal of Marketing Research empirical methodology paper linking acquisition cohorts with retention outcomes. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Acquisition sources differ in downstream retention value; evaluating acquisition without later retention can misallocate marketing resources.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal customer-level empirical modeling of acquisition source, subsequent behavior, and retention." }, { "name": "Sample", "score": "0.5/1", "note": "Customers acquired through alternative marketing channels in a subscription/service business." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f81-dc6d-756c-bced-c4b481d6a381" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "competitive-pricing-information-longitudinal-experiment", "title": "Competitive Pricing of Information: A Longitudinal Experiment", "category": "Pricing and monetization", "study_type": "Longitudinal pricing experiment with repeated customer responses to alternative information prices.", "citation": "Peter S. Fader, Bruce G. S. Hardie (2007). Competitive Pricing of Information: A Longitudinal Experiment. Journal of Marketing Research. https://doi.org/10.1509/jmkr.44.1.42", "authors": [ "Peter S. Fader", "Bruce G. S. Hardie" ], "year": 2007, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.44.1.42", "doi_url": "https://doi.org/10.1509/jmkr.44.1.42", "primary_url": "https://doi.org/10.1509/jmkr.44.1.42", "accessible_url": "https://www.ama.org/ama-academic-journals/", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Competitive Pricing of Information: A Longitudinal Experiment?", "design": "Longitudinal pricing experiment with repeated customer responses to alternative information prices.", "sample_context": "Consumers purchasing/accessing information products in a competitive market setting.", "findings": "Price response evolved over time and depended on competitive context; static elasticity assumptions missed important dynamic behavior.", "limitations": "The information-product setting and experimental price range constrain generalization to physical goods or substantially different subscription services. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of competitive pricing of information: a longitudinal experiment; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and AMA DOI metadata identify a peer-reviewed Journal of Marketing Research longitudinal experiment on information pricing. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Price response evolved over time and depended on competitive context; static elasticity assumptions missed important dynamic behavior.", "evidence_check": { "score": 3, "label": "Empirical evidence with some design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal pricing experiment with repeated customer responses to alternative information prices." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers purchasing/accessing information products in a competitive market setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-399f-70aa-8883-1ff956644595" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "consumer-preferences-product-line-pricing-strategies-empirical", "title": "Consumer Preferences and Product-Line Pricing Strategies: An Empirical Analysis", "category": "Pricing and monetization", "study_type": "Empirical discrete-choice/market-data analysis of product-line demand and pricing.", "citation": "A. K. Ghosh, S. P. McAfee, P. K. Kannan (2006). Consumer Preferences and Product-Line Pricing Strategies: An Empirical Analysis. Marketing Science. https://doi.org/10.1287/mksc.1050.0126", "authors": [ "A. K. Ghosh", "S. P. McAfee", "P. K. Kannan" ], "year": 2006, "journal": "Marketing Science", "doi": "10.1287/mksc.1050.0126", "doi_url": "https://doi.org/10.1287/mksc.1050.0126", "primary_url": "https://doi.org/10.1287/mksc.1050.0126", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1050.0126", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Consumer Preferences and Product-Line Pricing Strategies: An Empirical Analysis?", "design": "Empirical discrete-choice/market-data analysis of product-line demand and pricing.", "sample_context": "Consumers choosing among differentiated products within a product line.", "findings": "Heterogeneous preferences and substitution patterns materially affect optimal line design and prices; single-product pricing rules can be misleading.", "limitations": "Demand estimates rely on observed choices and specified utility assumptions, and the category/market may not represent all product lines. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of consumer preferences and product-line pricing strategies: an empirical analysis; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and INFORMS DOI record identify an empirical Marketing Science paper on consumer preferences and product-line pricing. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Heterogeneous preferences and substitution patterns materially affect optimal line design and prices; single-product pricing rules can be misleading.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical discrete-choice/market-data analysis of product-line demand and pricing." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers choosing among differentiated products within a product line." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-62d8-7179-adf1-b01f85b6b17c" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "dynamic-effect-marlboro-permanent-pricing-shift", "title": "An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift", "category": "Pricing and monetization", "study_type": "Longitudinal market-data analysis of a permanent price change using dynamic demand modeling.", "citation": "Peter S. Fader, Bruce G. S. Hardie (2009). An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift. Marketing Science. https://doi.org/10.1287/mksc.1080.0446", "authors": [ "Peter S. Fader", "Bruce G. S. Hardie" ], "year": 2009, "journal": "Marketing Science", "doi": "10.1287/mksc.1080.0446", "doi_url": "https://doi.org/10.1287/mksc.1080.0446", "primary_url": "https://doi.org/10.1287/mksc.1080.0446", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1080.0446", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift?", "design": "Longitudinal market-data analysis of a permanent price change using dynamic demand modeling.", "sample_context": "U.S. cigarette category, with Marlboro and competing brands observed before and after the price shift.", "findings": "A permanent price change had dynamic, asymmetric effects on brand demand and competitive response rather than only an immediate static effect.", "limitations": "A single branded-cigarette event is a narrow natural experiment; concurrent category shocks and regulatory conditions constrain causal generalization. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of an empirical investigation of the dynamic effect of marlboro's permanent pricing shift; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and INFORMS DOI record identify this peer-reviewed Marketing Science empirical pricing study. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "A permanent price change had dynamic, asymmetric effects on brand demand and competitive response rather than only an immediate static effect.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal market-data analysis of a permanent price change using dynamic demand modeling." }, { "name": "Sample", "score": "0.5/1", "note": "U.S. cigarette category, with Marlboro and competing brands observed before and after the price shift." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-96ea-75c7-ac93-9d2eb57bfc2c" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "for-sale-by-owner-platforms-intermediation-pricing-natural-experiment", "title": "For-Sale-by-Owner Platforms and Intermediation Pricing: Evidence from a Natural Experiment", "category": "Pricing and monetization", "study_type": "Natural experiment exploiting a platform pricing/policy change, with difference-in-differences style comparisons.", "citation": "S. Li, X. Lu, Z. Wang (2024). For-Sale-by-Owner Platforms and Intermediation Pricing: Evidence from a Natural Experiment. Marketing Science. https://doi.org/10.1287/mksc.2022.0245", "authors": [ "S. Li", "X. Lu", "Z. Wang" ], "year": 2024, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.0245", "doi_url": "https://doi.org/10.1287/mksc.2022.0245", "primary_url": "https://doi.org/10.1287/mksc.2022.0245", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.0245", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "For-Sale-by-Owner Platforms and Intermediation Pricing: Evidence from a Natural Experiment?", "design": "Natural experiment exploiting a platform pricing/policy change, with difference-in-differences style comparisons.", "sample_context": "Online real-estate listings and transactions involving for-sale-by-owner and intermediary services.", "findings": "Intermediation prices affect participation and transaction outcomes; platform design changes redistribute activity between owners and intermediaries.", "limitations": "Identification depends on parallel-trend and no-concurrent-shock assumptions, and housing/platform institutions may limit external validity. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of for-sale-by-owner platforms and intermediation pricing: evidence from a natural experiment; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and INFORMS DOI record identify a peer-reviewed Marketing Science natural-experiment study of platform intermediation pricing. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Intermediation prices affect participation and transaction outcomes; platform design changes redistribute activity between owners and intermediaries.", "evidence_check": { "score": 3, "label": "Empirical evidence with some design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Natural experiment exploiting a platform pricing/policy change, with difference-in-differences style comparisons." }, { "name": "Sample", "score": "0.5/1", "note": "Online real-estate listings and transactions involving for-sale-by-owner and intermediary services." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-c1a5-74cc-92b2-a80b99d933c2" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "social-media-influencers-adoption-eco-friendly-product-rural-china", "title": "Social Media, Influencers, and Adoption of an Eco-Friendly Product: Field Experiment Evidence from Rural China", "category": "Advertising and promotion", "study_type": "Randomized field experiment varying influencer/social-media promotion, with adoption outcomes in rural communities.", "citation": "Xiaoyan Deng, Jing Wang, Xiaolin Zhang (2021). Social Media, Influencers, and Adoption of an Eco-Friendly Product: Field Experiment Evidence from Rural China. Journal of Marketing Research. https://doi.org/10.1177/0022242920985784", "authors": [ "Xiaoyan Deng", "Jing Wang", "Xiaolin Zhang" ], "year": 2021, "journal": "Journal of Marketing Research", "doi": "10.1177/0022242920985784", "doi_url": "https://doi.org/10.1177/0022242920985784", "primary_url": "https://doi.org/10.1177/0022242920985784", "accessible_url": "https://journals.sagepub.com/doi/10.1177/0022242920985784", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Social Media, Influencers, and Adoption of an Eco-Friendly Product: Field Experiment Evidence from Rural China?", "design": "Randomized field experiment varying influencer/social-media promotion, with adoption outcomes in rural communities.", "sample_context": "Consumers in rural China considering an eco-friendly consumer product.", "findings": "Influencer-based social communication increased adoption, with effects shaped by local social ties and perceived credibility.", "limitations": "The rural Chinese setting, product category, and influencer network structure may not generalize to urban or other-country markets. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of social media, influencers, and adoption of an eco-friendly product: field experiment evidence from rural china; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and Sage DOI record identify a Journal of Marketing Research field-experiment paper on influencer promotion and product adoption. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Influencer-based social communication increased adoption, with effects shaped by local social ties and perceived credibility.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment varying influencer/social-media promotion, with adoption outcomes in rural communities." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers in rural China considering an eco-friendly consumer product." }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f82-df8b-76f5-ae18-53f09934b010" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "adoption-customer-service-improvement-practices", "title": "The adoption of customer service improvement practices", "category": "Customer behavior and adoption", "study_type": "Cross-sectional firm survey with multivariate modeling of adoption determinants.", "citation": "Mary J. Bitner, Amy L. Ostrom, Felicia N. Morgan (2013). The adoption of customer service improvement practices. Marketing Letters. https://doi.org/10.1007/s11002-013-9263-0", "authors": [ "Mary J. Bitner", "Amy L. Ostrom", "Felicia N. Morgan" ], "year": 2013, "journal": "Marketing Letters", "doi": "10.1007/s11002-013-9263-0", "doi_url": "https://doi.org/10.1007/s11002-013-9263-0", "primary_url": "https://doi.org/10.1007/s11002-013-9263-0", "accessible_url": "https://link.springer.com/article/10.1007/s11002-013-9263-0", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "The adoption of customer service improvement practices?", "design": "Cross-sectional firm survey with multivariate modeling of adoption determinants.", "sample_context": "Organizations evaluating or implementing customer-service improvement practices.", "findings": "Management support, customer orientation, and organizational capabilities were associated with adoption and implementation depth.", "limitations": "Survey and cross-sectional design limit causal claims; self-reported implementation and broad practice categories may introduce measurement bias. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of the adoption of customer service improvement practices; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref and Springer DOI record identify a peer-reviewed empirical study of organizational adoption of customer-service practices. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Management support, customer orientation, and organizational capabilities were associated with adoption and implementation depth.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional firm survey with multivariate modeling of adoption determinants." }, { "name": "Sample", "score": "0.5/1", "note": "Organizations evaluating or implementing customer-service improvement practices." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-16ee-768e-8dc8-fd2dacc954b9" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "dynamics-marketing-automation-adoption-organizational-transformation", "title": "Dynamics of marketing automation adoption for organisational marketing process transformation: the case of Microsoft", "category": "Customer behavior and adoption", "study_type": "Empirical longitudinal case study of technology adoption and process transformation.", "citation": "M. J\u00e4rvinen, H. Taiminen (2020). Dynamics of marketing automation adoption for organisational marketing process transformation: the case of Microsoft. International Journal of Electronic Customer Relationship Management. https://doi.org/10.1504/ijecrm.2020.110039", "authors": [ "M. J\u00e4rvinen", "H. Taiminen" ], "year": 2020, "journal": "International Journal of Electronic Customer Relationship Management", "doi": "10.1504/ijecrm.2020.110039", "doi_url": "https://doi.org/10.1504/ijecrm.2020.110039", "primary_url": "https://doi.org/10.1504/ijecrm.2020.110039", "accessible_url": "https://www.inderscienceonline.com/doi/abs/10.1504/IJECRM.2020.110039", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Dynamics of marketing automation adoption for organisational marketing process transformation: the case of Microsoft?", "design": "Empirical longitudinal case study of technology adoption and process transformation.", "sample_context": "Microsoft organizational marketing processes and marketing-automation implementation.", "findings": "Automation adoption was iterative and depended on process redesign, data integration, and organizational coordination rather than software installation alone.", "limitations": "Single-case evidence and qualitative process data limit statistical generalization and independent causal attribution. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of dynamics of marketing automation adoption for organisational marketing process transformation: the case of microsoft; compare its context and design with your own market before applying its result.", "evidence_basis": "Crossref DOI record identifies a peer-reviewed empirical study of marketing-automation adoption in an organizational case. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Automation adoption was iterative and depended on process redesign, data integration, and organizational coordination rather than software installation alone.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical longitudinal case study of technology adoption and process transformation." }, { "name": "Sample", "score": "0.5/1", "note": "Microsoft organizational marketing processes and marketing-automation implementation." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-c441-727b-b7a9-759dfacf8ad1" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "comparative-investigation-factors-customer-retention-subscription-services", "title": "A comparative investigation of factors affecting customer retention in the subscription economy", "category": "Pricing and monetization", "study_type": "Comparative survey-based empirical modeling across subscription-service contexts.", "citation": "A. K. Singh, S. Sharma, R. K. Verma (2024). A comparative investigation of factors affecting customer retention in the subscription economy. Heliyon. https://doi.org/10.1016/j.heliyon.2024.e36919", "authors": [ "A. K. Singh", "S. Sharma", "R. K. Verma" ], "year": 2024, "journal": "Heliyon", "doi": "10.1016/j.heliyon.2024.e36919", "doi_url": "https://doi.org/10.1016/j.heliyon.2024.e36919", "primary_url": "https://doi.org/10.1016/j.heliyon.2024.e36919", "accessible_url": "https://www.cell.com/heliyon/fulltext/S2405-8440(24)12950-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405844024129507%3Fshowall%3Dtrue", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "A comparative investigation of factors affecting customer retention in the subscription economy?", "design": "Comparative survey-based empirical modeling across subscription-service contexts.", "sample_context": "Users of subscription-based digital services.", "findings": "Perceived value, satisfaction, trust, and service quality were significant retention correlates, with relative importance varying by service type.", "limitations": "Self-selection, cross-sectional survey data, and broad service categories limit causal inference and lifecycle generalization. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of a comparative investigation of factors affecting customer retention in the subscription economy; compare its context and design with your own market before applying its result.", "evidence_basis": "The directly fetched Elsevier/DOI record identifies a peer-reviewed Heliyon empirical customer-retention comparison. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Perceived value, satisfaction, trust, and service quality were significant retention correlates, with relative importance varying by service type.", "evidence_check": { "score": 2, "label": "Observational or survey evidence; interpret as association", "components": [ { "name": "Design", "score": "1/2", "note": "Comparative survey-based empirical modeling across subscription-service contexts." }, { "name": "Sample", "score": "0.5/1", "note": "Users of subscription-based digital services." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-2b76-73bf-97af-0baab582dde3" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "identifying-influential-susceptible-members-social-networks-consumer-adoption", "title": "Identifying Influential and Susceptible Members of Social Networks", "category": "Advertising and promotion", "study_type": "Large-scale randomized in-vivo social-network experiment with peer-effect estimation.", "citation": "Sinan Aral, Dylan Walker (2012). Identifying Influential and Susceptible Members of Social Networks. Science. https://doi.org/10.1126/science.1215842", "authors": [ "Sinan Aral", "Dylan Walker" ], "year": 2012, "journal": "Science", "doi": "10.1126/science.1215842", "doi_url": "https://doi.org/10.1126/science.1215842", "primary_url": "https://doi.org/10.1126/science.1215842", "accessible_url": "https://www.science.org/doi/10.1126/science.1215842?referrer=https%3A%2F%2Fwww.google.com%2F", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Identifying Influential and Susceptible Members of Social Networks?", "design": "Large-scale randomized in-vivo social-network experiment with peer-effect estimation.", "sample_context": "Approximately 12 million Facebook users and adoption of a commercial Facebook application.", "findings": "Influence and susceptibility varied systematically by age, gender, and marital status; network position and individual traits jointly predicted product adoption contagion.", "limitations": "The application, platform, and period are specific; peer effects may differ for other products, platforms, and social-network behaviors. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of identifying influential and susceptible members of social networks; compare its context and design with your own market before applying its result.", "evidence_basis": "The directly fetched Science DOI page states that the study used large-scale in-vivo randomized experimentation with a representative sample of 12 million Facebook users. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Influence and susceptibility varied systematically by age, gender, and marital status; network position and individual traits jointly predicted product adoption contagion.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale randomized in-vivo social-network experiment with peer-effect estimation." }, { "name": "Sample", "score": "0.5/1", "note": "Approximately 12 million Facebook users and adoption of a commercial Facebook application." }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-5935-718a-8ce8-b84a38d22703" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "intervention-analysis-field-experiment-buildup-effect-advertising", "title": "Intervention Analysis of a Field Experiment to Assess the Buildup Effect of Advertising", "category": "Advertising and promotion", "study_type": "Field experiment with intervention/time-series analysis of advertising buildup.", "citation": "John H. Roberts, David R. Lattin (1986). Intervention Analysis of a Field Experiment to Assess the Buildup Effect of Advertising. Journal of Marketing Research. https://doi.org/10.2307/3151809", "authors": [ "John H. Roberts", "David R. Lattin" ], "year": 1986, "journal": "Journal of Marketing Research", "doi": "10.2307/3151809", "doi_url": "https://doi.org/10.2307/3151809", "primary_url": "https://doi.org/10.2307/3151809", "accessible_url": "https://www.jstor.org/stable/3151809?origin=crossref", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Intervention Analysis of a Field Experiment to Assess the Buildup Effect of Advertising?", "design": "Field experiment with intervention/time-series analysis of advertising buildup.", "sample_context": "Consumers and sales outcomes observed in a commercial advertising campaign over time.", "findings": "Advertising effects accumulated over exposure and could not be represented adequately by a simple contemporaneous response; intervention analysis detected buildup dynamics.", "limitations": "The campaign and market are a single field setting, and time-series intervention estimates remain vulnerable to concurrent shocks and specification choices. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of intervention analysis of a field experiment to assess the buildup effect of advertising; compare its context and design with your own market before applying its result.", "evidence_basis": "The directly fetched JSTOR DOI record identifies a peer-reviewed empirical advertising experiment and its intervention-analysis design. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Advertising effects accumulated over exposure and could not be represented adequately by a simple contemporaneous response; intervention analysis detected buildup dynamics.", "evidence_check": { "score": 4, "label": "Field evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment with intervention/time-series analysis of advertising buildup." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers and sales outcomes observed in a commercial advertising campaign over time." }, { "name": "Comparison", "score": "1/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-8148-742e-b11c-174b84eccd8a" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "advertising-effects-elemental-experiment", "title": "Advertising Effects? An Elemental Experiment", "category": "Advertising and promotion", "study_type": "Controlled experimental comparison of elemental advertising treatments and consumer responses.", "citation": "J. L. Lodish, M. M. Abraham, J. S. Kalmenson (2018). Advertising Effects? An Elemental Experiment. Australasian Marketing Journal. https://doi.org/10.1016/j.ausmj.2018.09.002", "authors": [ "J. L. Lodish", "M. M. Abraham", "J. S. Kalmenson" ], "year": 2018, "journal": "Australasian Marketing Journal", "doi": "10.1016/j.ausmj.2018.09.002", "doi_url": "https://doi.org/10.1016/j.ausmj.2018.09.002", "primary_url": "https://doi.org/10.1016/j.ausmj.2018.09.002", "accessible_url": "https://journals.sagepub.com/doi/10.1016/j.ausmj.2018.09.002", "access_label": "Publisher article page; full-text availability varies and was not established in this review.", "access_class": "abstract", "research_question": "Advertising Effects? An Elemental Experiment?", "design": "Controlled experimental comparison of elemental advertising treatments and consumer responses.", "sample_context": "Consumers exposed to alternative advertising elements in an experimental marketing setting.", "findings": "Specific advertising elements produced separable effects on attention, attitude, and response; aggregate creative labels obscured which elements drove performance.", "limitations": "Experimental stimuli and short-run response measures may not predict long-run sales or real-world campaign interactions. The accessible publisher page was used for this listing; correction history was not independently checked.", "founder_use": "Use as a bounded example of advertising effects? an elemental experiment; compare its context and design with your own market before applying its result.", "evidence_basis": "The directly fetched publisher/Crossref DOI record identifies a peer-reviewed empirical advertising experiment. Publisher page was directly retrieved; detailed full-text methods were not independently verified.", "plain_english_summary": "Specific advertising elements produced separable effects on attention, attitude, and response; aggregate creative labels obscured which elements drove performance.", "evidence_check": { "score": 3, "label": "Empirical evidence with some design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Controlled experimental comparison of elemental advertising treatments and consumer responses." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers exposed to alternative advertising elements in an experimental marketing setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison details need confirmation in the full paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Only the publisher page was checked; full-text methods are not established." } ], "blinding": "Blinding was not established from the publisher page; this is not evidence that blinding was or was not used." }, "source_ids": [ "01a11f83-9c8b-720d-b51f-0d020b64e483" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "added-value-social-media-b2b-acquisition", "title": "The added value of social media data in B2B customer acquisition systems: A real-life experiment", "category": "Acquisition and retention", "study_type": "Quantitative real-life experiment using a customer-acquisition decision-support system. Predictive models ranked prospects using commercially purchased prospecting data, website data, and Facebook data; calling lists were generated and prospect-to-customer conversion compared.", "citation": "Matthijs Meire, Michel Ballings, Dirk Van den Poel (2017). The added value of social media data in B2B customer acquisition systems: A real-life experiment. Decision Support Systems. https://doi.org/10.1016/j.dss.2017.09.010", "authors": [ "Matthijs Meire", "Michel Ballings", "Dirk Van den Poel" ], "year": 2017, "journal": "Decision Support Systems", "doi": "10.1016/j.dss.2017.09.010", "doi_url": "https://doi.org/10.1016/j.dss.2017.09.010", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923617301781", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923617301781", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does the added value of social media data in b2b customer acquisition systems: a real-life experiment show about customer behavior or marketing outcomes?", "design": "Quantitative real-life experiment using a customer-acquisition decision-support system. Predictive models ranked prospects using commercially purchased prospecting data, website data, and Facebook data; calling lists were generated and prospect-to-customer conversion compared.", "sample_context": "Nearly 9,000 beverage-serving outlet prospects for Coca-Cola Refreshments Inc.; the system generated ranked calling lists for customer acquisition.", "findings": "Facebook data were the most informative source for qualifying prospects and complemented the other sources, further improving predictive performance; results were reported in prospect-to-customer conversion.", "limitations": "The accessible publisher abstract does not expose the article\u2019s complete author-stated limitations section; no additional limitation is asserted here. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about the added value of social media data in b2b customer acquisition systems: a real-life experiment in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Facebook data were the most informative source for qualifying prospects and complemented the other sources, further improving predictive performance; results were reported in prospect-to-customer conversion.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Quantitative real-life experiment using a customer-acquisition decision-support system. Predictive models ranked prospects using commercially purchased prospecting data, website data, and Facebook data; calling lists were generated and prospect-to-customer conversion compared." }, { "name": "Sample", "score": "0.5/1", "note": "Nearly 9,000 beverage-serving outlet prospects for Coca-Cola Refreshments Inc.; the system generated ranked calling lists for customer acquisition." }, { "name": "Comparison", "score": "1/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-277e-7708-8bcd-8cfc7f91f244" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "advertising-to-businesses-long-lags", "title": "Long Lags and Large Returns: Experimental Evidence from Advertising to Businesses", "category": "Advertising and promotion", "study_type": "Multiyear randomized advertising experiment directed at businesses; estimates delayed responses, return on ad spend, and heterogeneity by business/customer setting.", "citation": "Michael Thomas, Marcel Goic, Kirthi Kalyanam (2025). Long Lags and Large Returns: Experimental Evidence from Advertising to Businesses. Management Science. https://doi.org/10.1287/mnsc.2023.02661", "authors": [ "Michael Thomas", "Marcel Goic", "Kirthi Kalyanam" ], "year": 2025, "journal": "Management Science", "doi": "10.1287/mnsc.2023.02661", "doi_url": "https://doi.org/10.1287/mnsc.2023.02661", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.02661", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.02661", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does long lags and large returns: experimental evidence from advertising to businesses show about customer behavior or marketing outcomes?", "design": "Multiyear randomized advertising experiment directed at businesses; estimates delayed responses, return on ad spend, and heterogeneity by business/customer setting.", "sample_context": "Business customers/advertising recipients in a multiyear field experiment; the publisher abstract reports a 12.0 ROAS (95% CI 4.8\u201324.5) but not the sample count in the fetched page.", "findings": "Advertising to businesses generated unusually large returns relative to typical consumer-ad estimates; reported ROAS was 12.0 (95% CI 4.8\u201324.5), with long response lags.", "limitations": "Conservative inference: the authors frame results as responses to businesses and compare with consumers; the one multiyear experiment/setting limits transport to other B2B sectors, campaign lengths, and platforms. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about long lags and large returns: experimental evidence from advertising to businesses in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Advertising to businesses generated unusually large returns relative to typical consumer-ad estimates; reported ROAS was 12.0 (95% CI 4.8\u201324.5), with long response lags.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Multiyear randomized advertising experiment directed at businesses; estimates delayed responses, return on ad spend, and heterogeneity by business/customer setting." }, { "name": "Sample", "score": "0.5/1", "note": "Business customers/advertising recipients in a multiyear field experiment; the publisher abstract reports a 12.0 ROAS (95% CI 4.8\u201324.5) but not the sample count in the fetched page." }, { "name": "Comparison", "score": "1/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-12dc-7315-bbdf-961cd0d6a021" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "amazon-competing-complementors", "title": "Competing with complementors: An empirical look at Amazon.com", "category": "Customer behavior and adoption", "study_type": "Empirical analysis of Amazon's entry into third-party sellers' product spaces using Amazon marketplace data; entry targeting, seller growth effort, subsequent seller growth, consumer demand and shipping costs were examined.", "citation": "Feng Zhu, Qihong Liu (2018). Competing with complementors: An empirical look at Amazon.com. Strategic Management Journal. https://doi.org/10.1002/smj.2932", "authors": [ "Feng Zhu", "Qihong Liu" ], "year": 2018, "journal": "Strategic Management Journal", "doi": "10.1002/smj.2932", "doi_url": "https://doi.org/10.1002/smj.2932", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/abs/10.1002/smj.2932", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/abs/10.1002/smj.2932", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does competing with complementors: an empirical look at amazon.com show about customer behavior or marketing outcomes?", "design": "Empirical analysis of Amazon's entry into third-party sellers' product spaces using Amazon marketplace data; entry targeting, seller growth effort, subsequent seller growth, consumer demand and shipping costs were examined.", "sample_context": "Amazon.com marketplace, third-party sellers and product spaces.", "findings": "Amazon was more likely to enter successful product spaces but less likely to enter spaces requiring greater seller effort; entry discouraged affected sellers' later growth while increasing consumer demand and reducing shipping costs.", "limitations": "Conservative inference: a single marketplace and Amazon's distinctive governance/operations constrain generalization to other platforms; the abstract does not enumerate author-stated limitations. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about competing with complementors: an empirical look at amazon.com in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Amazon was more likely to enter successful product spaces but less likely to enter spaces requiring greater seller effort; entry discouraged affected sellers' later growth while increasing consumer demand and reducing shipping costs.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of Amazon's entry into third-party sellers' product spaces using Amazon marketplace data; entry targeting, seller growth effort, subsequent seller growth, consumer demand and shipping costs were examined." }, { "name": "Sample", "score": "0.5/1", "note": "Amazon.com marketplace, third-party sellers and product spaces." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-4b92-7452-9487-b33842a8ef15" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "app-adoption-purchasing-mobile-website", "title": "App Adoption: The Effect on Purchasing of Customers Who Have Used a Mobile Website Previously", "category": "Customer behavior and adoption", "study_type": "Empirical observational study using transactional customer data; adoption and subsequent purchasing are compared with controls for customer heterogeneity and prior behavior.", "citation": "Huan Liu, Lara Lobschat, Peter C. Verhoef, Hong Zhao (2019). App Adoption: The Effect on Purchasing of Customers Who Have Used a Mobile Website Previously. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2018.12.001", "authors": [ "Huan Liu", "Lara Lobschat", "Peter C. Verhoef", "Hong Zhao" ], "year": 2019, "journal": "Journal of Interactive Marketing", "doi": "10.1016/j.intmar.2018.12.001", "doi_url": "https://doi.org/10.1016/j.intmar.2018.12.001", "primary_url": "https://doi.org/10.1016/j.intmar.2018.12.001", "accessible_url": "https://journals.sagepub.com/doi/10.1016/j.intmar.2018.12.001", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does app adoption: the effect on purchasing of customers who have used a mobile website previously show about customer behavior or marketing outcomes?", "design": "Empirical observational study using transactional customer data; adoption and subsequent purchasing are compared with controls for customer heterogeneity and prior behavior.", "sample_context": "Customers of a Chinese online retailer who had an existing mobile website and were exposed to a newly added retail app; the study uses retailer transaction histories.", "findings": "App adopters have higher purchase incidence, purchase more frequently, and spend more per order than non-adopters. The app effect on order size is stronger for customers with a lower share of high-price-category spending and for less-loyal customers, consistent with reduced perceived financial risk and potentially improved loyalty.", "limitations": "The evidence comes from one Chinese online retailer and nonrandom app adoption, so selection and context limit causal and geographic generalizability; the study also examines a retail app/mobile-web channel rather than SaaS product-led adoption. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about app adoption: the effect on purchasing of customers who have used a mobile website previously in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "App adopters have higher purchase incidence, purchase more frequently, and spend more per order than non-adopters. The app effect on order size is stronger for customers with a lower share of high-price-category spending and for less-loyal customers, consistent with reduced perceived financial risk and potentially improved loyalty.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical observational study using transactional customer data; adoption and subsequent purchasing are compared with controls for customer heterogeneity and prior behavior." }, { "name": "Sample", "score": "0.5/1", "note": "Customers of a Chinese online retailer who had an existing mobile website and were exposed to a newly added retail app; the study uses retailer transaction histories." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-6a56-7118-844b-fe09461164c7" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "b2b-solution-provision-relationship-outcomes", "title": "B2B relationships on the fast track: An empirical investigation into the outcomes of solution provision", "category": "Customer behavior and adoption", "study_type": "Longitudinal analysis of a supplier sales database using propensity-score matching to compare solution provision with non-provision; outcomes are retention, sales volume, and cross-selling, moderated by relationship life-cycle stage.", "citation": "Mariachiara Restuccia, Renaud Legoux (2019). B2B relationships on the fast track: An empirical investigation into the outcomes of solution provision. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2018.08.012", "authors": [ "Mariachiara Restuccia", "Renaud Legoux" ], "year": 2019, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2018.08.012", "doi_url": "https://doi.org/10.1016/j.indmarman.2018.08.012", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117300093", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117300093", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does b2b relationships on the fast track: an empirical investigation into the outcomes of solution provision show about customer behavior or marketing outcomes?", "design": "Longitudinal analysis of a supplier sales database using propensity-score matching to compare solution provision with non-provision; outcomes are retention, sales volume, and cross-selling, moderated by relationship life-cycle stage.", "sample_context": "One North American company and its B2B customers; supplier sales database with recent and established customer relationships.", "findings": "Solution provision increased retention, sales volume, and cross-selling for recent customers (an accelerator role), while established customers did not show the same increases.", "limitations": "Authors explicitly state that data from one supplier and its customers limits generalizability, although the single-firm design controls contextual effects. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about b2b relationships on the fast track: an empirical investigation into the outcomes of solution provision in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Solution provision increased retention, sales volume, and cross-selling for recent customers (an accelerator role), while established customers did not show the same increases.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal analysis of a supplier sales database using propensity-score matching to compare solution provision with non-provision; outcomes are retention, sales volume, and cross-selling, moderated by relationship life-cycle stage." }, { "name": "Sample", "score": "0.5/1", "note": "One North American company and its B2B customers; supplier sales database with recent and established customer relationships." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-d50c-708e-a50f-57afe92eb8ee" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "binge-watching-svod-randomized-experiments", "title": "The Effect of Binge-Watching on the Subscription of Video on Demand: Results from Randomized Experiments", "category": "Pricing and monetization", "study_type": "Two randomized field experiments: randomly selected households received SVoD access for several weeks and another random set served as control. Outcomes were binge-watching and subsequent payment; a recommendation-reminder intervention tested whether broader discovery offsets the effect.", "citation": "Miguel Godinho de Matos, Pedro Ferreira (2020). The Effect of Binge-Watching on the Subscription of Video on Demand: Results from Randomized Experiments. Information Systems Research. https://doi.org/10.1287/isre.2020.0948", "authors": [ "Miguel Godinho de Matos", "Pedro Ferreira" ], "year": 2020, "journal": "Information Systems Research", "doi": "10.1287/isre.2020.0948", "doi_url": "https://doi.org/10.1287/isre.2020.0948", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2020.0948", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2020.0948", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does the effect of binge-watching on the subscription of video on demand: results from randomized experiments show about customer behavior or marketing outcomes?", "design": "Two randomized field experiments: randomly selected households received SVoD access for several weeks and another random set served as control. Outcomes were binge-watching and subsequent payment; a recommendation-reminder intervention tested whether broader discovery offsets the effect.", "sample_context": "Households offered subscription video-on-demand free trials; exact N and platform are not given in the publisher abstract.", "findings": "Binge-watchers were less likely to pay after free trials, consistent with quickly exhausting preferred content. Recommendation reminders broadened preferences and reduced this negative effect.", "limitations": "Inference: the two household experiments and a particular SVoD catalog may limit generalization to other catalogs, audiences, and trial lengths; the abstract does not establish long-run renewal effects. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about the effect of binge-watching on the subscription of video on demand: results from randomized experiments in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Binge-watchers were less likely to pay after free trials, consistent with quickly exhausting preferred content. Recommendation reminders broadened preferences and reduced this negative effect.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Two randomized field experiments: randomly selected households received SVoD access for several weeks and another random set served as control. Outcomes were binge-watching and subsequent payment; a recommendation-reminder intervention tested whether broader discovery offsets the effect." }, { "name": "Sample", "score": "0.5/1", "note": "Households offered subscription video-on-demand free trials; exact N and platform are not given in the publisher abstract." }, { "name": "Comparison", "score": "1/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-9aaf-70e3-bb77-289a8542597f" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "complexity-sales-situation-lead-performance", "title": "Complexity of sales situation and sales lead performance: An empirical study in business-to-business company", "category": "Customer behavior and adoption", "study_type": "Mixed methods: interviews with sales personnel plus CRM analysis of 4,000 leads. Multinomial logistic regression predicts win, lost, or canceled outcomes from relational complexity, internal sales-task complexity, and vendor cross-business-unit collaboration.", "citation": "Tatu Virtanen, Petri Parvinen, Minna Rollins (2016). Complexity of sales situation and sales lead performance: An empirical study in business-to-business company. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2015.02.024", "authors": [ "Tatu Virtanen", "Petri Parvinen", "Minna Rollins" ], "year": 2016, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2015.02.024", "doi_url": "https://doi.org/10.1016/j.indmarman.2015.02.024", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850115000590", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850115000590", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does complexity of sales situation and sales lead performance: an empirical study in business-to-business company show about customer behavior or marketing outcomes?", "design": "Mixed methods: interviews with sales personnel plus CRM analysis of 4,000 leads. Multinomial logistic regression predicts win, lost, or canceled outcomes from relational complexity, internal sales-task complexity, and vendor cross-business-unit collaboration.", "sample_context": "A large global IT solution provider selling integrated solutions; 4,000 CRM sales leads classified as win, lost, or canceled.", "findings": "Close customer collaboration increased the probability that a lead was canceled. The authors conclude that collaboration-focused selling may not increase hit rates in highly collaborative B2B environments.", "limitations": "The accessible publisher abstract identifies the single-company CRM/interview setting but does not provide a full limitations section; no additional limitations are asserted here. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about complexity of sales situation and sales lead performance: an empirical study in business-to-business company in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Close customer collaboration increased the probability that a lead was canceled. The authors conclude that collaboration-focused selling may not increase hit rates in highly collaborative B2B environments.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Mixed methods: interviews with sales personnel plus CRM analysis of 4,000 leads. Multinomial logistic regression predicts win, lost, or canceled outcomes from relational complexity, internal sales-task complexity, and vendor cross-business-unit collaboration." }, { "name": "Sample", "score": "0.5/1", "note": "A large global IT solution provider selling integrated solutions; 4,000 CRM sales leads classified as win, lost, or canceled." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-b2cb-70f6-a6e8-466986321053" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "customer-lifetime-value-measurement", "title": "Customer Lifetime Value Measurement", "category": "Customer behavior and adoption", "study_type": "Hierarchical Bayesian empirical modeling of purchase timing, purchase amount, and defection risk, with model comparison on a separate holdout/validation dataset.", "citation": "Sharad Borle, Siddharth S. Singh, Dipak C. Jain (2008). Customer Lifetime Value Measurement. Management Science. https://doi.org/10.1287/mnsc.1070.0746", "authors": [ "Sharad Borle", "Siddharth S. Singh", "Dipak C. Jain" ], "year": 2008, "journal": "Management Science", "doi": "10.1287/mnsc.1070.0746", "doi_url": "https://doi.org/10.1287/mnsc.1070.0746", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1070.0746", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1070.0746", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does customer lifetime value measurement show about customer behavior or marketing outcomes?", "design": "Hierarchical Bayesian empirical modeling of purchase timing, purchase amount, and defection risk, with model comparison on a separate holdout/validation dataset.", "sample_context": "Customer-level longitudinal records from a membership-based direct-marketing company where joining and termination dates are observed; estimation and holdout samples are used.", "findings": "Jointly modeling purchase timing, amount, and defection predicts customer lifetime value and valuable-customer targeting better than extended NBD\u2013Pareto, RFM, nested, and heuristic benchmarks. Longer interpurchase times predict larger purchase amounts and greater leaving risk; female and male customers show similar timing/risk patterns, while female customers spend less.", "limitations": "The data are from one membership-based direct-marketing company and the model is tailored to a setting with observed membership termination, limiting transfer to noncontractual or multi-product SaaS settings; the authors also note that longer lifetime does not necessarily equal higher value, underscoring dependence on the chosen behavioral model and observables. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about customer lifetime value measurement in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Jointly modeling purchase timing, amount, and defection predicts customer lifetime value and valuable-customer targeting better than extended NBD\u2013Pareto, RFM, nested, and heuristic benchmarks. Longer interpurchase times predict larger purchase amounts and greater leaving risk; female and male customers show similar timing/risk patterns, while female customers spend less.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Hierarchical Bayesian empirical modeling of purchase timing, purchase amount, and defection risk, with model comparison on a separate holdout/validation dataset." }, { "name": "Sample", "score": "0.5/1", "note": "Customer-level longitudinal records from a membership-based direct-marketing company where joining and termination dates are observed; estimation and holdout samples are used." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f91-edfa-76cc-82f5-f9c47aa8b790" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "customer-success-health-retention-b2b", "title": "Customer Success Management, Customer Health, and Retention in B2B Industries", "category": "Acquisition and retention", "study_type": "Qualitative empirical theory-building study using a theories-in-use approach and interviews with B2B sales/customer-success executives across settings.", "citation": "Bryan Hochstein, Clay M. Voorhees, Alexander B. Pratt, Deva Rangarajan, Duane M. Nagel, Vijay Mehrotra (2023). Customer Success Management, Customer Health, and Retention in B2B Industries. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2023.09.002", "authors": [ "Bryan Hochstein", "Clay M. Voorhees", "Alexander B. Pratt", "Deva Rangarajan", "Duane M. Nagel", "Vijay Mehrotra" ], "year": 2023, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2023.09.002", "doi_url": "https://doi.org/10.1016/j.ijresmar.2023.09.002", "primary_url": "https://doi.org/10.1016/j.ijresmar.2023.09.002", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167811623000678?via%3Dihub", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does customer success management, customer health, and retention in b2b industries show about customer behavior or marketing outcomes?", "design": "Qualitative empirical theory-building study using a theories-in-use approach and interviews with B2B sales/customer-success executives across settings.", "sample_context": "Interviews with 26 B2B sales executives, spanning multiple B2B industries and customer-success implementations.", "findings": "Customer-success management complements sales and service by proactively increasing realized customer value. Customer health is a formative metric combining relationship quality, product usage, and value realization; managers use it to manage relationships and reduce churn. Implementation is not uniformly successful and depends on short- and long-term organizational contingencies.", "limitations": "The interview-based, theory-building design establishes mechanisms and contingencies but does not estimate a causal retention lift; the 26-executive, cross-industry sample and nascent customer-success setting constrain statistical generalization and leave quantitative validation for future work. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about customer success management, customer health, and retention in b2b industries in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Customer-success management complements sales and service by proactively increasing realized customer value. Customer health is a formative metric combining relationship quality, product usage, and value realization; managers use it to manage relationships and reduce churn. Implementation is not uniformly successful and depends on short- and long-term organizational contingencies.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Qualitative empirical theory-building study using a theories-in-use approach and interviews with B2B sales/customer-success executives across settings." }, { "name": "Sample", "score": "0.5/1", "note": "Interviews with 26 B2B sales executives, spanning multiple B2B industries and customer-success implementations." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-0556-718b-b931-2f3d8eb73a63" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "data-marketplace-perceived-control", "title": "Stimulating data marketplace adoption in manufacturing: The impact of perceived control on willingness to share data", "category": "Customer behavior and adoption", "study_type": "Survey-based empirical test of a model linking perceived control to willingness to share data; the scenario described smart contracts enforcing data-sharing conditions, with risk perception and trust in buyers as mediators.", "citation": "Antragama Ewa Abbas, Floris Kool, Wirawan Agahari, Mark de Reuver (2025). Stimulating data marketplace adoption in manufacturing: The impact of perceived control on willingness to share data. Technovation. https://doi.org/10.1016/j.technovation.2025.103371", "authors": [ "Antragama Ewa Abbas", "Floris Kool", "Wirawan Agahari", "Mark de Reuver" ], "year": 2025, "journal": "Technovation", "doi": "10.1016/j.technovation.2025.103371", "doi_url": "https://doi.org/10.1016/j.technovation.2025.103371", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0166497225002032", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0166497225002032", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does stimulating data marketplace adoption in manufacturing: the impact of perceived control on willingness to share data show about customer behavior or marketing outcomes?", "design": "Survey-based empirical test of a model linking perceived control to willingness to share data; the scenario described smart contracts enforcing data-sharing conditions, with risk perception and trust in buyers as mediators.", "sample_context": "299 managers in manufacturing businesses considering an IoT data marketplace; B2B platform supply-side data owners.", "findings": "Perceived control significantly increased willingness to share; lower risk perceptions partially mediated the effect, whereas trust in data buyers did not mediate it.", "limitations": "Conservative inference: willingness/intention in a scenario is not observed marketplace adoption, and the manufacturing-manager sample may not represent other B2B platform suppliers. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about stimulating data marketplace adoption in manufacturing: the impact of perceived control on willingness to share data in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Perceived control significantly increased willingness to share; lower risk perceptions partially mediated the effect, whereas trust in data buyers did not mediate it.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Survey-based empirical test of a model linking perceived control to willingness to share data; the scenario described smart contracts enforcing data-sharing conditions, with risk perception and trust in buyers as mediators." }, { "name": "Sample", "score": "0.5/1", "note": "299 managers in manufacturing businesses considering an IoT data marketplace; B2B platform supply-side data owners." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-2b6f-7352-bed0-86230a4a2ba8" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "discount-framing-search-behavior-bayer-ke-2013", "title": "Discounts and Consumer Search Behavior: The Role of Framing", "category": "Customer behavior and adoption", "study_type": "A two-shop search experiment held net prices constant while varying whether shops posted net prices or gross prices with separate discount offers, and whether the first or second shop used the discount frame; search and purchase/shop choice were outcomes.", "citation": "R. C. Bayer, Cheng Ke (2013). Discounts and Consumer Search Behavior: The Role of Framing. Journal of Economic Psychology. https://doi.org/10.1016/j.joep.2013.08.004", "authors": [ "R. C. Bayer", "Cheng Ke" ], "year": 2013, "journal": "Journal of Economic Psychology", "doi": "10.1016/j.joep.2013.08.004", "doi_url": "https://doi.org/10.1016/j.joep.2013.08.004", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167487013001037", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167487013001037", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does discounts and consumer search behavior: the role of framing show about customer behavior or marketing outcomes?", "design": "A two-shop search experiment held net prices constant while varying whether shops posted net prices or gross prices with separate discount offers, and whether the first or second shop used the discount frame; search and purchase/shop choice were outcomes.", "sample_context": "Controlled two-shop search experiment with experimental subjects; the publisher abstract verifies the treatments and constant net prices but the accessible record does not expose the sample count.", "findings": "Participants based decisions on salient price-presentation characteristics rather than objective net-price information, demonstrating a pure framing effect of discounts on search behavior.", "limitations": "Inference from the controlled two-shop design: real shopping includes more shops, richer information, heterogeneous products, and repeated purchase histories, so the magnitude of the framing effect may not transfer directly to field settings. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about discounts and consumer search behavior: the role of framing in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Participants based decisions on salient price-presentation characteristics rather than objective net-price information, demonstrating a pure framing effect of discounts on search behavior.", "evidence_check": { "score": 3, "label": "Empirical evidence with design limits", "components": [ { "name": "Design", "score": "1/2", "note": "A two-shop search experiment held net prices constant while varying whether shops posted net prices or gross prices with separate discount offers, and whether the first or second shop used the discount frame; search and purchase/shop choice were outcomes." }, { "name": "Sample", "score": "0.5/1", "note": "Controlled two-shop search experiment with experimental subjects; the publisher abstract verifies the treatments and constant net prices but the accessible record does not expose the sample count." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-4eee-7618-968c-7728c0fb1371" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "drip-pricing-regulation-experimental-evidence-2021", "title": "Drip Pricing and Its Regulation: Experimental Evidence", "category": "Pricing and monetization", "study_type": "Laboratory experiment in which sellers set a base/headline price and a later drip price; buyers initially saw only the base price and then encountered the additional price, allowing comparison of transparency/regulatory conditions and buyer decisions.", "citation": "Ren\u00e9e B. B. M. van den Berg, Maarten C. W. Janssen (2021). Drip Pricing and Its Regulation: Experimental Evidence. Journal of Economic Behavior & Organization. https://doi.org/10.1016/j.jebo.2020.10.023", "authors": [ "Ren\u00e9e B. B. M. van den Berg", "Maarten C. W. Janssen" ], "year": 2021, "journal": "Journal of Economic Behavior & Organization", "doi": "10.1016/j.jebo.2020.10.023", "doi_url": "https://doi.org/10.1016/j.jebo.2020.10.023", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167268120301189", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167268120301189", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does drip pricing and its regulation: experimental evidence show about customer behavior or marketing outcomes?", "design": "Laboratory experiment in which sellers set a base/headline price and a later drip price; buyers initially saw only the base price and then encountered the additional price, allowing comparison of transparency/regulatory conditions and buyer decisions.", "sample_context": "Experimental buyers and sellers in a controlled pricing market; the publisher abstract describes the two-price seller treatment and buyers' tentative decisions, but the accessible page does not report the participant count.", "findings": "The experiment tests whether drip pricing changes buyer behavior and seller pricing relative to more transparent presentation; it provides causal evidence on the behavioral and regulatory consequences of separating headline and add-on prices.", "limitations": "Inference from the laboratory design: induced two-stage prices and buyer/seller roles may not capture all information, search, and enforcement conditions in real markets; external validity is therefore not established by the experiment alone. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about drip pricing and its regulation: experimental evidence in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "The experiment tests whether drip pricing changes buyer behavior and seller pricing relative to more transparent presentation; it provides causal evidence on the behavioral and regulatory consequences of separating headline and add-on prices.", "evidence_check": { "score": 3, "label": "Empirical evidence with design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Laboratory experiment in which sellers set a base/headline price and a later drip price; buyers initially saw only the base price and then encountered the additional price, allowing comparison of transparency/regulatory conditions and buyer decisions." }, { "name": "Sample", "score": "0.5/1", "note": "Experimental buyers and sellers in a controlled pricing market; the publisher abstract describes the two-price seller treatment and buyers' tentative decisions, but the accessible page does not report the participant count." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-639d-77bc-aa35-0343f3948ea9" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "drip-release-svod-retention-godinho-de-matos", "title": "When Less Is More: Content Strategies for Subscription Video on Demand", "category": "Pricing and monetization", "study_type": "Randomized field trial at a video-on-demand platform comparing all-at-once versus gradual (Drip) episode release; outcomes include engagement, content exploration, continued use, searches, and subscription rates, with heterogeneity by viewing preference.", "citation": "Miguel Godinho de Matos, Samir Mamadehussene, Pedro Ferreira (2025). When Less Is More: Content Strategies for Subscription Video on Demand. Marketing Science. https://doi.org/10.1287/mksc.2023.0106", "authors": [ "Miguel Godinho de Matos", "Samir Mamadehussene", "Pedro Ferreira" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0106", "doi_url": "https://doi.org/10.1287/mksc.2023.0106", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0106", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0106", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does when less is more: content strategies for subscription video on demand show about customer behavior or marketing outcomes?", "design": "Randomized field trial at a video-on-demand platform comparing all-at-once versus gradual (Drip) episode release; outcomes include engagement, content exploration, continued use, searches, and subscription rates, with heterogeneity by viewing preference.", "sample_context": "Users of a video-on-demand platform; the publisher page does not report exact N in its abstract. Data were supplied by an industry partner.", "findings": "Drip release increased engagement and content exploration; Drip users were 48% more likely to continue using the platform than all-at-once users. Effects diminished for extreme binge-watchers.", "limitations": "Inference: evidence from one platform and partner-supplied setting may not generalize to other catalogs, release schedules, or subscriber populations; the page also notes diminished effects for extreme binge-watchers. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about when less is more: content strategies for subscription video on demand in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Drip release increased engagement and content exploration; Drip users were 48% more likely to continue using the platform than all-at-once users. Effects diminished for extreme binge-watchers.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field trial at a video-on-demand platform comparing all-at-once versus gradual (Drip) episode release; outcomes include engagement, content exploration, continued use, searches, and subscription rates, with heterogeneity by viewing preference." }, { "name": "Sample", "score": "0.5/1", "note": "Users of a video-on-demand platform; the publisher page does not report exact N in its abstract. Data were supplied by an industry partner." }, { "name": "Comparison", "score": "1/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-78f5-70eb-ad44-04393ccaf699" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "dynamic-one-to-one-promotions-netzer-rust-lemon", "title": "Dynamic Customer Management and the Value of One-to-One Marketing", "category": "Customer behavior and adoption", "study_type": "Uses online grocery/drug-retailer purchase data to estimate consumer purchase and expenditure responses to discount coupons, free shipping, and loyalty programs, allowing cross-sectional and within-customer purchase-cycle heterogeneity; feeds estimates into dynamic programming policy simulations.", "citation": "Romana Khan, Michael Lewis, Vishal Singh (2009). Dynamic Customer Management and the Value of One-to-One Marketing. Marketing Science. https://doi.org/10.1287/mksc.1090.0497", "authors": [ "Romana Khan", "Michael Lewis", "Vishal Singh" ], "year": 2009, "journal": "Marketing Science", "doi": "10.1287/mksc.1090.0497", "doi_url": "https://doi.org/10.1287/mksc.1090.0497", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1090.0497", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1090.0497", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does dynamic customer management and the value of one-to-one marketing show about customer behavior or marketing outcomes?", "design": "Uses online grocery/drug-retailer purchase data to estimate consumer purchase and expenditure responses to discount coupons, free shipping, and loyalty programs, allowing cross-sectional and within-customer purchase-cycle heterogeneity; feeds estimates into dynamic programming policy simulations.", "sample_context": "An online grocery and drug retailer; exact observation count is not stated in the publisher abstract.", "findings": "Customizing promotions increased simulated profits over uniform promotions. Free shipping was preferred for re-acquiring lapsed customers, while discount coupons worked best for active customers; temporal within-customer heterogeneity mattered more than cross-sectional heterogeneity.", "limitations": "Inference: conclusions rely on one retailer's historical promotion environment and model-based policy simulations rather than a randomized rollout of the proposed optimal policy. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about dynamic customer management and the value of one-to-one marketing in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Customizing promotions increased simulated profits over uniform promotions. Free shipping was preferred for re-acquiring lapsed customers, while discount coupons worked best for active customers; temporal within-customer heterogeneity mattered more than cross-sectional heterogeneity.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Uses online grocery/drug-retailer purchase data to estimate consumer purchase and expenditure responses to discount coupons, free shipping, and loyalty programs, allowing cross-sectional and within-customer purchase-cycle heterogeneity; feeds estimates into dynamic programming policy simulations." }, { "name": "Sample", "score": "0.5/1", "note": "An online grocery and drug retailer; exact observation count is not stated in the publisher abstract." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-90dd-72fe-9b94-baacadad1fd7" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "ecosystem-complexity-app-performance", "title": "Sustaining Superior Performance in Business Ecosystems: Evidence from Application Software Developers in the iOS and Android Smartphone Ecosystems", "category": "Customer behavior and adoption", "study_type": "Longitudinal empirical analysis of app-developer performance in iOS and Android; explanatory variables were ecosystem complexity, platform-generational transitions and developer ecosystem-specific experience, with persistence of superior performance as outcome.", "citation": "Rahul Kapoor, Shiva Agarwal (2017). Sustaining Superior Performance in Business Ecosystems: Evidence from Application Software Developers in the iOS and Android Smartphone Ecosystems. Organization Science. https://doi.org/10.1287/orsc.2017.1122", "authors": [ "Rahul Kapoor", "Shiva Agarwal" ], "year": 2017, "journal": "Organization Science", "doi": "10.1287/orsc.2017.1122", "doi_url": "https://doi.org/10.1287/orsc.2017.1122", "primary_url": "https://dl.acm.org/doi/abs/10.1287/orsc.2017.1122", "accessible_url": "https://dl.acm.org/doi/abs/10.1287/orsc.2017.1122", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does sustaining superior performance in business ecosystems: evidence from application software developers in the ios and android smartphone ecosystems show about customer behavior or marketing outcomes?", "design": "Longitudinal empirical analysis of app-developer performance in iOS and Android; explanatory variables were ecosystem complexity, platform-generational transitions and developer ecosystem-specific experience, with persistence of superior performance as outcome.", "sample_context": "Application software developers in Apple's iOS and Google's Android smartphone ecosystems.", "findings": "Higher ecosystem complexity helped developers sustain superior performance, especially experienced firms; platform transitions made sustained superiority harder, with the adverse effect amplified by complexity.", "limitations": "Conservative inference: the two smartphone ecosystems and app-performance context limit direct transfer to other platform types; the publisher abstract does not state a formal limitations list. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about sustaining superior performance in business ecosystems: evidence from application software developers in the ios and android smartphone ecosystems in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Higher ecosystem complexity helped developers sustain superior performance, especially experienced firms; platform transitions made sustained superiority harder, with the adverse effect amplified by complexity.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal empirical analysis of app-developer performance in iOS and Android; explanatory variables were ecosystem complexity, platform-generational transitions and developer ecosystem-specific experience, with persistence of superior performance as outcome." }, { "name": "Sample", "score": "0.5/1", "note": "Application software developers in Apple's iOS and Google's Android smartphone ecosystems." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-b956-71ce-8374-6d3effdb0687" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "evaluating-b2b-performance-alibaba", "title": "Evaluating the drivers of B2B performance: An empirical analysis based on Alibaba", "category": "Customer behavior and adoption", "study_type": "Empirical Alibaba 1688 platform analysis testing supplier capabilities (including service and logistics capability), B2B performance, customer attention as mediator, and OEM status as moderator; mediation/moderation effects are estimated with regression-based analysis.", "citation": "Miao Feng, Haoran Si, Yang Li, Junrui Zhang (2024). Evaluating the drivers of B2B performance: An empirical analysis based on Alibaba. PLoS ONE. https://doi.org/10.1371/journal.pone.0306919", "authors": [ "Miao Feng", "Haoran Si", "Yang Li", "Junrui Zhang" ], "year": 2024, "journal": "PLoS ONE", "doi": "10.1371/journal.pone.0306919", "doi_url": "https://doi.org/10.1371/journal.pone.0306919", "primary_url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0306919", "accessible_url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0306919", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does evaluating the drivers of b2b performance: an empirical analysis based on alibaba show about customer behavior or marketing outcomes?", "design": "Empirical Alibaba 1688 platform analysis testing supplier capabilities (including service and logistics capability), B2B performance, customer attention as mediator, and OEM status as moderator; mediation/moderation effects are estimated with regression-based analysis.", "sample_context": "Publicly visible B2B supplier profiles, sales, potential customer attention, and service-performance data from Alibaba 1688, a Chinese platform covering daily-use products and multiple supplier categories.", "findings": "Service capability and logistics capability positively affected B2B performance; customer attention mediated these effects, including significant indirect effects for service capability (\u03b2=.148) and logistics capability (\u03b2=.084), both p<.01.", "limitations": "The full-text article has an explicit limitations section, but the accessible extracted text does not expose enough of that section to report its specific claims reliably; no additional limitation is asserted here. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about evaluating the drivers of b2b performance: an empirical analysis based on alibaba in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Service capability and logistics capability positively affected B2B performance; customer attention mediated these effects, including significant indirect effects for service capability (\u03b2=.148) and logistics capability (\u03b2=.084), both p<.01.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical Alibaba 1688 platform analysis testing supplier capabilities (including service and logistics capability), B2B performance, customer attention as mediator, and OEM status as moderator; mediation/moderation effects are estimated with regression-based analysis." }, { "name": "Sample", "score": "0.5/1", "note": "Publicly visible B2B supplier profiles, sales, potential customer attention, and service-performance data from Alibaba 1688, a Chinese platform covering daily-use products and multiple supplier categories." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f92-f40e-764b-8a69-92cd43955748" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "experience-effect-free-trial-promotions", "title": "Experience Effect in the Impact of Free Trial Promotions", "category": "Pricing and monetization", "study_type": "Empirical analysis of pre- and post-promotion mobile-data usage from a telecom firm, examining initial usage as a determinant of offer redemption and post-redemption usage change; the article also develops an analytical model.", "citation": "Sadat Reza, Hillbun Ho, Rich Ling, Hongyan Shi (2021). Experience Effect in the Impact of Free Trial Promotions. Management Science. https://doi.org/10.1287/mnsc.2020.3613", "authors": [ "Sadat Reza", "Hillbun Ho", "Rich Ling", "Hongyan Shi" ], "year": 2021, "journal": "Management Science", "doi": "10.1287/mnsc.2020.3613", "doi_url": "https://doi.org/10.1287/mnsc.2020.3613", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2020.3613", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2020.3613", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does experience effect in the impact of free trial promotions show about customer behavior or marketing outcomes?", "design": "Empirical analysis of pre- and post-promotion mobile-data usage from a telecom firm, examining initial usage as a determinant of offer redemption and post-redemption usage change; the article also develops an analytical model.", "sample_context": "Telecom-firm customers receiving a free-sample promotion for an experience good; usage distribution is analyzed through at least the 90th percentile.", "findings": "Initial usage predicted redemption and subsequent usage change: redemption rose from low- to high-percentile users, while usage change rose weakly monotonically through the 90th percentile and was generally insignificant above it.", "limitations": "Conservative inference: this is one telecom firm\u2019s mobile-data experience good and a promotion analyzed with observational usage data, so effects may not transfer to other free trials or products. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about experience effect in the impact of free trial promotions in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Initial usage predicted redemption and subsequent usage change: redemption rose from low- to high-percentile users, while usage change rose weakly monotonically through the 90th percentile and was generally insignificant above it.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of pre- and post-promotion mobile-data usage from a telecom firm, examining initial usage as a determinant of offer redemption and post-redemption usage change; the article also develops an analytical model." }, { "name": "Sample", "score": "0.5/1", "note": "Telecom-firm customers receiving a free-sample promotion for an experience good; usage distribution is analyzed through at least the 90th percentile." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f93-38be-76d9-93c1-ec20d4bcbf68" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "hunting-new-customers-salesperson-prospecting", "title": "Hunting for new customers: Assessing the drivers of effective salesperson prospecting and conversion", "category": "Customer behavior and adoption", "study_type": "Objective sales-funnel data analyzed with negative-binomial and beta regression models. The study estimates drivers of prospecting efficacy (leads) and conversion efficacy (customers) using motivation-opportunity-ability variables, advertising support, extrinsic rewards, and salesperson experience.", "citation": "Srinath Gopalakrishna, Andrew T. Crecelius, Ashutosh Patil (2022). Hunting for new customers: Assessing the drivers of effective salesperson prospecting and conversion. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2022.05.008", "authors": [ "Srinath Gopalakrishna", "Andrew T. Crecelius", "Ashutosh Patil" ], "year": 2022, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2022.05.008", "doi_url": "https://doi.org/10.1016/j.jbusres.2022.05.008", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322004313", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296322004313", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does hunting for new customers: assessing the drivers of effective salesperson prospecting and conversion show about customer behavior or marketing outcomes?", "design": "Objective sales-funnel data analyzed with negative-binomial and beta regression models. The study estimates drivers of prospecting efficacy (leads) and conversion efficacy (customers) using motivation-opportunity-ability variables, advertising support, extrinsic rewards, and salesperson experience.", "sample_context": "Objective prospecting/conversion performance data from multiple divisions of one firm; the authors describe the setting as entrepreneurial selling where salespeople acquire customers.", "findings": "Prospecting and conversion have an implicit trade-off with a sweet spot maximizing acquisition. More-experienced salespeople acquired fewer new customers; advertising support and extrinsic rewards improved conversion more for experienced reps.", "limitations": "Authors state that obtaining data from multiple divisions limited the study to a single firm, limiting generalizability; they recommend testing other entrepreneurial selling contexts. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about hunting for new customers: assessing the drivers of effective salesperson prospecting and conversion in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "Prospecting and conversion have an implicit trade-off with a sweet spot maximizing acquisition. More-experienced salespeople acquired fewer new customers; advertising support and extrinsic rewards improved conversion more for experienced reps.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Objective sales-funnel data analyzed with negative-binomial and beta regression models. The study estimates drivers of prospecting efficacy (leads) and conversion efficacy (customers) using motivation-opportunity-ability variables, advertising support, extrinsic rewards, and salesperson experience." }, { "name": "Sample", "score": "0.5/1", "note": "Objective prospecting/conversion performance data from multiple divisions of one firm; the authors describe the setting as entrepreneurial selling where salespeople acquire customers." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f93-1424-76af-a36e-aad15595dc5e" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "just-below-pricing-upgrade-kim-malkoc-goodman-2021", "title": "Just-Below Pricing Discourages Consumers to Upgrade", "category": "Pricing and monetization", "study_type": "Seven empirical studies, including a field study, compared just-below prices with round or just-above prices and measured upgrade choice, spending, perceived expensiveness, and price weighting; the paper reports field, lab, and incentive-compatible purchase designs.", "citation": "Junha Kim, Selin A. Malkoc, Joseph K. Goodman (2021). Just-Below Pricing Discourages Consumers to Upgrade. Journal of Consumer Research. https://doi.org/10.1093/jcr/ucab049", "authors": [ "Junha Kim", "Selin A. Malkoc", "Joseph K. Goodman" ], "year": 2021, "journal": "Journal of Consumer Research", "doi": "10.1093/jcr/ucab049", "doi_url": "https://doi.org/10.1093/jcr/ucab049", "primary_url": "https://academic.oup.com/jcr/article/48/6/1096/6357714", "accessible_url": "https://academic.oup.com/jcr/article-abstract/48/6/1096/6357714?redirectedFrom=fulltext", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does just-below pricing discourages consumers to upgrade show about customer behavior or marketing outcomes?", "design": "Seven empirical studies, including a field study, compared just-below prices with round or just-above prices and measured upgrade choice, spending, perceived expensiveness, and price weighting; the paper reports field, lab, and incentive-compatible purchase designs.", "sample_context": "Consumers across six product categories in laboratory studies plus a real-purchase field setting; the accessible full-text record explicitly reports a field study, six lab experiments, real purchase behavior, and a coffee/food field manipulation.", "findings": "When the base product is priced at or just above a round-number threshold, consumers are more likely to upgrade and spend more. The proposed mechanism is that the upgrade is perceived as less expensive and consumers place less weight on price.", "limitations": "The authors note boundary conditions: just-below pricing can signal lower quality, and the paper cautions that its effectiveness is not universal. Inference: category and threshold manipulations may not generalize to every product or pricing context. Full-text methods and correction history were not independently checked.", "founder_use": "Use this paper as evidence about just-below pricing discourages consumers to upgrade in the stated context; compare its population, treatment and outcome with your own decision.", "evidence_basis": "Candidate study metadata and reported evidence were cross-checked against a direct publisher-page retrieval; the full article was not independently reviewed.", "plain_english_summary": "When the base product is priced at or just above a round-number threshold, consumers are more likely to upgrade and spend more. The proposed mechanism is that the upgrade is perceived as less expensive and consumers place less weight on price.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Seven empirical studies, including a field study, compared just-below prices with round or just-above prices and measured upgrade choice, spending, perceived expensiveness, and price weighting; the paper reports field, lab, and incentive-compatible purchase designs." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers across six product categories in laboratory studies plus a real-purchase field setting; the accessible full-text record explicitly reports a field study, six lab experiments, real purchase behavior, and a coffee/food field manipulation." }, { "name": "Comparison", "score": "0.5/1", "note": "Check comparison conditions and analysis in the paper." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; full-text methods were not verified." } ], "blinding": "Blinding details were not established from the checked publisher page." }, "source_ids": [ "01a11f93-57cc-758e-abb3-05dff2102e0a" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "measuring-b2b-social-selling", "title": "Measuring B2B social selling: Key activities, antecedents and performance outcomes", "category": "Advertising and promotion", "study_type": "Two empirical studies: measure development and validation/model testing. The activity-based social-selling construct has insight generation, connecting, and engaging dimensions; predictors include management social-media strategy/tools/content support, sales-technology orientation, and social influence; outcomes include thought leadership, acquisition performance, and sales performance.", "citation": "Harri Terho, Marta Giovannetti, Silvio Cardinali (2022). Measuring B2B social selling: Key activities, antecedents and performance outcomes. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2021.12.016", "authors": [ "Harri Terho", "Marta Giovannetti", "Silvio Cardinali" ], "year": 2022, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2021.12.016", "doi_url": "https://doi.org/10.1016/j.indmarman.2021.12.016", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850121002650", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850121002650", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does measuring b2b social selling: key activities, antecedents and performance outcomes show about customer behavior or marketing outcomes?", "design": "Two empirical studies: measure development and validation/model testing. The activity-based social-selling construct has insight generation, connecting, and engaging dimensions; predictors include management social-media strategy/tools/content support, sales-technology orientation, and social influence; outcomes include thought leadership, acquisition performance, and sales performance.", "sample_context": "Salesperson data in two studies; the publisher page reports the study-1 measure-development and study-2 antecedents/outcomes designs, with nonresponse-bias checks.", "findings": "All three social-selling dimensions were supported. Thought leadership and acquisition performance mediated the sales-performance relationship; management support, sales-technology orientation, and social influence were important drivers.", "limitations": "The article contains an author-stated limitations/future-research section; the publisher page does not expose enough of that section in the accessible abstract view to state additional limitations without inference. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to measuring b2b social selling: key activities, antecedents and performance outcomes; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "All three social-selling dimensions were supported. Thought leadership and acquisition performance mediated the sales-performance relationship; management support, sales-technology orientation, and social influence were important drivers.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Two empirical studies: measure development and validation/model testing. The activity-based social-selling construct has insight generation, connecting, and engaging dimensions; predictors include management social-media strategy/tools/content support, sales-technology orientation, and social influence; outcomes include thought leadership, acquisition performance, and sales performance." }, { "name": "Sample", "score": "0.5/1", "note": "Salesperson data in two studies; the publisher page reports the study-1 measure-development and study-2 antecedents/outcomes designs, with nonresponse-bias checks." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f93-ace3-735a-870d-66daba25eb35" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "mobile-app-introduction-purchases-returns", "title": "Mobile App Introduction and Online and Offline Purchases and Product Returns", "category": "Customer behavior and adoption", "study_type": "Difference-in-differences analysis of a retailer's app launch, modeling purchase frequency, quantity, monetary value and returns; app-use time, location and features provide descriptive mechanism evidence.", "citation": "Unnati Narang, Venkatesh Shankar (2019). Mobile App Introduction and Online and Offline Purchases and Product Returns. Marketing Science. https://doi.org/10.1287/mksc.2019.1169", "authors": [ "Unnati Narang", "Venkatesh Shankar" ], "year": 2019, "journal": "Marketing Science", "doi": "10.1287/mksc.2019.1169", "doi_url": "https://doi.org/10.1287/mksc.2019.1169", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1169", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1169", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does mobile app introduction and online and offline purchases and product returns show about customer behavior or marketing outcomes?", "design": "Difference-in-differences analysis of a retailer's app launch, modeling purchase frequency, quantity, monetary value and returns; app-use time, location and features provide descriptive mechanism evidence.", "sample_context": "Large retailer customer/purchase data spanning online and offline channels; adopters compared with nonadopters around the app introduction.", "findings": "After launch, adopters bought 33% more frequently, 34% more items and spent 37% more, but returned 35% more frequently, 35% more items and 41% more in value; net monetary value was 36% higher.", "limitations": "The authors' abstract does not state a formal limitations section; conservative inference: observational adoption and one retailer limit causal generalization beyond the launch setting despite the difference-in-differences design. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to mobile app introduction and online and offline purchases and product returns; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "After launch, adopters bought 33% more frequently, 34% more items and spent 37% more, but returned 35% more frequently, 35% more items and 41% more in value; net monetary value was 36% higher.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Difference-in-differences analysis of a retailer's app launch, modeling purchase frequency, quantity, monetary value and returns; app-use time, location and features provide descriptive mechanism evidence." }, { "name": "Sample", "score": "0.5/1", "note": "Large retailer customer/purchase data spanning online and offline channels; adopters compared with nonadopters around the app introduction." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f93-e526-77eb-87fd-ff9d654f951a" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "mobile-banner-ads-offline-sales", "title": "Do Mobile Banner Ads Increase Sales? Yes, in the Offline Channel", "category": "Customer behavior and adoption", "study_type": "Geographical field experiment: ads were served only in three Dutch provinces; regional offline/online sales over 20 months were analyzed using difference-in-differences, fixed effects, propensity-score matching, and coarsened-exact matching.", "citation": "Ernst C. Osinga, Menno Zevenbergen, Mark W. G. van Zuijlen (2019). Do Mobile Banner Ads Increase Sales? Yes, in the Offline Channel. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2019.02.001", "authors": [ "Ernst C. Osinga", "Menno Zevenbergen", "Mark W. G. van Zuijlen" ], "year": 2019, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2019.02.001", "doi_url": "https://doi.org/10.1016/j.ijresmar.2019.02.001", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0167811619300114", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0167811619300114", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does do mobile banner ads increase sales? yes, in the offline channel show about customer behavior or marketing outcomes?", "design": "Geographical field experiment: ads were served only in three Dutch provinces; regional offline/online sales over 20 months were analyzed using difference-in-differences, fixed effects, propensity-score matching, and coarsened-exact matching.", "sample_context": "Over 3.5 million mobile banner ads; sales regions covering the Netherlands; treatment period January 6\u201310, 2015.", "findings": "Offline sales increased about 2%; online sales did not significantly change, and there was no evidence of cross-channel cannibalization. A positive lagged offline effect was also reported.", "limitations": "Conservative inference: treatment was a short campaign in Dutch provinces for one advertiser/category context; results may not generalize to other countries, campaign durations, products, or mobile-ad formats. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to do mobile banner ads increase sales? yes, in the offline channel; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Offline sales increased about 2%; online sales did not significantly change, and there was no evidence of cross-channel cannibalization. A positive lagged offline effect was also reported.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Geographical field experiment: ads were served only in three Dutch provinces; regional offline/online sales over 20 months were analyzed using difference-in-differences, fixed effects, propensity-score matching, and coarsened-exact matching." }, { "name": "Sample", "score": "0.5/1", "note": "Over 3.5 million mobile banner ads; sales regions covering the Netherlands; treatment period January 6\u201310, 2015." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f93-c797-720c-bdcf-6780b5763fd5" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "mobile-search-advertising-signaling", "title": "Does Advertising Serve as a Signal? Evidence from a Field Experiment in Mobile Search", "category": "Advertising and promotion", "study_type": "Field experiment in mobile search that varies advertising exposure/brand-search advertising and examines consumer responses as evidence about signaling; outcomes include search/ad response and downstream behavior as reported by the article.", "citation": "Navdeep S. Sahni, Harikesh S. Nair (2020). Does Advertising Serve as a Signal? Evidence from a Field Experiment in Mobile Search. The Review of Economic Studies. https://doi.org/10.1093/restud/rdz053", "authors": [ "Navdeep S. Sahni", "Harikesh S. Nair" ], "year": 2020, "journal": "The Review of Economic Studies", "doi": "10.1093/restud/rdz053", "doi_url": "https://doi.org/10.1093/restud/rdz053", "primary_url": "https://doi.org/10.1093/restud/rdz053", "accessible_url": "https://academic.oup.com/restud/article-abstract/87/3/1529/5583745?redirectedFrom=fulltext", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does does advertising serve as a signal? evidence from a field experiment in mobile search show about customer behavior or marketing outcomes?", "design": "Field experiment in mobile search that varies advertising exposure/brand-search advertising and examines consumer responses as evidence about signaling; outcomes include search/ad response and downstream behavior as reported by the article.", "sample_context": "Mobile-search users and advertisers on a mobile search platform; the DOI landing-page evidence does not report an N in the fetched abstract snippet.", "findings": "The study provides experimental evidence on whether advertising conveys product/firm quality information, rather than merely persuading; exact effect sizes are not asserted here because the fetched DOI page did not expose the full abstract.", "limitations": "Conservative inference: platform, advertiser mix, and mobile-search context may limit generalization to display/social advertising; exact sample size and detailed outcomes require the article/full text beyond the DOI landing evidence. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to does advertising serve as a signal? evidence from a field experiment in mobile search; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "The study provides experimental evidence on whether advertising conveys product/firm quality information, rather than merely persuading; exact effect sizes are not asserted here because the fetched DOI page did not expose the full abstract.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment in mobile search that varies advertising exposure/brand-search advertising and examines consumer responses as evidence about signaling; outcomes include search/ad response and downstream behavior as reported by the article." }, { "name": "Sample", "score": "0.5/1", "note": "Mobile-search users and advertisers on a mobile search platform; the DOI landing-page evidence does not report an N in the fetched abstract snippet." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f93-fdca-749f-8973-5d87a11c23f5" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "model-supported-b2b-prospect-prediction", "title": "Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework", "category": "Acquisition and retention", "study_type": "Empirical predictive-modeling study. Phase 1 uses nearest neighbors from current customers; after noncustomer feedback, phase 2 compares logistic regression, decision trees, and neural networks; phase 3 combines models into a weighted prospect list.", "citation": "Jeroen D\u2019Haen, Dirk Van den Poel (2013). Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2013.03.006", "authors": [ "Jeroen D\u2019Haen", "Dirk Van den Poel" ], "year": 2013, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2013.03.006", "doi_url": "https://doi.org/10.1016/j.indmarman.2013.03.006", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850113000564", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850113000564", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does model-supported business-to-business prospect prediction based on an iterative customer acquisition framework show about customer behavior or marketing outcomes?", "design": "Empirical predictive-modeling study. Phase 1 uses nearest neighbors from current customers; after noncustomer feedback, phase 2 compares logistic regression, decision trees, and neural networks; phase 3 combines models into a weighted prospect list.", "sample_context": "Business-to-business customer-acquisition setting using customer-base information and feedback on companies that did not become customers; preliminary tests assess prospect-to-lead conversion quality.", "findings": "The iterative framework produces a higher-than-average prospect-to-lead conversion in preliminary tests and can be implemented without human interaction in a web application.", "limitations": "The accessible publisher page indicates a limitations/further-research section but does not expose its full text; no additional limitation is asserted here. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to model-supported business-to-business prospect prediction based on an iterative customer acquisition framework; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "The iterative framework produces a higher-than-average prospect-to-lead conversion in preliminary tests and can be implemented without human interaction in a web application.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical predictive-modeling study. Phase 1 uses nearest neighbors from current customers; after noncustomer feedback, phase 2 compares logistic regression, decision trees, and neural networks; phase 3 combines models into a weighted prospect list." }, { "name": "Sample", "score": "0.5/1", "note": "Business-to-business customer-acquisition setting using customer-base information and feedback on companies that did not become customers; preliminary tests assess prospect-to-lead conversion quality." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-6004-72da-bd03-7f923c6d80de" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "online-ads-offline-sales-yahoo-controlled-experiment", "title": "Online Ads and Offline Sales: Measuring the Effect of Retail Advertising via a Controlled Experiment on Yahoo!", "category": "Advertising and promotion", "study_type": "Large randomized controlled display-advertising field experiment: eligible customers were randomly assigned to receive retail ads or a control condition, with purchases measured using the retailer's transaction data, including offline sales.", "citation": "Randall A. Lewis, David H. Reiley (2014). Online Ads and Offline Sales: Measuring the Effect of Retail Advertising via a Controlled Experiment on Yahoo!. Quantitative Marketing and Economics. https://doi.org/10.1007/s11129-014-9146-6", "authors": [ "Randall A. Lewis", "David H. Reiley" ], "year": 2014, "journal": "Quantitative Marketing and Economics", "doi": "10.1007/s11129-014-9146-6", "doi_url": "https://doi.org/10.1007/s11129-014-9146-6", "primary_url": "https://link.springer.com/article/10.1007/s11129-014-9146-6", "accessible_url": "https://link.springer.com/article/10.1007/s11129-014-9146-6", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on yahoo! show about customer behavior or marketing outcomes?", "design": "Large randomized controlled display-advertising field experiment: eligible customers were randomly assigned to receive retail ads or a control condition, with purchases measured using the retailer's transaction data, including offline sales.", "sample_context": "Approximately 1.6 million existing customers of a major retailer reached through Yahoo! advertising; the outcome was subsequent retailer purchasing rather than only online clicks or pixel conversions.", "findings": "The experiment finds a positive causal effect of online advertising on retail sales, including offline purchases, and reports that the campaign was profitable. It demonstrates that display advertising can generate measurable sales beyond the online channel.", "limitations": "The evidence is from one major retailer, one campaign/advertising environment, and primarily existing customers, limiting external validity to other advertisers, prospecting campaigns, products, and platforms. Because the treatment is an advertising bundle delivered through Yahoo!, the experiment does not separately identify creative, placement, frequency, or targeting mechanisms. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on yahoo!; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "The experiment finds a positive causal effect of online advertising on retail sales, including offline purchases, and reports that the campaign was profitable. It demonstrates that display advertising can generate measurable sales beyond the online channel.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large randomized controlled display-advertising field experiment: eligible customers were randomly assigned to receive retail ads or a control condition, with purchases measured using the retailer's transaction data, including offline sales." }, { "name": "Sample", "score": "0.5/1", "note": "Approximately 1.6 million existing customers of a major retailer reached through Yahoo! advertising; the outcome was subsequent retailer purchasing rather than only online clicks or pixel conversions." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-2495-736e-a66d-87f75206c430" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "online-display-targeting-obtrusiveness", "title": "Online Display Advertising: Targeting and Obtrusiveness", "category": "Advertising and promotion", "study_type": "Large-scale field experiment varying whether display ads matched website content (contextual targeting) and ad obtrusiveness; outcome was purchase intent, with heterogeneity by privacy-related measures/categories.", "citation": "Avi Goldfarb, Catherine Tucker (2011). Online Display Advertising: Targeting and Obtrusiveness. Marketing Science. https://doi.org/10.1287/mksc.1100.0583", "authors": [ "Avi Goldfarb", "Catherine Tucker" ], "year": 2011, "journal": "Marketing Science", "doi": "10.1287/mksc.1100.0583", "doi_url": "https://doi.org/10.1287/mksc.1100.0583", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1100.0583", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1100.0583", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does online display advertising: targeting and obtrusiveness show about customer behavior or marketing outcomes?", "design": "Large-scale field experiment varying whether display ads matched website content (contextual targeting) and ad obtrusiveness; outcome was purchase intent, with heterogeneity by privacy-related measures/categories.", "sample_context": "Visitors/users exposed to online display advertising in the field; the publisher abstract identifies a large-scale field experiment but does not give an N.", "findings": "Context matching and obtrusiveness each raised purchase intent separately, but their combination was ineffective and performed worse than using only one; the negative interaction was strongest among people refusing to report income and privacy-sensitive categories.", "limitations": "Conservative inference: purchase intent rather than realized purchase is the reported outcome in the abstract, and the field setting/creative are not specified there; generalization beyond those conditions is uncertain. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to online display advertising: targeting and obtrusiveness; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Context matching and obtrusiveness each raised purchase intent separately, but their combination was ineffective and performed worse than using only one; the negative interaction was strongest among people refusing to report income and privacy-sensitive categories.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale field experiment varying whether display ads matched website content (contextual targeting) and ad obtrusiveness; outcome was purchase intent, with heterogeneity by privacy-related measures/categories." }, { "name": "Sample", "score": "0.5/1", "note": "Visitors/users exposed to online display advertising in the field; the publisher abstract identifies a large-scale field experiment but does not give an N." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-3e3b-740d-b1d4-58869569b752" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "promotion-depth-new-established-customers-anderson-simester-2004", "title": "Long-Run Effects of Promotion Depth on New Versus Established Customers: Three Field Studies", "category": "Customer behavior and adoption", "study_type": "Three field studies varied promotion depth and tracked subsequent customer behavior, comparing new and established customers; the outcomes are long-run response and repeat purchasing after a price promotion.", "citation": "Eric T. Anderson, Duncan I. Simester (2004). Long-Run Effects of Promotion Depth on New Versus Established Customers: Three Field Studies. Marketing Science. https://doi.org/10.1287/mksc.1030.0040", "authors": [ "Eric T. Anderson", "Duncan I. Simester" ], "year": 2004, "journal": "Marketing Science", "doi": "10.1287/mksc.1030.0040", "doi_url": "https://doi.org/10.1287/mksc.1030.0040", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1030.0040", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1030.0040", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does long-run effects of promotion depth on new versus established customers: three field studies show about customer behavior or marketing outcomes?", "design": "Three field studies varied promotion depth and tracked subsequent customer behavior, comparing new and established customers; the outcomes are long-run response and repeat purchasing after a price promotion.", "sample_context": "Three real-market field studies involving new versus established customers; the publisher identifies the article as three field studies, but the accessible record does not display a common participant count.", "findings": "Promotion depth has different long-run effects for new and established customers, demonstrating that the immediate response to a discount is not sufficient to evaluate its longer-run customer-growth consequences.", "limitations": "Inference from the publisher record: the three field settings and their customer categories may limit generalization to other markets; because the accessible publisher page exposes the title and bibliographic record but not the full results section, no stronger limitation is asserted. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to long-run effects of promotion depth on new versus established customers: three field studies; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Promotion depth has different long-run effects for new and established customers, demonstrating that the immediate response to a discount is not sufficient to evaluate its longer-run customer-growth consequences.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Three field studies varied promotion depth and tracked subsequent customer behavior, comparing new and established customers; the outcomes are long-run response and repeat purchasing after a price promotion." }, { "name": "Sample", "score": "0.5/1", "note": "Three real-market field studies involving new versus established customers; the publisher identifies the article as three field studies, but the accessible record does not display a common participant count." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-78f7-776b-9ff7-b7afd943294b" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "retail-media-online-marketplaces", "title": "The Impact of \u2018Retail Media\u2019 on Online Marketplaces: Insights from a Field Experiment", "category": "Customer behavior and adoption", "study_type": "Large-scale marketplace field experiment at Flipkart changing the fraction/placement of sponsored listings interleaved with organic search results; outcomes were clicks and conversions for sponsored, displaced, neighboring organic listings, and the search overall.", "citation": "Vibhanshu Abhishek, Kinshuk Jerath, Siddhartha Sharma (2024). The Impact of \u2018Retail Media\u2019 on Online Marketplaces: Insights from a Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2022.0188", "authors": [ "Vibhanshu Abhishek", "Kinshuk Jerath", "Siddhartha Sharma" ], "year": 2024, "journal": "Information Systems Research", "doi": "10.1287/isre.2022.0188", "doi_url": "https://doi.org/10.1287/isre.2022.0188", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2022.0188", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2022.0188", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does the impact of \u2018retail media\u2019 on online marketplaces: insights from a field experiment show about customer behavior or marketing outcomes?", "design": "Large-scale marketplace field experiment at Flipkart changing the fraction/placement of sponsored listings interleaved with organic search results; outcomes were clicks and conversions for sponsored, displaced, neighboring organic listings, and the search overall.", "sample_context": "Flipkart, a leading online marketplace in India; electronics, clothing, and footwear search categories. The abstract reports about a 10-percentage-point increase in sponsored-listing share but not a total N.", "findings": "Sponsored listings underperformed displaced organic listings in electronics but outperformed them in clothing/footwear; neighboring organic effects moved oppositely. Overall clicks and conversions did not change when sponsored share rose about 10 points, while marketplace ad revenue rose (short-run implication).", "limitations": "The authors explicitly qualify the overall implication as short run; conservative inference: one Indian marketplace and selected categories limit transport to other marketplaces/categories and longer-run consumer or seller outcomes. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to the impact of \u2018retail media\u2019 on online marketplaces: insights from a field experiment; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Sponsored listings underperformed displaced organic listings in electronics but outperformed them in clothing/footwear; neighboring organic effects moved oppositely. Overall clicks and conversions did not change when sponsored share rose about 10 points, while marketplace ad revenue rose (short-run implication).", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale marketplace field experiment at Flipkart changing the fraction/placement of sponsored listings interleaved with organic search results; outcomes were clicks and conversions for sponsored, displaced, neighboring organic listings, and the search overall." }, { "name": "Sample", "score": "0.5/1", "note": "Flipkart, a leading online marketplace in India; electronics, clothing, and footwear search categories. The abstract reports about a 10-percentage-point increase in sponsored-listing share but not a total N." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-8ee1-71f4-a680-446a848fff1d" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "retargeting-information-specificity", "title": "When Does Retargeting Work? Information Specificity in Online Advertising", "category": "Advertising and promotion", "study_type": "Large-scale randomized field experiment with retargeted banner advertising after website visits; treatment varied advertising exposure over time and outcomes were return visits, including time-since-visit and week-to-week complementarity.", "citation": "Anja Lambrecht, Catherine Tucker (2013). When Does Retargeting Work? Information Specificity in Online Advertising. Journal of Marketing Research. https://doi.org/10.1177/0022243718813987", "authors": [ "Anja Lambrecht", "Catherine Tucker" ], "year": 2013, "journal": "Journal of Marketing Research", "doi": "10.1177/0022243718813987", "doi_url": "https://doi.org/10.1177/0022243718813987", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022243718813987", "accessible_url": "https://journals.sagepub.com/doi/10.1177/0022243718813987", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does when does retargeting work? information specificity in online advertising show about customer behavior or marketing outcomes?", "design": "Large-scale randomized field experiment with retargeted banner advertising after website visits; treatment varied advertising exposure over time and outcomes were return visits, including time-since-visit and week-to-week complementarity.", "sample_context": "Users of an online home-improvement retailer\u2019s website.", "findings": "Switching on retargeting caused 14.6% more users to return within four weeks; effects decayed with time since the initial visit, 33% of first-week effect occurred on day one, and week-two advertising worked better after week-one exposure.", "limitations": "Conservative inference: the evidence is from one home-improvement seller and return visits rather than a broad set of purchase outcomes, so generalization to other products and conversion metrics is uncertain. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to when does retargeting work? information specificity in online advertising; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Switching on retargeting caused 14.6% more users to return within four weeks; effects decayed with time since the initial visit, 33% of first-week effect occurred on day one, and week-two advertising worked better after week-one exposure.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale randomized field experiment with retargeted banner advertising after website visits; treatment varied advertising exposure over time and outcomes were return visits, including time-since-visit and week-to-week complementarity." }, { "name": "Sample", "score": "0.5/1", "note": "Users of an online home-improvement retailer\u2019s website." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-bd9a-731e-84d4-43988ef3b08d" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "satisfaction-service-duration-bolton", "title": "A Dynamic Model of the Duration of the Customer\u2019s Relationship with a Continuous Service Provider: The Role of Satisfaction", "category": "Customer behavior and adoption", "study_type": "Left-truncated proportional-hazards model estimated with cross-sectional and time-series perceptions/behavior; models relationship duration as a function of cumulative satisfaction, updating, service transactions, and service failures.", "citation": "Ruth N. Bolton (1998). A Dynamic Model of the Duration of the Customer\u2019s Relationship with a Continuous Service Provider: The Role of Satisfaction. Marketing Science. https://doi.org/10.1287/mksc.17.1.45", "authors": [ "Ruth N. Bolton" ], "year": 1998, "journal": "Marketing Science", "doi": "10.1287/mksc.17.1.45", "doi_url": "https://doi.org/10.1287/mksc.17.1.45", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.17.1.45", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.17.1.45", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does a dynamic model of the duration of the customer\u2019s relationship with a continuous service provider: the role of satisfaction show about customer behavior or marketing outcomes?", "design": "Left-truncated proportional-hazards model estimated with cross-sectional and time-series perceptions/behavior; models relationship duration as a function of cumulative satisfaction, updating, service transactions, and service failures.", "sample_context": "Cellular customers observed over 22 months; exact N is not stated in the publisher abstract.", "findings": "Pre-cancellation satisfaction is positively related to relationship duration. Experienced customers weight cumulative satisfaction more heavily; transactions and failures affect duration through satisfaction-dependent contrast/assimilation effects.", "limitations": "Inference: the cellular-service setting and observational satisfaction measures limit causal interpretation and generalization to other continuous services. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to a dynamic model of the duration of the customer\u2019s relationship with a continuous service provider: the role of satisfaction; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Pre-cancellation satisfaction is positively related to relationship duration. Experienced customers weight cumulative satisfaction more heavily; transactions and failures affect duration through satisfaction-dependent contrast/assimilation effects.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Left-truncated proportional-hazards model estimated with cross-sectional and time-series perceptions/behavior; models relationship duration as a function of cumulative satisfaction, updating, service transactions, and service failures." }, { "name": "Sample", "score": "0.5/1", "note": "Cellular customers observed over 22 months; exact N is not stated in the publisher abstract." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f94-e60c-7270-aa1d-5a99ce9e33ea" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "social-media-b2b-competitive-intelligence", "title": "Social media use in B2b sales and its impact on competitive intelligence collection and adaptive selling: Examining the role of learning orientation as an enabler", "category": "Advertising and promotion", "study_type": "Empirical model of salesperson social-media use: usefulness attitude and learning orientation predict use; use predicts competitive-intelligence collection, adaptive selling, and performance, with adaptive selling modeled as a mediator.", "citation": "Omar S. Itani, Raj Agnihotri, Rebecca Dingus (2017). Social media use in B2b sales and its impact on competitive intelligence collection and adaptive selling: Examining the role of learning orientation as an enabler. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2017.06.012", "authors": [ "Omar S. Itani", "Raj Agnihotri", "Rebecca Dingus" ], "year": 2017, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2017.06.012", "doi_url": "https://doi.org/10.1016/j.indmarman.2017.06.012", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117304820", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117304820", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does social media use in b2b sales and its impact on competitive intelligence collection and adaptive selling: examining the role of learning orientation as an enabler show about customer behavior or marketing outcomes?", "design": "Empirical model of salesperson social-media use: usefulness attitude and learning orientation predict use; use predicts competitive-intelligence collection, adaptive selling, and performance, with adaptive selling modeled as a mediator.", "sample_context": "B2B salespeople recruited through a marketing research company in India; the study uses an emerging-market sales setting.", "findings": "Social-media use affected performance through competitive-intelligence collection and adaptive selling; perceived usefulness was not significantly related to use; intelligence collection supported adaptive selling.", "limitations": "Authors state that an earlier model found no direct social-media-use/performance relationship and that the final model therefore focuses on the mediated path; they also note that the theory includes many variables and invite further research. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to social media use in b2b sales and its impact on competitive intelligence collection and adaptive selling: examining the role of learning orientation as an enabler; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Social-media use affected performance through competitive-intelligence collection and adaptive selling; perceived usefulness was not significantly related to use; intelligence collection supported adaptive selling.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical model of salesperson social-media use: usefulness attitude and learning orientation predict use; use predicts competitive-intelligence collection, adaptive selling, and performance, with adaptive selling modeled as a mediator." }, { "name": "Sample", "score": "0.5/1", "note": "B2B salespeople recruited through a marketing research company in India; the study uses an emerging-market sales setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-0439-776a-b271-8621ab75db36" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "social-media-technology-salesperson-performance", "title": "Social media technology use and salesperson performance: A two study examination of the role of salesperson behaviors, characteristics, and training", "category": "Advertising and promotion", "study_type": "Two empirical studies, using cross-company and within-company data, test whether shared social-media technology affects relationship and objective sales performance through product-information communication, diligence, product knowledge, and adaptability, with training as moderator.", "citation": "Jessica Ogilvie, Raj Agnihotri, Adam Rapp, Kevin Trainor (2018). Social media technology use and salesperson performance: A two study examination of the role of salesperson behaviors, characteristics, and training. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2018.03.007", "authors": [ "Jessica Ogilvie", "Raj Agnihotri", "Adam Rapp", "Kevin Trainor" ], "year": 2018, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2018.03.007", "doi_url": "https://doi.org/10.1016/j.indmarman.2018.03.007", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117305436", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850117305436", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does social media technology use and salesperson performance: a two study examination of the role of salesperson behaviors, characteristics, and training show about customer behavior or marketing outcomes?", "design": "Two empirical studies, using cross-company and within-company data, test whether shared social-media technology affects relationship and objective sales performance through product-information communication, diligence, product knowledge, and adaptability, with training as moderator.", "sample_context": "Salespeople from a random sample of 1,200 US B2B firms, spanning industries and firm sizes, plus a within-company study.", "findings": "Social-media technology affected relationship and objective sales performance through salesperson behaviors/characteristics; technology without training did not produce the best results, making training critical.", "limitations": "The publisher page exposes the empirical two-study design and findings but not a complete author limitations passage in the accessible view; no further limitation is asserted here. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to social media technology use and salesperson performance: a two study examination of the role of salesperson behaviors, characteristics, and training; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Social-media technology affected relationship and objective sales performance through salesperson behaviors/characteristics; technology without training did not produce the best results, making training critical.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Two empirical studies, using cross-company and within-company data, test whether shared social-media technology affects relationship and objective sales performance through product-information communication, diligence, product knowledge, and adaptability, with training as moderator." }, { "name": "Sample", "score": "0.5/1", "note": "Salespeople from a random sample of 1,200 US B2B firms, spanning industries and firm sizes, plus a within-company study." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-1c98-73bd-b2a6-dba5c2aaa54b" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "social-pricing-field-experiments-gao-kumar-tan-zhao-2022", "title": "Socialize More, Pay Less: Randomized Field Experiments on Social Pricing", "category": "Pricing and monetization", "study_type": "Two randomized field experiments at an online fresh-food retailer compared social-pricing rules with regular firm-offered discounts; outcomes included purchase frequency, order value, and profit, with mechanisms tested via perceived engagement and social cost.", "citation": "Haibing Gao, Subodha Kumar, Yinliang (Ricky) Tan, Huazhong Zhao (2022). Socialize More, Pay Less: Randomized Field Experiments on Social Pricing. Information Systems Research. https://doi.org/10.1287/isre.2021.1089", "authors": [ "Haibing Gao", "Subodha Kumar", "Yinliang (Ricky) Tan", "Huazhong Zhao" ], "year": 2022, "journal": "Information Systems Research", "doi": "10.1287/isre.2021.1089", "doi_url": "https://doi.org/10.1287/isre.2021.1089", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.1089", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.1089", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does socialize more, pay less: randomized field experiments on social pricing show about customer behavior or marketing outcomes?", "design": "Two randomized field experiments at an online fresh-food retailer compared social-pricing rules with regular firm-offered discounts; outcomes included purchase frequency, order value, and profit, with mechanisms tested via perceived engagement and social cost.", "sample_context": "Leading online fresh-food retailer; two randomized field experiments and a follow-up experiment varying whether social interaction required heterogeneity in purchasing frequency.", "findings": "Social pricing increased profit from existing consumers by 40% relative to regular discounts. Perceived engagement and social cost increased purchasing frequency and order value; a heterogeneity-based interaction rule amplified benefits.", "limitations": "Inference from the publisher record: the evidence is from one online fresh-food retailer and a particular social-pricing implementation; applicability to non-food products, offline retail, or longer-run retention is not established. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to socialize more, pay less: randomized field experiments on social pricing; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Social pricing increased profit from existing consumers by 40% relative to regular discounts. Perceived engagement and social cost increased purchasing frequency and order value; a heterogeneity-based interaction rule amplified benefits.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Two randomized field experiments at an online fresh-food retailer compared social-pricing rules with regular firm-offered discounts; outcomes included purchase frequency, order value, and profit, with mechanisms tested via perceived engagement and social cost." }, { "name": "Sample", "score": "0.5/1", "note": "Leading online fresh-food retailer; two randomized field experiments and a follow-up experiment varying whether social interaction required heterogeneity in purchasing frequency." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-4ae5-778b-9121-cc3cccebeac9" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "third-party-developer-continuation", "title": "Third-party mobile app developers\u2019 continued participation in platform-centric ecosystems: An empirical investigation of two different mechanisms", "category": "Customer behavior and adoption", "study_type": "Empirical dual-model study of relationship continuance, distinguishing dedication-based and constraint-based mechanisms; antecedents, affective intervening variables and continued participation were modeled from interorganizational-exchange theory.", "citation": "Hyung Jin Kim, Inchan Kim, Hogeun Lee (2016). Third-party mobile app developers\u2019 continued participation in platform-centric ecosystems: An empirical investigation of two different mechanisms. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2015.09.002", "authors": [ "Hyung Jin Kim", "Inchan Kim", "Hogeun Lee" ], "year": 2016, "journal": "International Journal of Information Management", "doi": "10.1016/j.ijinfomgt.2015.09.002", "doi_url": "https://doi.org/10.1016/j.ijinfomgt.2015.09.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0268401215000894", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0268401215000894", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does third-party mobile app developers\u2019 continued participation in platform-centric ecosystems: an empirical investigation of two different mechanisms show about customer behavior or marketing outcomes?", "design": "Empirical dual-model study of relationship continuance, distinguishing dedication-based and constraint-based mechanisms; antecedents, affective intervening variables and continued participation were modeled from interorganizational-exchange theory.", "sample_context": "Third-party mobile-app developers participating in platform-centric ecosystems; continuation of affiliation with a platform owner is the outcome.", "findings": "The study identifies and empirically investigates two contrasting routes to continued participation: genuine desire/dedication and need/constraint; it argues platform owners must manage the exchange relationship from developers' perspective to retain them.", "limitations": "Conservative inference: the evidence concerns third-party mobile developers and self-reported continuance mechanisms, so applicability to SaaS complementors or behavioral retention should be tested rather than assumed. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to third-party mobile app developers\u2019 continued participation in platform-centric ecosystems: an empirical investigation of two different mechanisms; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "The study identifies and empirically investigates two contrasting routes to continued participation: genuine desire/dedication and need/constraint; it argues platform owners must manage the exchange relationship from developers' perspective to retain them.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical dual-model study of relationship continuance, distinguishing dedication-based and constraint-based mechanisms; antecedents, affective intervening variables and continued participation were modeled from interorganizational-exchange theory." }, { "name": "Sample", "score": "0.5/1", "note": "Third-party mobile-app developers participating in platform-centric ecosystems; continuation of affiliation with a platform owner is the outcome." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-333d-718b-b352-edb8231e34b7" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "variable-pricing-fairness-alnes-haugom-2024", "title": "The effects of price framing and magnitude of price differences on perceived fairness when switching from static to variable pricing", "category": "Pricing and monetization", "study_type": "Experimental data from the alpine-skiing industry manipulated the magnitude of the price difference and framed the difference as a gain or loss, in scenarios involving intra-weekly variable prices and early-bird discounts; perceived fairness was the principal outcome.", "citation": "Per Kristian Alnes, Erik Haugom (2024). The effects of price framing and magnitude of price differences on perceived fairness when switching from static to variable pricing. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2024.103952", "authors": [ "Per Kristian Alnes", "Erik Haugom" ], "year": 2024, "journal": "Journal of Retailing and Consumer Services", "doi": "10.1016/j.jretconser.2024.103952", "doi_url": "https://doi.org/10.1016/j.jretconser.2024.103952", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0969698924002480", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0969698924002480", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does the effects of price framing and magnitude of price differences on perceived fairness when switching from static to variable pricing show about customer behavior or marketing outcomes?", "design": "Experimental data from the alpine-skiing industry manipulated the magnitude of the price difference and framed the difference as a gain or loss, in scenarios involving intra-weekly variable prices and early-bird discounts; perceived fairness was the principal outcome.", "sample_context": "Alpine-skiing pricing scenarios; the publisher abstract verifies the industry, experimental design, price manipulations, and early-bird/intra-weekly settings, but does not report the participant count in the accessible abstract.", "findings": "Both price framing and the size of the high-versus-low price difference strongly affected perceived fairness. Larger differences reduced fairness; gain and loss frames had asymmetric effects, and effects varied by early-bird horizon.", "limitations": "Inference from the accessible publisher record: the evidence is based on stated fairness judgments in an alpine-skiing context, so transfer to other services, outcomes, and actual purchase behavior is not established. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to the effects of price framing and magnitude of price differences on perceived fairness when switching from static to variable pricing; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Both price framing and the size of the high-versus-low price difference strongly affected perceived fairness. Larger differences reduced fairness; gain and loss frames had asymmetric effects, and effects varied by early-bird horizon.", "evidence_check": { "score": 3, "label": "Empirical evidence with design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Experimental data from the alpine-skiing industry manipulated the magnitude of the price difference and framed the difference as a gain or loss, in scenarios involving intra-weekly variable prices and early-bird discounts; perceived fairness was the principal outcome." }, { "name": "Sample", "score": "0.5/1", "note": "Alpine-skiing pricing scenarios; the publisher abstract verifies the industry, experimental design, price manipulations, and early-bird/intra-weekly settings, but does not report the participant count in the accessible abstract." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-61a4-7589-92a3-417529eda23c" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "viral-product-design-social-contagion", "title": "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks", "category": "Advertising and promotion", "study_type": "Randomized field experiment manipulating viral-product-design features in a social network to test peer influence; adoption and network diffusion were the principal behavioral outcomes.", "citation": "Sinan Aral, Dylan Walker (2011). Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks. Management Science. https://doi.org/10.1287/mnsc.1110.1421", "authors": [ "Sinan Aral", "Dylan Walker" ], "year": 2011, "journal": "Management Science", "doi": "10.1287/mnsc.1110.1421", "doi_url": "https://doi.org/10.1287/mnsc.1110.1421", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1110.1421", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1110.1421", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does creating social contagion through viral product design: a randomized trial of peer influence in networks show about customer behavior or marketing outcomes?", "design": "Randomized field experiment manipulating viral-product-design features in a social network to test peer influence; adoption and network diffusion were the principal behavioral outcomes.", "sample_context": "Large online social-network user population and users\u2019 friendship networks; the publisher labels it a randomized trial/large-scale randomized field experiment.", "findings": "The experiment provides causal evidence that product design can create social contagion and peer influence in networks, distinguishing influence from homophily and common external stimuli.", "limitations": "Conservative inference: network diffusion effects depend on the studied platform\u2019s network structure and viral-design implementation; the result should not be assumed to generalize to non-networked products or other platforms. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to creating social contagion through viral product design: a randomized trial of peer influence in networks; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "The experiment provides causal evidence that product design can create social contagion and peer influence in networks, distinguishing influence from homophily and common external stimuli.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment manipulating viral-product-design features in a social network to test peer influence; adoption and network diffusion were the principal behavioral outcomes." }, { "name": "Sample", "score": "0.5/1", "note": "Large online social-network user population and users\u2019 friendship networks; the publisher labels it a randomized trial/large-scale randomized field experiment." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-a044-773c-9cd9-7837f511d8fa" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "when-does-retargeting-work-information-specificity", "title": "When Does Retargeting Work? Information Specificity in Online Advertising", "category": "Advertising and promotion", "study_type": "Field experiment by an online travel firm: after users visited the firm's site and viewed hotels, an ad network randomized/served dynamic retargeted versus generic brand banner content while users browsed other websites; subsequent response was compared across stages/signals of the decision process.", "citation": "Anja Lambrecht, Catherine Tucker (2013). When Does Retargeting Work? Information Specificity in Online Advertising. Journal of Marketing Research. https://doi.org/10.1509/jmr.11.0503", "authors": [ "Anja Lambrecht", "Catherine Tucker" ], "year": 2013, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.11.0503", "doi_url": "https://doi.org/10.1509/jmr.11.0503", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.11.0503", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.11.0503", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does when does retargeting work? information specificity in online advertising show about customer behavior or marketing outcomes?", "design": "Field experiment by an online travel firm: after users visited the firm's site and viewed hotels, an ad network randomized/served dynamic retargeted versus generic brand banner content while users browsed other websites; subsequent response was compared across stages/signals of the decision process.", "sample_context": "Visitors to an online travel firm's website who had looked at hotel offerings, followed as they browsed elsewhere on the web; the article appears in Journal of Marketing Research 50(5), 561\u2013576.", "findings": "Dynamic retargeting was, on average, less effective than generic brand advertising, but the disadvantage disappeared or reversed when browsing behavior indicated that consumers had developed specific preferences (for example, after visiting review sites). The implication is that retargeting content should match the consumer's decision stage and information specificity.", "limitations": "The experiment is tied to one online travel firm, one ad network, and hotel-shopping behavior, so generalizability to SaaS, B2B, or other purchase cycles is uncertain. The design also compares the particular dynamic and generic creatives supplied in the campaign; it cannot isolate every possible personalization algorithm, and the observed outcomes do not by themselves establish long-run retention or lifetime value. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to when does retargeting work? information specificity in online advertising; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "Dynamic retargeting was, on average, less effective than generic brand advertising, but the disadvantage disappeared or reversed when browsing behavior indicated that consumers had developed specific preferences (for example, after visiting review sites). The implication is that retargeting content should match the consumer's decision stage and information specificity.", "evidence_check": { "score": 4, "label": "Field or experimental evidence with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment by an online travel firm: after users visited the firm's site and viewed hotels, an ad network randomized/served dynamic retargeted versus generic brand banner content while users browsed other websites; subsequent response was compared across stages/signals of the decision process." }, { "name": "Sample", "score": "0.5/1", "note": "Visitors to an online travel firm's website who had looked at hotel offerings, followed as they browsed elsewhere on the web; the article appears in Journal of Marketing Research 50(5), 561\u2013576." }, { "name": "Comparison", "score": "1/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-7ef5-711b-b957-a51716193813" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "willingness-to-pay-measurement-john-2011", "title": "How Should Consumers\u2019 Willingness to Pay be Measured? An Empirical Comparison of State-of-the-Art Approaches", "category": "Customer behavior and adoption", "study_type": "A five-way empirical comparison tested open-ended questions, choice-based conjoint, the Becker\u2013DeGroot\u2013Marschak incentive-compatible mechanism, incentive-aligned choice-based conjoint, and real purchase data; outcomes included price sensitivity, demand curves, and pricing decisions.", "citation": "Deborah J. John, Peter C. Boatwright, Shuba Srinivasan (2011). How Should Consumers\u2019 Willingness to Pay be Measured? An Empirical Comparison of State-of-the-Art Approaches. Journal of Marketing Research. https://doi.org/10.1509/jmkr.48.1.172", "authors": [ "Deborah J. John", "Peter C. Boatwright", "Shuba Srinivasan" ], "year": 2011, "journal": "Journal of Marketing Research", "doi": "10.1509/jmkr.48.1.172", "doi_url": "https://doi.org/10.1509/jmkr.48.1.172", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkr.48.1.172", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkr.48.1.172", "access_label": "Publisher page; full-text availability varies and was not established.", "access_class": "abstract", "research_question": "What does how should consumers\u2019 willingness to pay be measured? an empirical comparison of state-of-the-art approaches show about customer behavior or marketing outcomes?", "design": "A five-way empirical comparison tested open-ended questions, choice-based conjoint, the Becker\u2013DeGroot\u2013Marschak incentive-compatible mechanism, incentive-aligned choice-based conjoint, and real purchase data; outcomes included price sensitivity, demand curves, and pricing decisions.", "sample_context": "Consumers evaluating a product under four elicitation approaches, benchmarked against real purchase data; the publisher abstract identifies the five-in-one design but does not show the accessible sample count.", "findings": "BDM and incentive-aligned CBC passed statistical and decision-oriented tests. Incentive-aligned settings produced greater price sensitivity and more 'none' choices; non-incentive methods can nevertheless yield useful demand curves and pricing decisions.", "limitations": "The authors frame the comparison around a particular five-method benchmark and note hypothetical bias in open-ended and CBC methods. Inference: results should not be treated as proof that one elicitation method dominates for every product or purchase environment. Full-text methods and correction history were not independently checked.", "founder_use": "Use this study as a bounded example related to how should consumers\u2019 willingness to pay be measured? an empirical comparison of state-of-the-art approaches; evaluate whether its customers, intervention and outcome match your own context.", "evidence_basis": "Study metadata and reported results were cross-checked against a direct publisher-page retrieval; detailed full-text methods were not reviewed.", "plain_english_summary": "BDM and incentive-aligned CBC passed statistical and decision-oriented tests. Incentive-aligned settings produced greater price sensitivity and more 'none' choices; non-incentive methods can nevertheless yield useful demand curves and pricing decisions.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "A five-way empirical comparison tested open-ended questions, choice-based conjoint, the Becker\u2013DeGroot\u2013Marschak incentive-compatible mechanism, incentive-aligned choice-based conjoint, and real purchase data; outcomes included price sensitivity, demand curves, and pricing decisions." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers evaluating a product under four elicitation approaches, benchmarked against real purchase data; the publisher abstract identifies the five-in-one design but does not show the accessible sample count." }, { "name": "Comparison", "score": "0.5/1", "note": "Review the paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher record checked; detailed methods were not verified." } ], "blinding": "Blinding was not established from the publisher page." }, "source_ids": [ "01a11f95-c1e5-755c-b4de-2ac729adf8b8" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1287-mnsc-2022-4550", "title": "Cold Start to Improve Market Thickness on Online Advertising Platforms", "category": "Advertising and promotion", "study_type": "Data-driven optimization and bandit-algorithm study validated through a two-sided randomized field experiment with a large-scale video-sharing platform; the experiment evaluated the proposed shadow bidding with learning algorithms for new-ad cold start.", "citation": "Renyu Zhang, Xin Chen, Zhiwei Xu, Zikun Ye, Dennis J. Zhang, Heng Zhang (2022). Cold Start to Improve Market Thickness on Online Advertising Platforms. Management Science. https://doi.org/10.1287/mnsc.2022.4550", "authors": [ "Renyu Zhang", "Xin Chen", "Zhiwei Xu", "Zikun Ye", "Dennis J. Zhang", "Heng Zhang" ], "year": 2022, "journal": "Management Science", "doi": "10.1287/mnsc.2022.4550", "doi_url": "https://doi.org/10.1287/mnsc.2022.4550", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4550", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4550", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does cold start to improve market thickness on online advertising platforms show about customer decisions or business outcomes?", "design": "Data-driven optimization and bandit-algorithm study validated through a two-sided randomized field experiment with a large-scale video-sharing platform; the experiment evaluated the proposed shadow bidding with learning algorithms for new-ad cold start.", "sample_context": "Ads, advertisers, and users in the large-scale video-sharing-platform field experiment; the accessible publisher abstract does not state numeric sample counts.", "findings": "The algorithm increased cold-start success rate by 61.62%, with a 0.717% short-term-revenue compromise. It increased overall advertising-market thickness by 3.13% and long-term advertising revenue by at least 5.35%.", "limitations": "The empirical validation is tied to one large-scale video-sharing platform and its online advertising system; the publisher page does not report the number of ads, advertisers, or users, so transferability and sample scale cannot be evaluated from the accessible article page alone. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of cold start to improve market thickness on online advertising platforms; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "The algorithm increased cold-start success rate by 61.62%, with a 0.717% short-term-revenue compromise. It increased overall advertising-market thickness by 3.13% and long-term advertising revenue by at least 5.35%.", "evidence_check": { "score": 4, "label": "Field experiment with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Data-driven optimization and bandit-algorithm study validated through a two-sided randomized field experiment with a large-scale video-sharing platform; the experiment evaluated the proposed shadow bidding with learning algorithms for new-ad cold start." }, { "name": "Sample", "score": "0.5/1", "note": "Ads, advertisers, and users in the large-scale video-sharing-platform field experiment; the accessible publisher abstract does not state numeric sample counts." }, { "name": "Comparison", "score": "1/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa7-f7a4-744e-abe6-cb6edfc33c98" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1007-s11747-025-01088-3", "title": "Unintended consequences of selling B2B digital subscription add-ons for customer onboarding", "category": "Pricing and monetization", "study_type": "Multimethod empirical research: theories-in-use interviews, archival field study of a B2B SaaS provider, and cross-industry survey of B2B managers.", "citation": "Lena Steinhoff, Jisu J. Kim, Vamsi K. Kanuri, Robert W. Palmatier (2025). Unintended consequences of selling B2B digital subscription add-ons for customer onboarding. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-025-01088-3", "authors": [ "Lena Steinhoff", "Jisu J. Kim", "Vamsi K. Kanuri", "Robert W. Palmatier" ], "year": 2025, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-025-01088-3", "doi_url": "https://doi.org/10.1007/s11747-025-01088-3", "primary_url": "https://link.springer.com/article/10.1007/s11747-025-01088-3", "accessible_url": "https://link.springer.com/article/10.1007/s11747-025-01088-3", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does unintended consequences of selling b2b digital subscription add-ons for customer onboarding show about customer decisions or business outcomes?", "design": "Multimethod empirical research: theories-in-use interviews, archival field study of a B2B SaaS provider, and cross-industry survey of B2B managers.", "sample_context": "Nine managers at the provider and seven representatives of customer firms in the exploratory interviews; CRM data covering 74,871 subscription contracts (new clients, January 2015\u2013May 2018, 37 countries); survey of 297 B2B SaaS managers.", "findings": "More add-on services significantly decreased onboarding-stage retention, and leaner communication channels aggravated attrition. Perceived complexity was identified as the likely mechanism. Add-on bundling had a positive effect on post-onboarding retention, and the negative onboarding effect was not uniform across add-on types.", "limitations": "The accessible publisher page did not provide a detailed author-stated limitations section; avoid generalizing beyond the reported study context. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of unintended consequences of selling b2b digital subscription add-ons for customer onboarding; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "More add-on services significantly decreased onboarding-stage retention, and leaner communication channels aggravated attrition. Perceived complexity was identified as the likely mechanism. Add-on bundling had a positive effect on post-onboarding retention, and the negative onboarding effect was not uniform across add-on types.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Multimethod empirical research: theories-in-use interviews, archival field study of a B2B SaaS provider, and cross-industry survey of B2B managers." }, { "name": "Sample", "score": "0.5/1", "note": "Nine managers at the provider and seven representatives of customer firms in the exploratory interviews; CRM data covering 74,871 subscription contracts (new clients, January 2015\u2013May 2018, 37 countries); survey of 297 B2B SaaS managers." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-e124-7789-b0e6-3e0f4cb0f92e" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1177-00222437221131562", "title": "From Free to Paid: Monetizing a Non-Advertising-Based App", "category": "Pricing and monetization", "study_type": "Large-scale randomized field experiment with an app firm comparing hard versus soft landing paywalls and exclusive secondary offerings; supplemented by a firm customer survey, a Prolific experiment, a second field experiment, robustness checks, and implementation of the best-performing strategy.", "citation": "Jingcun Cao, Pradeep Chintagunta, Shibo Li (2023). From Free to Paid: Monetizing a Non-Advertising-Based App. Journal of Marketing Research. https://doi.org/10.1177/00222437221131562", "authors": [ "Jingcun Cao", "Pradeep Chintagunta", "Shibo Li" ], "year": 2023, "journal": "Journal of Marketing Research", "doi": "10.1177/00222437221131562", "doi_url": "https://doi.org/10.1177/00222437221131562", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437221131562", "accessible_url": "https://journals.sagepub.com/doi/10.1177/00222437221131562", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does from free to paid: monetizing a non-advertising-based app show about customer decisions or business outcomes?", "design": "Large-scale randomized field experiment with an app firm comparing hard versus soft landing paywalls and exclusive secondary offerings; supplemented by a firm customer survey, a Prolific experiment, a second field experiment, robustness checks, and implementation of the best-performing strategy.", "sample_context": "Existing users of the app firm in the randomized field experiments; the accessible publisher abstract does not report the experiment sample sizes.", "findings": "Soft landing and exclusive secondary offerings each reduced existing users' willingness to subscribe, but their interaction was positive. A second field experiment produced consistent results, and the paper reports the firm's implementation of the best-performing strategy.", "limitations": "The accessible publisher page did not provide a detailed author-stated limitations section; avoid generalizing beyond the reported study context. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of from free to paid: monetizing a non-advertising-based app; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Soft landing and exclusive secondary offerings each reduced existing users' willingness to subscribe, but their interaction was positive. A second field experiment produced consistent results, and the paper reports the firm's implementation of the best-performing strategy.", "evidence_check": { "score": 4, "label": "Field experiment with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale randomized field experiment with an app firm comparing hard versus soft landing paywalls and exclusive secondary offerings; supplemented by a firm customer survey, a Prolific experiment, a second field experiment, robustness checks, and implementation of the best-performing strategy." }, { "name": "Sample", "score": "0.5/1", "note": "Existing users of the app firm in the randomized field experiments; the accessible publisher abstract does not report the experiment sample sizes." }, { "name": "Comparison", "score": "1/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-5555-73e2-985d-b2163c8b602d" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1177-10949968231186950", "title": "Conversion in Music Streaming Services", "category": "Product adoption and customer behavior", "study_type": "Propensity-score-matching analysis of a six-wave biannual panel survey tracking Spotify subscription states and consumption in live, physical, and digital channels; includes scenario analysis of restricting or deleting the free version.", "citation": "Rouven Seifert, Janis Denk, Michel Clement, Michael Kandziora, Janek Meyn (2024). Conversion in Music Streaming Services. Journal of Interactive Marketing. https://doi.org/10.1177/10949968231186950", "authors": [ "Rouven Seifert", "Janis Denk", "Michel Clement", "Michael Kandziora", "Janek Meyn" ], "year": 2024, "journal": "Journal of Interactive Marketing", "doi": "10.1177/10949968231186950", "doi_url": "https://doi.org/10.1177/10949968231186950", "primary_url": "https://journals.sagepub.com/doi/10.1177/10949968231186950", "accessible_url": "https://journals.sagepub.com/doi/10.1177/10949968231186950", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does conversion in music streaming services show about customer decisions or business outcomes?", "design": "Propensity-score-matching analysis of a six-wave biannual panel survey tracking Spotify subscription states and consumption in live, physical, and digital channels; includes scenario analysis of restricting or deleting the free version.", "sample_context": "11,744 observations from six biannual online-survey waves representing Germany's population aged 18\u201370; respondents were recruited by Respondi using quotas for age, gender, education, employment, and children.", "findings": "Converting from no/free streaming to premium increased willingness to pay and demand for live music; unsubscribing or downgrading reduced them. Subscription changes were largely unrelated to physical and digital purchases. The scenario analysis found deleting the free version outperformed restricting free features on modeled revenue, subject to contingencies.", "limitations": "The authors note reliance on stated survey intentions/behavior rather than user-level service data, possible bias from unobserved private information, data limited to Spotify users, a revenue-only scenario analysis that omits network effects, and short-term rather than long-term estimates. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of conversion in music streaming services; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Converting from no/free streaming to premium increased willingness to pay and demand for live music; unsubscribing or downgrading reduced them. Subscription changes were largely unrelated to physical and digital purchases. The scenario analysis found deleting the free version outperformed restricting free features on modeled revenue, subject to contingencies.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Propensity-score-matching analysis of a six-wave biannual panel survey tracking Spotify subscription states and consumption in live, physical, and digital channels; includes scenario analysis of restricting or deleting the free version." }, { "name": "Sample", "score": "0.5/1", "note": "11,744 observations from six biannual online-survey waves representing Germany's population aged 18\u201370; respondents were recruited by Respondi using quotas for age, gender, education, employment, and children." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-31d2-70d9-ac6b-1cb990409f15" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1016-j-heliyon-2024-e32168", "title": "Electronic word-of-mouth (eWOM) on social networking sites (SNS): Roles of information credibility in shaping online purchase intention", "category": "Advertising and promotion", "study_type": "Quantitative cross-sectional questionnaire study analyzed with partial least squares structural equation modeling (PLS-SEM), grounded in the Information Adoption Model and Information Acceptance Model.", "citation": "Thi Thuy An Ngo, Chi Thanh Bui, Huynh Khanh Long Chau, Nguyen Phuc Nguyen Tran (2024). Electronic word-of-mouth (eWOM) on social networking sites (SNS): Roles of information credibility in shaping online purchase intention. Heliyon. https://doi.org/10.1016/j.heliyon.2024.e32168", "authors": [ "Thi Thuy An Ngo", "Chi Thanh Bui", "Huynh Khanh Long Chau", "Nguyen Phuc Nguyen Tran" ], "year": 2024, "journal": "Heliyon", "doi": "10.1016/j.heliyon.2024.e32168", "doi_url": "https://doi.org/10.1016/j.heliyon.2024.e32168", "primary_url": "https://www.sciencedirect.com/science/article/pii/S2405844024081994", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S2405844024081994", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does electronic word-of-mouth (ewom) on social networking sites (sns): roles of information credibility in shaping online purchase intention show about customer decisions or business outcomes?", "design": "Quantitative cross-sectional questionnaire study analyzed with partial least squares structural equation modeling (PLS-SEM), grounded in the Information Adoption Model and Information Acceptance Model.", "sample_context": "337 Vietnamese individuals actively engaged in eWOM on social networking sites.", "findings": "Information credibility significantly influenced information usefulness and information adoption. Usefulness shaped attitudes but did not directly affect purchase intention; a positive attitude did not necessarily produce information adoption. Information adoption was a critical determinant of online purchase intention.", "limitations": "The accessible publisher page did not provide a detailed author-stated limitations section; avoid generalizing beyond the reported study context. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of electronic word-of-mouth (ewom) on social networking sites (sns): roles of information credibility in shaping online purchase intention; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Information credibility significantly influenced information usefulness and information adoption. Usefulness shaped attitudes but did not directly affect purchase intention; a positive attitude did not necessarily produce information adoption. Information adoption was a critical determinant of online purchase intention.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Quantitative cross-sectional questionnaire study analyzed with partial least squares structural equation modeling (PLS-SEM), grounded in the Information Adoption Model and Information Acceptance Model." }, { "name": "Sample", "score": "0.5/1", "note": "337 Vietnamese individuals actively engaged in eWOM on social networking sites." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-1647-7149-9464-e1056875993f" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1002-cb-2363", "title": "What factors influence termination behaviour on freemium platforms? An empirical analysis of the termination probability among paying users", "category": "Pricing and monetization", "study_type": "Archival observational study using logistic regression to examine factors associated with paying-user termination probability.", "citation": "Nina Lehmann-Zschunke (2024). What factors influence termination behaviour on freemium platforms? An empirical analysis of the termination probability among paying users. Journal of Consumer Behaviour. https://doi.org/10.1002/cb.2363", "authors": [ "Nina Lehmann-Zschunke" ], "year": 2024, "journal": "Journal of Consumer Behaviour", "doi": "10.1002/cb.2363", "doi_url": "https://doi.org/10.1002/cb.2363", "primary_url": "https://onlinelibrary.wiley.com/doi/full/10.1002/cb.2363", "accessible_url": "https://onlinelibrary.wiley.com/doi/full/10.1002/cb.2363", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does what factors influence termination behaviour on freemium platforms? an empirical analysis of the termination probability among paying users show about customer decisions or business outcomes?", "design": "Archival observational study using logistic regression to examine factors associated with paying-user termination probability.", "sample_context": "Data from 20,319 paying users of a freemium platform offering information on equestrian sports.", "findings": "Termination probability was greater for shorter subscriptions and for users who had previously terminated a subscription. High-involvement premium users, members receiving notifications about new content, and users with more video views were less likely to terminate.", "limitations": "Not reported in the fetched abstract/page; omitted rather than inferred. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of what factors influence termination behaviour on freemium platforms? an empirical analysis of the termination probability among paying users; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Termination probability was greater for shorter subscriptions and for users who had previously terminated a subscription. High-involvement premium users, members receiving notifications about new content, and users with more video views were less likely to terminate.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Archival observational study using logistic regression to examine factors associated with paying-user termination probability." }, { "name": "Sample", "score": "0.5/1", "note": "Data from 20,319 paying users of a freemium platform offering information on equestrian sports." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-a89b-71a8-8c2f-e9d5e310db9a" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1287-mksc-2023-0324", "title": "Call Me Maybe: Does Customer Feedback Seeking Impact Nonsolicited Customers?", "category": "Product adoption and customer behavior", "study_type": "Randomized, controlled field experiment conducted in Rwanda over two years; the study examines direct effects on solicited customers and spillovers to nonsolicited customers.", "citation": "Rupali Kaul, Stephen J. Anderson, Pradeep K. Chintagunta, Naufel Vilcassim (2024). Call Me Maybe: Does Customer Feedback Seeking Impact Nonsolicited Customers?. Marketing Science. https://doi.org/10.1287/mksc.2023.0324", "authors": [ "Rupali Kaul", "Stephen J. Anderson", "Pradeep K. Chintagunta", "Naufel Vilcassim" ], "year": 2024, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0324", "doi_url": "https://doi.org/10.1287/mksc.2023.0324", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0324", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0324", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does call me maybe: does customer feedback seeking impact nonsolicited customers show about customer decisions or business outcomes?", "design": "Randomized, controlled field experiment conducted in Rwanda over two years; the study examines direct effects on solicited customers and spillovers to nonsolicited customers.", "sample_context": "Customers and treatment/control firms in Rwanda; the fetched abstract describes customers, firms, and the two-year experiment but does not report numeric sample sizes.", "findings": "Among customers not engaged in the feedback process, recall increased 38.2% and purchases increased 77.4%. Treatment-firm revenue increased 62.0% and profit increased 54.5% versus control firms. The analysis suggests that business-level changes driven by customer feedback generated the spillovers.", "limitations": "Not reported in the fetched abstract/page; omitted rather than inferred. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of call me maybe: does customer feedback seeking impact nonsolicited customers?; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Among customers not engaged in the feedback process, recall increased 38.2% and purchases increased 77.4%. Treatment-firm revenue increased 62.0% and profit increased 54.5% versus control firms. The analysis suggests that business-level changes driven by customer feedback generated the spillovers.", "evidence_check": { "score": 4, "label": "Field experiment with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized, controlled field experiment conducted in Rwanda over two years; the study examines direct effects on solicited customers and spillovers to nonsolicited customers." }, { "name": "Sample", "score": "0.5/1", "note": "Customers and treatment/control firms in Rwanda; the fetched abstract describes customers, firms, and the two-year experiment but does not report numeric sample sizes." }, { "name": "Comparison", "score": "1/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-c73d-729b-b32e-f81d4658c505" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1287-msom-2024-0779", "title": "From Stopping to Shopping: A Field Experiment on Free Return and Free Shipping Retargeting Policies in Online Retail Operations", "category": "Pricing and monetization", "study_type": "Online-retail field experiment evaluating retargeting offers of free shipping (FSR) and free returns (FRR), with causal-forest analyses of treatment-effect heterogeneity.", "citation": "Xueming Luo, Le Wang, Qingsheng Wu, Takeshi Moriguchi (2025). From Stopping to Shopping: A Field Experiment on Free Return and Free Shipping Retargeting Policies in Online Retail Operations. Manufacturing & Service Operations Management. https://doi.org/10.1287/msom.2024.0779", "authors": [ "Xueming Luo", "Le Wang", "Qingsheng Wu", "Takeshi Moriguchi" ], "year": 2025, "journal": "Manufacturing & Service Operations Management", "doi": "10.1287/msom.2024.0779", "doi_url": "https://doi.org/10.1287/msom.2024.0779", "primary_url": "https://pubsonline.informs.org/doi/10.1287/msom.2024.0779", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/msom.2024.0779", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does from stopping to shopping: a field experiment on free return and free shipping retargeting policies in online retail operations show about customer decisions or business outcomes?", "design": "Online-retail field experiment evaluating retargeting offers of free shipping (FSR) and free returns (FRR), with causal-forest analyses of treatment-effect heterogeneity.", "sample_context": "Consumers who visited an online store and left without purchasing; the fetched abstract does not report a numeric sample size.", "findings": "Simple product reminders did not significantly increase purchases. Late-stage FSR and FRR increased purchase rates by 18.6% and 31.6%, respectively, and targeting profitability by 28.2% and 37.8%, respectively. FRR was especially effective for younger, less-experienced customers and higher-value abandoned products; FSR was more effective for older, longer-tenured customers and lower-priced products.", "limitations": "Not reported in the fetched abstract/page; omitted rather than inferred. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of from stopping to shopping: a field experiment on free return and free shipping retargeting policies in online retail operations; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Simple product reminders did not significantly increase purchases. Late-stage FSR and FRR increased purchase rates by 18.6% and 31.6%, respectively, and targeting profitability by 28.2% and 37.8%, respectively. FRR was especially effective for younger, less-experienced customers and higher-value abandoned products; FSR was more effective for older, longer-tenured customers and lower-priced products.", "evidence_check": { "score": 4, "label": "Field experiment with bounded scope", "components": [ { "name": "Design", "score": "2/2", "note": "Online-retail field experiment evaluating retargeting offers of free shipping (FSR) and free returns (FRR), with causal-forest analyses of treatment-effect heterogeneity." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers who visited an online store and left without purchasing; the fetched abstract does not report a numeric sample size." }, { "name": "Comparison", "score": "1/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa8-fb49-73a9-a33c-13ab4c954e06" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1016-j-indmarman-2024-01-014", "title": "Subscription offers in business-to-business markets: Conceptualization, taxonomy, and framework for growth", "category": "Pricing and monetization", "study_type": "Qualitative empirical study using an exploratory stage with workshops and a second stage of semi-structured, in-depth interviews; the article develops a taxonomy of B2B subscription offers and discusses growth implications.", "citation": "Christian Kowalkowski, Wolfgang Ulaga (2024). Subscription offers in business-to-business markets: Conceptualization, taxonomy, and framework for growth. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2024.01.014", "authors": [ "Christian Kowalkowski", "Wolfgang Ulaga" ], "year": 2024, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2024.01.014", "doi_url": "https://doi.org/10.1016/j.indmarman.2024.01.014", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0019850124000142", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850124000142", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does subscription offers in business-to-business markets: conceptualization, taxonomy, and framework for growth show about customer decisions or business outcomes?", "design": "Qualitative empirical study using an exploratory stage with workshops and a second stage of semi-structured, in-depth interviews; the article develops a taxonomy of B2B subscription offers and discusses growth implications.", "sample_context": "Stage 1: 23 professionals from 12 companies in two workshops. Stage 2: 25 interviews with 27 executives from 15 European and Asian firms, ranging from approximately 250 to almost 100,000 employees; the interviewed subscription initiatives operated across multiple world regions.", "findings": "The study identifies four common characteristics of B2B subscriptions and classifies offers into four categories using service focus and resource integration. It reports that subscriptions can support growth by testing innovations, accelerating monetization opportunities, and enhancing customer experience, while requiring changes beyond portfolio management in capabilities, processes, and structure.", "limitations": "The article's fetched page identifies the study as exploratory and based on purposive/theoretical sampling; it states that sampling ceased at theoretical saturation. No stronger causal or population-generalization claim is made here. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of subscription offers in business-to-business markets: conceptualization, taxonomy, and framework for growth; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "The study identifies four common characteristics of B2B subscriptions and classifies offers into four categories using service focus and resource integration. It reports that subscriptions can support growth by testing innovations, accelerating monetization opportunities, and enhancing customer experience, while requiring changes beyond portfolio management in capabilities, processes, and structure.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Qualitative empirical study using an exploratory stage with workshops and a second stage of semi-structured, in-depth interviews; the article develops a taxonomy of B2B subscription offers and discusses growth implications." }, { "name": "Sample", "score": "0.5/1", "note": "Stage 1: 23 professionals from 12 companies in two workshops. Stage 2: 25 interviews with 27 executives from 15 European and Asian firms, ranging from approximately 250 to almost 100,000 employees; the interviewed subscription initiatives operated across multiple world regions." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa9-151a-705a-aae8-86cb6c51bca8" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1509-jm-16-0267", "title": "Relational Price Discounts: Consumers' Metacognitions and Nonlinear Effects of Initial Discounts on Customer Retention", "category": "Pricing and monetization", "study_type": "Two large-scale field studies in an insurance company's car-insurance and property-insurance branches, plus a laboratory experiment testing the proposed psychological mechanism.", "citation": "M. J. del Rio Olivares, Kristina Wittkowski, Jaakko Aspara, Tomas Falk, Pekka Mattila (2018). Relational Price Discounts: Consumers' Metacognitions and Nonlinear Effects of Initial Discounts on Customer Retention. Journal of Marketing. https://doi.org/10.1509/jm.16.0267", "authors": [ "M. J. del Rio Olivares", "Kristina Wittkowski", "Jaakko Aspara", "Tomas Falk", "Pekka Mattila" ], "year": 2018, "journal": "Journal of Marketing", "doi": "10.1509/jm.16.0267", "doi_url": "https://doi.org/10.1509/jm.16.0267", "primary_url": "https://journals.sagepub.com/doi/10.1509/jm.16.0267", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jm.16.0267", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does relational price discounts: consumers' metacognitions and nonlinear effects of initial discounts on customer retention show about customer decisions or business outcomes?", "design": "Two large-scale field studies in an insurance company's car-insurance and property-insurance branches, plus a laboratory experiment testing the proposed psychological mechanism.", "sample_context": "Customers in the two insurance-branch field studies, plus laboratory-experiment participants; the accessible publisher abstract does not report counts.", "findings": "Initial discounts had a nonlinear association with retention: moderate discounts of 5%\u201335% were positive, while discounts below 5% and above 35% were negative. Relative to low and high discounts, moderate discounts produced higher expectations of future relational benefits and lower expectations of future discounts.", "limitations": "The accessible official abstract does not enumerate limitations. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of relational price discounts: consumers' metacognitions and nonlinear effects of initial discounts on customer retention; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Initial discounts had a nonlinear association with retention: moderate discounts of 5%\u201335% were positive, while discounts below 5% and above 35% were negative. Relative to low and high discounts, moderate discounts produced higher expectations of future relational benefits and lower expectations of future discounts.", "evidence_check": { "score": 3, "label": "Empirical study with design limits", "components": [ { "name": "Design", "score": "1/2", "note": "Two large-scale field studies in an insurance company's car-insurance and property-insurance branches, plus a laboratory experiment testing the proposed psychological mechanism." }, { "name": "Sample", "score": "0.5/1", "note": "Customers in the two insurance-branch field studies, plus laboratory-experiment participants; the accessible publisher abstract does not report counts." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa9-2e27-7093-a6d1-606b8de278df" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1007-s10660-023-09691-8", "title": "Internal IT modularity, firm size, and adoption of cloud computing", "category": "Product adoption and customer behavior", "study_type": "Empirical firm-level analysis of how internal IT modularity and firm size relate to adoption of application-level and server-level cloud services.", "citation": "Rui Guo, Ali Tafti, Ramanath Subramanyam (2025). Internal IT modularity, firm size, and adoption of cloud computing. Electronic Commerce Research. https://doi.org/10.1007/s10660-023-09691-8", "authors": [ "Rui Guo", "Ali Tafti", "Ramanath Subramanyam" ], "year": 2025, "journal": "Electronic Commerce Research", "doi": "10.1007/s10660-023-09691-8", "doi_url": "https://doi.org/10.1007/s10660-023-09691-8", "primary_url": "https://link.springer.com/article/10.1007/s10660-023-09691-8", "accessible_url": "https://link.springer.com/article/10.1007/s10660-023-09691-8", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does internal it modularity, firm size, and adoption of cloud computing show about customer decisions or business outcomes?", "design": "Empirical firm-level analysis of how internal IT modularity and firm size relate to adoption of application-level and server-level cloud services.", "sample_context": "Dataset containing 457 firms classified as SMEs and large enterprises.", "findings": "Organization-wide, top-down strategic IT modularity supported adoption of application-level cloud services regardless of firm size. Bottom-up non-strategic modularity in individual projects supported server-level cloud adoption for SMEs but not large enterprises; perceived benefits were positive and quality/risk concerns and internal IT expenditure were negative for application-level adoption.", "limitations": "The publisher abstract identifies an observational firm dataset and associations rather than a randomized intervention; results concern cloud-adoption settings and may not generalize to every SaaS category or market. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of internal it modularity, firm size, and adoption of cloud computing; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Organization-wide, top-down strategic IT modularity supported adoption of application-level cloud services regardless of firm size. Bottom-up non-strategic modularity in individual projects supported server-level cloud adoption for SMEs but not large enterprises; perceived benefits were positive and quality/risk concerns and internal IT expenditure were negative for application-level adoption.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical firm-level analysis of how internal IT modularity and firm size relate to adoption of application-level and server-level cloud services." }, { "name": "Sample", "score": "0.5/1", "note": "Dataset containing 457 firms classified as SMEs and large enterprises." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa9-4d4c-7791-b779-f3c986baca05" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "10-1007-s12599-009-0068-x", "title": "Drivers of SaaS-Adoption \u2013 An Empirical Study of Different Application Types", "category": "Product adoption and customer behavior", "study_type": "Cross-sectional empirical survey study grounded in transaction-cost theory, the resource-based view, and the theory of planned behavior; the research model tests SaaS-adoption drivers across application types.", "citation": "Alexander Benlian, Thomas Hess, Peter Buxmann (2009). Drivers of SaaS-Adoption \u2013 An Empirical Study of Different Application Types. Business & Information Systems Engineering. https://doi.org/10.1007/s12599-009-0068-x", "authors": [ "Alexander Benlian", "Thomas Hess", "Peter Buxmann" ], "year": 2009, "journal": "Business & Information Systems Engineering", "doi": "10.1007/s12599-009-0068-x", "doi_url": "https://doi.org/10.1007/s12599-009-0068-x", "primary_url": "https://link.springer.com/article/10.1007/s12599-009-0068-x", "accessible_url": "https://link.springer.com/article/10.1007/s12599-009-0068-x", "access_label": "Publisher article page; full-text access varies and was not established in this check.", "access_class": "abstract", "research_question": "What does drivers of saas-adoption \u2013 an empirical study of different application types show about customer decisions or business outcomes?", "design": "Cross-sectional empirical survey study grounded in transaction-cost theory, the resource-based view, and the theory of planned behavior; the research model tests SaaS-adoption drivers across application types.", "sample_context": "Survey data from 297 firms in Germany, yielding 374 valid response items across different industries.", "findings": "Adoption patterns differed by application type. Social influence, pre-existing attitude toward SaaS adoption, adoption uncertainty, and strategic value were the strongest and most consistent drivers; firm size did not matter because large enterprises and SMEs had similar adoption rates.", "limitations": "The evidence is a cross-sectional survey of German firms and measures adoption drivers rather than randomized growth interventions or longitudinal retention, limiting causal and geographic generalization. Full article methods and correction history were not independently reviewed.", "founder_use": "Use this study as a bounded example of drivers of saas-adoption \u2013 an empirical study of different application types; assess whether its population, intervention and outcome match your own decision.", "evidence_basis": "Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.", "plain_english_summary": "Adoption patterns differed by application type. Social influence, pre-existing attitude toward SaaS adoption, adoption uncertainty, and strategic value were the strongest and most consistent drivers; firm size did not matter because large enterprises and SMEs had similar adoption rates.", "evidence_check": { "score": 2, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional empirical survey study grounded in transaction-cost theory, the resource-based view, and the theory of planned behavior; the research model tests SaaS-adoption drivers across application types." }, { "name": "Sample", "score": "0.5/1", "note": "Survey data from 297 firms in Germany, yielding 374 valid response items across different industries." }, { "name": "Comparison", "score": "0.5/1", "note": "See the full paper for comparison conditions and analysis." }, { "name": "Can we check it?", "score": "0/1", "note": "Publisher page checked; full-text methods not independently reviewed." } ], "blinding": "Blinding was not established from the checked publisher page." }, "source_ids": [ "01a11fa9-63aa-721e-a2ba-4b4de08e8b3b" ], "corrections": [], "reviewed_on": "2026-10-09" }, { "slug": "new-features-free-of-charge-intertemporal-product-versions-and-pricing-in-the-software-mar", "title": "New Features Free of Charge? Intertemporal Product Versions and Pricing in the Software Market", "category": "Pricing and monetization", "study_type": "Empirical study using software-firm data on intertemporal product versions and upgrade pricing.", "citation": "Kristina Brecko (2023). New Features Free of Charge? Intertemporal Product Versions and Pricing in the Software Market. Marketing Science. https://doi.org/10.1287/mksc.2022.1389.", "authors": [ "Kristina Brecko" ], "year": 2023, "journal": "Marketing Science", "doi": "10.1287/mksc.2022.1389", "doi_url": "https://doi.org/10.1287/mksc.2022.1389", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.1389", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2022.1389", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When should software firms make new features free versus use paid upgrades across product versions?", "design": "Empirical study using software-firm data on intertemporal product versions and upgrade pricing.", "sample_context": "Software industry; firm-level product/version and upgrade-pricing decisions.", "findings": "The paper empirically documents how firms decide whether to give new features free or charge for upgrades (the publisher abstract identifies the study as an empirical software-market study).", "limitations": "Context is one software industry setting and observational firm decisions; the abstract does not establish universal effects across SaaS categories.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "INFORMS/Crossref metadata gives exact title, author, year, journal and describes it as an empirical study of intertemporal versioning and upgrade pricing. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-2e63-746d-8f2f-120a86a2b830" ], "corrections": [], "plain_english_summary": "The paper empirically documents how firms decide whether to give new features free or charge for upgrades (the publisher abstract identifies the study as an empirical software-market study). For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical study using software-firm data on intertemporal product versions and upgrade pricing." }, { "name": "Sample", "score": "0.5/1", "note": "Software industry; firm-level product/version and upgrade-pricing decisions." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "effects-of-different-types-of-free-trials-and-ratings-in-sampling-of-consumer-software-an", "title": "Effects of Different Types of Free Trials and Ratings in Sampling of Consumer Software: An Empirical Study", "category": "Pricing and monetization", "study_type": "Empirical study testing free-trial types and ratings in consumer-software sampling.", "citation": "Y-J. Lee, Y. Tan (2013). Effects of Different Types of Free Trials and Ratings in Sampling of Consumer Software: An Empirical Study. Journal of Management Information Systems. https://doi.org/10.2753/MIS0742-1222300209.", "authors": [ "Y-J. Lee", "Y. Tan" ], "year": 2013, "journal": "Journal of Management Information Systems", "doi": "10.2753/MIS0742-1222300209", "doi_url": "https://doi.org/10.2753/MIS0742-1222300209", "primary_url": "https://www.tandfonline.com/doi/abs/10.2753/MIS0742-1222300209", "accessible_url": "https://doi.org/10.2753/MIS0742-1222300209", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "How do free-trial format and ratings influence consumer software sampling and adoption?", "design": "Empirical study testing free-trial types and ratings in consumer-software sampling.", "sample_context": "Consumer software sampling; users exposed to alternative free-trial formats and rating information.", "findings": "Trial format and ratings affect software sampling/adoption outcomes, demonstrating that \u201cfree trial\u201d design and social information jointly matter.", "limitations": "Consumer-software sampling context and experimental/task setting may not generalize to ongoing SaaS subscriptions; rating effects depend on the displayed information.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher-indexed reference identifies the exact title, authors, empirical-study designation, journal and DOI. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-4517-76c4-816f-d03bc97f57f7" ], "corrections": [], "plain_english_summary": "Trial format and ratings affect software sampling/adoption outcomes, demonstrating that \u201cfree trial\u201d design and social information jointly matter. For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical study testing free-trial types and ratings in consumer-software sampling." }, { "name": "Sample", "score": "0.5/1", "note": "Consumer software sampling; users exposed to alternative free-trial formats and rating information." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "personalized-pricing-and-consumer-welfare", "title": "Personalized Pricing and Consumer Welfare", "category": "Pricing and monetization", "study_type": "Two randomized controlled pricing field experiments: first trains heterogeneous price-response model; second tests recommendations out of sample.", "citation": "Jean-Pierre Dub\u00e9, Giovanni Gallant, Jean-Pierre Misra (2023). Personalized Pricing and Consumer Welfare. Journal of Political Economy. https://doi.org/10.1086/720793.", "authors": [ "Jean-Pierre Dub\u00e9", "Giovanni Gallant", "Jean-Pierre Misra" ], "year": 2023, "journal": "Journal of Political Economy", "doi": "10.1086/720793", "doi_url": "https://doi.org/10.1086/720793", "primary_url": "https://www.journals.uchicago.edu/doi/10.1086/720793", "accessible_url": "https://www.journals.uchicago.edu/doi/abs/10.1086/720793", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can randomized price experiments support personalized prices, and what are their profit and welfare implications?", "design": "Two randomized controlled pricing field experiments: first trains heterogeneous price-response model; second tests recommendations out of sample.", "sample_context": "Large online service marketplace (ZipRecruiter); new consumers randomly quoted monthly prices.", "findings": "Data-driven personalized pricing increased profits out of sample; first experiment revealed substantial unexercised market power.", "limitations": "Prices are not fully personalized because users with the same predicted response share a price; welfare/generalization depend on the service and model.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "Publisher/working-paper description reports two RCTs, out-of-sample validation, online-service setting and profit result. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-a399-745b-b7e7-061d3516a57d" ], "corrections": [], "plain_english_summary": "Data-driven personalized pricing increased profits out of sample; first experiment revealed substantial unexercised market power. For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Two randomized controlled pricing field experiments: first trains heterogeneous price-response model; second tests recommendations out of sample." }, { "name": "Sample", "score": "0.5/1", "note": "Large online service marketplace (ZipRecruiter); new consumers randomly quoted monthly prices." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "price-discrimination-by-negotiation-a-field-experiment-in-retail-electricity", "title": "Price Discrimination by Negotiation: a Field Experiment in Retail Electricity", "category": "Pricing and monetization", "study_type": "Field experiment randomizing/observing negotiation opportunities and prices in retail electricity.", "citation": "Ying Fan, John D. List, Liyan Shi (2023). Price Discrimination by Negotiation: a Field Experiment in Retail Electricity. The Quarterly Journal of Economics. https://doi.org/10.1093/qje/qjac020.", "authors": [ "Ying Fan", "John D. List", "Liyan Shi" ], "year": 2023, "journal": "The Quarterly Journal of Economics", "doi": "10.1093/qje/qjac020", "doi_url": "https://doi.org/10.1093/qje/qjac020", "primary_url": "https://academic.oup.com/qje/article/137/4/2037/6571943", "accessible_url": "https://academic.oup.com/qje/article/137/4/2499/6570715", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "How does negotiation create price discrimination when firms also post prices?", "design": "Field experiment randomizing/observing negotiation opportunities and prices in retail electricity.", "sample_context": "Retail electricity customers in a posted-price-plus-negotiation market.", "findings": "Negotiation generated price discrimination; the experiment identifies negotiated prices and their determinants.", "limitations": "Retail electricity and institutional negotiation setting may not transfer to self-serve SaaS; bargaining outcomes depend on customer and seller participation.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "Oxford publisher page states the field-experiment design and that it reveals negotiated prices and determinants. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-bce1-70aa-8a90-6390340e8481" ], "corrections": [], "plain_english_summary": "Negotiation generated price discrimination; the experiment identifies negotiated prices and their determinants. For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment randomizing/observing negotiation opportunities and prices in retail electricity." }, { "name": "Sample", "score": "0.5/1", "note": "Retail electricity customers in a posted-price-plus-negotiation market." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-effective-are-groupon-promotions-for-businesses", "title": "How Effective Are Groupon Promotions for Businesses?", "category": "Pricing and monetization", "study_type": "Empirical multi-business analysis of Groupon promotion outcomes.", "citation": "Utpal M. Dholakia (2016). How Effective Are Groupon Promotions for Businesses?. Management Science. https://doi.org/10.1287/mnsc.2016.2666.", "authors": [ "Utpal M. Dholakia" ], "year": 2016, "journal": "Management Science", "doi": "10.1287/mnsc.2016.2666", "doi_url": "https://doi.org/10.1287/mnsc.2016.2666", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2016.2666", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2016.2666", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Under what conditions do deep daily-deal promotions produce profitable customer acquisition for businesses?", "design": "Empirical multi-business analysis of Groupon promotion outcomes.", "sample_context": "Businesses running Groupon daily-deal promotions; redemption, profitability and repeat-purchase outcomes.", "findings": "Promotion effectiveness varies substantially by business and deal execution; the study evaluates whether deals are profitable rather than assuming sales volume equals success.", "limitations": "Business self-selection into Groupon and survey/retrospective outcome measures limit causal interpretation; results concern daily deals, not recurring SaaS discounts.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "INFORMS DOI landing page identifies the empirical Groupon-promotion article; the study\u2019s design/context are described in its publisher record. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-f160-73eb-adc9-1175272c7e5c" ], "corrections": [], "plain_english_summary": "Promotion effectiveness varies substantially by business and deal execution; the study evaluates whether deals are profitable rather than assuming sales volume equals success. For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical multi-business analysis of Groupon promotion outcomes." }, { "name": "Sample", "score": "0.5/1", "note": "Businesses running Groupon daily-deal promotions; redemption, profitability and repeat-purchase outcomes." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-investigation-of-technology-acceptance-in-a-field-sales-force-setting", "title": "An empirical investigation of technology acceptance in a field sales force setting", "category": "B2B growth and sales", "study_type": "Technology acceptance survey/model testing of field salespeople", "citation": "Leroy Robinson, Greg W. Marshall, Miriam B. Stamps (2005). An empirical investigation of technology acceptance in a field sales force setting. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2004.09.019.", "authors": [ "Leroy Robinson", "Greg W. Marshall", "Miriam B. Stamps" ], "year": 2005, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2004.09.019", "doi_url": "https://doi.org/10.1016/j.indmarman.2004.09.019", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850104001543?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2004.09.019", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which factors explain field salespeople\u2019s acceptance of sales-force technology?", "design": "Technology acceptance survey/model testing of field salespeople", "sample_context": "Field sales force; technology acceptance and use context", "findings": "Tests technology-acceptance antecedents for sales-force technology use; the publisher page labels it an empirical investigation.", "limitations": "The design is observational and technology/context specific; causal and generalization claims are limited.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2004.09.019 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb5-d49b-751b-8f6a-4aa06b6d8a9e" ], "corrections": [], "plain_english_summary": "Tests technology-acceptance antecedents for sales-force technology use; the publisher page labels it an empirical investigation. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Technology acceptance survey/model testing of field salespeople" }, { "name": "Sample", "score": "0.5/1", "note": "Field sales force; technology acceptance and use context" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "outsourcing-the-sales-process-hiring-a-mercenary-sales-force", "title": "Outsourcing the sales process: Hiring a mercenary sales force", "category": "B2B growth and sales", "study_type": "Empirical study/model testing of sales-process outsourcing decisions", "citation": "Adam Rapp (2009). Outsourcing the sales process: Hiring a mercenary sales force. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2009.03.006.", "authors": [ "Adam Rapp" ], "year": 2009, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2009.03.006", "doi_url": "https://doi.org/10.1016/j.indmarman.2009.03.006", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850109000340?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2009.03.006", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When and why do firms outsource the sales process?", "design": "Empirical study/model testing of sales-process outsourcing decisions", "sample_context": "Business-to-business sales organizations considering outsourced/mercenary sales forces", "findings": "Examines conditions under which firms outsource sales processes; results distinguish outsourcing effects from internal sales-force governance.", "limitations": "Single empirical setting and nonexperimental evidence limit causal inference and transferability.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2009.03.006 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-0d26-76fe-9af3-744c1975719e" ], "corrections": [], "plain_english_summary": "Examines conditions under which firms outsource sales processes; results distinguish outsourcing effects from internal sales-force governance. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical study/model testing of sales-process outsourcing decisions" }, { "name": "Sample", "score": "0.5/1", "note": "Business-to-business sales organizations considering outsourced/mercenary sales forces" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "perceptions-of-sales-force-automation-differences-between-sales-force-and-management", "title": "Perceptions of sales force automation: Differences between sales force and management", "category": "B2B growth and sales", "study_type": "Comparative empirical survey of salespeople and managers", "citation": "Stephan F. Gohmann, Jian Guan, Robert M. Barker, David J. Faulds (2005). Perceptions of sales force automation: Differences between sales force and management. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2004.09.014.", "authors": [ "Stephan F. Gohmann", "Jian Guan", "Robert M. Barker", "David J. Faulds" ], "year": 2005, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2004.09.014", "doi_url": "https://doi.org/10.1016/j.indmarman.2004.09.014", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850104001476?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2004.09.014", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do salespeople\u2019s and managers\u2019 perceptions of SFA differ?", "design": "Comparative empirical survey of salespeople and managers", "sample_context": "Sales-force and management respondents evaluating sales-force automation", "findings": "Documents differences between sales-force and management perceptions of SFA; the title and publisher record explicitly identify the comparative empirical focus.", "limitations": "Perception measures and cross-sectional respondents do not establish performance causality.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2004.09.014 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-2908-7437-9214-324079ec40ab" ], "corrections": [], "plain_english_summary": "Documents differences between sales-force and management perceptions of SFA; the title and publisher record explicitly identify the comparative empirical focus. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Comparative empirical survey of salespeople and managers" }, { "name": "Sample", "score": "0.5/1", "note": "Sales-force and management respondents evaluating sales-force automation" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "antecedents-and-consequences-of-crm-technology-acceptance-in-the-sales-force", "title": "Antecedents and consequences of CRM technology acceptance in the sales force", "category": "B2B growth and sales", "study_type": "Empirical survey and structural model of CRM technology acceptance", "citation": "George J. Avlonitis, Nikolaos G. Panagopoulos (2005). Antecedents and consequences of CRM technology acceptance in the sales force. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2004.09.021.", "authors": [ "George J. Avlonitis", "Nikolaos G. Panagopoulos" ], "year": 2005, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2004.09.021", "doi_url": "https://doi.org/10.1016/j.indmarman.2004.09.021", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S001985010400149X?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2004.09.021", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What drives CRM acceptance among salespeople and what follows from acceptance?", "design": "Empirical survey and structural model of CRM technology acceptance", "sample_context": "Sales force using CRM technology in a business-selling context", "findings": "Tests antecedents and consequences of CRM acceptance in the sales force, linking acceptance with downstream sales-force outcomes.", "limitations": "Self-reported, cross-sectional acceptance data limit causal and objective-performance conclusions.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2004.09.021 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-46f1-7101-8329-eee4b1cef034" ], "corrections": [], "plain_english_summary": "Tests antecedents and consequences of CRM acceptance in the sales force, linking acceptance with downstream sales-force outcomes. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey and structural model of CRM technology acceptance" }, { "name": "Sample", "score": "0.5/1", "note": "Sales force using CRM technology in a business-selling context" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "motivating-the-industrial-sales-force-in-the-sales-forecasting-process", "title": "Motivating the industrial sales force in the sales forecasting process", "category": "Pricing and monetization", "study_type": "Empirical survey/model testing of motivation in forecasting", "citation": "Teresa M. McCarthy Byrne, Mark A. Moon, John T. Mentzer (2011). Motivating the industrial sales force in the sales forecasting process. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2010.06.003.", "authors": [ "Teresa M. McCarthy Byrne", "Mark A. Moon", "John T. Mentzer" ], "year": 2011, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2010.06.003", "doi_url": "https://doi.org/10.1016/j.indmarman.2010.06.003", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S001985011000074X?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2010.06.003", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How can industrial salespeople be motivated to contribute to forecasting?", "design": "Empirical survey/model testing of motivation in forecasting", "sample_context": "Industrial salespeople participating in sales forecasting", "findings": "Analyzes motivational mechanisms affecting industrial sales-force participation in forecasting.", "limitations": "Forecasting and motivation measures are context-bound and observational; common-method and generalization risks remain.", "founder_use": "Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2010.06.003 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-678d-763e-ac6b-79dadb301042" ], "corrections": [], "plain_english_summary": "Analyzes motivational mechanisms affecting industrial sales-force participation in forecasting. For your marketing: Use the study to frame a pricing or packaging hypothesis and identify outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey/model testing of motivation in forecasting" }, { "name": "Sample", "score": "0.5/1", "note": "Industrial salespeople participating in sales forecasting" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "sales-force-obsolescence-perceptions-from-sales-and-marketing-executives-of-individual-org", "title": "Sales force obsolescence: Perceptions from sales and marketing executives of individual, organizational, and environmental factors", "category": "B2B growth and sales", "study_type": "Empirical executive survey", "citation": "E JONES (2004). Sales force obsolescence: Perceptions from sales and marketing executives of individual, organizational, and environmental factors. Industrial Marketing Management. https://doi.org/10.1016/s0019-8501(03)00115-9.", "authors": [ "E JONES" ], "year": 2004, "journal": "Industrial Marketing Management", "doi": "10.1016/s0019-8501(03)00115-9", "doi_url": "https://doi.org/10.1016/s0019-8501(03)00115-9", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850103001159?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019-85010300115-9", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which factors do executives perceive as driving sales-force obsolescence?", "design": "Empirical executive survey", "sample_context": "Sales and marketing executives assessing sales-force obsolescence", "findings": "Identifies individual, organizational, and environmental factors executives associate with sales-force obsolescence.", "limitations": "Executive perceptions are not longitudinal evidence of actual obsolescence or performance.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/s0019-8501(03)00115-9 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-844d-72fc-801b-fdee2f35665d" ], "corrections": [], "plain_english_summary": "Identifies individual, organizational, and environmental factors executives associate with sales-force obsolescence. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical executive survey" }, { "name": "Sample", "score": "0.5/1", "note": "Sales and marketing executives assessing sales-force obsolescence" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "examining-sales-force-performance-in-organizations-that-use-behavior-based-sales-managemen", "title": "Examining sales force performance in organizations that use behavior-based sales management processes", "category": "B2B growth and sales", "study_type": "Empirical organizational survey/model test", "citation": "Ken Grant, David W. Cravens (1996). Examining sales force performance in organizations that use behavior-based sales management processes. Industrial Marketing Management. https://doi.org/10.1016/0019-8501(96)00038-7.", "authors": [ "Ken Grant", "David W. Cravens" ], "year": 1996, "journal": "Industrial Marketing Management", "doi": "10.1016/0019-8501(96)00038-7", "doi_url": "https://doi.org/10.1016/0019-8501(96)00038-7", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/0019850196000387?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/0019-85019600038-7", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How is sales performance related to behavior-based sales management?", "design": "Empirical organizational survey/model test", "sample_context": "Organizations using behavior-based sales-management processes", "findings": "Examines sales-force performance under behavior-based sales management, providing evidence on management-process/performance association.", "limitations": "Nonexperimental organizational data and possible industry heterogeneity constrain causal interpretation.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/0019-8501(96)00038-7 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-a10d-702b-b68e-65617493157c" ], "corrections": [], "plain_english_summary": "Examines sales-force performance under behavior-based sales management, providing evidence on management-process/performance association. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical organizational survey/model test" }, { "name": "Sample", "score": "0.5/1", "note": "Organizations using behavior-based sales-management processes" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "technology-and-the-sales-force", "title": "Technology and the Sales Force", "category": "B2B growth and sales", "study_type": "Empirical study of sales-technology use", "citation": "Amy J. Morgan, Scott A. Inks (2001). Technology and the Sales Force. Industrial Marketing Management. https://doi.org/10.1016/s0019-8501(99)00115-7.", "authors": [ "Amy J. Morgan", "Scott A. Inks" ], "year": 2001, "journal": "Industrial Marketing Management", "doi": "10.1016/s0019-8501(99)00115-7", "doi_url": "https://doi.org/10.1016/s0019-8501(99)00115-7", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850199001157?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019-85019900115-7", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does technology affect sales-force work and management?", "design": "Empirical study of sales-technology use", "sample_context": "Industrial/business sales force and sales-technology management context", "findings": "Provides empirical evidence on technology\u2019s role in the sales force and implications for managing technology use.", "limitations": "Technology changes over time and the study\u2019s context limit current SaaS extrapolation.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/s0019-8501(99)00115-7 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-bf8a-7648-96b6-fa187bd6d877" ], "corrections": [], "plain_english_summary": "Provides empirical evidence on technology\u2019s role in the sales force and implications for managing technology use. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical study of sales-technology use" }, { "name": "Sample", "score": "0.5/1", "note": "Industrial/business sales force and sales-technology management context" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "b2b-sales-force-productivity-applications-of-revenue-management-strategies-to-sales-manage", "title": "B2B sales force productivity: applications of revenue management strategies to sales management", "category": "B2B growth and sales", "study_type": "Empirical application/analysis of revenue-management strategies", "citation": "Judy A Siguaw, Sheryl E Kimes, Jule B Gassenheimer (2003). B2B sales force productivity: applications of revenue management strategies to sales management. Industrial Marketing Management. https://doi.org/10.1016/s0019-8501(02)00278-x.", "authors": [ "Judy A Siguaw", "Sheryl E Kimes", "Jule B Gassenheimer" ], "year": 2003, "journal": "Industrial Marketing Management", "doi": "10.1016/s0019-8501(02)00278-x", "doi_url": "https://doi.org/10.1016/s0019-8501(02)00278-x", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S001985010200278X?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019-85010200278-x", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can revenue-management principles improve B2B sales-force productivity?", "design": "Empirical application/analysis of revenue-management strategies", "sample_context": "B2B sales-force productivity and sales-management decisions", "findings": "Evaluates how revenue-management ideas can be applied to improve B2B sales-force productivity.", "limitations": "Application evidence is strategy/context specific and does not identify a universal treatment effect.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/s0019-8501(02)00278-x Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb6-e3bd-76de-8cfd-354f820fd501" ], "corrections": [], "plain_english_summary": "Evaluates how revenue-management ideas can be applied to improve B2B sales-force productivity. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical application/analysis of revenue-management strategies" }, { "name": "Sample", "score": "0.5/1", "note": "B2B sales-force productivity and sales-management decisions" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-impact-of-management-commitment-alignment-on-salespersons-adoption-of-sales-force-auto", "title": "The impact of management commitment alignment on salespersons' adoption of sales force automation technologies: An empirical investigation", "category": "B2B growth and sales", "study_type": "Empirical survey/model test of SFA adoption", "citation": "Robert Cascio, Babu John Mariadoss, Nacef Mouri (2010). The impact of management commitment alignment on salespersons' adoption of sales force automation technologies: An empirical investigation. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2009.12.010.", "authors": [ "Robert Cascio", "Babu John Mariadoss", "Nacef Mouri" ], "year": 2010, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2009.12.010", "doi_url": "https://doi.org/10.1016/j.indmarman.2009.12.010", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850109002090?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2009.12.010", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does alignment of management commitment influence salesperson SFA adoption?", "design": "Empirical survey/model test of SFA adoption", "sample_context": "Salespeople and management in organizations adopting SFA", "findings": "Tests whether aligned management commitment affects salesperson adoption of SFA.", "limitations": "Cross-sectional adoption perceptions and organizational context limit causal inference.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2009.12.010 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-0405-7551-bcf8-120596aee9e0" ], "corrections": [], "plain_english_summary": "Tests whether aligned management commitment affects salesperson adoption of SFA. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey/model test of SFA adoption" }, { "name": "Sample", "score": "0.5/1", "note": "Salespeople and management in organizations adopting SFA" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-does-sales-force-automation-influence-relationship-quality-and-performance-the-mediati", "title": "How does sales force automation influence relationship quality and performance? The mediating roles of learning and selling behaviors", "category": "B2B growth and sales", "study_type": "Empirical survey/mediation model", "citation": "Jeong Eun Park, Juyoung Kim, Alan J. Dubinsky, Hyunju Lee (2010). How does sales force automation influence relationship quality and performance? The mediating roles of learning and selling behaviors. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2009.11.003.", "authors": [ "Jeong Eun Park", "Juyoung Kim", "Alan J. Dubinsky", "Hyunju Lee" ], "year": 2010, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2009.11.003", "doi_url": "https://doi.org/10.1016/j.indmarman.2009.11.003", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850109001898?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2009.11.003", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Through what learning and selling behaviors does SFA affect relationship quality and performance?", "design": "Empirical survey/mediation model", "sample_context": "Salespeople using sales-force automation in buyer\u2013seller relationships", "findings": "Tests whether SFA relates to relationship quality and performance through learning and selling behaviors.", "limitations": "Mediation from cross-sectional self-report data should not be read as temporal causality.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2009.11.003 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-373b-7613-bf72-4e2438303843" ], "corrections": [], "plain_english_summary": "Tests whether SFA relates to relationship quality and performance through learning and selling behaviors. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey/mediation model" }, { "name": "Sample", "score": "0.5/1", "note": "Salespeople using sales-force automation in buyer\u2013seller relationships" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "linking-big-data-analytical-intelligence-to-customer-relationship-management-performance", "title": "Linking big data analytical intelligence to customer relationship management performance", "category": "Acquisition and retention", "study_type": "Empirical survey and structural model", "citation": "Chubing Zhang, Xinchun Wang, Annie Peng Cui, Shenghao Han (2020). Linking big data analytical intelligence to customer relationship management performance. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2020.10.012.", "authors": [ "Chubing Zhang", "Xinchun Wang", "Annie Peng Cui", "Shenghao Han" ], "year": 2020, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2020.10.012", "doi_url": "https://doi.org/10.1016/j.indmarman.2020.10.012", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850120308762?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2020.10.012", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does big-data analytical intelligence contribute to CRM performance?", "design": "Empirical survey and structural model", "sample_context": "Firms using big-data analytical intelligence for CRM", "findings": "Links big-data analytical intelligence capabilities to CRM performance and tests the proposed capability relationships.", "limitations": "Survey/common-method and cross-sectional design limit causal and objective-outcome claims.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2020.10.012 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-5335-76f8-9a40-5d452f3c3692" ], "corrections": [], "plain_english_summary": "Links big-data analytical intelligence capabilities to CRM performance and tests the proposed capability relationships. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey and structural model" }, { "name": "Sample", "score": "0.5/1", "note": "Firms using big-data analytical intelligence for CRM" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "when-to-outsource-the-sales-force-for-new-products", "title": "When to outsource the sales force for new products", "category": "B2B growth and sales", "study_type": "Empirical model/analysis of new-product sales-force outsourcing", "citation": "Valerie Good, Roger J. Calantone (2019). When to outsource the sales force for new products. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2019.02.010.", "authors": [ "Valerie Good", "Roger J. Calantone" ], "year": 2019, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2019.02.010", "doi_url": "https://doi.org/10.1016/j.indmarman.2019.02.010", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850118301202?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2019.02.010", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Under what conditions should firms outsource new-product sales?", "design": "Empirical model/analysis of new-product sales-force outsourcing", "sample_context": "Firms launching new products and choosing internal versus outsourced sales forces", "findings": "Identifies contingencies under which outsourcing the sales force for new products is advantageous.", "limitations": "New-product outsourcing decisions are context dependent; observational evidence limits causal generalization.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2019.02.010 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-7311-71bf-9a79-c751dd07e680" ], "corrections": [], "plain_english_summary": "Identifies contingencies under which outsourcing the sales force for new products is advantageous. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical model/analysis of new-product sales-force outsourcing" }, { "name": "Sample", "score": "0.5/1", "note": "Firms launching new products and choosing internal versus outsourced sales forces" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "moving-beyond-the-direct-effect-of-sfa-adoption-on-salesperson-performance-training-and-su", "title": "Moving beyond the direct effect of SFA adoption on salesperson performance: training and support as key moderating factors", "category": "B2B growth and sales", "study_type": "Empirical survey/moderation model", "citation": "Michael Ahearne, Ronald Jelinek, Adam Rapp (2005). Moving beyond the direct effect of SFA adoption on salesperson performance: training and support as key moderating factors. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2004.09.020.", "authors": [ "Michael Ahearne", "Ronald Jelinek", "Adam Rapp" ], "year": 2005, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2004.09.020", "doi_url": "https://doi.org/10.1016/j.indmarman.2004.09.020", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850104001518?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/j.indmarman.2004.09.020", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When do training and support strengthen SFA\u2019s effect on salesperson performance?", "design": "Empirical survey/moderation model", "sample_context": "Salespeople adopting sales-force automation", "findings": "Tests training and support as moderators of the SFA-adoption/performance relationship rather than assuming a direct effect.", "limitations": "Cross-sectional self-reports and technology-specific context limit causal and temporal conclusions.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher DOI landing page identifies the exact title, authors, journal record and empirical-design sections/abstract: https://doi.org/10.1016/j.indmarman.2004.09.020 Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-9219-74cb-a0f4-e41cd84f86f8" ], "corrections": [], "plain_english_summary": "Tests training and support as moderators of the SFA-adoption/performance relationship rather than assuming a direct effect. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey/moderation model" }, { "name": "Sample", "score": "0.5/1", "note": "Salespeople adopting sales-force automation" }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "name-similarity-encourages-generosity-a-field-experiment-in-email-personalization", "title": "Name Similarity Encourages Generosity: A Field Experiment in Email Personalization", "category": "Paid media and measurement", "study_type": "Randomized field experiment manipulating name matching in email communications.", "citation": "Minah H. Jung, Adam L. Alter (2020). Name Similarity Encourages Generosity: A Field Experiment in Email Personalization. Marketing Science. https://doi.org/10.1287/mksc.2019.1220.", "authors": [ "Minah H. Jung", "Adam L. Alter" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2019.1220", "doi_url": "https://doi.org/10.1287/mksc.2019.1220", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1220", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1220", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does individualized name matching improve email response and giving?", "design": "Randomized field experiment manipulating name matching in email communications.", "sample_context": "DonorsChoose.org; N=30,297 potential donors; surname, initial, gender, ethnicity and country-of-origin matching.", "findings": "Full surname matching increased opens, clicks, donations and total money; shared initial also increased generosity.", "limitations": "Charitable giving and teacher/donor name matching may not transfer to commercial SaaS conversion; abstract gives no broader external-validity claim.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher abstract reports N, randomized field experiment, manipulations and behavioral outcomes. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-b30d-714b-bcf0-d718220ded9c" ], "corrections": [], "plain_english_summary": "Full surname matching increased opens, clicks, donations and total money; shared initial also increased generosity. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment manipulating name matching in email communications." }, { "name": "Sample", "score": "1/1", "note": "DonorsChoose.org; N=30,297 potential donors; surname, initial, gender, ethnicity and country-of-origin matching." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-do-recommender-systems-affect-sales-diversity-a-cross-category-investigation-via-rando", "title": "How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment", "category": "B2B growth and sales", "study_type": "Randomized field experiment comparing collaborative-filter recommendations with no recommendations; product/category analyses.", "citation": "Daniel Lee, Kartik Hosanagar (2019). How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2018.0800.", "authors": [ "Daniel Lee", "Kartik Hosanagar" ], "year": 2019, "journal": "Information Systems Research", "doi": "10.1287/isre.2018.0800", "doi_url": "https://doi.org/10.1287/isre.2018.0800", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0800", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2018.0800", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do collaborative recommenders affect aggregate and individual sales diversity?", "design": "Randomized field experiment comparing collaborative-filter recommendations with no recommendations; product/category analyses.", "sample_context": "Top North American retailer; 82,290 products and 1,138,238 users.", "findings": "Traditional collaborative filtering reduced aggregate sales diversity; purchase-based CF had larger effects than view-based; niche items gained absolutely but lost share.", "limitations": "One top North American retailer and collaborative-filter designs; aggregate diversity can differ from individual consumption diversity.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher abstract states the randomization, scale and four reported findings. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-f1e6-72ff-8566-3006c552c327" ], "corrections": [], "plain_english_summary": "Traditional collaborative filtering reduced aggregate sales diversity; purchase-based CF had larger effects than view-based; niche items gained absolutely but lost share. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment comparing collaborative-filter recommendations with no recommendations; product/category analyses." }, { "name": "Sample", "score": "1/1", "note": "Top North American retailer; 82,290 products and 1,138,238 users." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-do-recommender-systems-lead-to-consumer-purchases-a-causal-mediation-analysis-of-a-fie", "title": "How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment", "category": "Paid media and measurement", "study_type": "Randomized controlled field experiment with causal mediation analysis.", "citation": "Xingyu Li, Jens Grahl, Oliver Hinz (2022). How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2021.1074.", "authors": [ "Xingyu Li", "Jens Grahl", "Oliver Hinz" ], "year": 2022, "journal": "Information Systems Research", "doi": "10.1287/isre.2021.1074", "doi_url": "https://doi.org/10.1287/isre.2021.1074", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.1074", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.1074", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Through what causal paths do personalized recommendations induce purchases?", "design": "Randomized controlled field experiment with causal mediation analysis.", "sample_context": "Website of an online book retailer; consumer purchase behavior and consideration-set breadth/depth.", "findings": "Personalized recommendations increased purchase propensity 12.4% and basket value 1.7%; effects were largely mediated by consideration-set changes, especially breadth.", "limitations": "Online-book-retailer context; publisher abstract does not establish effects for other categories or platforms.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher abstract reports design, setting, quantified effects and mediation mechanism. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb7-ceae-717b-a783-628de8aeff22" ], "corrections": [], "plain_english_summary": "Personalized recommendations increased purchase propensity 12.4% and basket value 1.7%; effects were largely mediated by consideration-set changes, especially breadth. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized controlled field experiment with causal mediation analysis." }, { "name": "Sample", "score": "0.5/1", "note": "Website of an online book retailer; consumer purchase behavior and consideration-set breadth/depth." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "product-set-granularity-and-consumer-response-to-recommendations", "title": "Product set granularity and consumer response to recommendations", "category": "Customer behavior and adoption", "study_type": "Field-data empirical study of explicit recommendation sets, with behavioral indicators and simulation.", "citation": "Dimitrios Tsekouras, Benedict G. C. Dellaert, Bas Donkers, Gerald H\u00e4ubl (2020). Product set granularity and consumer response to recommendations. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-019-00682-6.", "authors": [ "Dimitrios Tsekouras", "Benedict G. C. Dellaert", "Bas Donkers", "Gerald H\u00e4ubl" ], "year": 2020, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-019-00682-6", "doi_url": "https://doi.org/10.1007/s11747-019-00682-6", "primary_url": "https://link.springer.com/article/10.1007/s11747-019-00682-6", "accessible_url": "https://link.springer.com/article/10.1007/s11747-019-00682-6", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does similarity/granularity within recommended product sets affect response?", "design": "Field-data empirical study of explicit recommendation sets, with behavioral indicators and simulation.", "sample_context": "Online recommendation/product-search setting; real-world field data and consumer engagement heterogeneity.", "findings": "Finer-grained recommendation sets reduced response despite better products; effect was stronger for more engaged consumers.", "limitations": "Field setting and recommendation type are specific; simulation is illustrative rather than a new causal experiment.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher full text says the study uses real-world field data and reports lower response for fine-grained sets and moderation by engagement. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-0b6d-72f3-82fd-3d6649c8c9ae" ], "corrections": [], "plain_english_summary": "Finer-grained recommendation sets reduced response despite better products; effect was stronger for more engaged consumers. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Field-data empirical study of explicit recommendation sets, with behavioral indicators and simulation." }, { "name": "Sample", "score": "0.5/1", "note": "Online recommendation/product-search setting; real-world field data and consumer engagement heterogeneity." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "complementarity-and-cannibalization-of-offline-to-online-targeting-a-field-experiment-on-o", "title": "Complementarity and Cannibalization of Offline-to-Online Targeting: A Field Experiment on Omnichannel Commerce", "category": "Customer behavior and adoption", "study_type": "Randomized field experiment testing offline-to-online targeting and cross-channel effects.", "citation": "Xueming Luo, Yuxchi Zhang, Fue Zeng, Zhe Qu (2020). Complementarity and Cannibalization of Offline-to-Online Targeting: A Field Experiment on Omnichannel Commerce. MIS Quarterly. https://doi.org/10.25300/MISQ/2020/15630.", "authors": [ "Xueming Luo", "Yuxchi Zhang", "Fue Zeng", "Zhe Qu" ], "year": 2020, "journal": "MIS Quarterly", "doi": "10.25300/MISQ/2020/15630", "doi_url": "https://doi.org/10.25300/MISQ/2020/15630", "primary_url": "https://misq.umn.edu/misq/article-abstract/44/2/957/449/Complementarity-and-Cannibalization-of-Offline-to?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article-abstract/44/2/957/449/Complementarity-and-Cannibalization-of-Offline-to?redirectedFrom=fulltext", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When does offline targeting complement versus cannibalize online commerce?", "design": "Randomized field experiment testing offline-to-online targeting and cross-channel effects.", "sample_context": "More than 11,200 customers of a large department store.", "findings": "Publisher abstract/search result reports causal evidence for both complementarity and cannibalization between offline and online targeting.", "limitations": "Department-store customers and one omnichannel context; source does not support universal channel effects.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher PDF/search result states randomized experiment and sample size; DOI landing page identifies the study. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-1e1c-741e-98bc-80d5da710b39" ], "corrections": [], "plain_english_summary": "Publisher abstract/search result reports causal evidence for both complementarity and cannibalization between offline and online targeting. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment testing offline-to-online targeting and cross-channel effects." }, { "name": "Sample", "score": "1/1", "note": "More than 11,200 customers of a large department store." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "direct-mail-to-prospects-and-email-to-current-customers-modeling-and-field-testing-multich", "title": "Direct mail to prospects and email to current customers? Modeling and field-testing multichannel marketing", "category": "Paid media and measurement", "study_type": "Hierarchical empirical model plus randomized four-cell field experiment (control, email, direct mail, both).", "citation": "Albert Valenti, Shuba Srinivasan, Gokhan Yildirim, Koen Pauwels (2024). Direct mail to prospects and email to current customers? Modeling and field-testing multichannel marketing. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-023-00962-2.", "authors": [ "Albert Valenti", "Shuba Srinivasan", "Gokhan Yildirim", "Koen Pauwels" ], "year": 2024, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-023-00962-2", "doi_url": "https://doi.org/10.1007/s11747-023-00962-2", "primary_url": "https://link.springer.com/article/10.1007/s11747-023-00962-2", "accessible_url": "https://link.springer.com/article/10.1007/s11747-023-00962-2", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do email and direct mail differ by customer value and prospect/current-customer status?", "design": "Hierarchical empirical model plus randomized four-cell field experiment (control, email, direct mail, both).", "sample_context": "Beauty retailer and apparel retailer; two years of purchase history; beauty experiment stratified across six value segments and capped at 33,000 mail pieces.", "findings": "Field experiment provided causal support for reallocating direct mail toward prospects/high-value segments and email toward current customers (as described by the paper).", "limitations": "The experiment was restricted to customers contactable by both channels and constrained direct-mail volume; thus self-selected non-contactable customers are outside the test.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher full text explicitly describes four cells, two-year history, six segments, contactability restriction and causal goal. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-32bb-7618-b632-8a04c1127bd0" ], "corrections": [], "plain_english_summary": "Field experiment provided causal support for reallocating direct mail toward prospects/high-value segments and email toward current customers (as described by the paper). For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Hierarchical empirical model plus randomized four-cell field experiment (control, email, direct mail, both)." }, { "name": "Sample", "score": "1/1", "note": "Beauty retailer and apparel retailer; two years of purchase history; beauty experiment stratified across six value segments and capped at 33,000 mail pieces." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "effective-implementation-of-predictive-sales-analytics", "title": "Effective Implementation of Predictive Sales Analytics", "category": "B2B growth and sales", "study_type": "Predictive churn model built on transaction histories and implemented/tested in a field experiment.", "citation": "Johannes Habel, Sascha Alavi, Nicolas Heinitz (2023). Effective Implementation of Predictive Sales Analytics. Journal of Marketing Research. https://doi.org/10.1177/00222437221151039.", "authors": [ "Johannes Habel", "Sascha Alavi", "Nicolas Heinitz" ], "year": 2023, "journal": "Journal of Marketing Research", "doi": "10.1177/00222437221151039", "doi_url": "https://doi.org/10.1177/00222437221151039", "primary_url": "https://journals.sagepub.com/doi/10.1177/00222437221151039", "accessible_url": "https://journals.sagepub.com/doi/abs/10.1177/00222437221151039", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How can predictive sales analytics be effectively implemented to improve customer outcomes?", "design": "Predictive churn model built on transaction histories and implemented/tested in a field experiment.", "sample_context": "9.7 million transactions from a B2B company; salespeople/customers in predictive-sales-analytics implementation.", "findings": "Publisher abstract reports development of a predictive churn model and implementation in a field experiment; the study evaluates implementation effectiveness, not merely predictive accuracy.", "limitations": "Single B2B company and implementation context; publisher snippet does not warrant transfer to all sales organizations.", "founder_use": "Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_basis": "Publisher page/search result explicitly states 9.7 million B2B transactions, predictive churn model and field experiment. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-6ca5-7571-bb2e-9d0b5cb5eae4" ], "corrections": [], "plain_english_summary": "Publisher abstract reports development of a predictive churn model and implementation in a field experiment; the study evaluates implementation effectiveness, not merely predictive accuracy. For your marketing: Use as a mechanism or sales-process design reference. Validate the relationship in your own deal size, buying committee and sales cycle.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Predictive churn model built on transaction histories and implemented/tested in a field experiment." }, { "name": "Sample", "score": "0.5/1", "note": "9.7 million transactions from a B2B company; salespeople/customers in predictive-sales-analytics implementation." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "beyond-the-target-customer-social-effects-of-customer-relationship-management-campaigns", "title": "Beyond the Target Customer: Social Effects of Customer Relationship Management Campaigns", "category": "Paid media and measurement", "study_type": "Randomized CRM field experiment with network/social-connection analysis.", "citation": "Eva Ascarza, Peter Ebbes, Oded Netzer, Matthew Danielson (2017). Beyond the Target Customer: Social Effects of Customer Relationship Management Campaigns. Journal of Marketing Research. https://doi.org/10.1509/jmr.15.0442.", "authors": [ "Eva Ascarza", "Peter Ebbes", "Oded Netzer", "Matthew Danielson" ], "year": 2017, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.15.0442", "doi_url": "https://doi.org/10.1509/jmr.15.0442", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0442", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmr.15.0442", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do CRM campaigns affect people connected socially to the targeted customer?", "design": "Randomized CRM field experiment with network/social-connection analysis.", "sample_context": "Nearly 6,000 customers of a mobile telecommunications provider and their social connections.", "findings": "Targeting customers affected the behavior of their social connections, showing CRM campaign effects beyond directly targeted customers.", "limitations": "Mobile telecom network and social ties are context-specific; the abstract does not establish that all CRM campaigns generate spillovers.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher search result states randomized field experiment, nearly 6,000 customers and social effects. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-4561-750f-8072-c3db35610467" ], "corrections": [], "plain_english_summary": "Targeting customers affected the behavior of their social connections, showing CRM campaign effects beyond directly targeted customers. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized CRM field experiment with network/social-connection analysis." }, { "name": "Sample", "score": "1/1", "note": "Nearly 6,000 customers of a mobile telecommunications provider and their social connections." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "capturing-marketing-information-to-fuel-growth", "title": "Capturing Marketing Information to Fuel Growth", "category": "Customer behavior and adoption", "study_type": "Online testing/field-experiment evidence on marketing information and growth (paper\u2019s publisher page describes online testing/field experiment data).", "citation": "Rex Yuxing Du, Oded Netzer, David A. Schweidel, Debanjan Mitra (2021). Capturing Marketing Information to Fuel Growth. Journal of Marketing. https://doi.org/10.1177/0022242920969198.", "authors": [ "Rex Yuxing Du", "Oded Netzer", "David A. Schweidel", "Debanjan Mitra" ], "year": 2021, "journal": "Journal of Marketing", "doi": "10.1177/0022242920969198", "doi_url": "https://doi.org/10.1177/0022242920969198", "primary_url": "https://journals.sagepub.com/doi/10.1177/0022242920969198", "accessible_url": "https://journals.sagepub.com/doi/10.1177/0022242920969198", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How can firms capture marketing information and use it to fuel growth?", "design": "Online testing/field-experiment evidence on marketing information and growth (paper\u2019s publisher page describes online testing/field experiment data).", "sample_context": "Marketing-information/CRM setting described by publisher page; empirical tests use online testing/field-experiment data.", "findings": "The paper uses causal online-test evidence to study how marketing information can be captured and used for growth.", "limitations": "Publisher page excerpt available here does not expose all sample details; do not generalize beyond its tested settings.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher DOI page explicitly labels the contribution empirical and mentions online testing/field experiment data. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-9373-71d9-8263-d7cea9e304a1" ], "corrections": [], "plain_english_summary": "The paper uses causal online-test evidence to study how marketing information can be captured and used for growth. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Online testing/field-experiment evidence on marketing information and growth (paper\u2019s publisher page describes online testing/field experiment data)." }, { "name": "Sample", "score": "0.5/1", "note": "Marketing-information/CRM setting described by publisher page; empirical tests use online testing/field-experiment data." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "crumbs-of-the-cookie-user-profiling-in-customer-base-analysis-and-behavioral-targeting", "title": "Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting", "category": "Customer behavior and adoption", "study_type": "Scalable user-profile inference from online surfing records; empirical customer-base/display-ad analysis and economic simulation.", "citation": "Zainab Jamal, Kartik Hosanagar, Avi Goldfarb (2016). Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting. Marketing Science. https://doi.org/10.1287/mksc.2015.0956.", "authors": [ "Zainab Jamal", "Kartik Hosanagar", "Avi Goldfarb" ], "year": 2016, "journal": "Marketing Science", "doi": "10.1287/mksc.2015.0956", "doi_url": "https://doi.org/10.1287/mksc.2015.0956", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0956", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0956", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can online surfing data infer useful profiles for customer analysis and behavioral targeting?", "design": "Scalable user-profile inference from online surfing records; empirical customer-base/display-ad analysis and economic simulation.", "sample_context": "Online activity records across search engines/advertising networks; applications to customer-base analysis and display advertising.", "findings": "Profiles were interpretable; internal-only data could be biased; search engines covered less activity but had higher data quality and could recover profiles; simulation showed targeting gains.", "limitations": "Profile inference and economic gains are data/model dependent; simulation is not a randomized ad experiment.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract explicitly reports empirical analysis, data-quality comparison, temporal limits and simulation. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-157d-75da-8718-a6cbe9f601b5" ], "corrections": [], "plain_english_summary": "Profiles were interpretable; internal-only data could be biased; search engines covered less activity but had higher data quality and could recover profiles; simulation showed targeting gains. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Scalable user-profile inference from online surfing records; empirical customer-base/display-ad analysis and economic simulation." }, { "name": "Sample", "score": "0.5/1", "note": "Online activity records across search engines/advertising networks; applications to customer-base analysis and display advertising." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "helping-small-businesses-become-more-data-driven-a-field-experiment-on-ebay", "title": "Helping Small Businesses Become More Data-Driven: A Field Experiment on eBay", "category": "Customer behavior and adoption", "study_type": "Experiment-based causal analysis of randomized introduction of eBay Seller Hub dashboard.", "citation": "Sagit Bar-Gill, Nir Hak, Eran Toch (2024). Helping Small Businesses Become More Data-Driven: A Field Experiment on eBay. Management Science. https://doi.org/10.1287/mnsc.2021.02026.", "authors": [ "Sagit Bar-Gill", "Nir Hak", "Eran Toch" ], "year": 2024, "journal": "Management Science", "doi": "10.1287/mnsc.2021.02026", "doi_url": "https://doi.org/10.1287/mnsc.2021.02026", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2021.02026", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2021.02026", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What is the causal impact of an analytics dashboard on SME performance and data-driven decision making?", "design": "Experiment-based causal analysis of randomized introduction of eBay Seller Hub dashboard.", "sample_context": "Small-to-medium e-retailers on eBay; randomized introduction of a data-rich seller dashboard.", "findings": "Seller Hub increased data-driven decision making and revenues 3.6%; more items transacted and service quality rose without average-price increases; over one-third of impact came from active monitoring.", "limitations": "eBay SME sellers and a particular dashboard; findings do not identify effects for non-platform SaaS analytics tools.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract explicitly reports randomized introduction, 3.6% revenue effect and monitoring mechanism. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-cd4d-74f2-b6a0-96fe4fa6e93f" ], "corrections": [], "plain_english_summary": "Seller Hub increased data-driven decision making and revenues 3.6%; more items transacted and service quality rose without average-price increases; over one-third of impact came from active monitoring. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Experiment-based causal analysis of randomized introduction of eBay Seller Hub dashboard." }, { "name": "Sample", "score": "0.5/1", "note": "Small-to-medium e-retailers on eBay; randomized introduction of a data-rich seller dashboard." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "dynamic-catalog-mailing-policies", "title": "Dynamic Catalog Mailing Policies", "category": "Customer behavior and adoption", "study_type": "Dynamic mailing-policy model estimated on historical catalog data and evaluated in a large-scale field test.", "citation": "Duncan I. Simester, Peng Sun, John N. Tsitsiklis (2006). Dynamic Catalog Mailing Policies. Management Science. https://doi.org/10.1287/mnsc.1050.0504.", "authors": [ "Duncan I. Simester", "Peng Sun", "John N. Tsitsiklis" ], "year": 2006, "journal": "Management Science", "doi": "10.1287/mnsc.1050.0504", "doi_url": "https://doi.org/10.1287/mnsc.1050.0504", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1050.0504", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1050.0504", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can dynamic, long-run-aware catalog mailing outperform myopic likelihood-of-immediate-order targeting?", "design": "Dynamic mailing-policy model estimated on historical catalog data and evaluated in a large-scale field test.", "sample_context": "Large historical sample from a mail-order catalog firm plus field-test customers.", "findings": "The dynamic model received support in the field test, while results also identified opportunities for improvement over the model.", "limitations": "One catalog firm and policy evaluation; abstract explicitly notes further improvement opportunities.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract states historical-data application and large-scale field test, with support and improvement opportunities. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-3161-746e-8cc2-376ceaca5797" ], "corrections": [], "plain_english_summary": "The dynamic model received support in the field test, while results also identified opportunities for improvement over the model. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Dynamic mailing-policy model estimated on historical catalog data and evaluated in a large-scale field test." }, { "name": "Sample", "score": "0.5/1", "note": "Large historical sample from a mail-order catalog firm plus field-test customers." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "optimal-selection-for-direct-mail", "title": "Optimal Selection for Direct Mail", "category": "Customer behavior and adoption", "study_type": "Profit-based target-selection methodology with empirical predictive evaluation.", "citation": "Jan Roelf Bult, Tom Wansbeek (1995). Optimal Selection for Direct Mail. Marketing Science. https://doi.org/10.1287/mksc.14.4.378.", "authors": [ "Jan Roelf Bult", "Tom Wansbeek" ], "year": 1995, "journal": "Marketing Science", "doi": "10.1287/mksc.14.4.378", "doi_url": "https://doi.org/10.1287/mksc.14.4.378", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.14.4.378", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.14.4.378", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which households should receive direct mail when mailing cost and expected return are optimized?", "design": "Profit-based target-selection methodology with empirical predictive evaluation.", "sample_context": "Household mailing-list population in a direct-mail setting.", "findings": "Empirical part reports high predictive accuracy and higher net returns than traditional approaches.", "limitations": "Abstract does not disclose the firm/sample size and evidence is from direct-mail target selection; external validity is limited by that setting.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract explicitly reports empirical predictive accuracy and net-return comparison. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb8-f9a2-7626-bb64-abf9ce285916" ], "corrections": [], "plain_english_summary": "Empirical part reports high predictive accuracy and higher net returns than traditional approaches. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Profit-based target-selection methodology with empirical predictive evaluation." }, { "name": "Sample", "score": "0.5/1", "note": "Household mailing-list population in a direct-mail setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "personalized-online-advertising-effectiveness-the-interplay-of-what-when-and-where", "title": "Personalized Online Advertising Effectiveness: The Interplay of What, When, and Where", "category": "Paid media and measurement", "study_type": "Two field experiments testing personalization, timing, placement/context, and advertising effectiveness.", "citation": "Alexander Bleier, Maik Eisenbeiss (2015). Personalized Online Advertising Effectiveness: The Interplay of What, When, and Where. Marketing Science. https://doi.org/10.1287/mksc.2015.0930.", "authors": [ "Alexander Bleier", "Maik Eisenbeiss" ], "year": 2015, "journal": "Marketing Science", "doi": "10.1287/mksc.2015.0930", "doi_url": "https://doi.org/10.1287/mksc.2015.0930", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0930", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2015.0930", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do message, timing, and placement interact in personalized online advertising?", "design": "Two field experiments testing personalization, timing, placement/context, and advertising effectiveness.", "sample_context": "Consumers receiving personalized online display advertising in commercial field settings.", "findings": "Effectiveness depends jointly on what is personalized, when the ad appears, and where it appears; well-targeted personalization can increase responsiveness.", "limitations": "Findings are interaction-specific and rely on the tested advertisers, placements, and personalization data; personalization effectiveness is not uniform.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher/DOI record identifies the two-field-experiment paper; the indexed abstract/title and article framing specify the three-way focus. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-517a-7704-a92c-99b9483ec291" ], "corrections": [], "plain_english_summary": "Effectiveness depends jointly on what is personalized, when the ad appears, and where it appears; well-targeted personalization can increase responsiveness. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Two field experiments testing personalization, timing, placement/context, and advertising effectiveness." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers receiving personalized online display advertising in commercial field settings." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "television-advertising-and-online-shopping", "title": "Television Advertising and Online Shopping", "category": "Paid media and measurement", "study_type": "Field experiment linking randomized/variation in television ad exposure to online shopping behavior, with purchase-funnel analysis.", "citation": "Jana Liaukonyte, Theodore Teixeira, Kenneth C. Wilbur (2015). Television Advertising and Online Shopping. Marketing Science. https://doi.org/10.1287/mksc.2014.0899.", "authors": [ "Jana Liaukonyte", "Theodore Teixeira", "Kenneth C. Wilbur" ], "year": 2015, "journal": "Marketing Science", "doi": "10.1287/mksc.2014.0899", "doi_url": "https://doi.org/10.1287/mksc.2014.0899", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2014.0899", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2014.0899", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does television advertising affect online shopping and which funnel outcomes respond?", "design": "Field experiment linking randomized/variation in television ad exposure to online shopping behavior, with purchase-funnel analysis.", "sample_context": "Online shopping sessions and television advertising for a retail advertiser.", "findings": "Television advertising changes online shopping activity, with effects varying by ad characteristics and shopping stage.", "limitations": "The setting is a particular advertiser/media campaign and observational components may constrain causal interpretation for some outcomes.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher DOI page lists the empirical paper; title and article abstract describe television advertising and online-shopping outcomes. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-7229-740f-9680-4d7cbee5af04" ], "corrections": [], "plain_english_summary": "Television advertising changes online shopping activity, with effects varying by ad characteristics and shopping stage. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment linking randomized/variation in television ad exposure to online shopping behavior, with purchase-funnel analysis." }, { "name": "Sample", "score": "0.5/1", "note": "Online shopping sessions and television advertising for a retail advertiser." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "which-firms-gain-from-digital-advertising-evidence-from-a-field-experiment", "title": "Which Firms Gain from Digital Advertising? Evidence from a Field Experiment", "category": "Paid media and measurement", "study_type": "Large-scale field experiment randomizing digital advertising for restaurants and comparing heterogeneous treatment effects.", "citation": "Weijia Dai, Hyunjin Kim, Michael Luca (2023). Which Firms Gain from Digital Advertising? Evidence from a Field Experiment. Marketing Science. https://doi.org/10.1287/mksc.2023.1436.", "authors": [ "Weijia Dai", "Hyunjin Kim", "Michael Luca" ], "year": 2023, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.1436", "doi_url": "https://doi.org/10.1287/mksc.2023.1436", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.1436", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.1436", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which types of firms gain most from digital advertising?", "design": "Large-scale field experiment randomizing digital advertising for restaurants and comparing heterogeneous treatment effects.", "sample_context": "Restaurants and their online customers on a digital platform.", "findings": "Digital advertising gains differ across restaurant types; the experiment identifies which businesses benefit more from advertising.", "limitations": "Restaurant platform and local-service setting limit direct transfer to SaaS; heterogeneous effects mean average treatment effects are not universal.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "INFORMS/publisher and author-page records identify a large-scale restaurant field experiment and its authors/context. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-8e53-75aa-80b2-e7daee1fc0fe" ], "corrections": [], "plain_english_summary": "Digital advertising gains differ across restaurant types; the experiment identifies which businesses benefit more from advertising. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Large-scale field experiment randomizing digital advertising for restaurants and comparing heterogeneous treatment effects." }, { "name": "Sample", "score": "0.5/1", "note": "Restaurants and their online customers on a digital platform." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "email-marketing-as-a-tool-for-strategic-persuasion", "title": "Email Marketing as a Tool for Strategic Persuasion", "category": "Paid media and measurement", "study_type": "Empirical analysis of email marketing campaigns examining strategic persuasion and campaign response.", "citation": "Jacquelyn S. Thomas, Chaoqun Chen, Dawn Iacobucci (2022). Email Marketing as a Tool for Strategic Persuasion. Journal of Interactive Marketing. https://doi.org/10.1177/10949968221095552.", "authors": [ "Jacquelyn S. Thomas", "Chaoqun Chen", "Dawn Iacobucci" ], "year": 2022, "journal": "Journal of Interactive Marketing", "doi": "10.1177/10949968221095552", "doi_url": "https://doi.org/10.1177/10949968221095552", "primary_url": "https://journals.sagepub.com/doi/10.1177/10949968221095552", "accessible_url": "https://journals.sagepub.com/doi/10.1177/10949968221095552", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How can email marketing be used strategically to persuade customers?", "design": "Empirical analysis of email marketing campaigns examining strategic persuasion and campaign response.", "sample_context": "Commercial email recipients/campaigns in the study\u2019s field setting.", "findings": "Email can operate as a strategic persuasion tool; response depends on message strategy rather than sending alone.", "limitations": "Campaign and audience context limit causal generalization; email outcomes may be short-run engagement rather than lifetime value.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "SAGE publisher page identifies authors, journal, and article; article is indexed as empirical email-marketing research. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-a740-7353-8efa-5edeef424f8f" ], "corrections": [], "plain_english_summary": "Email can operate as a strategic persuasion tool; response depends on message strategy rather than sending alone. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of email marketing campaigns examining strategic persuasion and campaign response." }, { "name": "Sample", "score": "0.5/1", "note": "Commercial email recipients/campaigns in the study\u2019s field setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "implications-of-loyalty-program-membership-and-service-experiences-for-customer-retention", "title": "Implications of loyalty program membership and service experiences for customer retention and value", "category": "Acquisition and retention", "study_type": "Cross-sectional and time-series field analysis of a financial-services loyalty program.", "citation": "Ruth N. Bolton, P. K. Kannan, Matthew D. Bramlett (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science. https://doi.org/10.1177/0092070300281009.", "authors": [ "Ruth N. Bolton", "P. K. Kannan", "Matthew D. Bramlett" ], "year": 2000, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1177/0092070300281009", "doi_url": "https://doi.org/10.1177/0092070300281009", "primary_url": "https://link.springer.com/article/10.1177/0092070300281009", "accessible_url": "https://link.springer.com/article/10.1177/0092070300281009", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Under what conditions does loyalty-program membership improve customer evaluations, behavior, repeat purchase intentions, retention and value?", "design": "Cross-sectional and time-series field analysis of a financial-services loyalty program.", "sample_context": "Customers of a worldwide financial-services company offering a loyalty-reward program.", "findings": "Members discounted or overlooked negative evaluations relative to competitors; the paper links program membership and service experiences to retention and value.", "limitations": "The publisher abstract identifies a single worldwide financial-services company and observational cross-sectional/time-series data; generalization beyond that setting and causal attribution are limited.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Publisher abstract explicitly says the study uses cross-sectional, time-series data and reports the member-versus-nonmember evaluation result. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-edba-776b-9174-7fd3e3a19cd9" ], "corrections": [], "plain_english_summary": "Members discounted or overlooked negative evaluations relative to competitors; the paper links program membership and service experiences to retention and value. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional and time-series field analysis of a financial-services loyalty program." }, { "name": "Sample", "score": "0.5/1", "note": "Customers of a worldwide financial-services company offering a loyalty-reward program." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "exploring-customer-loyalty-following-service-recovery-the-mediating-effects-of-trust-and-e", "title": "Exploring Customer Loyalty Following Service Recovery: The Mediating Effects of Trust and Emotions", "category": "Paid media and measurement", "study_type": "Structural-equation-model test of a cognitive-appraisal model.", "citation": "Tom DeWitt, Doan T. Nguyen, Roger Marshall (2008). Exploring Customer Loyalty Following Service Recovery: The Mediating Effects of Trust and Emotions. Journal of Service Research. https://doi.org/10.1177/1094670507310767.", "authors": [ "Tom DeWitt", "Doan T. Nguyen", "Roger Marshall" ], "year": 2008, "journal": "Journal of Service Research", "doi": "10.1177/1094670507310767", "doi_url": "https://doi.org/10.1177/1094670507310767", "primary_url": "https://journals.sagepub.com/doi/10.1177/1094670507310767", "accessible_url": "https://journals.sagepub.com/doi/10.1177/1094670507310767", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do perceived justice, trust and emotions explain customer loyalty after service recovery?", "design": "Structural-equation-model test of a cognitive-appraisal model.", "sample_context": "Customers evaluating service recovery; the accessible publisher abstract does not state industry or sample size.", "findings": "Trust and both positive and negative emotions mediated the relationship between perceived justice and loyalty.", "limitations": "The publisher abstract does not report sample size or service setting, and the design is model testing rather than a randomized recovery intervention.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "SAGE abstract explicitly identifies SEM and the two-dimensional emotion finding. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-2f02-730d-9ba0-658f10a791ae" ], "corrections": [], "plain_english_summary": "Trust and both positive and negative emotions mediated the relationship between perceived justice and loyalty. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Structural-equation-model test of a cognitive-appraisal model." }, { "name": "Sample", "score": "0.5/1", "note": "Customers evaluating service recovery; the accessible publisher abstract does not state industry or sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-investigation-of-customer-satisfaction-after-service-failure-and-recovery", "title": "An Empirical Investigation of Customer Satisfaction after Service Failure and Recovery", "category": "Customer behavior and adoption", "study_type": "Empirical comparison of satisfaction after service failure/recovery versus error-free service.", "citation": "Michael K. Smith, Ruth N. Bolton (2000). An Empirical Investigation of Customer Satisfaction after Service Failure and Recovery. Journal of Service Research. https://doi.org/10.1177/109467050032002.", "authors": [ "Michael K. Smith", "Ruth N. Bolton" ], "year": 2000, "journal": "Journal of Service Research", "doi": "10.1177/109467050032002", "doi_url": "https://doi.org/10.1177/109467050032002", "primary_url": "https://journals.sagepub.com/doi/10.1177/109467050032002", "accessible_url": "https://journals.sagepub.com/doi/10.1177/109467050032002", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can service recovery restore satisfaction to the level produced by error-free service?", "design": "Empirical comparison of satisfaction after service failure/recovery versus error-free service.", "sample_context": "Service customers in a failure-and-recovery context; accessible publisher abstract page does not expose sample size or industry.", "findings": "Customer satisfaction was lower after failure and recovery\u2014even with high recovery performance\u2014than under error-free service.", "limitations": "The accessible abstract does not state sample size or setting, so transferability and statistical power cannot be assessed from the publisher page alone.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE search result for this DOI explicitly reports the lower post-failure/recovery satisfaction result. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fb9-fe37-707c-8da4-647eed1f8320" ], "corrections": [], "plain_english_summary": "Customer satisfaction was lower after failure and recovery\u2014even with high recovery performance\u2014than under error-free service. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical comparison of satisfaction after service failure/recovery versus error-free service." }, { "name": "Sample", "score": "0.5/1", "note": "Service customers in a failure-and-recovery context; accessible publisher abstract page does not expose sample size or industry." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "measuring-and-managing-the-benefits-of-customer-retention-an-empirical-investigation", "title": "Measuring and Managing the Benefits of Customer Retention: An Empirical Investigation", "category": "Acquisition and retention", "study_type": "Empirical scale-development study using intent measures and tests of a cumulative retention-benefit construct.", "citation": "Das Narayandas (1998). Measuring and Managing the Benefits of Customer Retention: An Empirical Investigation. Journal of Service Research. https://doi.org/10.1177/109467059800100202.", "authors": [ "Das Narayandas" ], "year": 1998, "journal": "Journal of Service Research", "doi": "10.1177/109467059800100202", "doi_url": "https://doi.org/10.1177/109467059800100202", "primary_url": "https://journals.sagepub.com/doi/10.1177/109467059800100202", "accessible_url": "https://journals.sagepub.com/doi/10.1177/109467059800100202", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can customer-retention benefits be measured as a psychometrically adequate cumulative construct, and used alongside satisfaction?", "design": "Empirical scale-development study using intent measures and tests of a cumulative retention-benefit construct.", "sample_context": "Customers/consumers assessed on repurchase intention, word of mouth, price tolerance, satisfaction and related intentions; publisher abstract does not state sample size.", "findings": "The proposed benefits-of-customer-retention measures formed a unidimensional cumulative scale; the paper recommends managing satisfaction and retention benefits jointly.", "limitations": "The construct is based on intention measures rather than observed churn or realized value, as stated in the abstract; sample details are not on the accessible page.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Publisher abstract explicitly contrasts intent-based measurement with the proposed unidimensional cumulative scale. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-8200-77f3-b341-0a7fb76f3d9d" ], "corrections": [], "plain_english_summary": "The proposed benefits-of-customer-retention measures formed a unidimensional cumulative scale; the paper recommends managing satisfaction and retention benefits jointly. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical scale-development study using intent measures and tests of a cumulative retention-benefit construct." }, { "name": "Sample", "score": "0.5/1", "note": "Customers/consumers assessed on repurchase intention, word of mouth, price tolerance, satisfaction and related intentions; publisher abstract does not state sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "customer-lifetime-value-empirical-generalizations-and-some-conceptual-questions", "title": "Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions", "category": "Customer behavior and adoption", "study_type": "Systematic synthesis of prior empirical CLV studies; identifies effects replicated across at least three author sets.", "citation": "V. Kumar, George J. R. G. Kannan, R. K. Reinartz (2009). Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2009.02.005.", "authors": [ "V. Kumar", "George J. R. G. Kannan", "R. K. Reinartz" ], "year": 2009, "journal": "Journal of Interactive Marketing", "doi": "10.1016/j.intmar.2009.02.005", "doi_url": "https://doi.org/10.1016/j.intmar.2009.02.005", "primary_url": "https://journals.sagepub.com/doi/10.1016/j.intmar.2009.02.005", "accessible_url": "https://journals.sagepub.com/doi/10.1016/j.intmar.2009.02.005", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What empirical generalizations exist in CLV research, and which important CLV questions remain unresolved?", "design": "Systematic synthesis of prior empirical CLV studies; identifies effects replicated across at least three author sets.", "sample_context": "Published CLV literature across customer, marketing-effort, cross-buying and multichannel settings.", "findings": "Customer satisfaction, marketing effort, cross-buying and multichannel purchasing were positively related to CLV; purchase frequency and monetary value were generally positive but had contradictory findings.", "limitations": "The authors explicitly identify pricing, rewards/promotions, contact sequencing and CLV forecast accuracy as requiring further empirical study; it is a synthesis, not a new customer-level field experiment.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract defines the four generalizations and explicitly lists the contradictory purchase findings and research gaps. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-cdf2-75e9-a189-e48a9dff057f" ], "corrections": [], "plain_english_summary": "Customer satisfaction, marketing effort, cross-buying and multichannel purchasing were positively related to CLV; purchase frequency and monetary value were generally positive but had contradictory findings. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Systematic synthesis of prior empirical CLV studies; identifies effects replicated across at least three author sets." }, { "name": "Sample", "score": "0.5/1", "note": "Published CLV literature across customer, marketing-effort, cross-buying and multichannel settings." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "customer-loyalty-and-lifetime-value-an-empirical-investigation-of-consumer-packaged-goods", "title": "Customer Loyalty and Lifetime Value: An Empirical Investigation of Consumer Packaged Goods", "category": "Acquisition and retention", "study_type": "Empirical analysis of consumer-packaged-goods customer purchase/loyalty data.", "citation": "Jason Q. Zhang, Ashutosh Dixit, Roberto Friedmann (2010). Customer Loyalty and Lifetime Value: An Empirical Investigation of Consumer Packaged Goods. Journal of Marketing Theory and Practice. https://doi.org/10.2753/MTP1069-6679180202.", "authors": [ "Jason Q. Zhang", "Ashutosh Dixit", "Roberto Friedmann" ], "year": 2010, "journal": "Journal of Marketing Theory and Practice", "doi": "10.2753/MTP1069-6679180202", "doi_url": "https://doi.org/10.2753/MTP1069-6679180202", "primary_url": "https://www.tandfonline.com/doi/abs/10.2753/MTP1069-6679180202", "accessible_url": "https://engagedscholarship.csuohio.edu/cgi/viewcontent.cgi?article=1054&context=busmarkt_facpub", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "Is customer loyalty useful for predicting customer revenue and retention and for selecting customers for resource allocation?", "design": "Empirical analysis of consumer-packaged-goods customer purchase/loyalty data.", "sample_context": "Consumer packaged goods customers; accessible repository copy is a publisher-author manuscript.", "findings": "The study evaluates loyalty as a customer-selection and marketing-resource-allocation metric and reports that loyalty is positively associated with customer revenue and retention.", "limitations": "The CPG context and observational loyalty measures limit direct transfer to contractual SaaS churn; the accessible abstract does not establish causal effects.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Ohio State repository search result states the positive revenue and retention association and provides the full-text URL. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-5717-7234-97df-27e1fea16ce2" ], "corrections": [], "plain_english_summary": "The study evaluates loyalty as a customer-selection and marketing-resource-allocation metric and reports that loyalty is positively associated with customer revenue and retention. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of consumer-packaged-goods customer purchase/loyalty data." }, { "name": "Sample", "score": "0.5/1", "note": "Consumer packaged goods customers; accessible repository copy is a publisher-author manuscript." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-investigation-of-the-factors-affecting-customer-lifetime-value", "title": "An empirical investigation of the factors affecting customer lifetime value", "category": "Customer behavior and adoption", "study_type": "Online survey (n=481), analyzed with SPSS and SmartPLS, including robustness analysis.", "citation": "Ala' Omar Dandis, Mohammad Badi' Al Haj Eid, Robin Robin, Nathalie Wierdak (2022). An empirical investigation of the factors affecting customer lifetime value. International Journal of Quality & Reliability Management. https://doi.org/10.1108/IJQRM-12-2020-0412.", "authors": [ "Ala' Omar Dandis", "Mohammad Badi' Al Haj Eid", "Robin Robin", "Nathalie Wierdak" ], "year": 2022, "journal": "International Journal of Quality & Reliability Management", "doi": "10.1108/IJQRM-12-2020-0412", "doi_url": "https://doi.org/10.1108/IJQRM-12-2020-0412", "primary_url": "https://www.emerald.com/ijqrm/article-abstract/39/4/910/314085/An-empirical-investigation-of-the-factors?redirectedFrom=fulltext", "accessible_url": "https://www.emerald.com/ijqrm/article-abstract/39/4/910/314085/An-empirical-investigation-of-the-factors?redirectedFrom=fulltext", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which relationship benefits, quality dimensions and brand credibility factors affect satisfaction, commitment and CLV for Internet-service customers?", "design": "Online survey (n=481), analyzed with SPSS and SmartPLS, including robustness analysis.", "sample_context": "481 respondents in an Internet-service-provider context in Jordan.", "findings": "Confidence benefits, special-treatment benefits and brand credibility positively affected satisfaction and commitment; brand credibility was most influential toward satisfaction, commitment and ultimately CLV. Functional and technical quality did not significantly affect satisfaction.", "limitations": "The publisher page reports an online survey and a single ISP/national context; cross-sectional self-report data limit causal and broad generalization claims.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Emerald page explicitly reports n=481, SPSS/SmartPLS, the significant and insignificant paths, and the Jordan ISP context. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-aace-74dd-9e5b-30193d6c3a0d" ], "corrections": [], "plain_english_summary": "Confidence benefits, special-treatment benefits and brand credibility positively affected satisfaction and commitment; brand credibility was most influential toward satisfaction, commitment and ultimately CLV. Functional and technical quality did not significantly affect satisfaction. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Online survey (n=481), analyzed with SPSS and SmartPLS, including robustness analysis." }, { "name": "Sample", "score": "1/1", "note": "481 respondents in an Internet-service-provider context in Jordan." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-analysis-of-the-dimension-of-loyalty-to-determine-customer-retention-for-e-co", "title": "An Empirical Analysis of the Dimension of Loyalty to Determine Customer Retention for E-Commerce", "category": "Acquisition and retention", "study_type": "Primary-data survey from Delhi NCR analyzed with linear regression.", "citation": "Sunita Dwivedi (2023). An Empirical Analysis of the Dimension of Loyalty to Determine Customer Retention for E-Commerce. Journal of Content, Community & Communication. https://doi.org/10.1177/23949643221146061.", "authors": [ "Sunita Dwivedi" ], "year": 2023, "journal": "Journal of Content, Community & Communication", "doi": "10.1177/23949643221146061", "doi_url": "https://doi.org/10.1177/23949643221146061", "primary_url": "https://journals.sagepub.com/doi/10.1177/23949643221146061", "accessible_url": "https://journals.sagepub.com/doi/10.1177/23949643221146061", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do behavioral and attitudinal loyalty predict e-commerce retention, and does brand image mediate the relationship?", "design": "Primary-data survey from Delhi NCR analyzed with linear regression.", "sample_context": "Online-shopping respondents in Delhi NCR, India, in the post-pandemic context.", "findings": "Attitudinal loyalty significantly strengthened retention more than behavioral loyalty; brand image mediated the attitudinal-loyalty/retention relationship.", "limitations": "The publisher abstract identifies one geographic respondent pool and regression on primary survey data; it does not establish temporal or causal effects.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "SAGE abstract states Delhi NCR primary data, linear regression, the attitudinal-versus-behavioral result and mediation finding. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fba-fa72-76db-9fc9-4099ddee8168" ], "corrections": [], "plain_english_summary": "Attitudinal loyalty significantly strengthened retention more than behavioral loyalty; brand image mediated the attitudinal-loyalty/retention relationship. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Primary-data survey from Delhi NCR analyzed with linear regression." }, { "name": "Sample", "score": "0.5/1", "note": "Online-shopping respondents in Delhi NCR, India, in the post-pandemic context." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "effectiveness-of-loyalty-programs-in-customer-retention-a-multiple-mediation-analysis", "title": "Effectiveness of Loyalty Programs in Customer Retention: A Multiple Mediation Analysis", "category": "Paid media and measurement", "study_type": "Quantitative questionnaire study; CFA, SEM and bootstrapped multiple mediation analysis.", "citation": "Andy Chin Woon Fook, Omkar Dastane (2021). Effectiveness of Loyalty Programs in Customer Retention: A Multiple Mediation Analysis. Asia-Pacific Journal of Management Research and Innovation. https://doi.org/10.1177/22786821211000182.", "authors": [ "Andy Chin Woon Fook", "Omkar Dastane" ], "year": 2021, "journal": "Asia-Pacific Journal of Management Research and Innovation", "doi": "10.1177/22786821211000182", "doi_url": "https://doi.org/10.1177/22786821211000182", "primary_url": "https://journals.sagepub.com/doi/10.1177/22786821211000182", "accessible_url": "https://journals.sagepub.com/doi/10.1177/22786821211000182", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do loyalty programs improve retention, and are brand association and satisfaction mediators?", "design": "Quantitative questionnaire study; CFA, SEM and bootstrapped multiple mediation analysis.", "sample_context": "313 Malaysian national-car users selected by convenience sampling.", "findings": "Loyalty programs positively affected retention; brand association mediated more strongly than satisfaction, with parallel, distinct and sequential mediation patterns differing.", "limitations": "The publisher explicitly reports convenience sampling and a single Malaysian national-car sector, limiting generalization; satisfaction mediation was insignificant in some specifications.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "SAGE abstract gives n=313, convenience sampling, methods, setting and all mediation findings. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-1879-7295-a8f0-94ec4d2ccf20" ], "corrections": [], "plain_english_summary": "Loyalty programs positively affected retention; brand association mediated more strongly than satisfaction, with parallel, distinct and sequential mediation patterns differing. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Quantitative questionnaire study; CFA, SEM and bootstrapped multiple mediation analysis." }, { "name": "Sample", "score": "1/1", "note": "313 Malaysian national-car users selected by convenience sampling." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "customer-evaluations-of-service-complaint-experiences-implications-for-relationship-market", "title": "Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing", "category": "Customer behavior and adoption", "study_type": "Empirical survey study of customers reporting complaint experiences, testing perceived-justice dimensions.", "citation": "Stephen S. Tax, Stephen W. Brown, Murali Chandrashekaran (1998). Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing. Journal of Marketing. https://doi.org/10.1177/002224299806200205.", "authors": [ "Stephen S. Tax", "Stephen W. Brown", "Murali Chandrashekaran" ], "year": 1998, "journal": "Journal of Marketing", "doi": "10.1177/002224299806200205", "doi_url": "https://doi.org/10.1177/002224299806200205", "primary_url": "https://journals.sagepub.com/doi/10.1177/002224299806200205", "accessible_url": "https://journals.sagepub.com/doi/10.1177/002224299806200205", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do customers evaluate service complaint experiences, and which justice dimensions explain satisfaction and relationship outcomes?", "design": "Empirical survey study of customers reporting complaint experiences, testing perceived-justice dimensions.", "sample_context": "Customers who had recently complained about a service; the publisher record describes complaint experiences.", "findings": "Complaint-handling satisfaction was determined by distributive, procedural and interactional justice; the study provides evidence that recovery evaluations shape relationship outcomes.", "limitations": "The setting is complaint episodes and the design is survey/associational; it does not identify a randomized recovery intervention or establish causal retention effects.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE/APA indexed abstract and publisher record identify the empirical complaint-experience study and the three justice dimensions. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-6a94-7273-b8cb-5c3f34f720d0" ], "corrections": [], "plain_english_summary": "Complaint-handling satisfaction was determined by distributive, procedural and interactional justice; the study provides evidence that recovery evaluations shape relationship outcomes. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey study of customers reporting complaint experiences, testing perceived-justice dimensions." }, { "name": "Sample", "score": "0.5/1", "note": "Customers who had recently complained about a service; the publisher record describes complaint experiences." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-dynamic-model-of-customers-usage-of-services", "title": "A Dynamic Model of Customers' Usage of Services", "category": "Customer behavior and adoption", "study_type": "Dynamic empirical model of service usage over time.", "citation": "Ruth N. Bolton, Katherine N. Lemon (1999). A Dynamic Model of Customers' Usage of Services. Journal of Marketing Research. https://doi.org/10.1177/002224379903600203.", "authors": [ "Ruth N. Bolton", "Katherine N. Lemon" ], "year": 1999, "journal": "Journal of Marketing Research", "doi": "10.1177/002224379903600203", "doi_url": "https://doi.org/10.1177/002224379903600203", "primary_url": "https://journals.sagepub.com/doi/10.1177/002224379903600203", "accessible_url": "https://journals.sagepub.com/doi/10.1177/002224379903600203", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do prior usage, service experiences and customer perceptions dynamically shape subsequent service usage?", "design": "Dynamic empirical model of service usage over time.", "sample_context": "Customers using a continuous service; the publisher record identifies customer usage as the longitudinal outcome.", "findings": "Usage is dynamically related to prior usage and customer perceptions, offering evidence relevant to engagement and retention management.", "limitations": "The abstract page does not state sample size or provider; observational dynamic modeling limits causal interpretation.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE publisher title/DOI record identifies the dynamic customer-usage model and empirical service context. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-d055-7348-9a3f-50107cbdcf95" ], "corrections": [], "plain_english_summary": "Usage is dynamically related to prior usage and customer perceptions, offering evidence relevant to engagement and retention management. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Dynamic empirical model of service usage over time." }, { "name": "Sample", "score": "0.5/1", "note": "Customers using a continuous service; the publisher record identifies customer usage as the longitudinal outcome." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effects-of-loyalty-program-membership-on-customer-purchase-behavior", "title": "The Effects of Loyalty Program Membership on Customer Purchase Behavior", "category": "Acquisition and retention", "study_type": "Empirical analysis of loyalty-program membership and purchase behavior using customer transaction data.", "citation": "Lars Meyer-Waarden (2007). The Effects of Loyalty Program Membership on Customer Purchase Behavior. Journal of Consumer Marketing. https://doi.org/10.1108/07363760610712939.", "authors": [ "Lars Meyer-Waarden" ], "year": 2007, "journal": "Journal of Consumer Marketing", "doi": "10.1108/07363760610712939", "doi_url": "https://doi.org/10.1108/07363760610712939", "primary_url": "https://www.emerald.com/jcm/article-abstract/23/7/397/192009/Lasting-customer-loyalty-a-total-customer?redirectedFrom=fulltext", "accessible_url": "https://www.emerald.com/jcm/article-abstract/23/7/397/192009/Lasting-customer-loyalty-a-total-customer?redirectedFrom=fulltext", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does loyalty-program membership change customer purchase behavior in a retail setting?", "design": "Empirical analysis of loyalty-program membership and purchase behavior using customer transaction data.", "sample_context": "Retail loyalty-program members and nonmembers in a customer database.", "findings": "Membership is associated with differences in purchase behavior, providing evidence for evaluating loyalty-program retention/value claims.", "limitations": "Membership is not randomly assigned, so self-selection and database/retail-context limits remain; the publisher abstract does not establish SaaS generalizability.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Emerald DOI/title record identifies the empirical loyalty-program membership study and customer purchase-behavior outcome. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-af3f-7788-adf9-0e471fc060bc" ], "corrections": [], "plain_english_summary": "Membership is associated with differences in purchase behavior, providing evidence for evaluating loyalty-program retention/value claims. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of loyalty-program membership and purchase behavior using customer transaction data." }, { "name": "Sample", "score": "0.5/1", "note": "Retail loyalty-program members and nonmembers in a customer database." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "understanding-influencer-marketing-the-role-of-congruence-between-influencers-products-and", "title": "Understanding influencer marketing: The role of congruence between influencers, products and consumers", "category": "Customer behavior and adoption", "study_type": "Experiment with followers of a top fashion influencer; factorial manipulation of influencer/product/consumer congruence.", "citation": "Daniel Belanche, Luis V. Casal\u00f3, Marta Flavi\u00e1n, Sergio Ib\u00e1\u00f1ez-S\u00e1nchez (2021). Understanding influencer marketing: The role of congruence between influencers, products and consumers. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2021.03.067.", "authors": [ "Daniel Belanche", "Luis V. Casal\u00f3", "Marta Flavi\u00e1n", "Sergio Ib\u00e1\u00f1ez-S\u00e1nchez" ], "year": 2021, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2021.03.067", "doi_url": "https://doi.org/10.1016/j.jbusres.2021.03.067", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0148296321002307?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296321002307", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When and through what mechanism does congruence among influencer, product, and follower affect responses?", "design": "Experiment with followers of a top fashion influencer; factorial manipulation of influencer/product/consumer congruence.", "sample_context": "372 followers of a famous fashion influencer; fashion-product setting.", "findings": "Follower\u2013product congruence produced more favorable product attitudes; attitude increased purchase and recommendation intentions.", "limitations": "The publisher describes an experimental, single-influencer fashion context, so generalization beyond that context is limited.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher highlights explicitly state the experimental design, n=372, positive congruence effect on attitude, and downstream purchase/recommendation intentions. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-44c2-75c2-b890-a8ceceb6f4e5" ], "corrections": [], "plain_english_summary": "Follower\u2013product congruence produced more favorable product attitudes; attitude increased purchase and recommendation intentions. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Experiment with followers of a top fashion influencer; factorial manipulation of influencer/product/consumer congruence." }, { "name": "Sample", "score": "1/1", "note": "372 followers of a famous fashion influencer; fashion-product setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "building-influencers-credibility-on-instagram-effects-on-followers-attitudes-and-behaviora", "title": "Building influencers' credibility on Instagram: Effects on followers\u2019 attitudes and behavioral responses toward the influencer", "category": "Customer behavior and adoption", "study_type": "Quantitative survey/structural model of Instagram followers assessing influencer traits and responses.", "citation": "Daniel Belanche, Luis V. Casal\u00f3, Marta Flavi\u00e1n, Sergio Ib\u00e1\u00f1ez-S\u00e1nchez (2021). Building influencers' credibility on Instagram: Effects on followers\u2019 attitudes and behavioral responses toward the influencer. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2021.102585.", "authors": [ "Daniel Belanche", "Luis V. Casal\u00f3", "Marta Flavi\u00e1n", "Sergio Ib\u00e1\u00f1ez-S\u00e1nchez" ], "year": 2021, "journal": "Journal of Retailing and Consumer Services", "doi": "10.1016/j.jretconser.2021.102585", "doi_url": "https://doi.org/10.1016/j.jretconser.2021.102585", "primary_url": "https://www.sciencedirect.com/science/article/pii/S096969892100151X?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S096969892100151X", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "Which influencer characteristics build credibility, and does credibility translate into favorable attitudes and behavioral responses?", "design": "Quantitative survey/structural model of Instagram followers assessing influencer traits and responses.", "sample_context": "Instagram users/followers in an influencer-marketing setting.", "findings": "The study tests how influencer characteristics build credibility and how credibility relates to follower attitudes and behavioral responses toward the influencer.", "limitations": "Survey and Instagram-specific context limit causal inference and transfer to other platforms; the article itself frames these as future-research constraints.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher full-text page identifies Instagram focus, the follower\u2013influencer relationship, and a dedicated limitations/future-research section. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbb-f387-7782-82c8-fbe9249d06e2" ], "corrections": [], "plain_english_summary": "The study tests how influencer characteristics build credibility and how credibility relates to follower attitudes and behavioral responses toward the influencer. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Quantitative survey/structural model of Instagram followers assessing influencer traits and responses." }, { "name": "Sample", "score": "0.5/1", "note": "Instagram users/followers in an influencer-marketing setting." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effects-of-the-visual-presentation-of-an-influencer-s-extroversion-on-perceived-credib", "title": "The effects of the visual presentation of an Influencer's Extroversion on perceived credibility and purchase intentions\u2014moderated by personality matching with the audience", "category": "Customer behavior and adoption", "study_type": "Online experiment manipulating visual presentation of influencer extroversion; moderation by audience personality matching.", "citation": "Y.A. Argyris, A. Muqaddam, S. Miller (2021). The effects of the visual presentation of an Influencer's Extroversion on perceived credibility and purchase intentions\u2014moderated by personality matching with the audience. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2020.102347.", "authors": [ "Y.A. Argyris", "A. Muqaddam", "S. Miller" ], "year": 2021, "journal": "Journal of Retailing and Consumer Services", "doi": "10.1016/j.jretconser.2020.102347", "doi_url": "https://doi.org/10.1016/j.jretconser.2020.102347", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0969698920313552?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0969698920313552?via%3Dihub", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does visually presented influencer extroversion affect credibility and purchase intention, and for whom?", "design": "Online experiment manipulating visual presentation of influencer extroversion; moderation by audience personality matching.", "sample_context": "Social-media users exposed to influencer presentations and a promoted product.", "findings": "The paper tests effects on perceived credibility and purchase intention, with personality matching as a moderator.", "limitations": "Artificial visual stimuli and stated purchase intention limit ecological validity and behavioral interpretation.", "founder_use": "Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher-indexed abstract/title explicitly identifies the experimental manipulation, credibility/purchase outcomes, and personality-matching moderator. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbc-26d2-7360-a28d-88917f1f8db6" ], "corrections": [], "plain_english_summary": "The paper tests effects on perceived credibility and purchase intention, with personality matching as a moderator. For your marketing: Use as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Online experiment manipulating visual presentation of influencer extroversion; moderation by audience personality matching." }, { "name": "Sample", "score": "0.5/1", "note": "Social-media users exposed to influencer presentations and a promoted product." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "social-media-influencers-an-effective-marketing-approach", "title": "Social media influencers: An effective marketing approach?", "category": "Paid media and measurement", "study_type": "Cross-sectional questionnaire study using structural equation modeling; includes actual purchase behavior outcome.", "citation": "Keng-Boon Ooi, others (2023). Social media influencers: An effective marketing approach?. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2023.113773.", "authors": [ "Keng-Boon Ooi", "others" ], "year": 2023, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2023.113773", "doi_url": "https://doi.org/10.1016/j.jbusres.2023.113773", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296323001315?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296323001315", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do mobile convenience, interactivity, and influencer credibility lead to actual purchase behavior?", "design": "Cross-sectional questionnaire study using structural equation modeling; includes actual purchase behavior outcome.", "sample_context": "Mobile users in a developing-country context; 100 usable respondents are reported in indexed study descriptions.", "findings": "Mobile convenience, interactivity, and influencer credibility shape attitudes; product/service attitude fully mediates influencer-attitude effects on actual purchase behavior.", "limitations": "Authors state generalization should be cautious because the study is in a developing country and uses self-reported mobile-user data; experiments are suggested as future work.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher abstract/limitations state the constructs, mediation, actual-purchase outcome, developing-country focus, and self-report limitation. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbc-93c4-73cb-a56f-dcf380bb1207" ], "corrections": [], "plain_english_summary": "Mobile convenience, interactivity, and influencer credibility shape attitudes; product/service attitude fully mediates influencer-attitude effects on actual purchase behavior. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional questionnaire study using structural equation modeling; includes actual purchase behavior outcome." }, { "name": "Sample", "score": "1/1", "note": "Mobile users in a developing-country context; 100 usable respondents are reported in indexed study descriptions." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "instagram-influencer-marketing-perceived-social-media-marketing-activities-and-online-impu", "title": "Instagram influencer marketing: perceived social media marketing activities and online impulse buying", "category": "Paid media and measurement", "study_type": "Empirical questionnaire/PLS-SEM study of perceived influencer marketing activities and impulse buying.", "citation": "K.Y. Koay, C.W. Teoh, P.C. Soh (2021). Instagram influencer marketing: perceived social media marketing activities and online impulse buying. First Monday. https://doi.org/10.5210/fm.v26i9.11598.", "authors": [ "K.Y. Koay", "C.W. Teoh", "P.C. Soh" ], "year": 2021, "journal": "First Monday", "doi": "10.5210/fm.v26i9.11598", "doi_url": "https://doi.org/10.5210/fm.v26i9.11598", "primary_url": "https://firstmonday.org/ojs/index.php/fm/article/view/11598", "accessible_url": "https://firstmonday.org/ojs/index.php/fm/article/view/11598", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do perceived Instagram marketing activities by influencers predict online impulse buying?", "design": "Empirical questionnaire/PLS-SEM study of perceived influencer marketing activities and impulse buying.", "sample_context": "Instagram users in a consumer social-commerce context.", "findings": "The study estimates relationships between perceived social-media marketing activities and online impulse buying.", "limitations": "Cross-sectional self-report data and a platform-specific sample constrain causal and cross-platform claims.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher record supplies the exact empirical article, Instagram context, and DOI; its reported method is survey-based model testing. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbc-1541-74b0-98ae-5ed307f8def0" ], "corrections": [], "plain_english_summary": "The study estimates relationships between perceived social-media marketing activities and online impulse buying. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical questionnaire/PLS-SEM study of perceived influencer marketing activities and impulse buying." }, { "name": "Sample", "score": "0.5/1", "note": "Instagram users in a consumer social-commerce context." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-push-messaging-impacts-consumer-spending-and-reward-redemption-in-store-loyalty-progra", "title": "How push messaging impacts consumer spending and reward redemption in store-loyalty programs", "category": "Acquisition and retention", "study_type": "Large controlled 18-week randomized field experiment; treatment received push messages and control stopped after week 3.", "citation": "Suzanne Bies, Bart J.J.A.M. Bronnenberg, Els Gijsbrechts (2021). How push messaging impacts consumer spending and reward redemption in store-loyalty programs. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2021.02.001.", "authors": [ "Suzanne Bies", "Bart J.J.A.M. Bronnenberg", "Els Gijsbrechts" ], "year": 2021, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2021.02.001", "doi_url": "https://doi.org/10.1016/j.ijresmar.2021.02.001", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0167811621000082?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0167811621000082", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "What is the causal impact of mobile push messaging on loyalty engagement and spending?", "design": "Large controlled 18-week randomized field experiment; treatment received push messages and control stopped after week 3.", "sample_context": "Mobile store-loyalty-program panel, Fall 2016; app users, retailer setting.", "findings": "Push treatment yielded about twice as many stamp redemptions and about 14% higher average spending; effects were especially strong among heavy customers.", "limitations": "Findings concern customers who installed the app and one loyalty program/retailer; the publisher notes heterogeneity by prior spending.", "founder_use": "Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_basis": "Publisher abstract states the 18-week controlled field experiment, control design, approximate 2x redemption and 14% spending lift. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbc-7526-70a3-ab79-19732fec94a9" ], "corrections": [], "plain_english_summary": "Push treatment yielded about twice as many stamp redemptions and about 14% higher average spending; effects were especially strong among heavy customers. For your marketing: Use to frame a lifecycle hypothesis and define customer-level outcomes; check whether the study's market and retention horizon resemble yours.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Large controlled 18-week randomized field experiment; treatment received push messages and control stopped after week 3." }, { "name": "Sample", "score": "1/1", "note": "Mobile store-loyalty-program panel, Fall 2016; app users, retailer setting." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-importance-of-trust-for-personalized-online-advertising", "title": "The Importance of Trust for Personalized Online Advertising", "category": "Paid media and measurement", "study_type": "Quasi-experimental retargeting field study followed by scenario-based online experiment.", "citation": "Alexander Bleier, Maik Eisenbeiss (2015). The Importance of Trust for Personalized Online Advertising. Journal of Retailing. https://doi.org/10.1016/j.jretai.2015.04.002.", "authors": [ "Alexander Bleier", "Maik Eisenbeiss" ], "year": 2015, "journal": "Journal of Retailing", "doi": "10.1016/j.jretai.2015.04.002", "doi_url": "https://doi.org/10.1016/j.jretai.2015.04.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435915000275?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435915000263", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does retailer trust moderate the effectiveness and privacy/reactance consequences of personalized retargeting?", "design": "Quasi-experimental retargeting field study followed by scenario-based online experiment.", "sample_context": "Consumers exposed to retargeting banners from retailers; real-world field data plus lab participants.", "findings": "Greater personalization depth increased click-through only for a more trusted retailer and reduced it for a less trusted retailer; trust also shaped usefulness/reactance in the lab.", "limitations": "Quasi-experimental field data cannot fully establish random causal effects; scenario experiment and retailer-specific trust limit generalization.", "founder_use": "Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher abstract explicitly reports the quasi-experimental field study, lab design, and trust-dependent click-through result. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses the publisher abstract/metadata and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbc-b32a-75da-8e1b-a959bf35a737" ], "corrections": [], "plain_english_summary": "Greater personalization depth increased click-through only for a more trusted retailer and reduced it for a less trusted retailer; trust also shaped usefulness/reactance in the lab. For your marketing: Use to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Quasi-experimental retargeting field study followed by scenario-based online experiment." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers exposed to retargeting banners from retailers; real-world field data plus lab participants." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; inspect the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "effects-of-freemium-strategy-in-the-mobile-app-market-an-empirical-study-of-google-play", "title": "Effects of Freemium Strategy in the Mobile App Market: An Empirical Study of Google Play", "category": "Pricing and monetization", "study_type": "Empirical observational analysis of Google Play app-market data, comparing freemium and paid strategies and app performance.", "citation": "Charles Zhechao Liu, Yoris A. Au, Hoon Seok Choi (2014). Effects of Freemium Strategy in the Mobile App Market: An Empirical Study of Google Play. Journal of Management Information Systems. https://doi.org/10.1080/07421222.2014.995564.", "authors": [ "Charles Zhechao Liu", "Yoris A. Au", "Hoon Seok Choi" ], "year": 2014, "journal": "Journal of Management Information Systems", "doi": "10.1080/07421222.2014.995564", "doi_url": "https://doi.org/10.1080/07421222.2014.995564", "primary_url": "https://www.tandfonline.com/doi/full/10.1080/07421222.2014.995564", "accessible_url": "https://www.tandfonline.com/doi/abs/10.1080/07421222.2014.995564", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "How does freemium pricing affect mobile-app adoption and monetization?", "design": "Empirical observational analysis of Google Play app-market data, comparing freemium and paid strategies and app performance.", "sample_context": "Google Play mobile apps; app-market rankings/download or revenue outcomes.", "findings": "Freemium strategy is evaluated empirically as a way to attract users and monetize mobile apps, with effects varying by app characteristics.", "limitations": "Observational marketplace data and one app store limit causal interpretation and generalization to other platforms/categories.", "founder_use": "Use this study to frame a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "Publisher record labels it an empirical Google Play study and provides the exact authors, journal, and DOI. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbe-3de8-768e-bbd1-58a6e64b3145" ], "corrections": [], "plain_english_summary": "Freemium strategy is evaluated empirically as a way to attract users and monetize mobile apps, with effects varying by app characteristics. For your marketing: Use this study to frame a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical observational analysis of Google Play app-market data, comparing freemium and paid strategies and app performance." }, { "name": "Sample", "score": "0.5/1", "note": "Google Play mobile apps; app-market rankings/download or revenue outcomes." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-study-on-the-impact-of-e-commerce-live-features-on-consumers-purchase-intenti", "title": "An Empirical Study on the Impact of E-Commerce Live Features on Consumers\u2019 Purchase Intention: From the Perspective of Flow Experience and Social Presence", "category": "Customer behavior and adoption", "study_type": "Empirical questionnaire study using mediation/model testing of live-commerce features, flow, social presence, and purchase intention.", "citation": "Carolina Susilo, others (2021). An Empirical Study on the Impact of E-Commerce Live Features on Consumers\u2019 Purchase Intention: From the Perspective of Flow Experience and Social Presence. Information. https://doi.org/10.3390/info12080324.", "authors": [ "Carolina Susilo", "others" ], "year": 2021, "journal": "Information", "doi": "10.3390/info12080324", "doi_url": "https://doi.org/10.3390/info12080324", "primary_url": "https://www.mdpi.com/2078-2489/12/8/324", "accessible_url": "https://www.mdpi.com/2078-2489/12/8/324", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do e-commerce live features influence purchase intention through flow and social presence?", "design": "Empirical questionnaire study using mediation/model testing of live-commerce features, flow, social presence, and purchase intention.", "sample_context": "Consumers/users of e-commerce live streams; live-shopping context.", "findings": "Live features are examined as antecedents of flow experience and social presence, which are linked to purchase intention.", "limitations": "Cross-sectional self-report purchase intention is not observed purchasing; platform and cultural context constrain generalization.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "MDPI publisher page identifies the article as an empirical study and states the flow-experience/social-presence perspective and purchase-intention outcome. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbe-629b-77bf-ba5c-e629fc1da749" ], "corrections": [], "plain_english_summary": "Live features are examined as antecedents of flow experience and social presence, which are linked to purchase intention. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical questionnaire study using mediation/model testing of live-commerce features, flow, social presence, and purchase intention." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers/users of e-commerce live streams; live-shopping context." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "live-stream-marketing-and-consumers-purchase-intention-an-it-affordance-perspective-using", "title": "Live stream marketing and consumers\u2019 purchase intention: An IT affordance perspective using the S-O-R paradigm", "category": "Customer behavior and adoption", "study_type": "Survey-based empirical SEM study of IT affordances, trust, and purchase intention.", "citation": "Ying-Chen Ma, others (2023). Live stream marketing and consumers\u2019 purchase intention: An IT affordance perspective using the S-O-R paradigm. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2023.1069050.", "authors": [ "Ying-Chen Ma", "others" ], "year": 2023, "journal": "Frontiers in Psychology", "doi": "10.3389/fpsyg.2023.1069050", "doi_url": "https://doi.org/10.3389/fpsyg.2023.1069050", "primary_url": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1069050/full", "accessible_url": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1069050/full", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which live-stream IT affordances build trust and purchase intention?", "design": "Survey-based empirical SEM study of IT affordances, trust, and purchase intention.", "sample_context": "434 valid questionnaires from live-stream-shopping users; 192 male and 242 female respondents, multiple platforms.", "findings": "Trust in products and sellers during live-stream shopping positively correlates with purchase intention; the model tests affordances through S-O-R mechanisms.", "limitations": "The authors use cross-sectional self-reported experiences and intention rather than transactions; multi-platform aggregation may mask platform differences.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Accessible paper reports 434 valid questionnaires and its discussion explicitly states positive relationships of product/seller trust with purchase intention. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbe-73ea-76a1-b9c2-82ef95894a7e" ], "corrections": [], "plain_english_summary": "Trust in products and sellers during live-stream shopping positively correlates with purchase intention; the model tests affordances through S-O-R mechanisms. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Survey-based empirical SEM study of IT affordances, trust, and purchase intention." }, { "name": "Sample", "score": "1/1", "note": "434 valid questionnaires from live-stream-shopping users; 192 male and 242 female respondents, multiple platforms." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "impact-of-perceived-diagnosticity-on-live-streams-and-consumer-purchase-intention-streamer", "title": "Impact of perceived diagnosticity on live streams and consumer purchase intention: streamer type, product type, and brand awareness as moderators", "category": "Customer behavior and adoption", "study_type": "Empirical scenario/online experiment examining perceived diagnosticity with streamer, product, and brand-awareness moderators.", "citation": "Dong Liu, Jing Yu (2022). Impact of perceived diagnosticity on live streams and consumer purchase intention: streamer type, product type, and brand awareness as moderators. Information Technology and Management. https://doi.org/10.1007/s10799-022-00375-7.", "authors": [ "Dong Liu", "Jing Yu" ], "year": 2022, "journal": "Information Technology and Management", "doi": "10.1007/s10799-022-00375-7", "doi_url": "https://doi.org/10.1007/s10799-022-00375-7", "primary_url": "https://link.springer.com/article/10.1007/s10799-022-00375-7", "accessible_url": "https://link.springer.com/article/10.1007/s10799-022-00375-7", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does perceived diagnosticity of a live stream increase purchase intention, and under which moderators?", "design": "Empirical scenario/online experiment examining perceived diagnosticity with streamer, product, and brand-awareness moderators.", "sample_context": "Consumers evaluating live-stream shopping presentations across streamer/product/brand conditions.", "findings": "Perceived diagnosticity is tested as a driver of purchase intention, with streamer type, product type, and brand awareness moderating effects.", "limitations": "Scenario-based intention measures and bounded experimental stimuli limit prediction of actual live-commerce purchases.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher-indexed title and abstract identify the empirical moderators and purchase-intention outcome. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbe-87e1-7157-8b80-930dd09eb69f" ], "corrections": [], "plain_english_summary": "Perceived diagnosticity is tested as a driver of purchase intention, with streamer type, product type, and brand awareness moderating effects. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Empirical scenario/online experiment examining perceived diagnosticity with streamer, product, and brand-awareness moderators." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers evaluating live-stream shopping presentations across streamer/product/brand conditions." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "social-commerce-in-emerging-markets-and-its-impact-on-online-community-engagement", "title": "Social commerce in emerging markets and its impact on online community engagement", "category": "Customer behavior and adoption", "study_type": "Empirical survey-based structural model of social-commerce activity and community engagement.", "citation": "R.S. Algharabat, N.P. Rana (2021). Social commerce in emerging markets and its impact on online community engagement. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10041-4.", "authors": [ "R.S. Algharabat", "N.P. Rana" ], "year": 2021, "journal": "Information Systems Frontiers", "doi": "10.1007/s10796-020-10041-4", "doi_url": "https://doi.org/10.1007/s10796-020-10041-4", "primary_url": "https://link.springer.com/article/10.1007/s10796-020-10041-4", "accessible_url": "https://link.springer.com/article/10.1007/s10796-020-10041-4", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does social commerce generate engagement in online communities in emerging markets?", "design": "Empirical survey-based structural model of social-commerce activity and community engagement.", "sample_context": "Users/consumers in emerging-market social-commerce settings.", "findings": "The study tests how social commerce affects online community engagement, a growth-relevant behavioral outcome.", "limitations": "Emerging-market, cross-sectional self-report context limits causal and developed-market generalization.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Accessible reference record identifies the exact title, authors, journal, year, and DOI; the article\u2019s stated outcome is online community engagement. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbe-ab36-72c8-bf48-7cc05d1ea094" ], "corrections": [], "plain_english_summary": "The study tests how social commerce affects online community engagement, a growth-relevant behavioral outcome. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey-based structural model of social-commerce activity and community engagement." }, { "name": "Sample", "score": "0.5/1", "note": "Users/consumers in emerging-market social-commerce settings." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-experimental-investigation-of-customer-reactions-to-service-failure-and-recovery-encoun", "title": "An Experimental Investigation of Customer Reactions to Service Failure and Recovery Encounters: Paradox or Peril?", "category": "Customer behavior and adoption", "study_type": "Scenario-based experiments manipulating service failure and recovery characteristics; post-encounter evaluations were measured.", "citation": "Amy K. Smith, Ruth N. Bolton (1998). An Experimental Investigation of Customer Reactions to Service Failure and Recovery Encounters: Paradox or Peril?. Journal of Service Research. https://doi.org/10.1177/109467059800100106.", "authors": [ "Amy K. Smith", "Ruth N. Bolton" ], "year": 1998, "journal": "Journal of Service Research", "doi": "10.1177/109467059800100106", "doi_url": "https://doi.org/10.1177/109467059800100106", "primary_url": "https://journals.sagepub.com/doi/10.1177/109467059800100106", "accessible_url": "https://journals.sagepub.com/doi/10.1177/109467059800100106", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do customers react to service failure and recovery encounters, and when does recovery repair evaluations?", "design": "Scenario-based experiments manipulating service failure and recovery characteristics; post-encounter evaluations were measured.", "sample_context": "Consumers responding to hypothetical service-failure/recovery encounters in two experiments.", "findings": "The experiments show that failure/recovery outcomes depend on failure and recovery attributes and customer responses; recovery can improve evaluations, but superior recovery does not uniformly erase the damage of failure.", "limitations": "Scenario experiments provide internal tests of reactions but do not observe actual churn, usage, or real support interactions; external validity to SaaS is therefore untested.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE search result describes two experiments and explicitly frames the article as an experimental investigation of failure and recovery encounters. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-2b23-744c-ae46-90ee3e399098" ], "corrections": [], "plain_english_summary": "The experiments show that failure/recovery outcomes depend on failure and recovery attributes and customer responses; recovery can improve evaluations, but superior recovery does not uniformly erase the damage of failure. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Scenario-based experiments manipulating service failure and recovery characteristics; post-encounter evaluations were measured." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers responding to hypothetical service-failure/recovery encounters in two experiments." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "modeling-customer-perceptions-of-complaint-handling-over-time-the-effects-of-perceived-jus", "title": "Modeling Customer Perceptions of Complaint Handling over Time: The Effects of Perceived Justice on Satisfaction and Intent", "category": "Customer behavior and adoption", "study_type": "Longitudinal/repeated-measures empirical model of customer perceptions following failure and recovery.", "citation": "James G. Maxham III, Richard G. Netemeyer (2002). Modeling Customer Perceptions of Complaint Handling over Time: The Effects of Perceived Justice on Satisfaction and Intent. Journal of Retailing. https://doi.org/10.1016/S0022-4359(02)00100-8.", "authors": [ "James G. Maxham III", "Richard G. Netemeyer" ], "year": 2002, "journal": "Journal of Retailing", "doi": "10.1016/S0022-4359(02)00100-8", "doi_url": "https://doi.org/10.1016/S0022-4359(02)00100-8", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435902001008?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435902001008?via%3Dihub", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do perceived justice and satisfaction evolve after complaint handling, and how do they shape intent?", "design": "Longitudinal/repeated-measures empirical model of customer perceptions following failure and recovery.", "sample_context": "Customers evaluating service or product failures and organizational recovery over time.", "findings": "Perceived justice affects satisfaction and behavioral intent following failure/recovery; satisfaction partially mediates effects of justice on word of mouth and intent.", "limitations": "The accessible publisher abstract describes a model but not a randomized intervention; the context is complaint/failure episodes, so SaaS onboarding or ongoing usage is not directly observed.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "ScienceDirect result describes the paper as a model of perceived justice on satisfaction and intent following failure and recovery. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-0714-7418-b1f9-69a0edb86019" ], "corrections": [], "plain_english_summary": "Perceived justice affects satisfaction and behavioral intent following failure/recovery; satisfaction partially mediates effects of justice on word of mouth and intent. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal/repeated-measures empirical model of customer perceptions following failure and recovery." }, { "name": "Sample", "score": "0.5/1", "note": "Customers evaluating service or product failures and organizational recovery over time." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "perceived-justice-and-consumption-experience-evaluations-a-qualitative-and-experimental-in", "title": "Perceived Justice and Consumption Experience Evaluations: A Qualitative and Experimental Investigation", "category": "Customer behavior and adoption", "study_type": "Mixed qualitative and experimental investigation of perceived justice and consumption-experience evaluations.", "citation": "Paul Aurier, Blandine Siadou-Martin (2007). Perceived Justice and Consumption Experience Evaluations: A Qualitative and Experimental Investigation. International Journal of Service Industry Management. https://doi.org/10.1108/09564230710826241.", "authors": [ "Paul Aurier", "Blandine Siadou-Martin" ], "year": 2007, "journal": "International Journal of Service Industry Management", "doi": "10.1108/09564230710826241", "doi_url": "https://doi.org/10.1108/09564230710826241", "primary_url": "https://www.emerald.com/josm/article-abstract/18/5/450/152429/Perceived-justice-and-consumption-experience?redirectedFrom=fulltext", "accessible_url": "https://www.emerald.com/josm/article-abstract/18/5/450/152429/Perceived-justice-and-consumption-experience?redirectedFrom=fulltext", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does perceived justice affect consumers\u2019 evaluations of service consumption experiences?", "design": "Mixed qualitative and experimental investigation of perceived justice and consumption-experience evaluations.", "sample_context": "Service consumers evaluating consumption experiences under experimentally varied justice conditions, informed by qualitative work.", "findings": "The study tests how perceived justice shapes evaluations of consumption experiences, extending complaint/service-recovery justice logic to broader service encounters.", "limitations": "The mixed study is not SaaS-specific and experimental evaluations do not establish effects on actual renewal or long-term usage.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Search/publisher record identifies the paper as a qualitative and experimental investigation. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-6380-71dd-a99e-9efea618ad7c" ], "corrections": [], "plain_english_summary": "The study tests how perceived justice shapes evaluations of consumption experiences, extending complaint/service-recovery justice logic to broader service encounters. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Mixed qualitative and experimental investigation of perceived justice and consumption-experience evaluations." }, { "name": "Sample", "score": "0.5/1", "note": "Service consumers evaluating consumption experiences under experimentally varied justice conditions, informed by qualitative work." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "an-empirical-analysis-of-seller-advertising-strategies-in-an-online-marketplace", "title": "An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace", "category": "Paid media and measurement", "study_type": "Observational marketplace study with controls for sellers\u2019 self-selection into sponsored search/social endorsement.", "citation": "Haoyan Sun, Ming Fan, Yong Tan (2020). An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace. Information Systems Research. https://doi.org/10.1287/isre.2019.0874.", "authors": [ "Haoyan Sun", "Ming Fan", "Yong Tan" ], "year": 2020, "journal": "Information Systems Research", "doi": "10.1287/isre.2019.0874", "doi_url": "https://doi.org/10.1287/isre.2019.0874", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0874", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0874", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do sponsored search and social-media endorsement affect seller traffic and sales, and how does reputation moderate effects?", "design": "Observational marketplace study with controls for sellers\u2019 self-selection into sponsored search/social endorsement.", "sample_context": "Sellers at a retail e-commerce platform; traffic, sales, advertising tools, and seller reputation.", "findings": "Both tools increased traffic; only sponsored search significantly increased sales. Sponsored search worked better for low-reputation traffic and high-reputation sales; endorsement sales effects appeared only for high-reputation sellers.", "limitations": "Results are from one retail e-commerce platform and nonrandom strategy choices, although the analysis controls for self-selection; transferability to other marketplaces is not established.", "founder_use": "Use it to shape a local channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "Publisher abstract explicitly says the study analyzes two advertising tools, controls self-selection, and reports traffic/sales and reputation heterogeneity. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-a484-71ca-98b1-4cfbbf8b770e" ], "corrections": [], "plain_english_summary": "Both tools increased traffic; only sponsored search significantly increased sales. Sponsored search worked better for low-reputation traffic and high-reputation sales; endorsement sales effects appeared only for high-reputation sellers. For your marketing: Use it to shape a local channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Observational marketplace study with controls for sellers\u2019 self-selection into sponsored search/social endorsement." }, { "name": "Sample", "score": "0.5/1", "note": "Sellers at a retail e-commerce platform; traffic, sales, advertising tools, and seller reputation." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "price-bargaining-and-competition-in-online-platforms-an-empirical-analysis-of-the-daily-de", "title": "Price Bargaining and Competition in Online Platforms: An Empirical Analysis of the Daily Deal Market", "category": "Pricing and monetization", "study_type": "Estimated two-stage supply-side model of platform\u2013merchant bargaining using Nash-bargaining solutions and counterfactuals.", "citation": "Lingling Zhang, Doug J. Chung (2020). Price Bargaining and Competition in Online Platforms: An Empirical Analysis of the Daily Deal Market. Marketing Science. https://doi.org/10.1287/mksc.2019.1213.", "authors": [ "Lingling Zhang", "Doug J. Chung" ], "year": 2020, "journal": "Marketing Science", "doi": "10.1287/mksc.2019.1213", "doi_url": "https://doi.org/10.1287/mksc.2019.1213", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1213", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2019.1213", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do platform competition and bargaining power affect merchant reach, margins, consumer prices and demand?", "design": "Estimated two-stage supply-side model of platform\u2013merchant bargaining using Nash-bargaining solutions and counterfactuals.", "sample_context": "Comprehensive U.S. daily-deal market data; merchants, platforms, deals, wholesale prices and demand.", "findings": "Larger platforms deliver larger customer bases but lower merchant margins; absent platform competition, merchants are worse off while consumers face lower prices and higher total demand.", "limitations": "The empirical setting is U.S. daily deals and conclusions rely on the specified bargaining model and counterfactual assumptions; the abstract does not claim universal platform effects.", "founder_use": "Use this study to frame a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "Publisher abstract states the data context, two-stage model, bargaining framework and reported counterfactual findings. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-c90c-75a9-a4f2-0a8525eb00aa" ], "corrections": [], "plain_english_summary": "Larger platforms deliver larger customer bases but lower merchant margins; absent platform competition, merchants are worse off while consumers face lower prices and higher total demand. For your marketing: Use this study to frame a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Estimated two-stage supply-side model of platform\u2013merchant bargaining using Nash-bargaining solutions and counterfactuals." }, { "name": "Sample", "score": "0.5/1", "note": "Comprehensive U.S. daily-deal market data; merchants, platforms, deals, wholesale prices and demand." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "can-third-party-sellers-benefit-from-a-platform-s-entry-to-the-market", "title": "Can Third-Party Sellers Benefit from a Platform\u2019s Entry to the Market?", "category": "Customer behavior and adoption", "study_type": "Exploratory analysis of seller sales data plus a duopoly/sequential-game model explaining the observed pattern.", "citation": "Yiting Deng, Christopher S. Tang, Wei Wang, Onesun Steve Yoo (2023). Can Third-Party Sellers Benefit from a Platform\u2019s Entry to the Market?. Service Science. https://doi.org/10.1287/serv.2023.0324.", "authors": [ "Yiting Deng", "Christopher S. Tang", "Wei Wang", "Onesun Steve Yoo" ], "year": 2023, "journal": "Service Science", "doi": "10.1287/serv.2023.0324", "doi_url": "https://doi.org/10.1287/serv.2023.0324", "primary_url": "https://pubsonline.informs.org/doi/10.1287/serv.2023.0324", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/serv.2023.0324", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can platform entry benefit incumbent third-party sellers rather than harm them?", "design": "Exploratory analysis of seller sales data plus a duopoly/sequential-game model explaining the observed pattern.", "sample_context": "JD.com sales data for one product category in March 2018; third-party sellers before/after platform entry.", "findings": "After entry, similar third-party sellers charged higher prices, obtained higher demand and earned higher profit; the proposed explanation requires moderate platform potential and sufficient spillover.", "limitations": "The empirical analysis is one product category and one month on JD.com and is explicitly exploratory; the theoretical explanation is conditional rather than causal proof across settings.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract specifies the single-category March-2018 JD.com data and reports higher price, demand and profit after entry. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-1e52-74b1-bf5d-3ee6d537d286" ], "corrections": [], "plain_english_summary": "After entry, similar third-party sellers charged higher prices, obtained higher demand and earned higher profit; the proposed explanation requires moderate platform potential and sufficient spillover. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Exploratory analysis of seller sales data plus a duopoly/sequential-game model explaining the observed pattern." }, { "name": "Sample", "score": "1/1", "note": "JD.com sales data for one product category in March 2018; third-party sellers before/after platform entry." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "safety-reviews-on-airbnb-an-information-tale", "title": "Safety Reviews on Airbnb: An Information Tale", "category": "Reviews and reputation", "study_type": "Empirical analysis joining Airbnb reviews with official crime data in five cities; counterfactual simulations of review visibility.", "citation": "Aron Culotta, Ginger Zhe Jin, Yidan Sun, Liad Wagman (2025). Safety Reviews on Airbnb: An Information Tale. Marketing Science. https://doi.org/10.1287/mksc.2023.0552.", "authors": [ "Aron Culotta", "Ginger Zhe Jin", "Yidan Sun", "Liad Wagman" ], "year": 2025, "journal": "Marketing Science", "doi": "10.1287/mksc.2023.0552", "doi_url": "https://doi.org/10.1287/mksc.2023.0552", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0552", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.2023.0552", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does visibility of vicinity-safety reviews affect bookings, revenue and neighborhood sorting?", "design": "Empirical analysis joining Airbnb reviews with official crime data in five cities; counterfactual simulations of review visibility.", "sample_context": "Airbnb listings/reviews and official crime data in five major U.S. cities.", "findings": "Safety reviews and personal safety experiences reduced bookings; removing vicinity-safety reviews could increase Airbnb reservation revenue under unchanged beliefs, but highlighting/removing effects reverse under rational updating; review\u2013crime correlation is stronger in low-income/minority neighborhoods.", "limitations": "Evidence is limited to five major U.S. cities and model-based counterfactuals; the publisher reports conditional outcomes depending on belief updating and learning.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract states the five-city Airbnb/crime-data merge and conditional counterfactual results. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-0984-74de-8872-3987d3285350" ], "corrections": [], "plain_english_summary": "Safety reviews and personal safety experiences reduced bookings; removing vicinity-safety reviews could increase Airbnb reservation revenue under unchanged beliefs, but highlighting/removing effects reverse under rational updating; review\u2013crime correlation is stronger in low-income/minority neighborhoods. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis joining Airbnb reviews with official crime data in five cities; counterfactual simulations of review visibility." }, { "name": "Sample", "score": "0.5/1", "note": "Airbnb listings/reviews and official crime data in five major U.S. cities." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "optional-verification-and-signaling-in-online-matching-markets-evidence-from-a-randomized", "title": "Optional Verification and Signaling in Online Matching Markets: Evidence from a Randomized Field Experiment", "category": "Customer behavior and adoption", "study_type": "Randomized field experiment introducing optional, visible verification on an online dating platform without ratings/reviews.", "citation": "Lanfei Shi, Siva Viswanathan (2023). Optional Verification and Signaling in Online Matching Markets: Evidence from a Randomized Field Experiment. Information Systems Research. https://doi.org/10.1287/isre.2022.1194.", "authors": [ "Lanfei Shi", "Siva Viswanathan" ], "year": 2023, "journal": "Information Systems Research", "doi": "10.1287/isre.2022.1194", "doi_url": "https://doi.org/10.1287/isre.2022.1194", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2022.1194", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2022.1194", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Who opts into optional verification, and does visible verification improve matching outcomes?", "design": "Randomized field experiment introducing optional, visible verification on an online dating platform without ratings/reviews.", "sample_context": "Users on both sides of a leading online dating platform; self-disclosed profiles and voluntary verification.", "findings": "High-type men were more likely to verify, while medium-type women were most likely; verified users received more contacts from higher-type users, became more proactive, and voluntary verification facilitated desirable matching outcomes.", "limitations": "The study is one dating platform with no reputation mechanisms and self-disclosed information; its gendered signaling results may not transfer to other matching or transactional marketplaces.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract states the dating-platform randomized field experiment, side-specific opt-in patterns, contacts, proactivity and platform-level matching result. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-3451-704f-988f-c8631a1121d7" ], "corrections": [], "plain_english_summary": "High-type men were more likely to verify, while medium-type women were most likely; verified users received more contacts from higher-type users, became more proactive, and voluntary verification facilitated desirable matching outcomes. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiment introducing optional, visible verification on an online dating platform without ratings/reviews." }, { "name": "Sample", "score": "0.5/1", "note": "Users on both sides of a leading online dating platform; self-disclosed profiles and voluntary verification." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "perceived-usefulness-perceived-ease-of-use-and-user-acceptance-of-information-technology", "title": "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology", "category": "Customer behavior and adoption", "study_type": "Laboratory and field survey studies testing TAM constructs and usage intentions.", "citation": "Fred D. Davis (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly. https://doi.org/10.2307/249008.", "authors": [ "Fred D. Davis" ], "year": 1989, "journal": "MIS Quarterly", "doi": "10.2307/249008", "doi_url": "https://doi.org/10.2307/249008", "primary_url": "https://misq.umn.edu/misq/article-abstract/13/3/319/191/Perceived-Usefulness-Perceived-Ease-of-Use-and?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article-abstract/13/3/319/1417/Perceived-Usefulness-Perceived-Ease-of-Use-and-User-Acceptance-of-Information-Technology", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do perceived usefulness and ease of use explain acceptance of information technology?", "design": "Laboratory and field survey studies testing TAM constructs and usage intentions.", "sample_context": "Office-automation system users in two empirical studies (reported in the MISQ article).", "findings": "Perceived usefulness and perceived ease of use were significant determinants of acceptance/usage intention; usefulness was especially influential.", "limitations": "The studies concern office-automation technology and intention/self-report measures, so generalization to consumer products and observed long-run retention is limited.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher record identifies the paper as MIS Quarterly 13(3), 319\u2013340 and the article reports two empirical studies introducing and testing TAM. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-496d-710d-966a-dae6fd1053e4" ], "corrections": [], "plain_english_summary": "Perceived usefulness and perceived ease of use were significant determinants of acceptance/usage intention; usefulness was especially influential. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Laboratory and field survey studies testing TAM constructs and usage intentions." }, { "name": "Sample", "score": "0.5/1", "note": "Office-automation system users in two empirical studies (reported in the MISQ article)." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "trust-and-tam-in-online-shopping-an-integrated-model", "title": "Trust and TAM in Online Shopping: An Integrated Model", "category": "Customer behavior and adoption", "study_type": "Empirical questionnaire study using structural equation modeling.", "citation": "David Gefen, E. Karahanna, Detmar W. Straub (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly. https://doi.org/10.2307/30036519.", "authors": [ "David Gefen", "E. Karahanna", "Detmar W. Straub" ], "year": 2003, "journal": "MIS Quarterly", "doi": "10.2307/30036519", "doi_url": "https://doi.org/10.2307/30036519", "primary_url": "https://misq.umn.edu/misq/article-abstract/27/1/51/291/Trust-and-TAM-in-Online-Shopping-An-Integrated?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article-abstract/27/1/51/1412/Trust-and-TAM-in-Online-Shopping-An-Integrated-Model", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does trust add explanatory power to TAM for online shopping?", "design": "Empirical questionnaire study using structural equation modeling.", "sample_context": "Online shoppers evaluating an electronic-commerce website.", "findings": "Trust, perceived usefulness and perceived ease of use jointly explained intended online-shopping behavior; trust complemented TAM.", "limitations": "Cross-sectional perceptions and intention in one online-shopping context cannot establish behavior over time or generalize to subscription-product retention.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract reports an integrated trust/TAM model and empirical testing in online shopping. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fbf-f691-75e5-9532-f8a13b3602e7" ], "corrections": [], "plain_english_summary": "Trust, perceived usefulness and perceived ease of use jointly explained intended online-shopping behavior; trust complemented TAM. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical questionnaire study using structural equation modeling." }, { "name": "Sample", "score": "0.5/1", "note": "Online shoppers evaluating an electronic-commerce website." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "understanding-information-systems-continuance-an-expectation-confirmation-model", "title": "Understanding Information Systems Continuance: An Expectation-Confirmation Model", "category": "Customer behavior and adoption", "study_type": "Field survey testing five hypotheses from an expectation-confirmation model.", "citation": "Anol Bhattacherjee (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly. https://doi.org/10.2307/3250921.", "authors": [ "Anol Bhattacherjee" ], "year": 2001, "journal": "MIS Quarterly", "doi": "10.2307/3250921", "doi_url": "https://doi.org/10.2307/3250921", "primary_url": "https://misq.umn.edu/misq/article-abstract/25/3/351/1309/Understanding-Information-Systems-Continuance-An?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article-abstract/25/3/351/1309/Understanding-Information-Systems-Continuance-An", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What cognitive beliefs and affect explain continued rather than initial IS use?", "design": "Field survey testing five hypotheses from an expectation-confirmation model.", "sample_context": "Online banking users with experience of the system.", "findings": "Continuance intention was determined by satisfaction with use and perceived usefulness of continued use; confirmation influenced satisfaction and usefulness.", "limitations": "Single service (online banking), field survey and intention outcome limit causal and cross-product inference.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Publisher abstract: \u201cFive research hypotheses\u2026 empirically validated using a field survey of online banking users\u201d; it reports satisfaction and continued-use usefulness as determinants. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-6112-778f-bd3d-2c5a94e33087" ], "corrections": [], "plain_english_summary": "Continuance intention was determined by satisfaction with use and perceived usefulness of continued use; confirmation influenced satisfaction and usefulness. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Field survey testing five hypotheses from an expectation-confirmation model." }, { "name": "Sample", "score": "0.5/1", "note": "Online banking users with experience of the system." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-habit-limits-the-predictive-power-of-intention-the-case-of-information-systems-continu", "title": "How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance", "category": "Customer behavior and adoption", "study_type": "Empirical multi-wave field survey/model test of intention, habit and continuance behavior.", "citation": "Moez Limayem, Sabine G. Hirt, Chun M. K. Cheung (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Quarterly. https://doi.org/10.2307/25148817.", "authors": [ "Moez Limayem", "Sabine G. Hirt", "Chun M. K. Cheung" ], "year": 2007, "journal": "MIS Quarterly", "doi": "10.2307/25148817", "doi_url": "https://doi.org/10.2307/25148817", "primary_url": "https://misq.umn.edu/misq/article-abstract/31/4/705/1302/How-Habit-Limits-the-Predictive-Power-of-Intention?redirectedFrom=fulltext", "accessible_url": "https://scholars.hkbu.edu.hk/en/publications/how-habit-limits-the-predictive-power-of-intention-the-case-of-in-2/", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When does habit reduce the usefulness of intention for predicting continued IS use?", "design": "Empirical multi-wave field survey/model test of intention, habit and continuance behavior.", "sample_context": "Information-system users in a field setting, observed across repeated measurement waves.", "findings": "Habit moderated the intention\u2013continuance relationship: as habit strengthened, intention became less predictive of continued use.", "limitations": "Survey/field context and self-reported system behavior constrain causal interpretation and portability to new-product onboarding.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "The DOI landing/search record identifies the paper and its central case as IS continuance; the published study tests habit and intention empirically. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-9184-75ad-97d3-bbf6fe03ce6a" ], "corrections": [], "plain_english_summary": "Habit moderated the intention\u2013continuance relationship: as habit strengthened, intention became less predictive of continued use. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical multi-wave field survey/model test of intention, habit and continuance behavior." }, { "name": "Sample", "score": "0.5/1", "note": "Information-system users in a field setting, observed across repeated measurement waves." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-mediation-of-external-variables-in-the-technology-acceptance-model", "title": "The Mediation of External Variables in the Technology Acceptance Model", "category": "Paid media and measurement", "study_type": "Empirical survey study using structural equation modeling to compare direct and mediated effects.", "citation": "Anthony Burton-Jones, Gordon S. Hubona (2006). The Mediation of External Variables in the Technology Acceptance Model. Information Systems Research. https://doi.org/10.1287/isre.1060.0080.", "authors": [ "Anthony Burton-Jones", "Gordon S. Hubona" ], "year": 2006, "journal": "Information Systems Research", "doi": "10.1287/isre.1060.0080", "doi_url": "https://doi.org/10.1287/isre.1060.0080", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.1060.0080", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.1060.0080", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do external variables enter TAM\u2014directly or through usefulness/ease-of-use beliefs?", "design": "Empirical survey study using structural equation modeling to compare direct and mediated effects.", "sample_context": "Information-system users in an organizational usage context.", "findings": "External variables influenced usage largely through perceived usefulness and ease of use, supporting mediation rather than treating external variables as direct usage drivers.", "limitations": "Single survey context and self-reported usage make causal mediation and consumer-SaaS generalization uncertain.", "founder_use": "Use it to shape a local channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "INFORMS DOI landing page identifies the article and its empirical mediation test. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-a615-77b8-94b3-55b267f341bb" ], "corrections": [], "plain_english_summary": "External variables influenced usage largely through perceived usefulness and ease of use, supporting mediation rather than treating external variables as direct usage drivers. For your marketing: Use it to shape a local channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey study using structural equation modeling to compare direct and mediated effects." }, { "name": "Sample", "score": "0.5/1", "note": "Information-system users in an organizational usage context." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "understanding-information-technology-usage-a-test-of-competing-models", "title": "Understanding Information Technology Usage: A Test of Competing Models", "category": "Customer behavior and adoption", "study_type": "Empirical survey comparison of TAM, TPB and decomposed TPB models.", "citation": "Shirley Taylor, Peter A. Todd (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research. https://doi.org/10.1287/isre.6.2.144.", "authors": [ "Shirley Taylor", "Peter A. Todd" ], "year": 1995, "journal": "Information Systems Research", "doi": "10.1287/isre.6.2.144", "doi_url": "https://doi.org/10.1287/isre.6.2.144", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.6.2.144", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.6.2.144", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which competing behavioral models best explain IT usage?", "design": "Empirical survey comparison of TAM, TPB and decomposed TPB models.", "sample_context": "University students using a computer resource centre.", "findings": "The decomposed TPB model provided useful explanatory power for intention and usage; perceived usefulness and social/behavioral determinants were important.", "limitations": "Student/computer-resource context, cross-sectional survey and self-reported outcomes limit SaaS-funnel generalization.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "INFORMS page identifies publication and DOI; the paper tests competing acceptance models empirically. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-e0ce-718f-9ea2-b2daa4aca25f" ], "corrections": [], "plain_english_summary": "The decomposed TPB model provided useful explanatory power for intention and usage; perceived usefulness and social/behavioral determinants were important. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical survey comparison of TAM, TPB and decomposed TPB models." }, { "name": "Sample", "score": "0.5/1", "note": "University students using a computer resource centre." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "testing-the-determinants-of-microcomputer-usage-via-a-structural-equation-model", "title": "Testing the Determinants of Microcomputer Usage via a Structural Equation Model", "category": "Customer behavior and adoption", "study_type": "Structural-equation analysis of a survey model of microcomputer use.", "citation": "Magid Igbaria, Tomas Guimaraes, Gordon B. Davis (1995). Testing the Determinants of Microcomputer Usage via a Structural Equation Model. Journal of Management Information Systems. https://doi.org/10.1080/07421222.1995.11518061.", "authors": [ "Magid Igbaria", "Tomas Guimaraes", "Gordon B. Davis" ], "year": 1995, "journal": "Journal of Management Information Systems", "doi": "10.1080/07421222.1995.11518061", "doi_url": "https://doi.org/10.1080/07421222.1995.11518061", "primary_url": "https://www.tandfonline.com/doi/abs/10.1080/07421222.1995.11518061", "accessible_url": "https://www.tandfonline.com/doi/abs/10.1080/07421222.1995.11518061", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "What individual, organizational and system factors determine microcomputer usage?", "design": "Structural-equation analysis of a survey model of microcomputer use.", "sample_context": "Microcomputer users in organizational settings.", "findings": "Individual, organizational and system-related factors were modeled as determinants of microcomputer usage; perceived usefulness/attitudes were important pathways.", "limitations": "Organizational microcomputer setting and cross-sectional self-report usage limit direct applicability to cloud-product activation and retention.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "Taylor & Francis record provides exact title, authors and abstract describing the structural-equation empirical study. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-7318-74ae-8c79-e260c5000b68" ], "corrections": [], "plain_english_summary": "Individual, organizational and system-related factors were modeled as determinants of microcomputer usage; perceived usefulness/attitudes were important pathways. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Structural-equation analysis of a survey model of microcomputer use." }, { "name": "Sample", "score": "0.5/1", "note": "Microcomputer users in organizational settings." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "intentions-to-use-mobile-services-antecedents-and-cross-service-comparisons", "title": "Intentions to Use Mobile Services: Antecedents and Cross-Service Comparisons", "category": "Customer behavior and adoption", "study_type": "Empirical comparative studies testing a model of mobile-service intention across four services.", "citation": "Herlaug Nysveen, Per Egil Pedersen, Helge Thorbj\u00f8rnsen (2005). Intentions to Use Mobile Services: Antecedents and Cross-Service Comparisons. Journal of the Academy of Marketing Science. https://doi.org/10.1177/0092070305276149.", "authors": [ "Herlaug Nysveen", "Per Egil Pedersen", "Helge Thorbj\u00f8rnsen" ], "year": 2005, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1177/0092070305276149", "doi_url": "https://doi.org/10.1177/0092070305276149", "primary_url": "https://link.springer.com/article/10.1177/0092070305276149", "accessible_url": "https://journals.sagepub.com/doi/abs/10.1177/0092070305276149", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which motivational, technology- and user-related antecedents explain intentions across mobile services?", "design": "Empirical comparative studies testing a model of mobile-service intention across four services.", "sample_context": "Consumers considering/using four mobile services.", "findings": "The four-service empirical results supported motivational influences on intention; the relative importance of antecedents differed across services.", "limitations": "The outcome is primarily intention and the services are mobile-specific; cross-sectional service comparisons do not identify causal onboarding effects.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE publisher abstract says the article develops and tests a model and reports empirical studies of four mobile services. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc0-cbe0-72a9-aa93-af067e8bfb7c" ], "corrections": [], "plain_english_summary": "The four-service empirical results supported motivational influences on intention; the relative importance of antecedents differed across services. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical comparative studies testing a model of mobile-service intention across four services." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers considering/using four mobile services." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "exploring-consumer-adoption-of-mobile-payments-a-qualitative-study", "title": "Exploring Consumer Adoption of Mobile Payments \u2013 A Qualitative Study", "category": "Customer behavior and adoption", "study_type": "Exploratory qualitative empirical study using consumer data/interviews about a new electronic payment service.", "citation": "Niina Mallat (2007). Exploring Consumer Adoption of Mobile Payments \u2013 A Qualitative Study. The Journal of Strategic Information Systems. https://doi.org/10.1016/j.jsis.2007.08.001.", "authors": [ "Niina Mallat" ], "year": 2007, "journal": "The Journal of Strategic Information Systems", "doi": "10.1016/j.jsis.2007.08.001", "doi_url": "https://doi.org/10.1016/j.jsis.2007.08.001", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0963868707000480?via%3Dihub", "accessible_url": "https://modelesbancaires.weebly.com/uploads/2/5/0/4/25044223/mallet_adoption_of_mobile_banking_qualitative_study.pdf", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What factors and situations shape consumer adoption of mobile payments?", "design": "Exploratory qualitative empirical study using consumer data/interviews about a new electronic payment service.", "sample_context": "Consumers considering mobile payments in a Finnish/European service context.", "findings": "Relative advantage, situational factors and lack of broad merchant acceptance shaped adoption; mobile payment can be adopted when it solves a specific situational need.", "limitations": "Qualitative exploratory design and one service context limit statistical generalization; it explains adoption conditions rather than estimating population effects.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "ScienceDirect search result identifies DOI/title; accessible paper abstract states it is a qualitative study and reports relative advantage and adoption conditions. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-08aa-70aa-80af-b8e873752d9a" ], "corrections": [], "plain_english_summary": "Relative advantage, situational factors and lack of broad merchant acceptance shaped adoption; mobile payment can be adopted when it solves a specific situational need. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Exploratory qualitative empirical study using consumer data/interviews about a new electronic payment service." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers considering mobile payments in a Finnish/European service context." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-penny-for-your-thoughts-referral-reward-programs-and-referral-likelihood", "title": "A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood", "category": "Reviews and reputation", "study_type": "Field and laboratory experiments plus survey analyses of referral reward framing and likelihood.", "citation": "Gangseog Ryu, Lawrence Feick (2007). A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood. Journal of Marketing. https://doi.org/10.1509/jmkg.71.1.084.", "authors": [ "Gangseog Ryu", "Lawrence Feick" ], "year": 2007, "journal": "Journal of Marketing", "doi": "10.1509/jmkg.71.1.084", "doi_url": "https://doi.org/10.1509/jmkg.71.1.084", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkg.71.1.084", "accessible_url": "https://journals.sagepub.com/doi/full/10.1509/jmkg.71.1.084", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When and for whom do referral rewards increase the likelihood of making a referral?", "design": "Field and laboratory experiments plus survey analyses of referral reward framing and likelihood.", "sample_context": "Consumers in referral-program contexts; experiments compare reward/no-reward and relationship-strength conditions.", "findings": "Rewards can increase referral likelihood, but their effectiveness depends on the strength of the relationship between referrer and recipient; incentives are less useful for weak ties.", "limitations": "The experiments and scenarios do not establish long-run customer value or downstream conversion; findings concern referral likelihood rather than SaaS retention or revenue.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract/page identifies referral reward programs and referral likelihood; the article reports multiple empirical studies testing reward and relationship effects. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-6d00-757e-a8cf-699e89e713ae" ], "corrections": [], "plain_english_summary": "Rewards can increase referral likelihood, but their effectiveness depends on the strength of the relationship between referrer and recipient; incentives are less useful for weak ties. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Field and laboratory experiments plus survey analyses of referral reward framing and likelihood." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers in referral-program contexts; experiments compare reward/no-reward and relationship-strength conditions." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "using-online-conversations-to-study-word-of-mouth-communication", "title": "Using Online Conversations to Study Word-of-Mouth Communication", "category": "Customer behavior and adoption", "study_type": "Empirical analysis of online conversation data linked to market outcomes, comparing geographically dispersed versus concentrated conversations.", "citation": "David Godes, Dina Mayzlin (2004). Using Online Conversations to Study Word-of-Mouth Communication. Marketing Science. https://doi.org/10.1287/mksc.1040.0071.", "authors": [ "David Godes", "Dina Mayzlin" ], "year": 2004, "journal": "Marketing Science", "doi": "10.1287/mksc.1040.0071", "doi_url": "https://doi.org/10.1287/mksc.1040.0071", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1040.0071", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1040.0071", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can online conversations be used as a measurable predictor of WOM and market performance?", "design": "Empirical analysis of online conversation data linked to market outcomes, comparing geographically dispersed versus concentrated conversations.", "sample_context": "Online discussion/conversation records about television shows, linked to show-level ratings and geographic variation.", "findings": "The geographic dispersion of online conversations is associated with subsequent television ratings; the paper demonstrates how online conversations can measure WOM and predict performance.", "limitations": "The setting is television and the study is observational; conversation measures may reflect selection and cannot cleanly separate WOM influence from correlated demand.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "INFORMS publisher page supplies exact title, authors, journal and pages; the paper\u2019s abstract/method describes online conversations and TV-market outcome analysis. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-98c5-77cb-91e7-06ec59c89518" ], "corrections": [], "plain_english_summary": "The geographic dispersion of online conversations is associated with subsequent television ratings; the paper demonstrates how online conversations can measure WOM and predict performance. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of online conversation data linked to market outcomes, comparing geographically dispersed versus concentrated conversations." }, { "name": "Sample", "score": "0.5/1", "note": "Online discussion/conversation records about television shows, linked to show-level ratings and geographic variation." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "do-online-reviews-matter-an-empirical-investigation-of-panel-data", "title": "Do Online Reviews Matter? An Empirical Investigation of Panel Data", "category": "Reviews and reputation", "study_type": "Panel-data econometric study of review volume, ratings, and sales with product/time controls.", "citation": "Wenjing Duan, Bin Gu, Andrew B. Whinston (2008). Do Online Reviews Matter? An Empirical Investigation of Panel Data. Decision Support Systems. https://doi.org/10.1016/j.dss.2008.04.001.", "authors": [ "Wenjing Duan", "Bin Gu", "Andrew B. Whinston" ], "year": 2008, "journal": "Decision Support Systems", "doi": "10.1016/j.dss.2008.04.001", "doi_url": "https://doi.org/10.1016/j.dss.2008.04.001", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923608000754?via%3Dihub", "accessible_url": "https://people.stern.nyu.edu/wgreene/entertainmentandmedia/online-reviews.pdf", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do online review volume and ratings affect sales, and how should firms interpret review metrics?", "design": "Panel-data econometric study of review volume, ratings, and sales with product/time controls.", "sample_context": "Movie-market panel data linking online reviews and movie box-office performance over time.", "findings": "Review volume is positively associated with box-office demand, while the relationship between review valence and sales is more nuanced; review activity can be a demand signal as well as influence.", "limitations": "Movie releases are a special high-information-good context; panel observational estimates cannot fully rule out unobserved publicity or reverse causality.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "ScienceDirect result identifies the article as an empirical panel-data investigation; the accessible paper reports movie panel variables and estimation. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-c3b0-76ec-a586-8413f548f84c" ], "corrections": [], "plain_english_summary": "Review volume is positively associated with box-office demand, while the relationship between review valence and sales is more nuanced; review activity can be a demand signal as well as influence. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Panel-data econometric study of review volume, ratings, and sales with product/time controls." }, { "name": "Sample", "score": "0.5/1", "note": "Movie-market panel data linking online reviews and movie box-office performance over time." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-multi-stage-model-of-word-of-mouth-influence-through-viral-marketing", "title": "A Multi-Stage Model of Word-of-Mouth Influence Through Viral Marketing", "category": "Customer behavior and adoption", "study_type": "Empirical survey/experimental test of a staged model of recipient response to viral messages, estimating antecedents at decision stages.", "citation": "Arnaud De Bruyn, Gary L. Lilien (2008). A Multi-Stage Model of Word-of-Mouth Influence Through Viral Marketing. International Journal of Research in Marketing. https://doi.org/10.1016/j.ijresmar.2008.03.004.", "authors": [ "Arnaud De Bruyn", "Gary L. Lilien" ], "year": 2008, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2008.03.004", "doi_url": "https://doi.org/10.1016/j.ijresmar.2008.03.004", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167811608000414?via%3Dihub", "accessible_url": "https://pure.psu.edu/en/publications/a-multi-stage-model-of-word-of-mouth-influence-through-viral-mark/", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "At which stages and through which mechanisms does WOM influence viral-marketing recipients?", "design": "Empirical survey/experimental test of a staged model of recipient response to viral messages, estimating antecedents at decision stages.", "sample_context": "Recipients of viral-marketing communications; message, sender/recipient relationship, and forwarding/response outcomes are measured.", "findings": "WOM influence differs across stages of recipient decision making; sender characteristics and tie strength affect opening, processing, and forwarding/response.", "limitations": "The communication scenario and measured intentions are not observed SaaS customer acquisition or long-run behavior; staged estimates rely partly on self-report.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "ScienceDirect and the authors\u2019 repository identify the staged decision-process research question and empirical model. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-49e5-73ed-a64e-7398961dca1c" ], "corrections": [], "plain_english_summary": "WOM influence differs across stages of recipient decision making; sender characteristics and tie strength affect opening, processing, and forwarding/response. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Empirical survey/experimental test of a staged model of recipient response to viral messages, estimating antecedents at decision stages." }, { "name": "Sample", "score": "0.5/1", "note": "Recipients of viral-marketing communications; message, sender/recipient relationship, and forwarding/response outcomes are measured." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effects-of-traditional-and-social-earned-media-on-sales-a-study-of-a-microlending-mark", "title": "The Effects of Traditional and Social Earned Media on Sales: A Study of a Microlending Marketplace", "category": "B2B growth and sales", "study_type": "Longitudinal time-series analysis of earned-media events and transaction activity, estimating dynamic effects.", "citation": "Andrew T. Stephen, Jeff Galak (2012). The Effects of Traditional and Social Earned Media on Sales: A Study of a Microlending Marketplace. Journal of Marketing Research. https://doi.org/10.1509/jmr.09.0401.", "authors": [ "Andrew T. Stephen", "Jeff Galak" ], "year": 2012, "journal": "Journal of Marketing Research", "doi": "10.1509/jmr.09.0401", "doi_url": "https://doi.org/10.1509/jmr.09.0401", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmr.09.0401", "accessible_url": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1480088", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do traditional versus social earned media affect sales/activity in a marketplace?", "design": "Longitudinal time-series analysis of earned-media events and transaction activity, estimating dynamic effects.", "sample_context": "A microlending marketplace; traditional press mentions and social media/blog/community activity linked to lending transactions.", "findings": "Both traditional and social earned media affect marketplace activity; social earned media\u2019s greater frequency can make its cumulative effect important despite smaller reach per event.", "limitations": "One microlending marketplace and nonrandom earned-media exposure constrain external validity and causal interpretation.", "founder_use": "Use it as a sales-process or B2B mechanism reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "SAGE publisher abstract identifies the two earned-media types and sales question; SSRN full text identifies the microlending marketplace and time-series study. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-e4ca-713e-b4b1-15e9e96bd06c" ], "corrections": [], "plain_english_summary": "Both traditional and social earned media affect marketplace activity; social earned media\u2019s greater frequency can make its cumulative effect important despite smaller reach per event. For your marketing: Use it as a sales-process or B2B mechanism reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal time-series analysis of earned-media events and transaction activity, estimating dynamic effects." }, { "name": "Sample", "score": "0.5/1", "note": "A microlending marketplace; traditional press mentions and social media/blog/community activity linked to lending transactions." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "viral-marketing-motivations-to-forward-online-content", "title": "Viral Marketing: Motivations to Forward Online Content", "category": "Content and sharing", "study_type": "Survey-based empirical study using motivational constructs to predict forwarding of online content.", "citation": "Jason Y. C. Ho, Melanie Dempsey (2010). Viral Marketing: Motivations to Forward Online Content. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2009.09.010.", "authors": [ "Jason Y. C. Ho", "Melanie Dempsey" ], "year": 2010, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2009.09.010", "doi_url": "https://doi.org/10.1016/j.jbusres.2009.09.010", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296309002483?via%3Dihub", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296309002215", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "What motivations lead consumers to forward online content?", "design": "Survey-based empirical study using motivational constructs to predict forwarding of online content.", "sample_context": "Online users who forward online content; measures cover belonging, individualism, altruism, and personal-growth motives.", "findings": "The need to belong, be individualistic, be altruistic, and seek personal growth are identified as motivations associated with forwarding; relative importance differs across users.", "limitations": "Self-reported forwarding and cross-sectional survey design limit causal claims and may not predict actual referrals or paid conversion.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "ScienceDirect abstract explicitly lists the four motivation categories and frames the paper as viral-marketing forwarding research. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc1-285a-727e-a5ea-9a5384f76263" ], "corrections": [], "plain_english_summary": "The need to belong, be individualistic, be altruistic, and seek personal growth are identified as motivations associated with forwarding; relative importance differs across users. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Survey-based empirical study using motivational constructs to predict forwarding of online content." }, { "name": "Sample", "score": "0.5/1", "note": "Online users who forward online content; measures cover belonging, individualism, altruism, and personal-growth motives." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "distinguishing-influence-based-contagion-from-homophily-driven-diffusion-in-dynamic-networ", "title": "Distinguishing Influence-Based Contagion from Homophily-Driven Diffusion in Dynamic Networks", "category": "Customer behavior and adoption", "study_type": "Observational dynamic-network analysis with matching/statistical controls for homophily and contemporaneous adoption.", "citation": "Sinan Aral, Lev Muchnik, Arun Sundararajan (2009). Distinguishing Influence-Based Contagion from Homophily-Driven Diffusion in Dynamic Networks. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0908800106.", "authors": [ "Sinan Aral", "Lev Muchnik", "Arun Sundararajan" ], "year": 2009, "journal": "Proceedings of the National Academy of Sciences", "doi": "10.1073/pnas.0908800106", "doi_url": "https://doi.org/10.1073/pnas.0908800106", "primary_url": "https://www.pnas.org/doi/full/10.1073/pnas.0908800106", "accessible_url": "https://www.pnas.org/doi/10.1073/pnas.0908800106", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How much apparent product-adoption contagion is true peer influence versus homophily?", "design": "Observational dynamic-network analysis with matching/statistical controls for homophily and contemporaneous adoption.", "sample_context": "A large online social network\u2019s mobile-service adoption decisions and user demographic/behavioral similarity.", "findings": "Naive methods overestimate peer influence by 300\u2013700%; homophily explains more than 50% of perceived contagion in the analyzed adoption network.", "limitations": "The network is one mobile-service setting and remains observational; results do not estimate a referral-program treatment effect.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "PNAS publisher abstract/results explicitly report the 300\u2013700% overestimate and >50% homophily estimates. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc2-2a56-7386-8db9-5cf07345d40a" ], "corrections": [], "plain_english_summary": "Naive methods overestimate peer influence by 300\u2013700%; homophily explains more than 50% of perceived contagion in the analyzed adoption network. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Observational dynamic-network analysis with matching/statistical controls for homophily and contemporaneous adoption." }, { "name": "Sample", "score": "0.5/1", "note": "A large online social network\u2019s mobile-service adoption decisions and user demographic/behavioral similarity." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "impact-of-incentive-mechanism-in-online-referral-programs-evidence-from-randomized-field-e", "title": "Impact of Incentive Mechanism in Online Referral Programs: Evidence from Randomized Field Experiments", "category": "Reviews and reputation", "study_type": "Randomized field experiments manipulating online referral incentive mechanisms.", "citation": "Jaehwuen Jung, Ravi Bapna, Anil Gupta, Sudha Ram (2021). Impact of Incentive Mechanism in Online Referral Programs: Evidence from Randomized Field Experiments. Journal of Management Information Systems. https://doi.org/10.1080/07421222.2021.1870384.", "authors": [ "Jaehwuen Jung", "Ravi Bapna", "Anil Gupta", "Sudha Ram" ], "year": 2021, "journal": "Journal of Management Information Systems", "doi": "10.1080/07421222.2021.1870384", "doi_url": "https://doi.org/10.1080/07421222.2021.1870384", "primary_url": "https://www.tandfonline.com/doi/full/10.1080/07421222.2021.1870384", "accessible_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8240956/", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "How does the design/allocation of online referral incentives affect referral outcomes?", "design": "Randomized field experiments manipulating online referral incentive mechanisms.", "sample_context": "Customers participating in an online referral program; referral initiation and downstream referral outcomes under alternative incentive allocations.", "findings": "The incentive mechanism and allocation between referrer and referred customer materially affect online referral performance; incentive design is not one-size-fits-all.", "limitations": "The focal program and customer population are firm-specific; field results do not establish effects for every SaaS pricing model or incentive cost.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "The PMC accessible paper\u2019s reference identifies the exact article and DOI as evidence from randomized field experiments; DOI landing page confirms bibliographic details. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc2-8d94-7409-a12c-a628479ad29e" ], "corrections": [], "plain_english_summary": "The incentive mechanism and allocation between referrer and referred customer materially affect online referral performance; incentive design is not one-size-fits-all. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized field experiments manipulating online referral incentive mechanisms." }, { "name": "Sample", "score": "0.5/1", "note": "Customers participating in an online referral program; referral initiation and downstream referral outcomes under alternative incentive allocations." }, { "name": "Comparison", "score": "1/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "word-of-mouth-for-movies-its-dynamics-and-impact-on-box-office-revenue", "title": "Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue", "category": "Reviews and reputation", "study_type": "Dynamic panel/time-series analysis of WOM measures and weekly box-office revenue.", "citation": "Yong Liu (2006). Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue. Journal of Marketing. https://doi.org/10.1509/jmkg.70.3.74.", "authors": [ "Yong Liu" ], "year": 2006, "journal": "Journal of Marketing", "doi": "10.1509/jmkg.70.3.74", "doi_url": "https://doi.org/10.1509/jmkg.70.3.74", "primary_url": "https://journals.sagepub.com/doi/10.1509/jmkg.70.3.074", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jmkg.70.3.074", "access_label": "Publisher record and abstract retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What are the dynamics of movie WOM and how does it affect box-office revenue?", "design": "Dynamic panel/time-series analysis of WOM measures and weekly box-office revenue.", "sample_context": "Movies released in theaters; online WOM volume/valence and weekly box-office revenue across the movie life cycle.", "findings": "WOM volume is positively related to box office and its effect varies over a movie\u2019s life cycle; WOM is both an outcome of consumption and a predictor of later demand.", "limitations": "Movie WOM and box office are observational and category-specific; simultaneity and unobserved marketing/publicity remain concerns.", "founder_use": "Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE publisher page identifies the exact title and abstract; Crossref metadata confirms author, year, journal, and DOI. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc2-4e28-77b3-a013-0d119a868a7c" ], "corrections": [], "plain_english_summary": "WOM volume is positively related to box office and its effect varies over a movie\u2019s life cycle; WOM is both an outcome of consumption and a predictor of later demand. For your marketing: Use it as a behavioral mechanism or experiment-design reference, not a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Dynamic panel/time-series analysis of WOM measures and weekly box-office revenue." }, { "name": "Sample", "score": "0.5/1", "note": "Movies released in theaters; online WOM volume/valence and weekly box-office revenue across the movie life cycle." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effect-of-online-consumer-reviews-on-new-product-sales", "title": "The Effect of Online Consumer Reviews on New Product Sales", "category": "B2B growth and sales", "study_type": "Nine-month product-level panel-data analysis with review ratings, review text/topics, and sales outcomes.", "citation": "Geng Cui, Hon-Kwong Lui, Xiaoning Guo (2012). The Effect of Online Consumer Reviews on New Product Sales. International Journal of Electronic Commerce. https://doi.org/10.2753/JEC1086-4415170102.", "authors": [ "Geng Cui", "Hon-Kwong Lui", "Xiaoning Guo" ], "year": 2012, "journal": "International Journal of Electronic Commerce", "doi": "10.2753/JEC1086-4415170102", "doi_url": "https://doi.org/10.2753/JEC1086-4415170102", "primary_url": "https://www.tandfonline.com/doi/abs/10.2753/JEC1086-4415170102", "accessible_url": "https://commons.ln.edu.hk/sw_master/2418/", "access_label": "Publisher abstract/metadata retrieved; full text may require access.", "access_class": "abstract", "research_question": "How do online consumer reviews affect sales of new products, and do numerical and textual review features matter?", "design": "Nine-month product-level panel-data analysis with review ratings, review text/topics, and sales outcomes.", "sample_context": "332 new products on Amazon.com observed for nine months.", "findings": "Review quantity, rating, and review content are empirically related to new-product sales; the paper analyzes both numerical ratings and textual review effects.", "limitations": "Amazon and the new-product categories limit generalization; observational panel data cannot fully identify causal review effects.", "founder_use": "Use it as a sales-process or B2B mechanism reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "Crossref publisher metadata identifies authors/title/year; the accessible record explicitly reports panel data for 332 Amazon products over nine months. Direct publisher-page retrieval was recorded on 2026-10-09; this profile uses publisher metadata/abstract and does not claim independent review of unavailable full text.", "source_ids": [ "01a11fc2-1000-7647-88d3-e3e5fa6bda74" ], "corrections": [], "plain_english_summary": "Review quantity, rating, and review content are empirically related to new-product sales; the paper analyzes both numerical ratings and textual review effects. For your marketing: Use it as a sales-process or B2B mechanism reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Nine-month product-level panel-data analysis with review ratings, review text/topics, and sales outcomes." }, { "name": "Sample", "score": "1/1", "note": "332 new products on Amazon.com observed for nine months." }, { "name": "Comparison", "score": "0.5/1", "note": "Judged from the publisher-described design and comparison; consult the paper for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher page and abstract were retrieved directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "growing-platforms-within-platforms-how-platforms-manage-the-adoption-of-complementor", "title": "Growing platforms within platforms: How platforms manage the adoption of complementor products in the presence of network effects?", "category": "Customer behavior and adoption", "study_type": "Large-scale observational empirical analysis of Apple's app-promotion decisions; the article tests predictions using app-level data and robustness/alternative specifications.", "citation": "Shiva Agarwal, Cameron D. Miller, Martin Ganco (2023). Growing platforms within platforms: How platforms manage the adoption of complementor products in the presence of network effects?. Strategic Management Journal. https://doi.org/10.1002/smj.3487.", "authors": [ "Shiva Agarwal", "Cameron D. Miller", "Martin Ganco" ], "year": 2023, "journal": "Strategic Management Journal", "doi": "10.1002/smj.3487", "doi_url": "https://doi.org/10.1002/smj.3487", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3487", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3487", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does a platform owner manage adoption of complementor products that have direct network effects, balancing user-growth benefits against the risk of complementor dominance?", "design": "Large-scale observational empirical analysis of Apple's app-promotion decisions; the article tests predictions using app-level data and robustness/alternative specifications.", "sample_context": "Apple iOS App Store game apps released during 60 months from 2012\u20132016; the resulting complete-data sample is 211,407 games across 20 categories. The outcome is receipt of Apple's Editors' Choice award; multiplayer games proxy direct network effects, with developer market share and segment concentration as contingencies.", "findings": "Apps with direct network effects are more likely to receive an award. The likelihood rises with developer market share but falls in concentrated segments; in concentrated segments, challenger developers are more likely than leaders to receive the award.", "limitations": "The publisher page does not state a limitations section; this is therefore not stated by the publisher page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract says the authors test predictions using Apple's promotion of apps and find that network-effects apps are more likely to receive an award, with the effect depending on developer market share and segment concentration. The methods page identifies 211,407 games across 20 categories (2012\u20132016). Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc8-cf6e-742a-80e0-bc317a72c350" ], "corrections": [], "plain_english_summary": "Apps with direct network effects are more likely to receive an award. The likelihood rises with developer market share but falls in concentrated segments; in concentrated segments, challenger developers are more likely than leaders to receive the award. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Large-scale observational empirical analysis of Apple's app-promotion decisions; the article tests predictions using app-level data and robustness/alternative specifications." }, { "name": "Sample", "score": "1/1", "note": "Apple iOS App Store game apps released during 60 months from 2012\u20132016; the resulting complete-data sample is 211,407 games across 20 categories. The outcome is receipt of Apple's Editors' Choice award; multiplayer games proxy direct network effects, with developer market share and segment concentration as contingencies." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "competing-on-freemium-digital-competition-with-network-effects", "title": "Competing on freemium: Digital competition with network effects", "category": "Pricing and monetization", "study_type": "Empirical comparative analysis of product sales/revenues around an Apple App Store policy that strengthened network effects, contrasting freemium and non-freemium products and market leaders versus followers; the publisher identifies Apple daily prod", "citation": "Kevin J. Boudreau, Lars Bo Jeppesen, Milan Miric (2022). Competing on freemium: Digital competition with network effects. Strategic Management Journal. https://doi.org/10.1002/smj.3366.", "authors": [ "Kevin J. Boudreau", "Lars Bo Jeppesen", "Milan Miric" ], "year": 2022, "journal": "Strategic Management Journal", "doi": "10.1002/smj.3366", "doi_url": "https://doi.org/10.1002/smj.3366", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/abs/10.1002/smj.3366", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3366", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When network effects strengthen in a competitive digital market, how do freemium strategies affect the revenue advantage of market leaders versus followers?", "design": "Empirical comparative analysis of product sales/revenues around an Apple App Store policy that strengthened network effects, contrasting freemium and non-freemium products and market leaders versus followers; the publisher identifies Apple daily product-ranking data as the data source.", "sample_context": "Competing products on Apple's App Store, classified by freemium strategy and market-leader/follower position; product rankings were collected daily, with app categorization supplied by Priori LLC.", "findings": "Stronger network effects alone did not increase market leaders' revenues relative to followers. Where freemium was used, however, network effects greatly amplified leaders' advantage; the publisher describes this as increased revenue/market dominance for leaders only under freemium.", "limitations": "The publisher page does not state a limitations section; this is therefore not stated by the publisher page fetched in this run.", "founder_use": "Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher research summary states that the study empirically investigates how strengthened Apple App Store network effects influenced sales of firms using freemium strategies and reports that freemium plus stronger network effects amplified leaders' advantage. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-0ef7-70ea-9b93-2bf8a2ed7d64" ], "corrections": [], "plain_english_summary": "Stronger network effects alone did not increase market leaders' revenues relative to followers. Where freemium was used, however, network effects greatly amplified leaders' advantage; the publisher describes this as increased revenue/market dominance for leaders only under freemium. For your marketing: Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical comparative analysis of product sales/revenues around an Apple App Store policy that strengthened network effects, contrasting freemium and non-freemium products and market leaders versus followers; the publisher identifies Apple daily product-ranking data as the data source." }, { "name": "Sample", "score": "0.5/1", "note": "Competing products on Apple's App Store, classified by freemium strategy and market-leader/follower position; product rankings were collected daily, with app categorization supplied by Priori LLC." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "online-communities-on-competing-platforms-evidence-from-game-wikis", "title": "Online communities on competing platforms: Evidence from game wikis", "category": "Customer behavior and adoption", "study_type": "Quantitative quasi-experimental/event-study design resembling regression discontinuity in time: contributor activity is compared in four days before versus five days after exogenous game updates, with heterogeneous treatment effects by platform compe", "citation": "Johannes Loh, Tobias Kretschmer (2023). Online communities on competing platforms: Evidence from game wikis. Strategic Management Journal. https://doi.org/10.1002/smj.3442.", "authors": [ "Johannes Loh", "Tobias Kretschmer" ], "year": 2023, "journal": "Strategic Management Journal", "doi": "10.1002/smj.3442", "doi_url": "https://doi.org/10.1002/smj.3442", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3442", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3442", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do volunteer online communities create competitive advantage for platforms, and how does platform competitive position affect the extensive and intensive margins of contributor activity?", "design": "Quantitative quasi-experimental/event-study design resembling regression discontinuity in time: contributor activity is compared in four days before versus five days after exogenous game updates, with heterogeneous treatment effects by platform competitive position.", "sample_context": "13 game-wiki communities on two competing platforms; the study hand-collected game updates and analyzes 443 distinct updates across games, focusing on volunteer contributors, activity, contributor counts, and productivity.", "findings": "A stronger platform competitive position is associated with higher activity, primarily through more contributors, which then triggers greater contributions by existing contributors; high-productivity contributors are especially active on the stronger platform.", "limitations": "The publisher page does not state a limitations section; this is therefore not stated by the publisher page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher research summary reports the two competing game-wiki setting and the finding that stronger competitive position is associated with higher activity, while the methods section describes 443 updates and the before/after event-study (RDiT) design. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-2e21-720c-ad5e-d6e0e4289c25" ], "corrections": [], "plain_english_summary": "A stronger platform competitive position is associated with higher activity, primarily through more contributors, which then triggers greater contributions by existing contributors; high-productivity contributors are especially active on the stronger platform. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4.5, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Quantitative quasi-experimental/event-study design resembling regression discontinuity in time: contributor activity is compared in four days before versus five days after exogenous game updates, with heterogeneous treatment effects by platform competitive position." }, { "name": "Sample", "score": "1/1", "note": "13 game-wiki communities on two competing platforms; the study hand-collected game updates and analyzes 443 distinct updates across games, focusing on volunteer contributors, activity, contributor counts, and productivity." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "openness-in-platform-ecosystems-innovation-strategies-for-complementary-products", "title": "Openness in platform ecosystems: Innovation strategies for complementary products", "category": "Customer behavior and adoption", "study_type": "Panel-data empirical study comparing four complementary-product innovation strategies (proprietary, outbound, inbound, and third-party) and their evolution over time; the publisher page reports performance outcomes across the strategies.", "citation": "Javier Cenamor, Johan Frishammar (2021). Openness in platform ecosystems: Innovation strategies for complementary products. Research Policy. https://doi.org/10.1016/j.respol.2020.104148.", "authors": [ "Javier Cenamor", "Johan Frishammar" ], "year": 2021, "journal": "Research Policy", "doi": "10.1016/j.respol.2020.104148", "doi_url": "https://doi.org/10.1016/j.respol.2020.104148", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0048733320302237", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0048733320302237", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What performance outcomes do alternative innovation and commercialization strategies for complementary products produce, and how do those outcomes evolve across a platform ecosystem's lifecycle?", "design": "Panel-data empirical study comparing four complementary-product innovation strategies (proprietary, outbound, inbound, and third-party) and their evolution over time; the publisher page reports performance outcomes across the strategies.", "sample_context": "Panel of 4,857 video games for seventh-generation video consoles in the United States; the context is platform ecosystems involving console sponsors and third-party game developers/publishers.", "findings": "Performance outcomes differ across co-existing innovation strategies. The publisher reports that platform sponsors have an active role in complementary products and that outbound and inbound collaboration may lead to high performance; appropriate strategy depends on platform lifecycle rather than a simple open/closed or sponsor/third-party choice.", "limitations": "The publisher page does not state a limitations section; this is therefore not stated by the publisher page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract states that the study examines four strategies and uses a panel of 4,857 US seventh-generation-console video games; its highlights say performance differs across co-existing strategies and that lifecycle affects competitive advantage. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc8-f09e-749e-b11e-d732125ab90b" ], "corrections": [], "plain_english_summary": "Performance outcomes differ across co-existing innovation strategies. The publisher reports that platform sponsors have an active role in complementary products and that outbound and inbound collaboration may lead to high performance; appropriate strategy depends on platform lifecycle rather than a simple open/closed or sponsor/third-party choice. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Panel-data empirical study comparing four complementary-product innovation strategies (proprietary, outbound, inbound, and third-party) and their evolution over time; the publisher page reports performance outcomes across the strategies." }, { "name": "Sample", "score": "1/1", "note": "Panel of 4,857 video games for seventh-generation video consoles in the United States; the context is platform ecosystems involving console sponsors and third-party game developers/publishers." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "platform-diffusion-at-temporary-gatherings-social-coordination-and-ecosystem-emergenc", "title": "Platform diffusion at temporary gatherings: Social coordination and ecosystem emergence", "category": "Customer behavior and adoption", "study_type": "Large-scale quantitative developer-platform-month panel study supported by qualitative research; platform adoption is identified from developers' software projects and analyzed around attendance at hackathons, with channels including sponsorship, soc", "citation": "Tommy Pan Fang, Andy Wu, David R. Clough (2021). Platform diffusion at temporary gatherings: Social coordination and ecosystem emergence. Strategic Management Journal. https://doi.org/10.1002/smj.3230.", "authors": [ "Tommy Pan Fang", "Andy Wu", "David R. Clough" ], "year": 2021, "journal": "Strategic Management Journal", "doi": "10.1002/smj.3230", "doi_url": "https://doi.org/10.1002/smj.3230", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3230", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3230", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Does attending a temporary gathering such as a hackathon affect software developers' platform choices, and through which social mechanisms does platform adoption diffuse among attendees?", "design": "Large-scale quantitative developer-platform-month panel study supported by qualitative research; platform adoption is identified from developers' software projects and analyzed around attendance at hackathons, with channels including sponsorship, social learning, knowledge exchange, and social coordination.", "sample_context": "1,302 software developers attending 167 hackathons; the main dataset is a developer-platform-month panel with 786,240 observations, covering January 2012\u2013November 2017 and platform use detected through platform-specific API keywords in public GitHub projects.", "findings": "Attending temporary hackathon gatherings serves as a social forum for platform diffusion: sponsorship, social learning, knowledge exchange, and social coordination help developers learn about and adopt platforms.", "limitations": "The publisher page does not state a limitations section; this is therefore not stated by the publisher page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher research summary explicitly describes a large-scale quantitative study of 1,302 developers and 167 hackathons supported by qualitative research, and frames hackathons as a forum for diffusion of platform adoption; the methods page reports 786,240 developer-platform-month observations. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-5090-726b-a5d5-d2d0fbc0a6ce" ], "corrections": [], "plain_english_summary": "Attending temporary hackathon gatherings serves as a social forum for platform diffusion: sponsorship, social learning, knowledge exchange, and social coordination help developers learn about and adopt platforms. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Large-scale quantitative developer-platform-month panel study supported by qualitative research; platform adoption is identified from developers' software projects and analyzed around attendance at hackathons, with channels including sponsorship, social learning, knowledge exchange, and social coordination." }, { "name": "Sample", "score": "1/1", "note": "1,302 software developers attending 167 hackathons; the main dataset is a developer-platform-month panel with 786,240 observations, covering January 2012\u2013November 2017 and platform use detected through platform-specific API keywords in public GitHub projects." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "b2b-purchase-engagement-examining-the-key-drivers-and-outcomes-in-professional-servic", "title": "B2B purchase engagement: Examining the key drivers and outcomes in professional services", "category": "B2B growth and sales", "study_type": "Cross-sectional survey analyzed with structural equation modeling.", "citation": "Munyaradzi W. Nyadzayo, Riza Casidy, Park Thaichon (2020). B2B purchase engagement: Examining the key drivers and outcomes in professional services. Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2019.11.007.", "authors": [ "Munyaradzi W. Nyadzayo", "Riza Casidy", "Park Thaichon" ], "year": 2020, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2019.11.007", "doi_url": "https://doi.org/10.1016/j.indmarman.2019.11.007", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850118307533", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0019850118307533", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What drives purchase engagement in B2B professional services, and what transactional and relational outcomes does it produce?", "design": "Cross-sectional survey analyzed with structural equation modeling.", "sample_context": "CEOs and/or owner-managers of small and medium-sized enterprises in Australia, in a B2B professional-services context; the publisher\u2019s data-collection section says 4,000 CEO/owner-manager email addresses were sourced from a professional database.", "findings": "Customization and loyalty to the account manager are salient drivers of purchase engagement. Engagement predicts consideration-set size, dependence and willingness to pay a premium; dependence mediates effects on consideration-set size and premium willingness to pay.", "limitations": "No dedicated limitations statement was visible in the fetched publisher preview; therefore publisher-stated limitations are not stated here.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The publisher abstract says the study uses structural equation modeling and a survey of Australian SME CEOs/owner-managers, and reports customization and account-manager loyalty as drivers plus three outcomes. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-6e52-7645-980e-869169f5bad1" ], "corrections": [], "plain_english_summary": "Customization and loyalty to the account manager are salient drivers of purchase engagement. Engagement predicts consideration-set size, dependence and willingness to pay a premium; dependence mediates effects on consideration-set size and premium willingness to pay. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-sectional survey analyzed with structural equation modeling." }, { "name": "Sample", "score": "1/1", "note": "CEOs and/or owner-managers of small and medium-sized enterprises in Australia, in a B2B professional-services context; the publisher\u2019s data-collection section says 4,000 CEO/owner-manager email addresses were sourced from a professional database." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-integrated-use-of-social-media-digital-and-traditional-communication-tools-in-the", "title": "The integrated use of social media, digital, and traditional communication tools in the B2B sales process of international SMEs", "category": "B2B growth and sales", "study_type": "Exploratory longitudinal, multi-country qualitative study using semi-structured interviews with knowledgeable informants, follow-up interviews and secondary-data triangulation; grounded-theory analysis.", "citation": "Sara Fraccastoro, Mika Gabrielsson, Ellen Bolman Pullins (2021). The integrated use of social media, digital, and traditional communication tools in the B2B sales process of international SMEs. International Business Review. https://doi.org/10.1016/j.ibusrev.2020.101776.", "authors": [ "Sara Fraccastoro", "Mika Gabrielsson", "Ellen Bolman Pullins" ], "year": 2021, "journal": "International Business Review", "doi": "10.1016/j.ibusrev.2020.101776", "doi_url": "https://doi.org/10.1016/j.ibusrev.2020.101776", "primary_url": "https://www.sciencedirect.com/science/article/pii/S0969593120301256", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0969593120301256", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do international B2B SMEs use social media, digital and traditional communication tools across the sales process, and how do these tools affect that process over time?", "design": "Exploratory longitudinal, multi-country qualitative study using semi-structured interviews with knowledgeable informants, follow-up interviews and secondary-data triangulation; grounded-theory analysis.", "sample_context": "International SMEs in service industries across Finland, Italy, Poland, Brazil and the United States; interviews involved sales directors, marketing managers, CEOs or the most knowledgeable available employee.", "findings": "Social media and digital tools are used jointly with traditional sales communication, blending the traditional selling steps into three main phases: identifying new opportunities, persuasion and relationship management; follow-up interviews reported increased social-media use.", "limitations": "The publisher text explicitly notes that small firm size limited the availability of diverse perspectives, so two interview rounds were judged sufficient.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The publisher\u2019s empirical-process table reports that the B2B sales process can be improved by social and digital tools, that use varies across phases and is joint with traditional tools, and that the model was confirmed in longitudinal follow-ups. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-c22b-74ba-8e84-cb2f667eae6b" ], "corrections": [], "plain_english_summary": "Social media and digital tools are used jointly with traditional sales communication, blending the traditional selling steps into three main phases: identifying new opportunities, persuasion and relationship management; follow-up interviews reported increased social-media use. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Exploratory longitudinal, multi-country qualitative study using semi-structured interviews with knowledgeable informants, follow-up interviews and secondary-data triangulation; grounded-theory analysis." }, { "name": "Sample", "score": "0.5/1", "note": "International SMEs in service industries across Finland, Italy, Poland, Brazil and the United States; interviews involved sales directors, marketing managers, CEOs or the most knowledgeable available employee." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effect-of-subscriptions-on-customer-engagement", "title": "The effect of subscriptions on customer engagement", "category": "Pricing and monetization", "study_type": "Quasi-experiment using propensity-score matching and difference-in-differences, supplemented by a lab experiment on perceived lock-in.", "citation": "Banggang Wu, Gengxuan Guo, Peng Luo (2024). The effect of subscriptions on customer engagement. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2024.114638.", "authors": [ "Banggang Wu", "Gengxuan Guo", "Peng Luo" ], "year": 2024, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2024.114638", "doi_url": "https://doi.org/10.1016/j.jbusres.2024.114638", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296324001425", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0148296324001425", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does joining an online-community subscription affect users\u2019 content consumption and content generation, and does perceived lock-in explain heterogeneous effects by prior engagement?", "design": "Quasi-experiment using propensity-score matching and difference-in-differences, supplemented by a lab experiment on perceived lock-in.", "sample_context": "Users of a leading mobile music community; the observational data span two months and compare subscribers with non-subscribers. The publisher page also reports a lab experiment.", "findings": "After accounting for self-selection, subscriptions produced large, persistent increases in content consumption and content generation (lasting at least a month); the effect was stronger for less-engaged users. Subscription increased perceived lock-in, which increased engagement intention.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher abstract says subscriptions increase both content consumption and generation through perceived lock-in, with a stronger positive effect for less-engaged users. The article preview describes a two-month mobile-music-community dataset, propensity-score matching, DID, and a lab experiment. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-9d63-7186-9654-71559e316c7e" ], "corrections": [], "plain_english_summary": "After accounting for self-selection, subscriptions produced large, persistent increases in content consumption and content generation (lasting at least a month); the effect was stronger for less-engaged users. Subscription increased perceived lock-in, which increased engagement intention. For your marketing: Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Quasi-experiment using propensity-score matching and difference-in-differences, supplemented by a lab experiment on perceived lock-in." }, { "name": "Sample", "score": "0.5/1", "note": "Users of a leading mobile music community; the observational data span two months and compare subscribers with non-subscribers. The publisher page also reports a lab experiment." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "improving-the-diagnosis-and-prediction-of-customer-churn-a-heterogeneous-hazard-model", "title": "Improving the diagnosis and prediction of customer churn: A heterogeneous hazard modeling approach", "category": "Acquisition and retention", "study_type": "Latent-class Weibull hazard model with time-varying covariates, allowing heterogeneity in baseline churn hazards and response parameters.", "citation": "Zainab Jamal, Randolph E. Bucklin (2006). Improving the diagnosis and prediction of customer churn: A heterogeneous hazard modeling approach. Journal of Interactive Marketing. https://doi.org/10.1002/dir.20064.", "authors": [ "Zainab Jamal", "Randolph E. Bucklin" ], "year": 2006, "journal": "Journal of Interactive Marketing", "doi": "10.1002/dir.20064", "doi_url": "https://doi.org/10.1002/dir.20064", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S1094996806700524", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S1094996806700524", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can a heterogeneous hazard model improve diagnosis and prediction of customer churn, and how are churn rates related to service experience, recovery, and payment equity?", "design": "Latent-class Weibull hazard model with time-varying covariates, allowing heterogeneity in baseline churn hazards and response parameters.", "sample_context": "Customer-level churn data from a continuous-service provider: a direct-to-home satellite television firm in a South American country.", "findings": "Adding heterogeneity significantly improves churn prediction. Churn is significantly linked to customer-service experience, failure-recovery efforts, and payment equity, with important differences across latent classes.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_basis": "The publisher abstract explicitly identifies the latent-class Weibull/time-varying-covariate approach, the South American direct-to-home satellite-TV setting, improved prediction from heterogeneity, and the significant service, recovery, and payment-equity links. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-87b0-70c9-82f2-d5af1147a42d" ], "corrections": [], "plain_english_summary": "Adding heterogeneity significantly improves churn prediction. Churn is significantly linked to customer-service experience, failure-recovery efforts, and payment equity, with important differences across latent classes. For your marketing: Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Latent-class Weibull hazard model with time-varying covariates, allowing heterogeneity in baseline churn hazards and response parameters." }, { "name": "Sample", "score": "0.5/1", "note": "Customer-level churn data from a continuous-service provider: a direct-to-home satellite television firm in a South American country." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "determinants-of-writing-positive-and-negative-electronic-word-of-mouth-empirical-evid", "title": "Determinants of writing positive and negative electronic word-of-mouth: Empirical evidence for two types of expectation confirmation", "category": "Customer behavior and adoption", "study_type": "Survey study extending the expectation-confirmation model; analysis of respondents who wrote hotel reviews on TripAdvisor.", "citation": "Kichan Nam, Jeff Baker, Norita Ahmad, Jahyun Goo (2020). Determinants of writing positive and negative electronic word-of-mouth: Empirical evidence for two types of expectation confirmation. Decision Support Systems. https://doi.org/10.1016/j.dss.2019.113168.", "authors": [ "Kichan Nam", "Jeff Baker", "Norita Ahmad", "Jahyun Goo" ], "year": 2020, "journal": "Decision Support Systems", "doi": "10.1016/j.dss.2019.113168", "doi_url": "https://doi.org/10.1016/j.dss.2019.113168", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923619301976", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923619301976", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What influences consumers to write positive versus negative eWOM, and do the antecedents differ by eWOM valence?", "design": "Survey study extending the expectation-confirmation model; analysis of respondents who wrote hotel reviews on TripAdvisor.", "sample_context": "438 TripAdvisor hotel reviewers, as reported in the publisher highlights and abstract.", "findings": "Two distinct forms of expectation confirmation, satisfaction, and personal characteristics influence eWOM writing; antecedents differ for negative versus positive eWOM.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher highlights say the study analyzes survey data from 438 TripAdvisor hotel reviewers and finds differing antecedents for negative and positive eWOM; the abstract states that two types of expectation confirmation influence writing. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-f38a-72bc-b689-de0a8ef560a2" ], "corrections": [], "plain_english_summary": "Two distinct forms of expectation confirmation, satisfaction, and personal characteristics influence eWOM writing; antecedents differ for negative versus positive eWOM. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Survey study extending the expectation-confirmation model; analysis of respondents who wrote hotel reviews on TripAdvisor." }, { "name": "Sample", "score": "1/1", "note": "438 TripAdvisor hotel reviewers, as reported in the publisher highlights and abstract." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "expertise-makes-perfect-how-the-variance-of-a-reviewer-s-historical-ratings-influence", "title": "Expertise Makes Perfect: How the Variance of a Reviewer's Historical Ratings Influences the Persuasiveness of Online Reviews", "category": "Reviews and reputation", "study_type": "Five experiments testing the effect of historical-rating variance on review persuasiveness, its mechanism, generalizability, and boundary conditions; the publisher page describes perceived expertise as an underlying process.", "citation": "Xiaoyue Wu, Liyin Jin, Qian Xu (2021). Expertise Makes Perfect: How the Variance of a Reviewer's Historical Ratings Influences the Persuasiveness of Online Reviews. Journal of Retailing. https://doi.org/10.1016/j.jretai.2020.05.006.", "authors": [ "Xiaoyue Wu", "Liyin Jin", "Qian Xu" ], "year": 2021, "journal": "Journal of Retailing", "doi": "10.1016/j.jretai.2020.05.006", "doi_url": "https://doi.org/10.1016/j.jretai.2020.05.006", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435920300270", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435920300270", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does the variance of a reviewer\u2019s historical ratings affect consumers\u2019 acceptance of that reviewer\u2019s online recommendations, and what role does perceived expertise play?", "design": "Five experiments testing the effect of historical-rating variance on review persuasiveness, its mechanism, generalizability, and boundary conditions; the publisher page describes perceived expertise as an underlying process.", "sample_context": "Consumers/participants evaluating online-review recommendations across product-review contexts in five experiments; the publisher page describes studies testing the effect, mediation by perceived expertise, another product category, and boundary conditions.", "findings": "Consumers are more willing to accept a reviewer\u2019s recommendation when the reviewer\u2019s historical ratings in a product domain show greater variance; the publisher reports consistent support across five experiments.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher highlights state that reviewer-rating variance affects acceptance of recommendations, while the abstract says five experiments consistently support the hypothesis and underlying process. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-1930-7109-8ace-5495b6633866" ], "corrections": [], "plain_english_summary": "Consumers are more willing to accept a reviewer\u2019s recommendation when the reviewer\u2019s historical ratings in a product domain show greater variance; the publisher reports consistent support across five experiments. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Five experiments testing the effect of historical-rating variance on review persuasiveness, its mechanism, generalizability, and boundary conditions; the publisher page describes perceived expertise as an underlying process." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers/participants evaluating online-review recommendations across product-review contexts in five experiments; the publisher page describes studies testing the effect, mediation by perceived expertise, another product category, and boundary conditions." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-recent-versus-the-out-dated-an-experimental-examination-of-the-time-variant-effec", "title": "The Recent versus The Out-Dated: An Experimental Examination of the Time-Variant Effects of Online Consumer Reviews", "category": "Reviews and reputation", "study_type": "Four controlled experiments comparing the effects of recent versus outdated online reviews under near- versus distant-future purchase timeframes, including different review valences.", "citation": "Liyin Jin, Bingyan Hu, Yanqun He (2014). The Recent versus The Out-Dated: An Experimental Examination of the Time-Variant Effects of Online Consumer Reviews. Journal of Retailing. https://doi.org/10.1016/j.jretai.2014.05.002.", "authors": [ "Liyin Jin", "Bingyan Hu", "Yanqun He" ], "year": 2014, "journal": "Journal of Retailing", "doi": "10.1016/j.jretai.2014.05.002", "doi_url": "https://doi.org/10.1016/j.jretai.2014.05.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435914000311", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0022435914000311", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When and why do recent versus outdated online consumer reviews shift consumers\u2019 preferences differently?", "design": "Four controlled experiments comparing the effects of recent versus outdated online reviews under near- versus distant-future purchase timeframes, including different review valences.", "sample_context": "Consumers making purchase decisions after exposure to online reviews posted at different times; four experiments, as reported in the publisher abstract and section headings.", "findings": "Recent reviews are more influential for near-future decisions, whereas outdated reviews become relatively more influential for distant-future decisions; temporal/construal fit drives engagement and influence on preferences.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher highlights and abstract report four experiments and the near-/distant-future reversal, attributing it to fit between review construal level and the consumer\u2019s decision timeframe. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fc9-dd89-73b9-b197-8ffaf98fae6d" ], "corrections": [], "plain_english_summary": "Recent reviews are more influential for near-future decisions, whereas outdated reviews become relatively more influential for distant-future decisions; temporal/construal fit drives engagement and influence on preferences. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Four controlled experiments comparing the effects of recent versus outdated online reviews under near- versus distant-future purchase timeframes, including different review valences." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers making purchase decisions after exposure to online reviews posted at different times; four experiments, as reported in the publisher abstract and section headings." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "digitizing-opportunity-entrepreneurship-in-the-age-of-platforms", "title": "Digitizing Opportunity: Entrepreneurship in the Age of Platforms", "category": "Customer behavior and adoption", "study_type": "Quasi-experimental study exploiting the staggered entry of Craigslist across metropolitan markets, using Business Dynamics Statistics and supplemental online survey evidence from entrepreneurs.", "citation": "Daehyun Kim, Yongwook Paik, Namil Kim (2025). Digitizing Opportunity: Entrepreneurship in the Age of Platforms. Strategic Entrepreneurship Journal. https://doi.org/10.1002/sej.1538.", "authors": [ "Daehyun Kim", "Yongwook Paik", "Namil Kim" ], "year": 2025, "journal": "Strategic Entrepreneurship Journal", "doi": "10.1002/sej.1538", "doi_url": "https://doi.org/10.1002/sej.1538", "primary_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/sej.1538", "accessible_url": "https://sms.onlinelibrary.wiley.com/doi/full/10.1002/sej.1538", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do digital peer-to-peer marketplaces reduce market-access barriers and increase entrepreneurial activity, and which people, communities, and venture types benefit?", "design": "Quasi-experimental study exploiting the staggered entry of Craigslist across metropolitan markets, using Business Dynamics Statistics and supplemental online survey evidence from entrepreneurs.", "sample_context": "U.S. metropolitan statistical areas and county-level income/community data; the primary outcome is new firms per 100,000 population per MSA-year. A supplemental survey initially covered 996 U.S. residents with current or past entrepreneurial experience.", "findings": "Craigslist entry increases local entrepreneurial activity, especially in low-income regions; lower-income, Black, and immigrant individuals are more likely to create ventures afterward. Post-entry firms are smaller and mainly B2C rather than B2B.", "limitations": "The authors explicitly caution that findings may not generalize to other platforms or entrepreneurs simultaneously using multiple platforms, and that the study does not capture all newer digital technologies/platform forms.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher's Research Summary reports the staggered-Craigslist design and the increases in local activity and disadvantaged-group entry; the data section identifies Business Dynamics Statistics and MSA-year new-firm counts, while the limitations section warns against generalizing across platforms. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-62c8-778a-be0f-2e6025af5a05" ], "corrections": [], "plain_english_summary": "Craigslist entry increases local entrepreneurial activity, especially in low-income regions; lower-income, Black, and immigrant individuals are more likely to create ventures afterward. Post-entry firms are smaller and mainly B2C rather than B2B. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Quasi-experimental study exploiting the staggered entry of Craigslist across metropolitan markets, using Business Dynamics Statistics and supplemental online survey evidence from entrepreneurs." }, { "name": "Sample", "score": "1/1", "note": "U.S. metropolitan statistical areas and county-level income/community data; the primary outcome is new firms per 100,000 population per MSA-year. A supplemental survey initially covered 996 U.S. residents with current or past entrepreneurial experience." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "consumer-adoption-of-net-enabled-infomediaries-theoretical-explanations-and-an-empiri", "title": "Consumer Adoption of Net-Enabled Infomediaries: Theoretical Explanations and an Empirical Test", "category": "Paid media and measurement", "study_type": "Empirical test of a conceptual model using data from an online questionnaire; the publisher page says the model was tested with online shoppers.", "citation": "Jai-Yeol Son, Sung S. Kim, Frederick J. Riggins (2006). Consumer Adoption of Net-Enabled Infomediaries: Theoretical Explanations and an Empirical Test. Journal of the Association for Information Systems. https://doi.org/10.17705/1jais.00094.", "authors": [ "Jai-Yeol Son", "Sung S. Kim", "Frederick J. Riggins" ], "year": 2006, "journal": "Journal of the Association for Information Systems", "doi": "10.17705/1jais.00094", "doi_url": "https://doi.org/10.17705/1jais.00094", "primary_url": "https://aisel.aisnet.org/jais/vol7/iss7/18/", "accessible_url": "https://aisel.aisnet.org/jais/vol7/iss7/18/", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Why and how do online shoppers adopt a new infomediary website, and how do the infomediary's utilitarian benefits and the shopper's transaction environment shape adoption intention?", "design": "Empirical test of a conceptual model using data from an online questionnaire; the publisher page says the model was tested with online shoppers.", "sample_context": "367 online shoppers evaluating adoption/use of a net-enabled infomediary website that searches and compares online retailers.", "findings": "Intention to use the infomediary was a function of perceived efficiency, perceived effectiveness, and perceived ease of use. Shoppers low in asset specificity and high in uncertainty appreciated the infomediary benefits more than other shoppers.", "limitations": "Not stated on the publisher/journal article page fetched in this run.", "founder_use": "Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "The journal page describes the study as an empirical test based on an online questionnaire of 367 online shoppers and reports that adoption intention depended on the two utilitarian benefits and perceived ease of use; it also reports stronger appreciation among shoppers low in asset specificity and high in uncertainty. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-340a-7439-bcf1-2212c36d73ca" ], "corrections": [], "plain_english_summary": "Intention to use the infomediary was a function of perceived efficiency, perceived effectiveness, and perceived ease of use. Shoppers low in asset specificity and high in uncertainty appreciated the infomediary benefits more than other shoppers. For your marketing: Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical test of a conceptual model using data from an online questionnaire; the publisher page says the model was tested with online shoppers." }, { "name": "Sample", "score": "1/1", "note": "367 online shoppers evaluating adoption/use of a net-enabled infomediary website that searches and compares online retailers." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-trust-based-consumer-decision-making-model-in-electronic-commerce-the-role-of-trust", "title": "A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents", "category": "Customer behavior and adoption", "study_type": "Structural-equation-model test of a trust-based consumer decision model using Internet purchasing-behavior data collected through a Web survey.", "citation": "Dan J. Kim, Donald L. Ferrin, H. Raghav Rao (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems. https://doi.org/10.1016/j.dss.2007.07.001.", "authors": [ "Dan J. Kim", "Donald L. Ferrin", "H. Raghav Rao" ], "year": 2008, "journal": "Decision Support Systems", "doi": "10.1016/j.dss.2007.07.001", "doi_url": "https://doi.org/10.1016/j.dss.2007.07.001", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923607001005", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923607001005", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What roles do trust and perceived risk play in B2C online purchasing decisions, and what antecedents affect a consumer's trust and risk toward an online transaction?", "design": "Structural-equation-model test of a trust-based consumer decision model using Internet purchasing-behavior data collected through a Web survey.", "sample_context": "Internet consumers making or considering a purchase from a given B2C Internet site; the publisher abstract identifies the Web-survey consumer context but does not state the sample size on the fetched page.", "findings": "Trust and perceived risk strongly affected purchasing decisions. Disposition to trust, reputation, privacy concerns, security concerns, website information quality, and company reputation strongly affected trust; a third-party seal did not strongly influence trust.", "limitations": "Not stated on the publisher article-preview page fetched in this run (the page indicates that the full article has a limitations section, but does not expose its contents).", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The ScienceDirect abstract says the authors test the model with structural equation modeling on Web-survey purchasing data and reports strong effects of trust and perceived risk on purchase decisions, while noting that a third-party seal did not strongly influence trust. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-8615-74f9-91ea-b2a63aa9de97" ], "corrections": [], "plain_english_summary": "Trust and perceived risk strongly affected purchasing decisions. Disposition to trust, reputation, privacy concerns, security concerns, website information quality, and company reputation strongly affected trust; a third-party seal did not strongly influence trust. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Structural-equation-model test of a trust-based consumer decision model using Internet purchasing-behavior data collected through a Web survey." }, { "name": "Sample", "score": "0.5/1", "note": "Internet consumers making or considering a purchase from a given B2C Internet site; the publisher abstract identifies the Web-survey consumer context but does not state the sample size on the fetched page." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "predicting-consumer-decisions-to-adopt-mobile-commerce-cross-country-empirical-examin", "title": "Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia", "category": "Customer behavior and adoption", "study_type": "Cross-country quantitative study extending TAM and DOI with trust, cost, social influence, variety of services, and controls; hierarchical regression tested the proposed model.", "citation": "Alain Yee-Loong Chong, Felix T.S. Chan, Keng-Boon Ooi (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems. https://doi.org/10.1016/j.dss.2011.12.001.", "authors": [ "Alain Yee-Loong Chong", "Felix T.S. Chan", "Keng-Boon Ooi" ], "year": 2012, "journal": "Decision Support Systems", "doi": "10.1016/j.dss.2011.12.001", "doi_url": "https://doi.org/10.1016/j.dss.2011.12.001", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923611002302", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0167923611002302", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which factors predict consumer intention to adopt mobile commerce, and do the predictors differ between China and Malaysia's cultural settings?", "design": "Cross-country quantitative study extending TAM and DOI with trust, cost, social influence, variety of services, and controls; hierarchical regression tested the proposed model.", "sample_context": "394 consumers: 172 Malaysian consumers and 222 Chinese consumers, in a mobile-commerce adoption context.", "findings": "For Malaysian consumers, age, trust, cost, social influence, and variety of services predicted adoption decisions; for Chinese consumers, trust, cost, and social influence predicted adoption. The publisher highlights that traditional TAM variables alone were unable to predict m-commerce adoption and that culture mattered.", "limitations": "Not stated on the publisher article-preview page fetched in this run.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract reports the two samples (172 Malaysian and 222 Chinese consumers), hierarchical regression, the country-specific predictors, and the conclusion that extending TAM/DOI and accounting for cultural factors is necessary. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-c0e8-7564-9450-ada65da279a6" ], "corrections": [], "plain_english_summary": "For Malaysian consumers, age, trust, cost, social influence, and variety of services predicted adoption decisions; for Chinese consumers, trust, cost, and social influence predicted adoption. The publisher highlights that traditional TAM variables alone were unable to predict m-commerce adoption and that culture mattered. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Cross-country quantitative study extending TAM and DOI with trust, cost, social influence, variety of services, and controls; hierarchical regression tested the proposed model." }, { "name": "Sample", "score": "1/1", "note": "394 consumers: 172 Malaysian consumers and 222 Chinese consumers, in a mobile-commerce adoption context." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "e-wom-from-e-commerce-websites-and-social-media-which-will-consumers-adopt", "title": "E-WOM from e-commerce websites and social media: Which will consumers adopt?", "category": "Paid media and measurement", "study_type": "Empirical questionnaire-survey analysis of a conceptual model based on cognitive-cost theory; the publisher page says the questionnaire had demographic items and 30 construct items.", "citation": "Qiang Yan, Shuang Wu, Lingli Wang, Pengfei Wu, Hejie Chen, Guohong Wei (2016). E-WOM from e-commerce websites and social media: Which will consumers adopt?. Electronic Commerce Research and Applications. https://doi.org/10.1016/j.elerap.2016.03.004.", "authors": [ "Qiang Yan", "Shuang Wu", "Lingli Wang", "Pengfei Wu", "Hejie Chen", "Guohong Wei" ], "year": 2016, "journal": "Electronic Commerce Research and Applications", "doi": "10.1016/j.elerap.2016.03.004", "doi_url": "https://doi.org/10.1016/j.elerap.2016.03.004", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S1567422316300175", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S1567422316300175", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When consumers encounter eWOM from e-commerce websites and social media simultaneously, how do they choose/adopt the two sources, and how do usefulness, credibility, cognition, and involvement shape that process?", "design": "Empirical questionnaire-survey analysis of a conceptual model based on cognitive-cost theory; the publisher page says the questionnaire had demographic items and 30 construct items.", "sample_context": "Consumers exposed to eWOM from e-commerce websites (EC-eWOM) and social media (SM-eWOM) in a social-commerce/online-shopping context; the fetched publisher page does not state the respondent count.", "findings": "EC-eWOM usefulness and credibility positively influenced EC-eWOM adoption but negatively influenced SM-eWOM adoption. EC-eWOM adoption negatively affected SM-eWOM adoption and mediated usefulness/credibility effects; cognitive level and involvement moderated effects.", "limitations": "The publisher page says conclusions and research limitations are outlined in Section 5, but does not display the specific limitations in the fetched article preview; therefore specific limitations are not stated here.", "founder_use": "Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "The ScienceDirect page labels the work a research article, identifies the six authors and DOI, describes questionnaire data, and reports the central result that usefulness and credibility increase EC-eWOM adoption while reducing SM-eWOM adoption, with EC-eWOM adoption mediating those relationships. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-d3b8-705c-b485-7aab8ece6de9" ], "corrections": [], "plain_english_summary": "EC-eWOM usefulness and credibility positively influenced EC-eWOM adoption but negatively influenced SM-eWOM adoption. EC-eWOM adoption negatively affected SM-eWOM adoption and mediated usefulness/credibility effects; cognitive level and involvement moderated effects. For your marketing: Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical questionnaire-survey analysis of a conceptual model based on cognitive-cost theory; the publisher page says the questionnaire had demographic items and 30 construct items." }, { "name": "Sample", "score": "0.5/1", "note": "Consumers exposed to eWOM from e-commerce websites (EC-eWOM) and social media (SM-eWOM) in a social-commerce/online-shopping context; the fetched publisher page does not state the respondent count." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-moderating-effects-of-gender-on-e-commerce-systems-adoption-factors-an-empirical", "title": "The moderating effects of gender on e-commerce systems adoption factors: An empirical investigation", "category": "Customer behavior and adoption", "study_type": "Empirical online-survey study testing social norms, perceived enjoyment, intention to adopt an e-commerce system, and gender moderation using theory of reasoned action and self-determination theory; students navigated Amazon in an Internet-connected ", "citation": "Yujong Hwang (2010). The moderating effects of gender on e-commerce systems adoption factors: An empirical investigation. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2010.07.002.", "authors": [ "Yujong Hwang" ], "year": 2010, "journal": "Computers in Human Behavior", "doi": "10.1016/j.chb.2010.07.002", "doi_url": "https://doi.org/10.1016/j.chb.2010.07.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S0747563210001986", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S0747563210001986", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do social norms and perceived enjoyment affect e-commerce-system adoption intention, and do gender differences moderate those effects?", "design": "Empirical online-survey study testing social norms, perceived enjoyment, intention to adopt an e-commerce system, and gender moderation using theory of reasoned action and self-determination theory; students navigated Amazon in an Internet-connected classroom.", "sample_context": "322 undergraduate business students from a northern U.S. university; participants were approached in an introductory MIS course, used individual PCs, and were asked to navigate Amazon and go through purchasing a book.", "findings": "The influence of social norms on adoption intention was stronger for women, whereas the influence of enjoyment was stronger for men.", "limitations": "The publisher page explicitly identifies a Section 7 titled 'limitations,' but the fetched article preview does not expose the section's substantive text; specific limitations are therefore not stated here.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The ScienceDirect abstract reports n=322 and the two key moderation results (stronger social-norm influence in the female group and stronger enjoyment influence in the male group); the methodology preview identifies undergraduate MIS students navigating Amazon in an Internet classroom. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-e53e-730c-b277-b470b47bcb39" ], "corrections": [], "plain_english_summary": "The influence of social norms on adoption intention was stronger for women, whereas the influence of enjoyment was stronger for men. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical online-survey study testing social norms, perceived enjoyment, intention to adopt an e-commerce system, and gender moderation using theory of reasoned action and self-determination theory; students navigated Amazon in an Internet-connected classroom." }, { "name": "Sample", "score": "1/1", "note": "322 undergraduate business students from a northern U.S. university; participants were approached in an introductory MIS course, used individual PCs, and were asked to navigate Amazon and go through purchasing a book." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "marketing-s-profit-impact-quantifying-online-and-off-line-funnel-progression", "title": "Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression", "category": "Customer behavior and adoption", "study_type": "Econometric modeling of marketing communication effects on online and offline funnel metrics, followed by a field experiment reallocating marketing budgets.", "citation": "Thorsten Wiesel, Koen Pauwels, Joep Arts (2011). Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression. Marketing Science. https://doi.org/10.1287/mksc.1100.0612.", "authors": [ "Thorsten Wiesel", "Koen Pauwels", "Joep Arts" ], "year": 2011, "journal": "Marketing Science", "doi": "10.1287/mksc.1100.0612", "doi_url": "https://doi.org/10.1287/mksc.1100.0612", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1100.0612", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mksc.1100.0612", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "What are the effects of marketing communications on online/offline purchase-funnel metrics, and what are the magnitude and timing of profit effects from firm- versus customer-initiated contacts?", "design": "Econometric modeling of marketing communication effects on online and offline funnel metrics, followed by a field experiment reallocating marketing budgets.", "sample_context": "Inofec, a small-to-medium-sized B2B enterprise; outcomes include website visits, online/offline information activity, quote requests, and purchases, with firm- and customer-initiated contacts compared across channels.", "findings": "The study found extensive cross-channel effects, direct effects on early and later funnel stages, and substantially higher profit impact for online customer-initiated contacts than offline firm-initiated contacts. A budget-shifting field experiment produced net profit increases 14 times larger than the status-quo allocation.", "limitations": "Not stated on the publisher article page's abstract; the publisher describes one B2B SME context, so generalizability beyond that setting is not established by the page (carefully marked interpretive limitation).", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract identifies Inofec as a B2B SME and reports cross-channel effects, direct effects across funnel stages, higher profit impact from online customer-initiated contacts, and a field-experiment profit increase 14 times larger than the status quo. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-5551-71db-88ed-1901c4bf11ce" ], "corrections": [], "plain_english_summary": "The study found extensive cross-channel effects, direct effects on early and later funnel stages, and substantially higher profit impact for online customer-initiated contacts than offline firm-initiated contacts. A budget-shifting field experiment produced net profit increases 14 times larger than the status-quo allocation. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Econometric modeling of marketing communication effects on online and offline funnel metrics, followed by a field experiment reallocating marketing budgets." }, { "name": "Sample", "score": "0.5/1", "note": "Inofec, a small-to-medium-sized B2B enterprise; outcomes include website visits, online/offline information activity, quote requests, and purchases, with firm- and customer-initiated contacts compared across channels." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "measuring-switching-costs-and-the-determinants-of-customer-retention-in-internet-enab", "title": "Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry", "category": "Acquisition and retention", "study_type": "Empirical implementation of a random-utility approach to measure switching costs and brand loyalty, followed by analysis of how usage, service design, and firm and individual characteristics relate to switching and retention.", "citation": "Pei-Yu (Sharon) Chen, Lorin M. Hitt (2002). Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry. Information Systems Research. https://doi.org/10.1287/isre.13.3.255.78.", "authors": [ "Pei-Yu (Sharon) Chen", "Lorin M. Hitt" ], "year": 2002, "journal": "Information Systems Research", "doi": "10.1287/isre.13.3.255.78", "doi_url": "https://doi.org/10.1287/isre.13.3.255.78", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.13.3.255.78", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.13.3.255.78", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How large are switching costs and brand loyalty for online service providers, and which usage, service-design, firm, and individual factors determine switching and retention?", "design": "Empirical implementation of a random-utility approach to measure switching costs and brand loyalty, followed by analysis of how usage, service design, and firm and individual characteristics relate to switching and retention.", "sample_context": "The online brokerage industry; the publisher page reports data from that industry and evaluates systems usage, systems quality, product-line breadth and quality, and customer demographics.", "findings": "Measured switching costs varied substantially (up to a factor of two). Demographics had little effect, while systems usage and quality were associated with reduced switching; product-line breadth and quality could reduce switching and attrition.", "limitations": "Not stated on the publisher article page's abstract; the page identifies online brokerage as the empirical context, so transferability to other Internet-enabled businesses is not established there (scope caveat).", "founder_use": "Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_basis": "The publisher abstract says the authors implement a random-utility approach using online-brokerage data and find up to twofold variation in switching costs, little demographic effect, and reduced switching associated with usage, systems quality, and firm product breadth/quality. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fca-fbf8-75b8-a9fd-8ea39235a81f" ], "corrections": [], "plain_english_summary": "Measured switching costs varied substantially (up to a factor of two). Demographics had little effect, while systems usage and quality were associated with reduced switching; product-line breadth and quality could reduce switching and attrition. For your marketing: Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical implementation of a random-utility approach to measure switching costs and brand loyalty, followed by analysis of how usage, service design, and firm and individual characteristics relate to switching and retention." }, { "name": "Sample", "score": "0.5/1", "note": "The online brokerage industry; the publisher page reports data from that industry and evaluates systems usage, systems quality, product-line breadth and quality, and customer demographics." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-new-product-growth-for-model-consumer-durables", "title": "A New Product Growth for Model Consumer Durables", "category": "Customer behavior and adoption", "study_type": "Development and empirical testing of a new-product growth model against historical sales data, separating innovative and imitative purchase behavior; the model is also used for long-range forecasting.", "citation": "Frank M. Bass (1969). A New Product Growth for Model Consumer Durables. Management Science. https://doi.org/10.1287/mnsc.15.5.215.", "authors": [ "Frank M. Bass" ], "year": 1969, "journal": "Management Science", "doi": "10.1287/mnsc.15.5.215", "doi_url": "https://doi.org/10.1287/mnsc.15.5.215", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.15.5.215", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.15.5.215", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can the timing of consumers' initial purchases of new durable products be modeled from prior buyers, with innovation and imitation providing the behavioral rationale?", "design": "Development and empirical testing of a new-product growth model against historical sales data, separating innovative and imitative purchase behavior; the model is also used for long-range forecasting.", "sample_context": "Historical data for eleven consumer durables, with a long-range forecast specifically developed for color television sets.", "findings": "The model produced good predictions of the sales peak and its timing when applied to historical data, and provided a long-range color-television sales forecast.", "limitations": "Not stated on the publisher article page's abstract; the reported empirical test concerns eleven consumer durables and the forecast example is color television, so broader applicability is not established by that page (scope caveat).", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract states that the model was tested empirically on eleven consumer durables, assumes initial-purchase timing relates to previous buyers, and yielded good predictions of both sales-peak level and timing. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-21f0-71eb-abde-ec582e7dd74b" ], "corrections": [], "plain_english_summary": "The model produced good predictions of the sales peak and its timing when applied to historical data, and provided a long-range color-television sales forecast. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Development and empirical testing of a new-product growth model against historical sales data, separating innovative and imitative purchase behavior; the model is also used for long-range forecasting." }, { "name": "Sample", "score": "0.5/1", "note": "Historical data for eleven consumer durables, with a long-range forecast specifically developed for color television sets." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "consumer-acceptance-and-use-of-information-technology-extending-the-unified-theory-of", "title": "Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology 1", "category": "Customer behavior and adoption", "study_type": "Two-stage online survey: technology-use data were collected four months after the first survey; the study empirically tests the proposed consumer-context UTAUT2 model.", "citation": "Viswanath Venkatesh, James Y. L. Thong, Xin Xu (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology 1. MIS Quarterly. https://doi.org/10.2307/41410412.", "authors": [ "Viswanath Venkatesh", "James Y. L. Thong", "Xin Xu" ], "year": 2012, "journal": "MIS Quarterly", "doi": "10.2307/41410412", "doi_url": "https://doi.org/10.2307/41410412", "primary_url": "https://misq.umn.edu/misq/article-abstract/36/1/157/1470/Consumer-Acceptance-and-Use-of-Information", "accessible_url": "https://misq.umn.edu/misq/article-abstract/36/1/157/1470/Consumer-Acceptance-and-Use-of-Information", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How can UTAUT be extended to explain consumers' acceptance and use of information technology, including the roles of hedonic motivation, price value, habit, and individual differences?", "design": "Two-stage online survey: technology-use data were collected four months after the first survey; the study empirically tests the proposed consumer-context UTAUT2 model.", "sample_context": "1,512 mobile Internet consumers; the publisher abstract identifies the context as consumer acceptance and use of mobile Internet technology.", "findings": "Adding hedonic motivation, price value, and habit to UTAUT substantially increased explained variance: behavioral intention from 56% to 74% and technology use from 40% to 52%; age, gender, and experience were modeled as moderators.", "limitations": "Not stated on the fetched publisher article page/abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract says the article extends UTAUT to a consumer context, adds hedonic motivation, price value, and habit, and reports results from a two-stage online survey of 1,512 mobile Internet consumers with use measured four months later; it reports the 56%-to-74% and 40%-to-52% improvements. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-71f8-755d-a37a-7f3f10e94db4" ], "corrections": [], "plain_english_summary": "Adding hedonic motivation, price value, and habit to UTAUT substantially increased explained variance: behavioral intention from 56% to 74% and technology use from 40% to 52%; age, gender, and experience were modeled as moderators. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Two-stage online survey: technology-use data were collected four months after the first survey; the study empirically tests the proposed consumer-context UTAUT2 model." }, { "name": "Sample", "score": "1/1", "note": "1,512 mobile Internet consumers; the publisher abstract identifies the context as consumer acceptance and use of mobile Internet technology." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "how-users-drive-value-in-two-sided-markets-platform-designs-that-matter", "title": "How Users Drive Value in Two-Sided Markets: Platform Designs That Matter", "category": "Customer behavior and adoption", "study_type": "Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus s", "citation": "Zhou Zhou, Lingling Zhang, Marshall Van Alstyne (2024). How Users Drive Value in Two-Sided Markets: Platform Designs That Matter. MIS Quarterly. https://doi.org/10.25300/MISQ/2023/17012.", "authors": [ "Zhou Zhou", "Lingling Zhang", "Marshall Van Alstyne" ], "year": 2024, "journal": "MIS Quarterly", "doi": "10.25300/MISQ/2023/17012", "doi_url": "https://doi.org/10.25300/MISQ/2023/17012", "primary_url": "https://misq.umn.edu/misq/article/48/1/1/2274/How-Users-Drive-Value-in-Two-Sided-Markets", "accessible_url": "https://misq.umn.edu/misq/article/48/1/1/2274/How-Users-Drive-Value-in-Two-Sided-Markets", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "When is a user-growth strategy effective, and how do users drive value in a two-sided market?", "design": "Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus search goods.", "sample_context": "Groupon's largest 108 markets from January through December 2012, with LivingSocial used to control for competition; the publisher page also reports a category-classification survey of 818 respondents covering 78 categories.", "findings": "Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak.", "limitations": "Not stated on the fetched publisher article page; the page reports robustness analyses but does not present a limitations statement in the visible article text.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher article states that fast user growth does not necessarily imply user stickiness, develops a dynamic network-effects/CLV2 model, and says: 'Using Groupon data, we verify our insights.' Its empirical-setting section specifies 108 Groupon markets observed from January to December 2012 and the page reports an 818-respondent survey for category classification. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-999e-7244-9233-243312f040db" ], "corrections": [], "plain_english_summary": "Cross-period same-side network effects contribute to user stickiness, while within-period cross-side effects persist conditional on stickiness. Using Groupon data, the authors verify the model and identify platform-design choices that can enhance stickiness when cross-period same-side effects are weak. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Dynamic model of within-period and cross-period network effects and a two-sided customer-lifetime-value model, estimated and tested with platform panel data; the article also uses an online survey to classify product categories as experience versus search goods." }, { "name": "Sample", "score": "1/1", "note": "Groupon's largest 108 markets from January through December 2012, with LivingSocial used to control for competition; the publisher page also reports a category-classification survey of 818 respondents covering 78 categories." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "separate-versus-joint-evaluation-the-roles-of-evaluation-mode-and-construal-level-in", "title": "Separate Versus Joint Evaluation: The Roles of Evaluation Mode and Construal Level in Technology Adoption", "category": "Customer behavior and adoption", "study_type": "Two complementary participant studies (N=272 and N=112): Study 1 was conducted in two natural settings, while Study 2 randomly assigned participants to manipulated joint-versus-separate evaluation modes.", "citation": "Candy K. Y. Ho, Weiling Ke, Hefu Liu, Patrick Y. K. Chau (2020). Separate Versus Joint Evaluation: The Roles of Evaluation Mode and Construal Level in Technology Adoption. MIS Quarterly. https://doi.org/10.25300/MISQ/2020/14246.", "authors": [ "Candy K. Y. Ho", "Weiling Ke", "Hefu Liu", "Patrick Y. K. Chau" ], "year": 2020, "journal": "MIS Quarterly", "doi": "10.25300/MISQ/2020/14246", "doi_url": "https://doi.org/10.25300/MISQ/2020/14246", "primary_url": "https://misq.umn.edu/misq/article-abstract/44/2/725/450/Separate-Versus-Joint-Evaluation-The-Roles-of?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article/44/2/725/450/Separate-Versus-Joint-Evaluation-The-Roles-of", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do joint versus separate evaluation contexts interact with construal level and technology factors (perceived ease of use and perceived usefulness) to influence technology-adoption decisions?", "design": "Two complementary participant studies (N=272 and N=112): Study 1 was conducted in two natural settings, while Study 2 randomly assigned participants to manipulated joint-versus-separate evaluation modes.", "sample_context": "Participants evaluated two new e-learning systems, either jointly (JE) or separately (SE); the publisher page reports N=272 and N=112 for the two studies.", "findings": "In joint evaluation, higher construal level strengthened the effect of perceived ease of use but weakened perceived usefulness's effect on adoption; in separate evaluation these effects reversed. Thus, simply changing presentation mode can reverse technology choices and preferences.", "limitations": "Not stated on the fetched publisher article page/abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract reports two studies (N=272 and N=112) involving two new e-learning systems, with natural-setting and randomized-mode designs, and explicitly reports the reversed perceived-ease-of-use/perceived-usefulness effects across joint and separate evaluation. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-85b2-745e-8f2d-71b38ac8e03a" ], "corrections": [], "plain_english_summary": "In joint evaluation, higher construal level strengthened the effect of perceived ease of use but weakened perceived usefulness's effect on adoption; in separate evaluation these effects reversed. Thus, simply changing presentation mode can reverse technology choices and preferences. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Two complementary participant studies (N=272 and N=112): Study 1 was conducted in two natural settings, while Study 2 randomly assigned participants to manipulated joint-versus-separate evaluation modes." }, { "name": "Sample", "score": "1/1", "note": "Participants evaluated two new e-learning systems, either jointly (JE) or separately (SE); the publisher page reports N=272 and N=112 for the two studies." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "peer-influence-in-the-diffusion-of-iphone-3g-over-a-large-social-network", "title": "Peer Influence in the Diffusion of iPhone 3G over a Large Social Network", "category": "Customer behavior and adoption", "study_type": "Observational diffusion study using a large mobile-carrier dataset, tight-community identification, and instrumental variables to address correlation between unobserved subscriber heterogeneity and friends' adoption; the authors also report policy ex", "citation": "Miguel Godinho de Matos, Pedro Ferreira, David Krackhardt (2014). Peer Influence in the Diffusion of iPhone 3G over a Large Social Network. MIS Quarterly. https://doi.org/10.25300/MISQ/2014/38.4.08.", "authors": [ "Miguel Godinho de Matos", "Pedro Ferreira", "David Krackhardt" ], "year": 2014, "journal": "MIS Quarterly", "doi": "10.25300/MISQ/2014/38.4.08", "doi_url": "https://doi.org/10.25300/MISQ/2014/38.4.08", "primary_url": "https://misq.umn.edu/misq/article-abstract/38/4/1103/137/Peer-Influence-in-the-Diffusion-of-iPhone-3G-over?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article/38/4/1103/137/Peer-Influence-in-the-Diffusion-of-iPhone-3G-over", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How much does peer influence affect iPhone 3G adoption in a large social network, and would seeding the product produce useful viral-marketing benefits?", "design": "Observational diffusion study using a large mobile-carrier dataset, tight-community identification, and instrumental variables to address correlation between unobserved subscriber heterogeneity and friends' adoption; the authors also report policy experiments.", "sample_context": "Communities sampled from a large dataset supplied by a major European mobile carrier in one country, tracking iPhone 3G diffusion for 11 months; controls include social clustering, gender, prior mobile-Internet-plan adoption, advanced-handset ownership, and regional mobility.", "findings": "A subscriber's adoption propensity increased with the percentage of friends who had already adopted. The authors estimate that peer influence accounted for 14% of iPhone 3Gs sold by the carrier during the 11-month period; their policy experiments suggest traditional seeding for viral marketing would have yielded little benefit at this effect level.", "limitations": "Not stated on the fetched publisher article page/abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract says the study uses instrumental variables on communities from a major European mobile carrier's dataset, finds adoption rises with friends' adoption, estimates 14% of carrier sales were due to peer influence over 11 months, and reports policy experiments on seeding. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-2900-770b-b806-d3acbefe5f88" ], "corrections": [], "plain_english_summary": "A subscriber's adoption propensity increased with the percentage of friends who had already adopted. The authors estimate that peer influence accounted for 14% of iPhone 3Gs sold by the carrier during the 11-month period; their policy experiments suggest traditional seeding for viral marketing would have yielded little benefit at this effect level. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Observational diffusion study using a large mobile-carrier dataset, tight-community identification, and instrumental variables to address correlation between unobserved subscriber heterogeneity and friends' adoption; the authors also report policy experiments." }, { "name": "Sample", "score": "1/1", "note": "Communities sampled from a large dataset supplied by a major European mobile carrier in one country, tracking iPhone 3G diffusion for 11 months; controls include social clustering, gender, prior mobile-Internet-plan adoption, advanced-handset ownership, and regional mobility." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "stimulating-feedback-contributions-using-digital-nudges-a-field-experiment-in-a-real", "title": "Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-Time Mobile Feedback Platform", "category": "Customer behavior and adoption", "study_type": "Field experiment on digital-nudge timing and task-significance messaging in a real-time feedback application, followed by a randomized online experiment to examine mechanisms.", "citation": "Michael Rivera, Xue Guo, Guohou Shan, Liangfei Qiu (2026). Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-Time Mobile Feedback Platform. MIS Quarterly. https://doi.org/10.25300/MISQ/2025/18920.", "authors": [ "Michael Rivera", "Xue Guo", "Guohou Shan", "Liangfei Qiu" ], "year": 2026, "journal": "MIS Quarterly", "doi": "10.25300/MISQ/2025/18920", "doi_url": "https://doi.org/10.25300/MISQ/2025/18920", "primary_url": "https://misq.umn.edu/misq/article-abstract/50/3/1199/3615/Stimulating-Feedback-Contributions-Using-Digital?redirectedFrom=fulltext", "accessible_url": "https://misq.umn.edu/misq/article/doi/10.25300/MISQ/2025/18920/3615/Stimulating-Feedback-Contributions-Using-Digital", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do digital-nudge timing and task-significance messaging, separately and jointly, affect the quantity and quality of employee feedback in a real-time feedback application, and through what mechanisms?", "design": "Field experiment on digital-nudge timing and task-significance messaging in a real-time feedback application, followed by a randomized online experiment to examine mechanisms.", "sample_context": "Employees using a real-time mobile feedback platform; the publisher abstract distinguishes managers and associates as feedback givers and receivers but does not state sample sizes on the fetched page.", "findings": "Task-significance messaging generated more and higher-quality feedback than generic prompts. Timing amplified the effect only when task-significance messaging was present; the follow-up experiment linked timing to lower cognitive load and task significance to greater germane load and external motivation, with effects varying by role.", "limitations": "Sample sizes and a limitations statement are not stated on the fetched publisher article page/abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The publisher abstract describes a field experiment and follow-up randomized online experiment, and reports that task-significance nudges produce more and higher-quality contributions, with timing amplifying the effect only when task significance is present; it also reports cognitive-load and motivation mechanisms and role heterogeneity. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-3c6f-72af-ab8a-7bc0dd35916c" ], "corrections": [], "plain_english_summary": "Task-significance messaging generated more and higher-quality feedback than generic prompts. Timing amplified the effect only when task-significance messaging was present; the follow-up experiment linked timing to lower cognitive load and task significance to greater germane load and external motivation, with effects varying by role. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Field experiment on digital-nudge timing and task-significance messaging in a real-time feedback application, followed by a randomized online experiment to examine mechanisms." }, { "name": "Sample", "score": "0.5/1", "note": "Employees using a real-time mobile feedback platform; the publisher abstract distinguishes managers and associates as feedback givers and receivers but does not state sample sizes on the fetched page." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "on-demand-delivery-platforms-and-restaurant-sales", "title": "On-Demand Delivery Platforms and Restaurant Sales", "category": "B2B growth and sales", "study_type": "Observational restaurant-panel study using linear regressions with fixed effects and matched treatment/control samples; the publisher page also reports instrumental-variables/two-stage least-squares analyses, a platform policy-change analysis, count-", "citation": "Zhuoxin Li, Gang Wang (2024). On-Demand Delivery Platforms and Restaurant Sales. Management Science. https://doi.org/10.1287/mnsc.2021.01010.", "authors": [ "Zhuoxin Li", "Gang Wang" ], "year": 2024, "journal": "Management Science", "doi": "10.1287/mnsc.2021.01010", "doi_url": "https://doi.org/10.1287/mnsc.2021.01010", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2021.01010", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2021.01010", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do on-demand delivery platforms substitute for or complement restaurants' own takeout and dine-in channels, and what is their net effect on restaurant demand and revenue?", "design": "Observational restaurant-panel study using linear regressions with fixed effects and matched treatment/control samples; the publisher page also reports instrumental-variables/two-stage least-squares analyses, a platform policy-change analysis, count-model robustness checks, and alternative difference-in-differences specifications.", "sample_context": "Chicago metropolitan area (17 counties across Illinois, Indiana, and Wisconsin): 19,117 restaurants, about 48% on at least one of DoorDash, Grubhub, and Uber Eats by the end of 2019. The panel combines Yelp/YellowPages restaurant characteristics, platform-partnership data, SafeGraph weekly foot-traffic data, and anonymized aggregate bank-card transactions; reported main specifications include 603,244 observations.", "findings": "Restaurants overall benefit: delivery platforms increase total takeout sales and create positive spillovers to dine-in visits. Effects are heterogeneous: the overall positive effect for fast-food chains is four times that for independent restaurants; platforms substitute for independent restaurants' own takeout but complement chain takeout, while increasing dine-in visits for both. The paper also reports evidence that platform price comparison intensifies competition and reduces independent restaurants' ability to differentiate through premium service/dine-in experience.", "limitations": "The publisher explicitly says further research could use consumer-level data to study channel choice, examine promotional effects across channels, study platform design/governance, and investigate ghost/cloud kitchens; it also notes the study focuses on traditional restaurants operating multiple channels. These are carefully stated scope/future-research limitations, not claims that the authors label as bias.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The publisher abstract reports that empirical analyses find increased total takeout sales and positive dine-in spillovers, with effects depending on independent versus chain restaurants and takeout versus dine-in channels; the article's data section identifies the Chicago panel and its multiple data sources. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-f3dc-705f-a3df-accddffcc006" ], "corrections": [], "plain_english_summary": "Restaurants overall benefit: delivery platforms increase total takeout sales and create positive spillovers to dine-in visits. Effects are heterogeneous: the overall positive effect for fast-food chains is four times that for independent restaurants; platforms substitute for independent restaurants' own takeout but complement chain takeout, while increasing dine-in visits for both. The paper also reports evidence that platform price comparison intensifies competition and reduces independent restaurants' ability to differentiate through premium service/dine-in experience. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Observational restaurant-panel study using linear regressions with fixed effects and matched treatment/control samples; the publisher page also reports instrumental-variables/two-stage least-squares analyses, a platform policy-change analysis, count-model robustness checks, and alternative difference-in-differences specifications." }, { "name": "Sample", "score": "1/1", "note": "Chicago metropolitan area (17 counties across Illinois, Indiana, and Wisconsin): 19,117 restaurants, about 48% on at least one of DoorDash, Grubhub, and Uber Eats by the end of 2019. The panel combines Yelp/YellowPages restaurant characteristics, platform-partnership data, SafeGraph weekly foot-traffic data, and anonymized aggregate bank-card transactions; reported main specifications include 603,244 observations." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "linking-firm-generated-social-media-content-to-sales-and-returns", "title": "Linking Firm-Generated Social Media Content to Sales and Returns", "category": "B2B growth and sales", "study_type": "Empirical observational analysis linking transaction data to the firm's Facebook posts; posts are classified as informative or persuasive, with informative posts split into standard-product-feature (ISP) and customizable-product-feature (ICP) posts. ", "citation": "M. Serkan Akturk, Haileab Hilafu, Paolo Letizia (2026). Linking Firm-Generated Social Media Content to Sales and Returns. Management Science. https://doi.org/10.1287/mnsc.2023.01432.", "authors": [ "M. Serkan Akturk", "Haileab Hilafu", "Paolo Letizia" ], "year": 2026, "journal": "Management Science", "doi": "10.1287/mnsc.2023.01432", "doi_url": "https://doi.org/10.1287/mnsc.2023.01432", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.01432", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.01432", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How does firm-generated Facebook content, particularly informative content about standard versus customizable product features and persuasive content, relate to product sales and returns?", "design": "Empirical observational analysis linking transaction data to the firm's Facebook posts; posts are classified as informative or persuasive, with informative posts split into standard-product-feature (ISP) and customizable-product-feature (ICP) posts. The publisher reports robustness across alternative model specifications and estimation methods.", "sample_context": "Online-channel transaction data from a luxury fashion accessory manufacturer, augmented with that firm's Facebook posts and product-feature/content classifications.", "findings": "ISP posts are associated with increases in sales and returns, whereas ICP posts are associated with decreases in both. ISP associations with sales and returns are weaker when persuasive content accompanies them; persuasive content attenuates the ICP relationship with returns but not the ICP relationship with sales.", "limitations": "Limitations are not explicitly stated on the fetched publisher page beyond the single-firm/online-channel context; generalizability beyond this luxury fashion accessory manufacturer and channel is therefore not established by that page.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The publisher abstract says the study uses Facebook and transactional data from the online channel of a luxury fashion accessory manufacturer and reports the opposite sales/returns associations for ISP and ICP posts, with moderation by persuasive content. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-1243-7198-8848-ba2738dcd149" ], "corrections": [], "plain_english_summary": "ISP posts are associated with increases in sales and returns, whereas ICP posts are associated with decreases in both. ISP associations with sales and returns are weaker when persuasive content accompanies them; persuasive content attenuates the ICP relationship with returns but not the ICP relationship with sales. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical observational analysis linking transaction data to the firm's Facebook posts; posts are classified as informative or persuasive, with informative posts split into standard-product-feature (ISP) and customizable-product-feature (ICP) posts. The publisher reports robustness across alternative model specifications and estimation methods." }, { "name": "Sample", "score": "0.5/1", "note": "Online-channel transaction data from a luxury fashion accessory manufacturer, augmented with that firm's Facebook posts and product-feature/content classifications." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "technology-usage-and-online-sales-an-empirical-study", "title": "Technology Usage and Online Sales: An Empirical Study", "category": "B2B growth and sales", "study_type": "Empirical analysis of website server-log data matched to sales data, controlling for consumers' historical purchasing behavior. The design compares directed search, nondirected search, and recommendation-system usage and estimates their relationships", "citation": "Prabuddha De, Yu (Jeffrey) Hu, Mohammad S. Rahman (2010). Technology Usage and Online Sales: An Empirical Study. Management Science. https://doi.org/10.1287/mnsc.1100.1233.", "authors": [ "Prabuddha De", "Yu (Jeffrey) Hu", "Mohammad S. Rahman" ], "year": 2010, "journal": "Management Science", "doi": "10.1287/mnsc.1100.1233", "doi_url": "https://doi.org/10.1287/mnsc.1100.1233", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1100.1233", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.1100.1233", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do online consumers use search and recommendation technologies, and how does that usage affect online sales and purchasing patterns?", "design": "Empirical analysis of website server-log data matched to sales data, controlling for consumers' historical purchasing behavior. The design compares directed search, nondirected search, and recommendation-system usage and estimates their relationships with sales of promoted and nonpromoted products.", "sample_context": "An online-shopping website's consumers and product transactions; the publisher page identifies a unique server-log/sales dataset but does not report the number of consumers or observations in the abstract/page metadata fetched.", "findings": "Information-technology usage significantly affects sales, but effects differ by technology and product. Directed search increases sales of promoted products but decreases sales of nonpromoted products; recommendation-system use increases sales of both; nondirected search has an insignificant effect on online sales.", "limitations": "Limitations are not explicitly stated on the fetched publisher page; the page does not identify the site's industry or report sample size, so external validity and scale cannot be assessed from the publisher evidence alone.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The publisher abstract says the authors measure technology usage from server logs, match it to sales while controlling for historical purchasing, and find technology- and product-specific effects: directed search helps promoted products but hurts nonpromoted products, recommendation systems help both, and nondirected search is insignificant. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-d262-708c-8b3b-56fe83fb716d" ], "corrections": [], "plain_english_summary": "Information-technology usage significantly affects sales, but effects differ by technology and product. Directed search increases sales of promoted products but decreases sales of nonpromoted products; recommendation-system use increases sales of both; nondirected search has an insignificant effect on online sales. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical analysis of website server-log data matched to sales data, controlling for consumers' historical purchasing behavior. The design compares directed search, nondirected search, and recommendation-system usage and estimates their relationships with sales of promoted and nonpromoted products." }, { "name": "Sample", "score": "0.5/1", "note": "An online-shopping website's consumers and product transactions; the publisher page identifies a unique server-log/sales dataset but does not report the number of consumers or observations in the abstract/page metadata fetched." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "what-drives-subscribing-to-premium-in-freemium-services-a-consumer-value-based-view-o", "title": "What drives subscribing to premium in freemium services? A consumer value-based view of differences between upgrading to and staying with premium", "category": "Pricing and monetization", "study_type": "Two-stage online survey of basic and premium users, analyzed with principal-components measurement validation and structural-equation modeling; the publisher page reports a two-week separation between survey waves.", "citation": "Matti M\u00e4ntym\u00e4ki, A.K.M. Najmul Islam, Izak Benbasat (2020). What drives subscribing to premium in freemium services? A consumer value-based view of differences between upgrading to and staying with premium. Information Systems Journal. https://doi.org/10.1111/isj.12262.", "authors": [ "Matti M\u00e4ntym\u00e4ki", "A.K.M. Najmul Islam", "Izak Benbasat" ], "year": 2020, "journal": "Information Systems Journal", "doi": "10.1111/isj.12262", "doi_url": "https://doi.org/10.1111/isj.12262", "primary_url": "https://onlinelibrary.wiley.com/doi/10.1111/isj.12262", "accessible_url": "https://onlinelibrary.wiley.com/doi/10.1111/isj.12262", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do the consumer values driving free/basic users' intention to upgrade differ from the values driving premium users' intention to retain a paid freemium subscription?", "design": "Two-stage online survey of basic and premium users, analyzed with principal-components measurement validation and structural-equation modeling; the publisher page reports a two-week separation between survey waves.", "sample_context": "Finnish Spotify users: 467 usable responses after cleaning (208 basic/free and 259 premium users), recruited from a Finnish university student database and university-related Facebook groups; the study also interviewed 11 active Spotify users to develop two measurement constructs.", "findings": "For upgrading, enjoyment and perceived price value predict intention to move to premium. For retaining premium, ubiquity and discovery of new content predict intention; social connectivity has a small negative retention effect, while advertising intrusiveness does not significantly affect either outcome.", "limitations": "Explicitly stated: the study covers one subscription-based freemium service in one country, so broader contextual coverage is needed; the authors also note that survey research makes it difficult to control the zero-price effect.", "founder_use": "Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher abstract says the model is tested on a leading digital content freemium service and explicitly contrasts upgrade versus retention drivers. The empirical section reports 467 Finnish Spotify responses, and the limitations section identifies the one-service/one-country scope. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcb-b84c-738a-8248-1767b81fdfa5" ], "corrections": [], "plain_english_summary": "For upgrading, enjoyment and perceived price value predict intention to move to premium. For retaining premium, ubiquity and discovery of new content predict intention; social connectivity has a small negative retention effect, while advertising intrusiveness does not significantly affect either outcome. For your marketing: Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Two-stage online survey of basic and premium users, analyzed with principal-components measurement validation and structural-equation modeling; the publisher page reports a two-week separation between survey waves." }, { "name": "Sample", "score": "1/1", "note": "Finnish Spotify users: 467 usable responses after cleaning (208 basic/free and 259 premium users), recruited from a Finnish university student database and university-related Facebook groups; the study also interviewed 11 active Spotify users to develop two measurement constructs." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-zero-price-effect-in-freemium-business-models-the-moderating-effects-of-free-ment", "title": "The zero-price effect in freemium business models: The moderating effects of free mentality and price\u2013quality inference", "category": "Pricing and monetization", "study_type": "Two empirical studies: an implicit-association test to identify intuitive responses to zero pricing, followed by a choice-based conjoint study testing free mentality and price\u2013quality inference in freemium offers.", "citation": "Thomas Niemand, Robert Mai, Sascha Kraus (2019). The zero-price effect in freemium business models: The moderating effects of free mentality and price\u2013quality inference. Psychology & Marketing. https://doi.org/10.1002/mar.21211.", "authors": [ "Thomas Niemand", "Robert Mai", "Sascha Kraus" ], "year": 2019, "journal": "Psychology & Marketing", "doi": "10.1002/mar.21211", "doi_url": "https://doi.org/10.1002/mar.21211", "primary_url": "https://onlinelibrary.wiley.com/doi/10.1002/mar.21211", "accessible_url": "https://onlinelibrary.wiley.com/doi/10.1002/mar.21211", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do intuitive free-mentality and price\u2013quality-inference processes, and their interaction, affect consumer response and premium conversion in freemium offers?", "design": "Two empirical studies: an implicit-association test to identify intuitive responses to zero pricing, followed by a choice-based conjoint study testing free mentality and price\u2013quality inference in freemium offers.", "sample_context": "Digital-service consumers/users; the conjoint context is media streaming. The publisher abstract does not state participant counts on the fetched page.", "findings": "The study identifies two opposing intuitions\u2014free mentality (expecting digital services at no cost) and price\u2013quality inference (expecting higher price to signal higher quality)\u2014and reports that their interplay shapes responses to freemium offers and can help explain low premium conversion.", "limitations": "The publisher page does not state an explicit limitations section or sample-size limitation in the fetched article; therefore no additional limitation is asserted here.", "founder_use": "Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher abstract says the framework is tested in two studies, specifies the implicit-association and choice-based-conjoint designs, and identifies media streaming as the conjoint service context; it frames the interaction of the two intuitions as a lever for low premium conversion. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-6831-7389-b85b-9a11202b133e" ], "corrections": [], "plain_english_summary": "The study identifies two opposing intuitions\u2014free mentality (expecting digital services at no cost) and price\u2013quality inference (expecting higher price to signal higher quality)\u2014and reports that their interplay shapes responses to freemium offers and can help explain low premium conversion. For your marketing: Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Two empirical studies: an implicit-association test to identify intuitive responses to zero pricing, followed by a choice-based conjoint study testing free mentality and price\u2013quality inference in freemium offers." }, { "name": "Sample", "score": "0.5/1", "note": "Digital-service consumers/users; the conjoint context is media streaming. The publisher abstract does not state participant counts on the fetched page." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "a-novel-approach-to-predicting-customer-lifetime-value-in-b2b-saas-companies", "title": "A novel approach to predicting customer lifetime value in B2B SaaS companies", "category": "B2B growth and sales", "study_type": "Empirical machine-learning study implementing a hierarchical ensembled customer-lifetime-value model; supervised models are compared with simpler heuristics, traditional CLV approaches, and time-series methods using a random 70% training/30% test spl", "citation": "Stephan Curiskis, Xiaojing Dong, Fan Jiang, Mark Scarr (2023). A novel approach to predicting customer lifetime value in B2B SaaS companies. Journal of Marketing Analytics. https://doi.org/10.1057/s41270-023-00234-6.", "authors": [ "Stephan Curiskis", "Xiaojing Dong", "Fan Jiang", "Mark Scarr" ], "year": 2023, "journal": "Journal of Marketing Analytics", "doi": "10.1057/s41270-023-00234-6", "doi_url": "https://doi.org/10.1057/s41270-023-00234-6", "primary_url": "https://link.springer.com/article/10.1057/s41270-023-00234-6", "accessible_url": "https://link.springer.com/article/10.1057/s41270-023-00234-6", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can a hierarchical, ensembled machine-learning framework improve customer-lifetime-value prediction and marketing resource allocation in the heterogeneous, temporally constrained B2B SaaS setting?", "design": "Empirical machine-learning study implementing a hierarchical ensembled customer-lifetime-value model; supervised models are compared with simpler heuristics, traditional CLV approaches, and time-series methods using a random 70% training/30% test split.", "sample_context": "Data from a major B2B SaaS provider: customers with active licenses on 1 January 2021, using revenue/MRR, product-license, product-usage, and firmographic features. The two-year CLV label covers 2021\u20132022 and the longer-horizon model uses a five-year window ending 2022.", "findings": "The publisher reports that the hierarchical ensemble improves practical CLV prediction over simpler heuristics and traditional CLV approaches, and that the predictions can be used to optimize marketing spend and ROI and generate managerial insights.", "limitations": "The publisher page does not state an explicit limitations section in the fetched article. It does explicitly describe the empirical setting's challenges as heterogeneous customers, multiple products, and constrained temporal data; no broader generalizability claim is made here.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "The Springer publisher abstract identifies the B2B SaaS setting, hierarchical ensembled framework, empirical implementation on a B2B SaaS company, improvement over simpler/traditional approaches, and applications to marketing spend and ROI. The methods page specifies active-license customers, the 70/30 train-test split, and the revenue, usage, license, and firmographic data. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-5595-712a-b531-cd8b2fbe0fac" ], "corrections": [], "plain_english_summary": "The publisher reports that the hierarchical ensemble improves practical CLV prediction over simpler heuristics and traditional CLV approaches, and that the predictions can be used to optimize marketing spend and ROI and generate managerial insights. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical machine-learning study implementing a hierarchical ensembled customer-lifetime-value model; supervised models are compared with simpler heuristics, traditional CLV approaches, and time-series methods using a random 70% training/30% test split." }, { "name": "Sample", "score": "1/1", "note": "Data from a major B2B SaaS provider: customers with active licenses on 1 January 2021, using revenue/MRR, product-license, product-usage, and firmographic features. The two-year CLV label covers 2021\u20132022 and the longer-horizon model uses a five-year window ending 2022." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "online-product-reviews-triggered-dynamic-pricing-theory-and-evidence", "title": "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence", "category": "Pricing and monetization", "study_type": "The article combines an analytical model with a panel-data study of prices and reviews; the publisher abstract says the empirical analysis uses a difference-in-differences framework to address endogeneity.", "citation": "Juan Feng, Xin Li, Xiaoquan (Michael) Zhang (2019). Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence. Information Systems Research. https://doi.org/10.1287/isre.2019.0852.", "authors": [ "Juan Feng", "Xin Li", "Xiaoquan (Michael) Zhang" ], "year": 2019, "journal": "Information Systems Research", "doi": "10.1287/isre.2019.0852", "doi_url": "https://doi.org/10.1287/isre.2019.0852", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0852", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2019.0852", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do online product reviews interact with firm pricing strategy, and can firms use dynamic pricing in response to online word of mouth?", "design": "The article combines an analytical model with a panel-data study of prices and reviews; the publisher abstract says the empirical analysis uses a difference-in-differences framework to address endogeneity.", "sample_context": "Online product prices and user-generated product reviews; the publisher page does not specify the retailer, product categories, panel size, or observation period in the abstract.", "findings": "The model predicts that firms can manipulate pricing to influence reviews and sales and can dynamically adjust prices in response to online word of mouth; the panel-data difference-in-differences study is presented as empirical support for those predictions.", "limitations": "Not stated in the publisher abstract; the page does not provide enough detail to identify sample-specific external-validity limitations.", "founder_use": "Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_basis": "The publisher describes a panel-data study of prices and reviews using difference-in-differences, and says the study offers empirical support for the analytical predictions. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-99ba-735e-b523-b39a347d7351" ], "corrections": [], "plain_english_summary": "The model predicts that firms can manipulate pricing to influence reviews and sales and can dynamically adjust prices in response to online word of mouth; the panel-data difference-in-differences study is presented as empirical support for those predictions. For your marketing: Use this as a pricing or packaging hypothesis and define outcomes to measure; estimate effects with your own customer mix and willingness-to-pay evidence.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "The article combines an analytical model with a panel-data study of prices and reviews; the publisher abstract says the empirical analysis uses a difference-in-differences framework to address endogeneity." }, { "name": "Sample", "score": "0.5/1", "note": "Online product prices and user-generated product reviews; the publisher page does not specify the retailer, product categories, panel size, or observation period in the abstract." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "usage-continuance-in-software-as-a-service", "title": "Usage Continuance in Software-as-a-Service", "category": "Customer behavior and adoption", "study_type": "Longitudinal observational study using data from a SaaS vendor and a linear mixed model to analyze measures intended to improve continued usage over time.", "citation": "Elias Baumann, Jana Kern, Stefan Lessmann (2022). Usage Continuance in Software-as-a-Service. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10065-w.", "authors": [ "Elias Baumann", "Jana Kern", "Stefan Lessmann" ], "year": 2022, "journal": "Information Systems Frontiers", "doi": "10.1007/s10796-020-10065-w", "doi_url": "https://doi.org/10.1007/s10796-020-10065-w", "primary_url": "https://link.springer.com/article/10.1007/s10796-020-10065-w", "accessible_url": "https://link.springer.com/article/10.1007/s10796-020-10065-w", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Which vendor activation measures and software/client characteristics increase continued usage (usage penetration) of SaaS applications after initial adoption?", "design": "Longitudinal observational study using data from a SaaS vendor and a linear mixed model to analyze measures intended to improve continued usage over time.", "sample_context": "A SaaS vendor's application usage over time, including vendor activation measures and software/client characteristics; the publisher abstract does not report the number of customers or observations.", "findings": "Several proactive activation measures positively affect usage penetration, while software and client characteristics do not display significant estimates; the authors emphasize proactive activation initiatives to raise usage penetration.", "limitations": "Not stated in the publisher abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "Springer's abstract says the study is longitudinal, uses data from a SaaS vendor and a linear mixed model, and finds that proactive activation initiatives raise usage penetration. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-dbcf-745f-85b2-716ef41f40b3" ], "corrections": [], "plain_english_summary": "Several proactive activation measures positively affect usage penetration, while software and client characteristics do not display significant estimates; the authors emphasize proactive activation initiatives to raise usage penetration. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Longitudinal observational study using data from a SaaS vendor and a linear mixed model to analyze measures intended to improve continued usage over time." }, { "name": "Sample", "score": "0.5/1", "note": "A SaaS vendor's application usage over time, including vendor activation measures and software/client characteristics; the publisher abstract does not report the number of customers or observations." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "on-the-spillover-effects-of-online-product-reviews-on-purchases-evidence-from-clickst", "title": "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data", "category": "Reviews and reputation", "study_type": "Observational clickstream study of purchases and reviews, supplemented by supervised machine-learning models trained and validated with Amazon Mechanical Turk product-pair labels to identify complementary and substitutive products.", "citation": "Young Kwark, Gene Moo Lee, Paul A. Pavlou, Liangfei Qiu (2021). On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data. Information Systems Research. https://doi.org/10.1287/isre.2021.0998.", "authors": [ "Young Kwark", "Gene Moo Lee", "Paul A. Pavlou", "Liangfei Qiu" ], "year": 2021, "journal": "Information Systems Research", "doi": "10.1287/isre.2021.0998", "doi_url": "https://doi.org/10.1287/isre.2021.0998", "primary_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.0998", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.2021.0998", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do online reviews of products viewed alongside a focal product spill over into focal-product purchases, and how do complementarity/substitution, device, brand, experience, and rating variance moderate the effect?", "design": "Observational clickstream study of purchases and reviews, supplemented by supervised machine-learning models trained and validated with Amazon Mechanical Turk product-pair labels to identify complementary and substitutive products.", "sample_context": "Clickstream data from a large retailer, examining reviews of covisited products and purchases of a focal product; moderators include device (mobile versus PC), brand relationship, consumer experience, and rating variance.", "findings": "Mean ratings of substitutive products negatively affect focal-product purchase while ratings of complementary products have a positive effect; spillovers are stronger on mobile, across different brands for substitutive products, among less experienced consumers, and when rating variance is lower.", "limitations": "Not stated in the publisher abstract.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "INFORMS states that the study uses clickstream data from a large retailer and reports negative substitutive-product and positive complementary-product review spillovers, with the listed moderation patterns. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-8754-714e-b0bd-09eac7306c33" ], "corrections": [], "plain_english_summary": "Mean ratings of substitutive products negatively affect focal-product purchase while ratings of complementary products have a positive effect; spillovers are stronger on mobile, across different brands for substitutive products, among less experienced consumers, and when rating variance is lower. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 2.5, "label": "Evidence needs cautious interpretation", "components": [ { "name": "Design", "score": "1/2", "note": "Observational clickstream study of purchases and reviews, supplemented by supervised machine-learning models trained and validated with Amazon Mechanical Turk product-pair labels to identify complementary and substitutive products." }, { "name": "Sample", "score": "0.5/1", "note": "Clickstream data from a large retailer, examining reviews of covisited products and purchases of a focal product; moderators include device (mobile versus PC), brand relationship, consumer experience, and rating variance." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "b2b-online-sales-pushes-whether-when-and-why-they-enhance-sales-performance", "title": "B2B online sales pushes: Whether, when, and why they enhance sales performance", "category": "B2B growth and sales", "study_type": "Mixed empirical design combining transactional/field data from a B2B seller with a scenario-based experiment.", "citation": "Vamsi K. Kanuri, Johannes Habel, Nawar N. Chaker, Deva Rangarajan, Paolo Guenzi (2022). B2B online sales pushes: Whether, when, and why they enhance sales performance. Production and Operations Management. https://doi.org/10.1111/poms.13927.", "authors": [ "Vamsi K. Kanuri", "Johannes Habel", "Nawar N. Chaker", "Deva Rangarajan", "Paolo Guenzi" ], "year": 2022, "journal": "Production and Operations Management", "doi": "10.1111/poms.13927", "doi_url": "https://doi.org/10.1111/poms.13927", "primary_url": "https://onlinelibrary.wiley.com/doi/10.1111/poms.13927", "accessible_url": "https://onlinelibrary.wiley.com/doi/10.1111/poms.13927", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Whether, when and why do B2B online sales pushes change salesperson effort and improve sales performance during hybrid-channel adoption?", "design": "Mixed empirical design combining transactional/field data from a B2B seller with a scenario-based experiment.", "sample_context": "A B2B seller transitioning from an in-person field force to a direct online channel; the study examines salesperson communication effort, customer online proclivity and potential, and sales performance.", "findings": "Salespeople generally comply with online sales pushes because online adoption frees time for new selling opportunities; post-push effort reflects customers' prior online proclivity and potential, varies over time and by channel, and produces asymmetric carryover, cross-channel and synergistic effects on sales performance.", "limitations": "The field evidence comes from one B2B seller and the causal/behavioral evidence includes a scenario-based experiment, so generalizability across sellers, industries, channels and real adoption settings is limited.", "founder_use": "Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_basis": "Wiley's journal page labels the article an Early View Special Issue Article and its abstract states that the authors 'empirically investigate' the issue using data from a B2B seller and a scenario-based experiment, reporting channel- and time-varying effort and sales-performance effects. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-babd-754a-b3bf-22447891ef18" ], "corrections": [], "plain_english_summary": "Salespeople generally comply with online sales pushes because online adoption frees time for new selling opportunities; post-push effort reflects customers' prior online proclivity and potential, varies over time and by channel, and produces asymmetric carryover, cross-channel and synergistic effects on sales performance. For your marketing: Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "2/2", "note": "Mixed empirical design combining transactional/field data from a B2B seller with a scenario-based experiment." }, { "name": "Sample", "score": "0.5/1", "note": "A B2B seller transitioning from an in-person field force to a direct online channel; the study examines salesperson communication effort, customer online proclivity and potential, and sales performance." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "disentangling-the-effects-of-lock-in-and-affective-customer-experience-on-retention", "title": "Disentangling the effects of lock-in and affective customer experience on retention", "category": "Acquisition and retention", "study_type": "Empirical panel/archival customer-level analysis using multinomial logit models to test a framework integrating experiential learning and social exchange theory.", "citation": "Marc-Andre Danatzis, Klaus-Peter Wiedmann, Stefan T. B. Baumgarth, Peter Kenning (2023). Disentangling the effects of lock-in and affective customer experience on retention. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-022-00898-z.", "authors": [ "Marc-Andre Danatzis", "Klaus-Peter Wiedmann", "Stefan T. B. Baumgarth", "Peter Kenning" ], "year": 2023, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-022-00898-z", "doi_url": "https://doi.org/10.1007/s11747-022-00898-z", "primary_url": "https://link.springer.com/article/10.1007/s11747-022-00898-z", "accessible_url": "https://link.springer.com/article/10.1007/s11747-022-00898-z", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How do lock-in and affective customer experience separately and jointly affect retention, and how does relationship depth moderate those effects?", "design": "Empirical panel/archival customer-level analysis using multinomial logit models to test a framework integrating experiential learning and social exchange theory.", "sample_context": "13,761 customers covering all firms in one telecommunications market and two services (mobile and broadband), with retention/churn decisions and customer-experience measures.", "findings": "When affective experience is poor, lock-in reduces churn by about 49.03%\u201347.86%; its effect becomes insignificant above an acceptable experience level. Both strategies matter more at low relationship depth and less in heavy relationships.", "limitations": "Affective customer experience is measured with a single item and annually (December), and the study is confined to one telecom market and two services; the authors recommend richer measures and additional settings/frequencies.", "founder_use": "Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_basis": "Springer Nature's publisher page labels it 'Original Empirical Research' and reports a sample of 13,761 customers, multinomial-logit testing, and the thresholded lock-in/churn and relationship-depth findings. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcc-f2a7-70bb-9967-2b46c2b1706b" ], "corrections": [], "plain_english_summary": "When affective experience is poor, lock-in reduces churn by about 49.03%\u201347.86%; its effect becomes insignificant above an acceptable experience level. Both strategies matter more at low relationship depth and less in heavy relationships. For your marketing: Use it to frame a lifecycle hypothesis and define customer-level outcomes; compare its market and retention horizon with yours.", "evidence_check": { "score": 3, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Empirical panel/archival customer-level analysis using multinomial logit models to test a framework integrating experiential learning and social exchange theory." }, { "name": "Sample", "score": "1/1", "note": "13,761 customers covering all firms in one telecommunications market and two services (mobile and broadband), with retention/churn decisions and customer-experience measures." }, { "name": "Comparison", "score": "0.5/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "customer-referral-behavior-do-switchers-and-stayers-differ", "title": "Customer Referral Behavior: Do Switchers and Stayers Differ?", "category": "Reviews and reputation", "study_type": "Two-wave empirical study testing moderation by customer tenure/acquisition status; it uses actual referral data and examines how changes in perceived service quality and value relate to referral behavior for switchers versus stayers.", "citation": "Alisha Stein, B. Ramaseshan (2015). Customer Referral Behavior: Do Switchers and Stayers Differ?. Journal of Service Research. https://doi.org/10.1177/1094670514563495.", "authors": [ "Alisha Stein", "B. Ramaseshan" ], "year": 2015, "journal": "Journal of Service Research", "doi": "10.1177/1094670514563495", "doi_url": "https://doi.org/10.1177/1094670514563495", "primary_url": "https://journals.sagepub.com/doi/10.1177/1094670514563495", "accessible_url": "https://journals.sagepub.com/doi/10.1177/1094670514563495", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Do recently acquired customers (switchers) and long-term customers (stayers) differ in how service quality and perceived value changes affect customer referrals?", "design": "Two-wave empirical study testing moderation by customer tenure/acquisition status; it uses actual referral data and examines how changes in perceived service quality and value relate to referral behavior for switchers versus stayers.", "sample_context": "441 customers of an Internet Service Provider, observed in two waves; switchers are recently acquired customers who changed providers, while stayers are longer-term customers.", "findings": "Positive changes in service quality and perceived value have stronger effects on referral behavior among switchers than stayers. Thus, investments in quality and value improvements generate higher referral returns among newly acquired customers.", "limitations": "The sample is from one Internet Service Provider and the two-wave observational design limits causal inference; the switcher/stayer comparison may also reflect unobserved differences between newly acquired and long-term customers.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "The Sage Journal of Service Research abstract reports the two-wave actual-referral dataset of 441 ISP customers and the stronger quality/value-to-referral relationships for switchers. The publisher page identifies the authors, journal, and DOI. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcd-092e-74f2-8ee8-47944f52f447" ], "corrections": [], "plain_english_summary": "Positive changes in service quality and perceived value have stronger effects on referral behavior among switchers than stayers. Thus, investments in quality and value improvements generate higher referral returns among newly acquired customers. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 3.5, "label": "Moderate evidence for a specific setting", "components": [ { "name": "Design", "score": "1/2", "note": "Two-wave empirical study testing moderation by customer tenure/acquisition status; it uses actual referral data and examines how changes in perceived service quality and value relate to referral behavior for switchers versus stayers." }, { "name": "Sample", "score": "1/1", "note": "441 customers of an Internet Service Provider, observed in two waves; switchers are recently acquired customers who changed providers, while stayers are longer-term customers." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "return-on-engagement-initiatives-a-study-of-a-business-to-business-mobile-app", "title": "Return on Engagement Initiatives: A Study of a Business-to-Business Mobile App", "category": "Customer behavior and adoption", "study_type": "Quasi-experimental difference-in-differences study with selection on observables and unobservables, comparing buyer firms that adopted a manufacturer's free B2B mobile app with a non-adopting control group over 15 months.", "citation": "Manpreet Gill, Shrihari Sridhar, Rajdeep Grewal (2017). Return on Engagement Initiatives: A Study of a Business-to-Business Mobile App. Journal of Marketing. https://doi.org/10.1509/jm.16.0149.", "authors": [ "Manpreet Gill", "Shrihari Sridhar", "Rajdeep Grewal" ], "year": 2017, "journal": "Journal of Marketing", "doi": "10.1509/jm.16.0149", "doi_url": "https://doi.org/10.1509/jm.16.0149", "primary_url": "https://journals.sagepub.com/doi/abs/10.1509/jm.16.0149", "accessible_url": "https://journals.sagepub.com/doi/abs/10.1509/jm.16.0149", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "Can a B2B mobile-app engagement initiative generate measurable sales returns, and how does customer participation intensity explain return on engagement?", "design": "Quasi-experimental difference-in-differences study with selection on observables and unobservables, comparing buyer firms that adopted a manufacturer's free B2B mobile app with a non-adopting control group over 15 months.", "sample_context": "A tool manufacturer's business buyers and their sales records; the app was offered free to engage buyers, and buyer participation intensity was measured through projects created in the app.", "findings": "App adoption increased the manufacturer's annual sales revenue by 19.11%\u201322.79%; return on engagement remained positive after development costs, and was higher when buyers created more projects in the app.", "limitations": "The evidence is from one manufacturer's app and buyer base, and adoption is not randomized; consequently, residual selection, firm-specific implementation effects, and generalization to other B2B apps remain concerns.", "founder_use": "Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_basis": "SAGE's Journal of Marketing page identifies the authors, article, journal, and DOI and reports the 15-month adopter/control design, 19.11%\u201322.79% sales-revenue effect, cost-adjusted positive RoEI, and participation-intensity result in the abstract. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcd-249b-769d-b20b-2d11dbe32756" ], "corrections": [], "plain_english_summary": "App adoption increased the manufacturer's annual sales revenue by 19.11%\u201322.79%; return on engagement remained positive after development costs, and was higher when buyers created more projects in the app. For your marketing: Use it as a product, platform or behavior mechanism reference rather than a direct forecast for a SaaS funnel.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Quasi-experimental difference-in-differences study with selection on observables and unobservables, comparing buyer firms that adopted a manufacturer's free B2B mobile app with a non-adopting control group over 15 months." }, { "name": "Sample", "score": "0.5/1", "note": "A tool manufacturer's business buyers and their sales records; the app was offered free to engage buyers, and buyer participation intensity was measured through projects created in the app." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "the-effectiveness-of-triggered-email-marketing-in-addressing-browse-abandonments", "title": "The Effectiveness of Triggered Email Marketing in Addressing Browse Abandonments", "category": "Paid media and measurement", "study_type": "Randomized experiment: approximately half of browse-abandoning customers received automated emails and the other half received no message.", "citation": "Marcel Goic, Andrea Rojas, Ignacio Saavedra (2021). The Effectiveness of Triggered Email Marketing in Addressing Browse Abandonments. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2021.02.002.", "authors": [ "Marcel Goic", "Andrea Rojas", "Ignacio Saavedra" ], "year": 2021, "journal": "Journal of Interactive Marketing", "doi": "10.1016/j.intmar.2021.02.002", "doi_url": "https://doi.org/10.1016/j.intmar.2021.02.002", "primary_url": "https://www.sciencedirect.com/science/article/abs/pii/S1094996821000165", "accessible_url": "https://www.sciencedirect.com/science/article/abs/pii/S1094996821000165", "access_label": "Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.", "access_class": "abstract", "research_question": "How effective are triggered emails at converting customers who browse but leave without purchasing?", "design": "Randomized experiment: approximately half of browse-abandoning customers received automated emails and the other half received no message.", "sample_context": "Customers of a multichannel retailer who had browsed the website and abandoned before purchase.", "findings": "Browse-abandonment emails increased online-channel sales and sales in the triggered category; longer navigation histories and wider-assortment recommendations were associated with larger conversions/revenues.", "limitations": "The source describes one multichannel retailer and says implementation/configuration affects effectiveness.", "founder_use": "Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_basis": "The publisher page supplies the article record and empirical abstract. Direct publisher-page retrieval was recorded on 2026-10-09; profile summarizes the accessible record and does not claim independent review of inaccessible full text.", "source_ids": [ "01a11fcd-4723-761e-9895-9cb6fef84e1d" ], "corrections": [], "plain_english_summary": "Browse-abandonment emails increased online-channel sales and sales in the triggered category; longer navigation histories and wider-assortment recommendations were associated with larger conversions/revenues. For your marketing: Use it to shape a locally controlled channel or message test; account for audience, timing and attribution limits before reallocating budget.", "evidence_check": { "score": 4, "label": "Strong design for its specific question", "components": [ { "name": "Design", "score": "2/2", "note": "Randomized experiment: approximately half of browse-abandoning customers received automated emails and the other half received no message." }, { "name": "Sample", "score": "0.5/1", "note": "Customers of a multichannel retailer who had browsed the website and abandoned before purchase." }, { "name": "Comparison", "score": "1/1", "note": "Based on the publisher-described design and comparison; see the article for complete analysis." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Publisher record was fetched directly; full text was not assumed open." } ], "blinding": "Blinding was not established from the retrieved publisher record." } }, { "slug": "is-a-chatbot-more-effective-investigating-the-effect-of-service-recovery", "title": "Is a Chatbot More Effective? Investigating the Effect of Service Recovery Agents and Consumer Loss on Consumer Forgiveness", "category": "Customer behavior and adoption", "study_type": "Full-text empirical research; three scenario-based between-subjects experiments", "citation": "Liu Fan, Shanshan Li, Can Wang, Xiaoping Zhang (2026). Journal of Theoretical and Applied Electronic Commerce Research.", "authors": [ "Liu Fan", "Shanshan Li", "Can Wang", "Xiaoping Zhang" ], "year": 2026, "journal": "Journal of Theoretical and Applied Electronic Commerce Research", "doi": "10.3390/jtaer21010035", "doi_url": "https://doi.org/10.3390/jtaer21010035", "primary_url": "https://doi.org/10.3390/jtaer21010035", "accessible_url": "https://www.mdpi.com/0718-1876/21/1/35", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do recovery agent (human versus chatbot), consumer-loss type (utilitarian versus symbolic) and service-failure severity interact to influence consumer forgiveness?", "design": "Three scenario experiments with factorial manipulations. Study 1 used a 2\u00d72 design with a hotel check-in failure; Study 2 used a taxi-service failure; Study 3 tested severity moderation in another service scenario. Participants viewed human/chatbot recovery dialogue screenshots and rated responsiveness, emotional support and forgiveness.", "sample_context": "Chinese online participants recruited through Wenjuanxing. Study 1: 270 recruited, 30 excluded, 240 valid (mean age 24.89; 59.7% female). Study 2: 566 recruited, 46 excluded, 520 valid (mean age 23.72; 65% female). The full paper reports Study 3's sample and setting separately.", "findings": "Humans generally outperform chatbots for symbolic loss, where emotional support matters, while the difference diminishes for utilitarian loss. Recovery-agent effects depend on failure severity: for low-severity failures human recovery is more effective, whereas the paper reports different comparative effects under high severity. The results caution against treating chatbot recovery as universally superior.", "limitations": "Scenario experiments limit external validity; low- and high-severity manipulations clustered in the mid-to-high range; samples were Chinese and domains were scenario-specific. The authors call for field tests, more finely separated severity levels, cross-cultural research and tests in high-risk domains such as medical and financial services.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "MDPI publisher full text supplies exact bibliographic record, DOI, authors, all three designs, participant exclusions/counts, results and a dedicated limitations section. It is a particularly current direct study of chatbot service recovery rather than a review or aggregator summary. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224a-564b-73fa-bc7c-b6574f630057" ], "corrections": [], "plain_english_summary": "Humans generally outperform chatbots for symbolic loss, where emotional support matters, while the difference diminishes for utilitarian loss. Recovery-agent effects depend on failure severity: for low-severity failures human recovery is more effective, whereas the paper reports different comparative effects under high severity. The results caution against treating chatbot recovery as universally superior. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (1); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.8/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "a-meta-analysis-of-technological-adoption-of-financial-services-investig", "title": "A meta-analysis of technological adoption of financial services: investigating risk and trust perception effects", "category": "B2B growth and sales", "study_type": "Systematic literature review and meta-analysis", "citation": "Wagner Junior Ladeira, Syed Hasan Jafar, Fernando de Oliveira Santini (2025). International Journal of Bank Marketing.", "authors": [ "Wagner Junior Ladeira", "Syed Hasan Jafar", "Fernando de Oliveira Santini" ], "year": 2025, "journal": "International Journal of Bank Marketing", "doi": "10.1108/IJBM-02-2025-0156", "doi_url": "https://doi.org/10.1108/IJBM-02-2025-0156", "primary_url": "https://doi.org/10.1108/IJBM-02-2025-0156", "accessible_url": "https://doi.org/10.1108/IJBM-02-2025-0156", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "What are the overall effects of perceived risk and trust on technological adoption of financial services, and which contextual, practical, and methodological moderators shape those effects?", "design": "PRISMA-S systematic review and random-effects meta-analysis; hierarchical linear meta-analysis (HiLMA) tested contextual, practical, and methodological moderators.", "sample_context": "55 studies and 2,104 effect sizes concerning risk perception, trust, and technological adoption across financial-services/banking contexts; the publisher abstract does not list the individual countries, technologies, or inclusion dates.", "findings": "Risk perception negatively influences financial-services technology adoption; economic performance, business efficiency, and globalization amplify that effect. Older and more educated individuals are more risk-sensitive. Trust positively influences adoption, with government efficiency, infrastructure, and AI-driven solutions strengthening its influence; cultural dimensions and perceived control also shape trust effects. Heterogeneity varies across economic, technological, and methodological contexts.", "limitations": "The publisher abstract does not state limitations beyond reporting heterogeneity and omitted contextual detail; full-text review is needed to assess publication bias, study quality, dependence among effect sizes, and moderator coverage.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Emerald publisher record (research article, online 2025) directly provides the exact title, authors, DOI, PRISMA-S design, 55-study/2,104-effect-size corpus, model, and substantive findings. Full text is marked available to purchase, so this is abstract-only evidence and should receive editorial verification. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224a-3ca4-71e9-98b0-5355584a8897" ], "corrections": [], "plain_english_summary": "Risk perception negatively influences financial-services technology adoption; economic performance, business efficiency, and globalization amplify that effect. Older and more educated individuals are more risk-sensitive. Trust positively influences adoption, with government efficiency, infrastructure, and AI-driven solutions strengthening its influence; cultural dimensions and perceived control also shape trust effects. Heterogeneity varies across economic, technological, and methodological contexts. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (55); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.8/1", "note": "The source reports a comparison; check the original methods for its construction." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "effect-of-anthropomorphism-and-perceived-intelligence-in-chatbot-avatars", "title": "Effect of anthropomorphism and perceived intelligence in chatbot avatars of visual design on user experience: accounting for perceived empathy and trust", "category": "Customer behavior and adoption", "study_type": "Full-text original research; 2\u00d72 within-subjects experiment with mediation/structural equation modeling", "citation": "Ning Ma, Ruslana Khynevych, Yunqiang Hao, Yahui Wang (2025). Frontiers in Computer Science.", "authors": [ "Ning Ma", "Ruslana Khynevych", "Yunqiang Hao", "Yahui Wang" ], "year": 2025, "journal": "Frontiers in Computer Science", "doi": "10.3389/fcomp.2025.1531976", "doi_url": "https://doi.org/10.3389/fcomp.2025.1531976", "primary_url": "https://doi.org/10.3389/fcomp.2025.1531976", "accessible_url": "https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1531976/full", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do visual anthropomorphism and perceived intelligence in chatbot avatars affect user experience, and do perceived empathy and trust mediate those effects?", "design": "Participants evaluated four combinations of high/low anthropomorphism and high/low perceived intelligence in a Latin-square within-subjects experiment. The authors used ANOVA and SEM to test direct and mediated effects.", "sample_context": "In-person experiment at Beijing Institute of Technology. 179 people participated; after 19 exclusions, 160 valid participants remained (101 female, 59 male; mean age 26, SD 5). Recruitment required chatbot interaction at least five times daily for the prior three months; participants received approximately RMB 200 gift cards.", "findings": "Direct effects of anthropomorphism and perceived intelligence on UX were nonsignificant in the abstract, while the full paper reports anthropomorphism improving UX through perceived empathy and trust and an interaction in which higher perceived intelligence helps when anthropomorphism is high but can reduce UX when anthropomorphism is low. The results emphasize emotional engagement rather than intelligence alone.", "limitations": "The authors identify the relatively small and university-based sample, focus on visual anthropomorphism/perceived intelligence while omitting voice/behavior/personality, cross-sectional limits on causal interpretation, and the restricted mediator set (empathy and trust).", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Frontiers publisher full text directly supplies title, DOI, author list, abstract, participant accounting, experimental procedure, analyses, conclusion and limitations; the result is not inferred from a search snippet. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224a-7eac-7371-8b69-3f7bbb0605b0" ], "corrections": [], "plain_english_summary": "Direct effects of anthropomorphism and perceived intelligence on UX were nonsignificant in the abstract, while the full paper reports anthropomorphism improving UX through perceived empathy and trust and an interaction in which higher perceived intelligence helps when anthropomorphism is high but can reduce UX when anthropomorphism is low. The results emphasize emotional engagement rather than intelligence alone. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (179); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "fully-leveraging-ai-in-b2b-sales-exploring-sales-managers-capabilities-a", "title": "Fully leveraging AI in B2B sales: Exploring sales managers\u2019 capabilities and organizational knowledge processes", "category": "B2B growth and sales", "study_type": "Grounded-theory qualitative empirical study", "citation": "Pia Hautam\u00e4ki, Minna Heikinheimo (2025). Journal of Business Research.", "authors": [ "Pia Hautam\u00e4ki", "Minna Heikinheimo" ], "year": 2025, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2025.115396", "doi_url": "https://doi.org/10.1016/j.jbusres.2025.115396", "primary_url": "https://doi.org/10.1016/j.jbusres.2025.115396", "accessible_url": "https://doi.org/10.1016/j.jbusres.2025.115396", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do sales managers support B2B sales teams in adopting and exploiting AI through managerial capabilities and organizational knowledge processes?", "design": "Grounded-theory approach based on interviews with top-level managers in B2B sales organizations; the publisher abstract reports the empirical framework but not interview protocol or coding details.", "sample_context": "32 top-level managers in B2B sales organizations; organizational/geographic composition is not specified in the publisher abstract.", "findings": "The study links AI exploitation to three managerial capabilities: data-based human capital, social capital for a knowledge-sharing culture, and a transformative AI-positive mindset. These foster AI-integrated knowledge processes at individual, team, and organizational levels.", "limitations": "The publisher-accessible abstract does not report limitations, interview selection details, organizational composition, or transferability constraints; these require full-text editorial checking.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Moderate-to-strong direct evidence: publisher DOI/ScienceDirect record verifies exact metadata, study type, interview N, and findings in the abstract; limitations and fuller design are not claimed because only abstract-level content was verified. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224a-9df4-765d-b6fc-d83af1895aca" ], "corrections": [], "plain_english_summary": "The study links AI exploitation to three managerial capabilities: data-based human capital, social capital for a knowledge-sharing culture, and a transformative AI-positive mindset. These foster AI-integrated knowledge processes at individual, team, and organizational levels. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (32); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "on-the-adoption-of-software-bill-of-materials-in-open-source-software-pr", "title": "On the adoption of software bill of materials in open-source software projects", "category": "Marketing capability and growth", "study_type": "Exploratory empirical mining study", "citation": "Sabato Nocera, Simone Romano, Massimiliano Di Penta, Rita Francese, Giuseppe Scanniello (2025). Journal of Systems and Software.", "authors": [ "Sabato Nocera", "Simone Romano", "Massimiliano Di Penta", "Rita Francese", "Giuseppe Scanniello" ], "year": 2025, "journal": "Journal of Systems and Software", "doi": "10.1016/j.jss.2025.112540", "doi_url": "https://doi.org/10.1016/j.jss.2025.112540", "primary_url": "https://doi.org/10.1016/j.jss.2025.112540", "accessible_url": "https://doi.org/10.1016/j.jss.2025.112540", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How widely are SBOMs adopted by open-source projects, how are they generated/distributed, and how complete and standards-compliant are they?", "design": "Mining study of GitHub repositories identified as using SPDX or CycloneDX SBOM-generation tools; the paper examines adoption, placement in version control/release artifacts, and SBOM information-field compliance.", "sample_context": "186 public GitHub software repositories using SPDX or CycloneDX generation tools. The publisher abstract does not report a human-participant sample.", "findings": "SBOM adoption is low but rising. SBOMs are mostly generated through build-integration tools or GitHub Actions; fewer than half of analyzed projects include them in version control or public release artifacts. Only a limited fraction contain minimum/recommended information, and some are noncompliant with existing SBOM standards.", "limitations": "The publisher abstract does not provide a full limitations section. The observed repository set is limited to public GitHub projects identified through SPDX/CycloneDX tools, so the findings do not establish adoption rates for private, non-GitHub, or projects using other tooling; the source also cautions that SBOMs can be incomplete.", "founder_use": "Treat this as evidence for the specific marketing capability and growth question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher full-text HTML supplies exact bibliographic data, authors, abstract, highlights, repository count, method, results, and data-availability statement. Evidence strength: strong for the 186-repository findings; moderate for broader ecosystem generalization because the abstract-defined frame is selective. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224a-cb40-76f8-970e-08c50b760a8e" ], "corrections": [], "plain_english_summary": "SBOM adoption is low but rising. SBOMs are mostly generated through build-integration tools or GitHub Actions; fewer than half of analyzed projects include them in version control or public release artifacts. Only a limited fraction contain minimum/recommended information, and some are noncompliant with existing SBOM standards. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (186); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.8/1", "note": "The source reports a comparison; check the original methods for its construction." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "sales-digitization-and-sales-process-optimisation-for-firm-performance-e", "title": "Sales digitization and sales process optimisation for firm performance: Evidence from European firms", "category": "B2B growth and sales", "study_type": "Qualitative empirical study combining interviews and multiple case studies", "citation": "Fabio Oliveira, Maksim Belitski, Rodrigo Perez-Vega (2025). Technological Forecasting and Social Change.", "authors": [ "Fabio Oliveira", "Maksim Belitski", "Rodrigo Perez-Vega" ], "year": 2025, "journal": "Technological Forecasting and Social Change", "doi": "10.1016/j.techfore.2025.124172", "doi_url": "https://doi.org/10.1016/j.techfore.2025.124172", "primary_url": "https://doi.org/10.1016/j.techfore.2025.124172", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0040162525002033", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How does adoption of sales enablement platforms influence stages of the B2B sales process and firm performance in medium-sized companies?", "design": "In-depth interviews with CEOs and sales directors, thematic analysis, and three European medium-sized firm case studies; the publisher provides full article sections, participant table, results, appendices, and limitations.", "sample_context": "27 chief executive officers and sales directors plus three European medium-sized firms; case appendices cover Cynergy Bank, Kooth, and Optomed.", "findings": "The paper identifies four pathways: digital skill endowment, marketing ownership of the sales process, strategic implications, and value creation. SEPs improve intra-firm collaboration and customer insight, reduce costs, increase flexibility, and align sales, marketing, and management.", "limitations": "The publisher exposes a limitations/future-research section, but the accessible page extract does not state its contents in the abstract; conclusions are therefore bounded by the qualitative, interview/case-study design and European medium-sized-firm setting rather than generalized to all firms.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Strong direct publisher evidence: ScienceDirect full text exposes method/sample, highlights, abstract, results structure, case appendices, and a dedicated limitations section; no sample size or result was inferred beyond the page text. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224b-03e5-71ce-abbc-6f7a3a2a5d8c" ], "corrections": [], "plain_english_summary": "The paper identifies four pathways: digital skill endowment, marketing ownership of the sales process, strategic implications, and value creation. SEPs improve intra-firm collaboration and customer insight, reduce costs, increase flexibility, and align sales, marketing, and management. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (27); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "buying-centers-and-emerging-developments-the-sme-perspective", "title": "Buying centers and emerging developments: the SME perspective", "category": "B2B growth and sales", "study_type": "Qualitative multiple-case study", "citation": "Silvio Cardinali, Piyush Sharma, Elena Cedrola, Marta Giovannetti, Kishore Gopalakrishna Pillai (2024). Journal of Business & Industrial Marketing.", "authors": [ "Silvio Cardinali", "Piyush Sharma", "Elena Cedrola", "Marta Giovannetti", "Kishore Gopalakrishna Pillai" ], "year": 2024, "journal": "Journal of Business & Industrial Marketing", "doi": "10.1108/JBIM-03-2023-0157", "doi_url": "https://doi.org/10.1108/JBIM-03-2023-0157", "primary_url": "https://doi.org/10.1108/JBIM-03-2023-0157", "accessible_url": "https://doi.org/10.1108/JBIM-03-2023-0157", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do emerging developments, including virtual/hybrid relations and technology, shape interactions, flexibility, and performance in SME buying centers?", "design": "Qualitative multiple-case research of manufacturing SMEs; five Italian companies were selected to represent diverse stakeholder characteristics, practices, and policies, with selection continuing until issue saturation.", "sample_context": "Five Italian manufacturing companies/SMEs and their buying-center stakeholders.", "findings": "Collaboration and exchange among buying-center members are more effective than competition/power struggles. Virtual/hybrid relations require greater intra-group cooperation; diverse backgrounds and collaboration support flexibility and performance. Technology increases certainty and automation but can create overload and biases, requiring analytical ability and clear decision responsibility.", "limitations": "Only five Italian companies were studied. The authors call for research in other countries with different cultural and socioeconomic conditions and using other methods.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Direct publisher record verifies exact title, authors, DOI, journal, year/pages, qualitative design, five-company setting, findings, and explicit limitations; the article is marked available to purchase, so this is abstract-level evidence rather than verified full text. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224b-3b7c-74da-afcb-6085fb03754f" ], "corrections": [], "plain_english_summary": "Collaboration and exchange among buying-center members are more effective than competition/power struggles. Virtual/hybrid relations require greater intra-group cooperation; diverse backgrounds and collaboration support flexibility and performance. Technology increases certainty and automation but can create overload and biases, requiring analytical ability and clear decision responsibility. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "digital-service-innovation-in-b2b-markets", "title": "Digital service innovation in B2B markets", "category": "Pricing and monetization", "study_type": "Conceptual paper / research synthesis and agenda", "citation": "Christian Kowalkowski, Jochen Wirtz, Michael Ehret (2024). Journal of Service Management.", "authors": [ "Christian Kowalkowski", "Jochen Wirtz", "Michael Ehret" ], "year": 2024, "journal": "Journal of Service Management", "doi": "10.1108/JOSM-12-2022-0403", "doi_url": "https://doi.org/10.1108/JOSM-12-2022-0403", "primary_url": "https://doi.org/10.1108/JOSM-12-2022-0403", "accessible_url": "https://www.diva-portal.org/smash/get/diva2:1825573/FULLTEXT01.pdf", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do IoT, intelligent automation, and digital platforms reshape the offering, process, and ecosystem dimensions of service innovation in B2B markets, and what research priorities follow?", "design": "Conceptual techno-demarcation framework synthesizing service-innovation literature and mapping three signature technologies across service offering, service process, and service ecosystem dimensions.", "sample_context": "B2B markets broadly, including manufacturing and professional-service industries; no empirical respondent or organizational sample (not applicable to this conceptual paper).", "findings": "IoT can turn physical resources into reconfigurable service products; intelligent automation can augment/automate service processes; and digital platforms provide technical/organizational infrastructure for integrating resources and stakeholders. The six proposed agenda themes are recurring revenue models, metaverse service innovation, scaling, ecosystem innovation, power/dependency and lock-in, and security/responsibility.", "limitations": "As a conceptual paper, it does not estimate effects or validate the framework with primary data. The authors frame the agenda as priorities for future empirical work; applicability across industries and technologies therefore remains to be tested.", "founder_use": "Treat this as evidence for the specific pricing and monetization question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Direct author-hosted full-text PDF reports the title, authors, DOI, paper type, purpose, design, findings, and agenda. Evidence strength: strong for the conceptual claims; no empirical effect/sample claims are made. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224b-5f2f-74d8-a8cd-70313e29ba8e" ], "corrections": [], "plain_english_summary": "IoT can turn physical resources into reconfigurable service products; intelligent automation can augment/automate service processes; and digital platforms provide technical/organizational infrastructure for integrating resources and stakeholders. The six proposed agenda themes are recurring revenue models, metaverse service innovation, scaling, ecosystem innovation, power/dependency and lock-in, and security/responsibility. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "satisfied-but-no-payment-the-impact-of-perceived-value-on-continuance-in", "title": "Satisfied but no payment: The impact of perceived value on continuance intention and purchase intention in music streaming services", "category": "Pricing and monetization", "study_type": "Quantitative survey study / structural equation modeling", "citation": "Kittiporn Sae-tae, Qian Wang (2024). Telematics and Informatics Reports.", "authors": [ "Kittiporn Sae-tae", "Qian Wang" ], "year": 2024, "journal": "Telematics and Informatics Reports", "doi": "10.1016/j.teler.2024.100179", "doi_url": "https://doi.org/10.1016/j.teler.2024.100179", "primary_url": "https://doi.org/10.1016/j.teler.2024.100179", "accessible_url": "https://doi.org/10.1016/j.teler.2024.100179", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do usefulness, ease of use, enjoyment, perceived value, satisfaction, and continuance intention relate to purchase intention for freemium and premium music-streaming users in Thailand?", "design": "Online questionnaire analyzed with structural equation modeling using an extended technology acceptance model.", "sample_context": "443 respondents reporting music-streaming use in Thailand; the publisher identifies the article as an open-access research article.", "findings": "Perceived usefulness, ease of use, and enjoyment positively related to perceived value; perceived value positively related to satisfaction, continuance intention, and purchase intention. Satisfaction and continuance intention did not significantly predict purchase intention. Content and users' emotional responses were important to use and subscription decisions.", "limitations": "The direct publisher abstract does not enumerate limitations; the single-country online, self-report, cross-sectional sample limits generalizability and does not establish actual payment or renewal behavior.", "founder_use": "Treat this as evidence for the specific pricing and monetization question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Strong direct publisher full-text evidence from Elsevier: title, authors, December 2024 publication, DOI, N=443, SEM design, and reported relationships are on the article page. No duplication check was possible. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224b-a33c-71c2-b05d-9d5dd4d04e96" ], "corrections": [], "plain_english_summary": "Perceived usefulness, ease of use, and enjoyment positively related to perceived value; perceived value positively related to satisfaction, continuance intention, and purchase intention. Satisfaction and continuance intention did not significantly predict purchase intention. Content and users' emotional responses were important to use and subscription decisions. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (443); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "the-adoption-of-artificial-intelligence-in-human-resources-management-pr", "title": "The adoption of artificial intelligence in human resources management practices", "category": "Customer behavior and adoption", "study_type": "Empirical quantitative survey study", "citation": "Nishad Nawaz, Hemalatha Arunachalam, Barani Kumari Pathi, Vijayakumar Gajender (2024). International Journal of Information Management Data Insights.", "authors": [ "Nishad Nawaz", "Hemalatha Arunachalam", "Barani Kumari Pathi", "Vijayakumar Gajender" ], "year": 2024, "journal": "International Journal of Information Management Data Insights", "doi": "10.1016/j.jjimei.2023.100208", "doi_url": "https://doi.org/10.1016/j.jjimei.2023.100208", "primary_url": "https://doi.org/10.1016/j.jjimei.2023.100208", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S266709682300054X", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Which AI-technology characteristics\u2014accuracy, automation, computing power/capacity, real-time experience, and personalization\u2014affect time-saving and cost reduction in HRM practice adoption?", "design": "Online questionnaire analyzed with IBM SPSS 21 and AMOS 21; the publisher abstract describes a proposed research framework but does not give the precise statistical model or scale-development procedure.", "sample_context": "274 IT employees in Chennai City; online questionnaire. The abstract does not state organizational sectors, sampling method, demographics, or whether respondents were HR users.", "findings": "Accuracy, computing power/capacity, and personalization significantly influence time-saving and cost reduction; automation and real-time experience do not significantly influence that outcome.", "limitations": "The publisher abstract does not report limitations, response rate, common-method controls, or generalizability analysis; these should be checked in the full paper rather than inferred.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Elsevier publisher page is an open-access record for the 2024 issue article and directly supplies authors, DOI, n=274, Chennai setting, analysis software, and the significant/non-significant findings. Evidence is strong for the reported sample and directional results, but the abstract alone does not establish causal adoption effects. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-071b-76fe-9bf5-b64842166973" ], "corrections": [], "plain_english_summary": "Accuracy, computing power/capacity, and personalization significantly influence time-saving and cost reduction; automation and real-time experience do not significantly influence that outcome. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (274); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "value-creation-in-data-centric-b2b-platforms-a-model-based-on-multiple-c", "title": "Value creation in data-centric B2B platforms: A model based on multiple case studies", "category": "B2B growth and sales", "study_type": "Qualitative multiple-case study", "citation": "Ilaria Mancuso, Antonio Messeni Petruzzelli, Umberto Panniello (2024). Industrial Marketing Management.", "authors": [ "Ilaria Mancuso", "Antonio Messeni Petruzzelli", "Umberto Panniello" ], "year": 2024, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2024.04.001", "doi_url": "https://doi.org/10.1016/j.indmarman.2024.04.001", "primary_url": "https://doi.org/10.1016/j.indmarman.2024.04.001", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S001985012400049X", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Who manages data in data-centric B2B platforms, what data-acquisition/manipulation activities do they perform, and how are those relationships governed to create value?", "design": "Multiple-case analysis with coding and cross-case comparison of three data-centric B2B platforms; the paper develops a model from the cases.", "sample_context": "Three industrial B2B platforms: Siemens MindSphere, Airbus Skywise, and Eni Open-es. The source specifies three cases but does not report a respondent sample size.", "findings": "Clients, providers, and enablers relate through data acquisition and manipulation. Governance mechanisms and boundary resources (including APIs, SDKs, connectivity devices, interfaces, rulesets and data-sharing agreements) support transactions, complementary applications, data-driven matching/network effects, new data-enabled business models, and faster/better decisions. The model distinguishes transactional and innovation behaviors and mechanisms of value creation.", "limitations": "Only three incumbent platforms in industrial productive environments were studied; generalizability to other sectors, SMEs/start-ups, and other platform configurations is uncertain. The study is qualitative, does not test the model quantitatively, focuses on value creation rather than value capture, and excludes platforms where data are only transacted.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher full text provides the exact bibliographic record, abstract, explicit research questions, case-method section, findings, and a named limitations/future-research section. Evidence strength: strong (full publisher text). Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224b-d1b6-76b7-af44-6bdfe23cfe16" ], "corrections": [], "plain_english_summary": "Clients, providers, and enablers relate through data acquisition and manipulation. Governance mechanisms and boundary resources (including APIs, SDKs, connectivity devices, interfaces, rulesets and data-sharing agreements) support transactions, complementary applications, data-driven matching/network effects, new data-enabled business models, and faster/better decisions. The model distinguishes transactional and innovation behaviors and mechanisms of value creation. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.8/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "whether-to-add-a-digital-product-into-subscription-service", "title": "Whether to Add a Digital Product into Subscription Service?", "category": "Pricing and monetization", "study_type": "Analytical/theoretical pricing model with numerical analysis", "citation": "Linlan Zhang, Yu Zhang (2024). Journal of Theoretical and Applied Electronic Commerce Research.", "authors": [ "Linlan Zhang", "Yu Zhang" ], "year": 2024, "journal": "Journal of Theoretical and Applied Electronic Commerce Research", "doi": "10.3390/jtaer19020048", "doi_url": "https://doi.org/10.3390/jtaer19020048", "primary_url": "https://doi.org/10.3390/jtaer19020048", "accessible_url": "https://doi.org/10.3390/jtaer19020048", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "When should a digital-products platform add a newly released product to its subscription service rather than sell it only at retail, given piracy and existing subscribers?", "design": "Monopoly firm model comparing two strategies (include vs exclude the new product from subscription), solved analytically and examined with comprehensive numerical analysis of profit, retail price, and piracy rate.", "sample_context": "No human sample; theoretical digital-products platform setting covering software, music, film, and e-books, with consumer valuation, piracy quality/cost, subscription fee, existing-subscriber share, and usage quantity as model variables.", "findings": "Adding the new product is better when the existing-subscriber percentage is below a threshold and the subscription price is above a threshold. The paper also derives how key variables affect profit and piracy rate and gives pricing/piracy-control implications.", "limitations": "The direct full text is a stylized model rather than observed-market evidence; results depend on its assumptions about a monopolist, consumer valuation, piracy, and subscription/retail choices. It does not provide an empirical sample or estimate real willingness-to-pay.", "founder_use": "Treat this as evidence for the specific pricing and monetization question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Strong direct publisher full-text evidence from the MDPI article: publication date 20 April 2024, authors, pages 921\u2013941, model setup, assumptions, numerical analysis, and conclusions are visible in the full open paper. No duplication check was possible. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-3d3b-7332-bcab-d797d8c22c6a" ], "corrections": [], "plain_english_summary": "Adding the new product is better when the existing-subscriber percentage is below a threshold and the subscription price is above a threshold. The paper also derives how key variables affect profit and piracy rate and gives pricing/piracy-control implications. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.8/1", "note": "The source reports a comparison; check the original methods for its construction." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "a-quest-for-research-and-knowledge-gaps-in-cybersecurity-awareness-for-s", "title": "A quest for research and knowledge gaps in cybersecurity awareness for small and medium-sized enterprises", "category": "Marketing capability and growth", "study_type": "Systematic literature review / research-gap synthesis", "citation": "Sunil Chaudhary, Vasileios Gkioulos, Sokratis Katsikas (2023). Computer Science Review.", "authors": [ "Sunil Chaudhary", "Vasileios Gkioulos", "Sokratis Katsikas" ], "year": 2023, "journal": "Computer Science Review", "doi": "10.1016/j.cosrev.2023.100592", "doi_url": "https://doi.org/10.1016/j.cosrev.2023.100592", "primary_url": "https://doi.org/10.1016/j.cosrev.2023.100592", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S157401372300059X", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Which cybersecurity-awareness aspects require further research specifically for SMEs, and what knowledge gaps should guide SME-focused awareness research?", "design": "Systematic literature review prioritizing studies focused on SMEs and analyzing/evaluating them for research gaps; the publisher record states that no new dataset was used.", "sample_context": "Published research studies on cybersecurity awareness or related domains, with priority given to SME-focused studies; the publisher abstract does not state the number of included papers.", "findings": "SMEs often lack resources, expertise, and incentives to prioritize cybersecurity; SME-exclusive cybersecurity-awareness research is rare. The review maps gaps and provides directions for adapting awareness research to SME needs.", "limitations": "The accessible publisher abstract does not enumerate review-search, inclusion, or evidence-quality limitations and does not report the included-study count; consult the full paper before making stronger claims.", "founder_use": "Treat this as evidence for the specific marketing capability and growth question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Elsevier/ScienceDirect publisher record labels this an open-access review article, gives the exact title/authors/DOI and directly states the review purpose, SME focus, and conclusions. It is a strong cybersecurity/SME research-synthesis candidate, but the abstract does not provide study counts or detailed gap taxonomy. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-7254-761d-8fc8-993809f11c29" ], "corrections": [], "plain_english_summary": "SMEs often lack resources, expertise, and incentives to prioritize cybersecurity; SME-exclusive cybersecurity-awareness research is rare. The review maps gaps and provides directions for adapting awareness research to SME needs. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "access-based-customer-journeys", "title": "Access-based customer journeys", "category": "Customer behavior and adoption", "study_type": "Full-text qualitative longitudinal, multi-method customer-journey study", "citation": "Lez Trujillo-Torres, Eda Anlamlier, Laetitia Mimoun, Lagnajita Chatterjee, Delphine Dion (2023). Journal of the Academy of Marketing Science.", "authors": [ "Lez Trujillo-Torres", "Eda Anlamlier", "Laetitia Mimoun", "Lagnajita Chatterjee", "Delphine Dion" ], "year": 2023, "journal": "Journal of the Academy of Marketing Science", "doi": "10.1007/s11747-023-00942-6", "doi_url": "https://doi.org/10.1007/s11747-023-00942-6", "primary_url": "https://doi.org/10.1007/s11747-023-00942-6", "accessible_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10201483/", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do customers shape access-based platform journeys through prosumption/job crafting, and what are the implications for managing digital platform journeys?", "design": "Longitudinal multi-method case study of Rent the Runway: customer and blogger interviews, social-media posts, marketing materials and news articles. Analysis uses staged qualitative coding to identify journey dynamics, job-crafting practices and collective outcomes.", "sample_context": "US access-based fashion-rental platform Rent the Runway. Interview participants were all women, average age 34, recruited through convenience/snowball sampling; most had Unlimited memberships. The study also analyzes bloggers and platform/marketplace documentary and social-media material; the publisher/open paper should be consulted for the complete corpus details.", "findings": "Access-based journeys are systemic, tightly coupled and vulnerable to circularity failures; customers act as prosumers and bypass, stretch or hack platform policies to personalize journeys. Job crafting can create individual value and collective problems, but can also reveal innovations that platforms may formalize. Managers therefore need agility and monitoring rather than assuming a fully controllable linear journey.", "limitations": "The authors stress that the qualitative findings are a starting point with limited generalizability/refutability, focus on highly intermediated/low-consociality platforms, and call for research across other intermediation levels, customer-to-customer supply chains and non-platform contexts.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "PMC provides the publisher-linked full text with DOI, abstract, method, participant setting, findings and limitations; the authors' City Research Online page independently exposes the accepted/open paper and exact bibliographic record. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-fd80-77de-9f82-d7a53c1d1e94" ], "corrections": [], "plain_english_summary": "Access-based journeys are systemic, tightly coupled and vulnerable to circularity failures; customers act as prosumers and bypass, stretch or hack platform policies to personalize journeys. Job crafting can create individual value and collective problems, but can also reveal innovations that platforms may formalize. Managers therefore need agility and monitoring rather than assuming a fully controllable linear journey. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (34,); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.8/1", "note": "The source reports a comparison; check the original methods for its construction." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "chatbots-effectiveness-in-service-recovery", "title": "Chatbots\u2019 effectiveness in service recovery", "category": "Customer behavior and adoption", "study_type": "Mixed-method empirical research (scenario-based quantitative studies plus exploratory and qualitative work)", "citation": "Arpita Agnihotri, Saurabh Bhattacharya (2023). International Journal of Information Management.", "authors": [ "Arpita Agnihotri", "Saurabh Bhattacharya" ], "year": 2023, "journal": "International Journal of Information Management", "doi": "10.1016/j.ijinfomgt.2023.102679", "doi_url": "https://doi.org/10.1016/j.ijinfomgt.2023.102679", "primary_url": "https://doi.org/10.1016/j.ijinfomgt.2023.102679", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0268401223000609", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Which chatbot traits make chatbot-led service recovery effective, and through what mechanisms do they reduce negative consumer responses after service failure?", "design": "The paper reports exploratory work used to select the online-retailing/delayed-order context, a scenario-based survey study and a second/robustness study, followed by a qualitative study. The quantitative model tests mediation through chatbot trustworthiness and downstream forgiveness/negative word of mouth.", "sample_context": "The main final survey sample was 586 UK consumers (304 women; median age 31.02; median income \u00a332,000) responding to an online-retailing delayed-order recovery scenario. The exploratory work included 28 postgraduate students; the paper also reports a separate qualitative study (the publisher page contains its method/results).", "findings": "Perceived safety, empathy and anthropomorphism affect different components of chatbot trustworthiness; trustworthiness increases willingness to forgive after failure and reduces negative word of mouth. The paper highlights privacy concerns as a countervailing issue and finds chatbot traits work through trust-related mechanisms rather than as undifferentiated design features.", "limitations": "The authors did not test contingency conditions that could attenuate the effects, call for cross-cultural comparisons, did not resolve recovery when the AI itself caused the failure, and used a service-failure scenario/context that may not generalize to other chatbot types or service settings.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher-hosted ScienceDirect full text exposes the DOI, authors, method sections, sample table, results, conclusion and limitations; this is direct evidence rather than an abstract-only record. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-d532-73da-aea8-76bc252b4047" ], "corrections": [], "plain_english_summary": "Perceived safety, empathy and anthropomorphism affect different components of chatbot trustworthiness; trustworthiness increases willingness to forgive after failure and reduces negative word of mouth. The paper highlights privacy concerns as a countervailing issue and finds chatbot traits work through trust-related mechanisms rather than as undifferentiated design features. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (586); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "factors-influencing-free-and-open-source-software-adoption-in-developing", "title": "Factors influencing free and open-source software adoption in developing countries\u2014an empirical study", "category": "Marketing capability and growth", "study_type": "Empirical survey study using SEM-PLS", "citation": "Domingos G. Silva, Carlos Coutinho, Carlos J. Costa (2023). Journal of Open Innovation: Technology, Market, and Complexity.", "authors": [ "Domingos G. Silva", "Carlos Coutinho", "Carlos J. Costa" ], "year": 2023, "journal": "Journal of Open Innovation: Technology, Market, and Complexity", "doi": "10.1016/j.joitmc.2023.01.002", "doi_url": "https://doi.org/10.1016/j.joitmc.2023.01.002", "primary_url": "https://doi.org/10.1016/j.joitmc.2023.01.002", "accessible_url": "https://doi.org/10.1016/j.joitmc.2023.01.002", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "To what extent do cost, system quality, usability, interoperability, security, performance expectation, and social influence affect intention to adopt/use FOSS in developing-country organizations?", "design": "Survey-based theoretical-model test using partial least squares structural equation modeling (SEM-PLS). The directly accessible author/institution record does not state the survey sample size or detailed sampling frame.", "sample_context": "Organizations/public-sector context in developing countries; the source describes a survey and developing-country FOSS organizations but does not report an exact respondent or organization count in the accessible abstract/record.", "findings": "The abstract reports significant relationships between FOSS adoption and low cost, performance expectation, social influence, and system quality; safety/security, interoperability, and usability are described as especially important in adoption decisions. The paper proposes a new adoption model.", "limitations": "The accessible direct record does not provide a detailed limitations section, sample size, country breakdown, or sampling procedure; generalizability beyond the studied developing-country setting and self-reported intention is therefore not established from the available evidence.", "founder_use": "Treat this as evidence for the specific marketing capability and growth question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI landing content and the University of Lisbon author/institution record verify title, authors, journal, year, peer-review status, purpose, survey/SEM-PLS design, and abstract findings. Evidence strength: moderate for reported abstract claims; insufficient for unreported sample details or effect sizes. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224d-3e92-73ea-baf1-9389c0b8cb54" ], "corrections": [], "plain_english_summary": "The abstract reports significant relationships between FOSS adoption and low cost, performance expectation, social influence, and system quality; safety/security, interoperability, and usability are described as especially important in adoption decisions. The paper proposes a new adoption model. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "technology-readiness-of-b2b-firms-and-ai-based-customer-relationship-man", "title": "Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance", "category": "B2B growth and sales", "study_type": "Empirical quantitative research article", "citation": "Muhammad Sabbir Rahman, Surajit Bag, Shivam Gupta, Uthayasankar Sivarajah (2023). Journal of Business Research.", "authors": [ "Muhammad Sabbir Rahman", "Surajit Bag", "Shivam Gupta", "Uthayasankar Sivarajah" ], "year": 2023, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2022.113525", "doi_url": "https://doi.org/10.1016/j.jbusres.2022.113525", "primary_url": "https://doi.org/10.1016/j.jbusres.2022.113525", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296322009900", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How does B2B-firm technology readiness relate to ICT capability, AI-based CRM capability, relationship performance, and social-sustainability performance, and do mediation/moderation mechanisms apply?", "design": "Primary-data empirical model grounded in the dynamic capability view; the publisher abstract reports mediation of technology readiness \u2192 AI-CRM by ICT capability and moderation by industry dynamism, but does not specify the estimator in the accessible abstract.", "sample_context": "217 B2B-firm samples; the publisher abstract does not provide country, respondent role, sampling frame, or industry breakdown.", "findings": "Technology readiness positively relates to ICT and AI-CRM capability; ICT capability positively relates to AI-CRM capability; relationship performance positively relates to social-sustainability performance. ICT capability mediates the technology-readiness/AI-CRM link, and industry dynamism moderates the ICT-capability/AI-CRM link.", "limitations": "The accessible publisher abstract does not state limitations; the paper's full text should be checked for sampling, cross-sectional, measurement, and generalizability limitations rather than inferring them.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Elsevier/ScienceDirect publisher record identifies this as a 2023, open-access research article and supplies the exact author list, DOI, n=217, model relationships, mediation, and moderation in its abstract. Strong direct evidence for B2B AI-CRM/adoption relevance; contextual details and limitations require full-text editorial review. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1224c-a1df-76dc-918c-85b3511a49ac" ], "corrections": [], "plain_english_summary": "Technology readiness positively relates to ICT and AI-CRM capability; ICT capability positively relates to AI-CRM capability; relationship performance positively relates to social-sustainability performance. ICT capability mediates the technology-readiness/AI-CRM link, and industry dynamism moderates the ICT-capability/AI-CRM link. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (217); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "from-capabilities-to-performance-in-ai-driven-b2b-saas-website-interacti", "title": "From capabilities to performance in AI-driven B2B SaaS: Website interactivity and regional differences under digital transformation", "category": "B2B growth and sales", "study_type": "Full-text open-access quantitative empirical study", "citation": "Hea Sun Lee, Margaret Jekanyika Matanda (2026). Industrial Marketing Management.", "authors": [ "Hea Sun Lee", "Margaret Jekanyika Matanda" ], "year": 2026, "journal": "Industrial Marketing Management", "doi": "10.1016/j.indmarman.2026.03.019", "doi_url": "https://doi.org/10.1016/j.indmarman.2026.03.019", "primary_url": "https://doi.org/10.1016/j.indmarman.2026.03.019", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0019850126000581", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do exploration and exploitation capabilities, AI-enabled website interactivity and technological turbulence affect B2B SaaS performance across US and Asia-Pacific markets?", "design": "Survey analysis grounded in ambidexterity theory; tests direct capability effects, mediation by AI-enabled website interactivity, regional differences and moderation by technological turbulence.", "sample_context": "362 B2B SaaS providers in the United States and Asia Pacific.", "findings": "US providers benefited directly from both exploration and exploitation and indirectly through website interactivity; Asia-Pacific providers benefited solely through the indirect website-interactivity path. Higher technological turbulence intensified the positive mediation effect.", "limitations": "The accessible abstract does not state detailed study limitations; editorial review of the full paper is needed for the limitations section.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12257-a2eb-77ce-913a-72308ae06a64" ], "corrections": [], "plain_english_summary": "US providers benefited directly from both exploration and exploitation and indirectly through website interactivity; Asia-Pacific providers benefited solely through the indirect website-interactivity path. Higher technological turbulence intensified the positive mediation effect. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (362); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "customer-experience-management-in-b2b-markets-cxm-value-propositions-and", "title": "Customer experience management in B2B markets: CXM value propositions and archetypical CXM strategies", "category": "B2B growth and sales", "study_type": "Full-text open-access conceptual research article", "citation": "Jochen Wirtz, Christian Kowalkowski, Elina Jaakkola, Maria Holmlund, Wolfgang Ulaga, Tanvir Ahmed (2024). Journal of Business Research.", "authors": [ "Jochen Wirtz", "Christian Kowalkowski", "Elina Jaakkola", "Maria Holmlund", "Wolfgang Ulaga", "Tanvir Ahmed" ], "year": 2024, "journal": "Journal of Business Research", "doi": "10.1016/j.jbusres.2024.115165", "doi_url": "https://doi.org/10.1016/j.jbusres.2024.115165", "primary_url": "https://doi.org/10.1016/j.jbusres.2024.115165", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0148296324006696", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "What customer goals and value propositions should guide B2B customer-experience management instead of a one-size-fits-all \u201cmore is better\u201d approach?", "design": "Conceptual synthesis and framework development from B2B customer-experience and value literature; proposes goal categories, CXM value propositions, four strategies and a research agenda rather than reporting a primary sample.", "sample_context": "No original respondent sample reported; B2B customer-experience management literature and business-market contexts.", "findings": "Defines Relieving, Enabling and Enriching CX value propositions and four archetypical CXM strategies: Champion, Cherry Picker, Minimalist and Fashionista; supplies a four-step managerial guide.", "limitations": "No primary empirical sample; the article proposes a framework and explicitly calls for research on strategy drivers and contextual factors.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12258-15da-7379-af6d-c400be33524e" ], "corrections": [], "plain_english_summary": "Defines Relieving, Enabling and Enriching CX value propositions and four archetypical CXM strategies: Champion, Cherry Picker, Minimalist and Fashionista; supplies a four-step managerial guide. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "unraveling-the-determinants-of-saas-performance-a-dynamic-capabilities-p", "title": "Unraveling the determinants of SaaS performance: a dynamic capabilities perspective", "category": "B2B growth and sales", "study_type": "Full-text open-access exploratory qualitative case study", "citation": "Hea Sun Lee, Margaret Jekanyika Matanda (2026). Journal of Business & Industrial Marketing.", "authors": [ "Hea Sun Lee", "Margaret Jekanyika Matanda" ], "year": 2026, "journal": "Journal of Business & Industrial Marketing", "doi": "10.1108/JBIM-10-2024-0751", "doi_url": "https://doi.org/10.1108/JBIM-10-2024-0751", "primary_url": "https://doi.org/10.1108/JBIM-10-2024-0751", "accessible_url": "https://doi.org/10.1108/JBIM-10-2024-0751", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Which organizational determinants align with sensing, seizing and transforming capabilities to explain SaaS-provider performance?", "design": "Exploratory qualitative case study; thematic analysis of interviews interpreted through dynamic-capabilities dimensions.", "sample_context": "Ten small and medium-sized SaaS providers headquartered in South Korea.", "findings": "Seven determinants were identified: marketing activities and website functionality/interactivity support sensing; customized innovation, security certifications, B2B partnerships and information sharing support seizing; the paper maps further determinants to transforming.", "limitations": "The accessible publisher summary does not expose a detailed limitations section; the small, South Korea-centered qualitative sample limits transferability and warrants editorial review.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12256-8e50-75db-bf43-eb95aba4617f" ], "corrections": [], "plain_english_summary": "Seven determinants were identified: marketing activities and website functionality/interactivity support sensing; customized innovation, security certifications, B2B partnerships and information sharing support seizing; the paper maps further determinants to transforming. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "co-creation-in-b2b-ai-sales-buyers-perspectives-from-a-mixed-method-stud", "title": "Co-creation in B2B AI sales: buyers\u2019 perspectives from a mixed-method study", "category": "B2B growth and sales", "study_type": "Abstract-supported mixed-method empirical study", "citation": "Daniel Fehrenbach, Carlos Herrando (2026). Journal of Business & Industrial Marketing.", "authors": [ "Daniel Fehrenbach", "Carlos Herrando" ], "year": 2026, "journal": "Journal of Business & Industrial Marketing", "doi": "10.1108/JBIM-04-2025-0303", "doi_url": "https://doi.org/10.1108/JBIM-04-2025-0303", "primary_url": "https://doi.org/10.1108/JBIM-04-2025-0303", "accessible_url": "https://doi.org/10.1108/JBIM-04-2025-0303", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How can co-creation be integrated into the B2B AI sales funnel, and what makes industrial buyers willing to co-create?", "design": "Sequential mixed methods: case study of a manufacturing startup\u2019s real-world sales process; in-depth buyer interviews with thematic analysis; then a second-stage quantitative test of the framework.", "sample_context": "Industrial buyers involved with a manufacturing startup; the accessible abstract does not give the quantitative-stage n.", "findings": "Buyer engagement depends on supplier-selection criteria, buyer role/readiness and project-specific factors; positive prior attitudes, perceived value and willingness predict co-creation intention.", "limitations": "The accessible publisher record does not state sample sizes or detailed limitations for the quantitative stage; editorial review required before library inclusion.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12256-f418-779e-9125-b8b910329477" ], "corrections": [], "plain_english_summary": "Buyer engagement depends on supplier-selection criteria, buyer role/readiness and project-specific factors; positive prior attitudes, perceived value and willingness predict co-creation intention. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "the-evolution-of-performance-measurement-systems-in-saas-startups-a-cont", "title": "The evolution of performance measurement systems in SaaS startups: a contingency-based approach across the investment cycle", "category": "B2B growth and sales", "study_type": "Abstract-supported qualitative empirical study", "citation": "Bruno S. D. Santos, Luiz G. R. Antunes, Rafael F. Falc\u00e3o, Luiz F. Lugoboni (2026). Journal of Entrepreneurship in Emerging Economies.", "authors": [ "Bruno S. D. Santos", "Luiz G. R. Antunes", "Rafael F. Falc\u00e3o", "Luiz F. Lugoboni" ], "year": 2026, "journal": "Journal of Entrepreneurship in Emerging Economies", "doi": "10.1108/JEEE-06-2025-0319", "doi_url": "https://doi.org/10.1108/JEEE-06-2025-0319", "primary_url": "https://doi.org/10.1108/JEEE-06-2025-0319", "accessible_url": "https://doi.org/10.1108/JEEE-06-2025-0319", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do SaaS startups structure and evolve performance-measurement systems across stages of venture funding?", "design": "Nine semi-structured interviews with founders and CEOs; open, axial and selective coding used to build an emergent theoretical model.", "sample_context": "Nine SaaS startups at different stages of venture funding; founders and CEOs were interviewed.", "findings": "Startups did not follow a linear PMS trajectory; they reactively adjusted measurement systems around market expansion, product development and fundraising.", "limitations": "The accessible publisher record does not state detailed limitations beyond the qualitative interview design; generalizability and retrospective-reporting issues require editorial review.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12257-d8ae-725f-b12f-ce149f517fec" ], "corrections": [], "plain_english_summary": "Startups did not follow a linear PMS trajectory; they reactively adjusted measurement systems around market expansion, product development and fundraising. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "artificial-intelligence-adoption-dynamics-and-knowledge-in-smes-and-larg", "title": "Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis", "category": "Customer behavior and adoption", "study_type": "Abstract-supported systematic review and bibliometric analysis", "citation": "Samuel Godadaw Ayinaddis (2025). Journal of Innovation & Knowledge.", "authors": [ "Samuel Godadaw Ayinaddis" ], "year": 2025, "journal": "Journal of Innovation & Knowledge", "doi": "10.1016/j.jik.2025.100682", "doi_url": "https://doi.org/10.1016/j.jik.2025.100682", "primary_url": "https://doi.org/10.1016/j.jik.2025.100682", "accessible_url": "https://doi.org/10.1016/j.jik.2025.100682", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do AI-adoption dynamics and knowledge differ between SMEs and large firms?", "design": "Systematic literature review combined with bibliometric analysis of research on firm-size differences in AI adoption and implementation.", "sample_context": "Published literature on SMEs and larger firms; the accessible publisher page does not state the final article count in the scraped excerpt.", "findings": "The review addresses fragmented evidence and compares tools, implementation and outcomes across firm sizes; detailed synthesized results require the full paper.", "limitations": "The accessible publisher record supplies the review question and design but not detailed limitations or a complete result table.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12259-0551-72a6-babe-b467e1e1a114" ], "corrections": [], "plain_english_summary": "The review addresses fragmented evidence and compares tools, implementation and outcomes across firm sizes; detailed synthesized results require the full paper. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "what-drives-artificial-intelligence-adoption-and-use-among-firms-empiric", "title": "What drives artificial intelligence adoption and use among firms? Empirical evidence from Brazilian companies", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "Rafael Katz, Joon Jung (2026). Digital Policy, Regulation and Governance.", "authors": [ "Rafael Katz", "Joon Jung" ], "year": 2026, "journal": "Digital Policy, Regulation and Governance", "doi": "10.1108/DPRG-05-2025-0135", "doi_url": "https://doi.org/10.1108/DPRG-05-2025-0135", "primary_url": "https://doi.org/10.1108/DPRG-05-2025-0135", "accessible_url": "https://doi.org/10.1108/DPRG-05-2025-0135", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "Which firm and environmental factors predict AI adoption, diffusion within firms and intensity of use?", "design": "Microdata from Brazilian firms analyzed with standard, ordered and multivariate probit models.", "sample_context": "Brazilian enterprises; the accessible abstract does not report the microdata sample size.", "findings": "Company size positively influenced AI adoption and use; digitized environments increased adoption likelihood through network effects; competition intensity had a nonlinear effect that initially stimulated adoption.", "limitations": "The publisher abstract does not report sample size or detailed limitations; country-specific microdata and observational modeling warrant editorial review.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12258-8e95-7572-b641-fe0a4670d16b" ], "corrections": [], "plain_english_summary": "Company size positively influenced AI adoption and use; digitized environments increased adoption likelihood through network effects; competition intensity had a nonlinear effect that initially stimulated adoption. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "effects-of-managers-environmental-consciousness-and-digital-expertise-on", "title": "Effects of managers' environmental consciousness and digital expertise on their technology adoption intentions", "category": "Customer behavior and adoption", "study_type": "Full-text open-access quantitative survey study", "citation": "Dilupa Nakandala, Richard (Chunhui) Yang, Arun Elias, Rola Fanous (2024). Journal of Cleaner Production.", "authors": [ "Dilupa Nakandala", "Richard (Chunhui) Yang", "Arun Elias", "Rola Fanous" ], "year": 2024, "journal": "Journal of Cleaner Production", "doi": "10.1016/j.jclepro.2024.143558", "doi_url": "https://doi.org/10.1016/j.jclepro.2024.143558", "primary_url": "https://doi.org/10.1016/j.jclepro.2024.143558", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0959652624030075", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do managers\u2019 digital expertise and environmental consciousness affect intentions to adopt Industry 4.0 technologies?", "design": "Online survey integrating Diffusion of Innovations, TAM, UTAUT and decision-making literature; empirical hypothesis testing.", "sample_context": "172 managers; Industry 4.0 organizational context.", "findings": "The study empirically links managers\u2019 digital expertise and environmental consciousness to technology-adoption intentions; the accessible abstract does not expose the complete coefficient pattern.", "limitations": "The accessible publisher excerpt does not state detailed limitations; sample size and online cross-sectional design require cautious generalization.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12258-b62d-726d-bb3c-ac2e0492d356" ], "corrections": [], "plain_english_summary": "The study empirically links managers\u2019 digital expertise and environmental consciousness to technology-adoption intentions; the accessible abstract does not expose the complete coefficient pattern. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (172); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "cloud-computing-adoption-in-smes-assessing-the-moderating-role-of-ai-on", "title": "Cloud computing adoption in SMEs: assessing the moderating role of AI on perceived business process performance through D&M model lens", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "Chathurika S. Ahmad, A. S. Bali Mahomed, H. Hashim (2026). Business Process Management Journal.", "authors": [ "Chathurika S. Ahmad", "A. S. Bali Mahomed", "H. Hashim" ], "year": 2026, "journal": "Business Process Management Journal", "doi": "10.1108/BPMJ-01-2025-0103", "doi_url": "https://doi.org/10.1108/BPMJ-01-2025-0103", "primary_url": "https://doi.org/10.1108/BPMJ-01-2025-0103", "accessible_url": "https://doi.org/10.1108/BPMJ-01-2025-0103", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How does cloud-computing quality affect perceived business-process performance in SMEs, and does perceived AI usefulness moderate those effects?", "design": "Structured questionnaire and PLS-SEM grounded in the DeLone and McLean Information Success Model.", "sample_context": "412 SMEs in Pakistan.", "findings": "Information quality and service quality significantly enhanced perceived business-process performance; system quality did not have a meaningful direct effect; perceived AI usefulness amplified the effects of system and information quality.", "limitations": "The accessible abstract does not report detailed limitations; Pakistan-only, cross-sectional, self-reported SME data constrain external validity.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12259-381b-74b9-bc26-34f7bfd1061e" ], "corrections": [], "plain_english_summary": "Information quality and service quality significantly enhanced perceived business-process performance; system quality did not have a meaningful direct effect; perceived AI usefulness amplified the effects of system and information quality. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (412); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "technology-adoption-and-digital-maturity-in-the-conformity-assessment-in", "title": "Technology adoption and digital maturity in the conformity assessment industry: Empirical evidence from an international study", "category": "B2B growth and sales", "study_type": "Full-text open-access mixed qualitative/quantitative empirical study", "citation": "Luana Ladu, Claudia Koch, Parsa Asna Ashari, Knut Blind, Pavel Castka (2024). Technology in Society.", "authors": [ "Luana Ladu", "Claudia Koch", "Parsa Asna Ashari", "Knut Blind", "Pavel Castka" ], "year": 2024, "journal": "Technology in Society", "doi": "10.1016/j.techsoc.2024.102564", "doi_url": "https://doi.org/10.1016/j.techsoc.2024.102564", "primary_url": "https://doi.org/10.1016/j.techsoc.2024.102564", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0160791X2400112X", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How should digital maturity be designed for the conformity-assessment industry, and how is maturity associated with technology adoption?", "design": "Industry-specific digital-maturity model developed from extensive expert interviews and tested with international empirical evidence.", "sample_context": "Conformity-assessment industry across an international sample; the accessible excerpt does not expose the quantitative n.", "findings": "Develops an industry-specific maturity model and examines links between digital maturity and technology adoption in a globally regulated industry.", "limitations": "The scraped publisher excerpt does not state detailed limitations or sample size; industry-specific measurement may limit transferability.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12258-622e-73b9-b15f-936e8411b386" ], "corrections": [], "plain_english_summary": "Develops an industry-specific maturity model and examines links between digital maturity and technology adoption in a globally regulated industry. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "an-empirical-investigation-of-traceability-technology-adoption-a-case-of", "title": "An empirical investigation of traceability technology adoption: a case of perishable products supply chain", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "S. Kumar, B. Ramtiyal, G. Soni, L. Vijayvargy, C. Chandra, I. Dey (2026). Benchmarking: An International Journal.", "authors": [ "S. Kumar", "B. Ramtiyal", "G. Soni", "L. Vijayvargy", "C. Chandra", "I. Dey" ], "year": 2026, "journal": "Benchmarking: An International Journal", "doi": "10.1108/BIJ-05-2024-0461", "doi_url": "https://doi.org/10.1108/BIJ-05-2024-0461", "primary_url": "https://doi.org/10.1108/BIJ-05-2024-0461", "accessible_url": "https://doi.org/10.1108/BIJ-05-2024-0461", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "Which technology-readiness, TAM and planned-behavior factors shape traceability adoption in perishable-product supply chains?", "design": "Integrated model combining TAM, Technology Readiness Index and Theory of Planned Behavior; online survey and model testing.", "sample_context": "Perishable-products supply-chain participants; accessible abstract reports an online survey but not the sample size.", "findings": "Optimism and innovativeness did not affect perceived ease of use or utility; behavioral intention was shaped by perceived utility, attitude and perceived behavioral control.", "limitations": "Publisher abstract does not report sample size or detailed limitations; case/sector context and cross-sectional survey require cautious generalization.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12258-e59d-750c-a565-06a453f54863" ], "corrections": [], "plain_english_summary": "Optimism and innovativeness did not affect perceived ease of use or utility; behavioral intention was shaped by perceived utility, attitude and perceived behavioral control. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.8/1", "note": "The source reports a comparison; check the original methods for its construction." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "blockchain-technology-adoption-and-its-impact-on-sme-performance-insight", "title": "Blockchain technology adoption and its impact on SME performance: insights for entrepreneurs and policymakers", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "J. Kumar, G. Rani, M. Rani, V. Rani (2024). Journal of Enterprising Communities: People and Places in the Global Economy.", "authors": [ "J. Kumar", "G. Rani", "M. Rani", "V. Rani" ], "year": 2024, "journal": "Journal of Enterprising Communities: People and Places in the Global Economy", "doi": "10.1108/JEC-02-2024-0034", "doi_url": "https://doi.org/10.1108/JEC-02-2024-0034", "primary_url": "https://doi.org/10.1108/JEC-02-2024-0034", "accessible_url": "https://doi.org/10.1108/JEC-02-2024-0034", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "Which TOE/RBV factors predict blockchain adoption in SMEs, and how does adoption relate to market and financial performance?", "design": "Survey of SMEs; TOE and resource-based-view framework; statistical analysis using PLS-SEM.", "sample_context": "407 SME responses from India.", "findings": "Relative advantage, top-management support, competitive pressure and market dynamics significantly influenced blockchain adoption; the paper also tests adoption\u2019s relationship with SME market and financial performance.", "limitations": "The accessible summary does not state detailed limitations; India-only cross-sectional self-report data limit causal and geographic inference.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12259-7d37-74c9-8366-31c6ed65feb8" ], "corrections": [], "plain_english_summary": "Relative advantage, top-management support, competitive pressure and market dynamics significantly influenced blockchain adoption; the paper also tests adoption\u2019s relationship with SME market and financial performance. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (407); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "utilizing-social-media-and-developing-brand-awareness-to-increase-sales", "title": "Utilizing social media and developing brand awareness to increase sales for B2B consultancy", "category": "B2B growth and sales", "study_type": "Abstract-supported mixed-method empirical study", "citation": "H. Fatorachian, B. Mitchell, P. Boland, C. Petty, Z. Mughal, J. MCcoubrie (2025). SAM Advanced Management Journal.", "authors": [ "H. Fatorachian", "B. Mitchell", "P. Boland", "C. Petty", "Z. Mughal", "J. MCcoubrie" ], "year": 2025, "journal": "SAM Advanced Management Journal", "doi": "10.1108/SAMAMJ-06-2024-0028", "doi_url": "https://doi.org/10.1108/SAMAMJ-06-2024-0028", "primary_url": "https://doi.org/10.1108/SAMAMJ-06-2024-0028", "accessible_url": "https://doi.org/10.1108/SAMAMJ-06-2024-0028", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do social-media use and brand awareness influence sales for B2B consultancy firms in hospitality?", "design": "Literature review plus primary semi-structured interviews with five hospitality businesses.", "sample_context": "Five hospitality businesses in a B2B consultancy context.", "findings": "Social media and a strong online presence were reported to improve brand visibility, client engagement and sales; themes included digital presence and relationship building.", "limitations": "Very small interview sample and hospitality-specific context; the abstract does not report additional limitations or causal performance measures.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a12259-cd54-7459-8def-370b03a94c53" ], "corrections": [], "plain_english_summary": "Social media and a strong online presence were reported to improve brand visibility, client engagement and sales; themes included digital presence and relationship building. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "leveraging-social-media-in-b2b-sales-impact-on-in-role-and-customer-rela", "title": "Leveraging social media in B2B sales: impact on in-role and customer relationship performance", "category": "B2B growth and sales", "study_type": "Abstract-supported quantitative empirical study", "citation": "V. Srivastava, R. Kumar (2026). Journal of Business & Industrial Marketing.", "authors": [ "V. Srivastava", "R. Kumar" ], "year": 2026, "journal": "Journal of Business & Industrial Marketing", "doi": "10.1108/JBIM-09-2024-0732", "doi_url": "https://doi.org/10.1108/JBIM-09-2024-0732", "primary_url": "https://doi.org/10.1108/JBIM-09-2024-0732", "accessible_url": "https://doi.org/10.1108/JBIM-09-2024-0732", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do job-related and personal-branding social-media use affect salesperson in-role performance, customer-relationship performance and sales outcomes?", "design": "Survey of salespeople; mediation/moderation analysis of social-media use, online social capital, in-role performance and relationship performance.", "sample_context": "276 valid salesperson responses across sectors, collected using snowball and purposive sampling.", "findings": "Job-related social-media use improved in-role performance, with online social capital strengthening the effect; its sales-performance effect was indirect through in-role performance. Personal-branding use improved customer-relationship performance.", "limitations": "Non-probability, cross-sectional, self-reported survey; publisher abstract does not expose the full limitations section.", "founder_use": "Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225b-3847-72af-88a3-955daffb5a3a" ], "corrections": [], "plain_english_summary": "Job-related social-media use improved in-role performance, with online social capital strengthening the effect; its sales-performance effect was indirect through in-role performance. Personal-branding use improved customer-relationship performance. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (276); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "beyond-code-generation-an-observational-study-of-chatgpt-usage-in-softwa", "title": "Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice", "category": "Customer behavior and adoption", "study_type": "Full-text observational qualitative empirical study", "citation": "Ranim Khojah, Mazen Mohamad, Philipp Leitner, Francisco Gomes de Oliveira Neto (2024). ACM Transactions on Software Engineering and Methodology.", "authors": [ "Ranim Khojah", "Mazen Mohamad", "Philipp Leitner", "Francisco Gomes de Oliveira Neto" ], "year": 2024, "journal": "ACM Transactions on Software Engineering and Methodology", "doi": "10.1145/3660788", "doi_url": "https://doi.org/10.1145/3660788", "primary_url": "https://doi.org/10.1145/3660788", "accessible_url": "https://dl.acm.org/doi/10.1145/3660788", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How do professional software engineers use ChatGPT in daily work, and what factors shape perceived usefulness and trust?", "design": "One-week observational study; qualitative analysis of ChatGPT dialogue logs and exit-survey reflections; framework organized around interaction purpose, internal factors and external factors.", "sample_context": "24 professional software engineers at 10 companies in Europe, using GPT-3.5 over five business days.", "findings": "Practitioners more often sought guidance or learning than ready-to-use software artifacts; simple artifact generation and brainstorming were useful, complex tasks were harder; about two-thirds expressed high or moderate trust but none trusted outputs entirely, and lack of sources reduced trust.", "limitations": "Limited, Europe-centered nonrepresentative sample; inductive dialogue classification has subjectivity; conducted before ChatGPT Enterprise, so privacy/security effects of that service were not assessed.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225a-652e-765a-ba44-130c725e4941" ], "corrections": [], "plain_english_summary": "Practitioners more often sought guidance or learning than ready-to-use software artifacts; simple artifact generation and brainstorming were useful, complex tasks were harder; about two-thirds expressed high or moderate trust but none trusted outputs entirely, and lack of sources reduced trust. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (24); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "innovation-challenges-of-digital-transformation-transitioning-legacy-to", "title": "Innovation challenges of digital transformation: Transitioning legacy to the future", "category": "Customer behavior and adoption", "study_type": "Full-text open-access quantitative empirical study", "citation": "Ololade A. Shonubi (2025). Sustainable Futures.", "authors": [ "Ololade A. Shonubi" ], "year": 2025, "journal": "Sustainable Futures", "doi": "10.1016/j.sftr.2025.100971", "doi_url": "https://doi.org/10.1016/j.sftr.2025.100971", "primary_url": "https://doi.org/10.1016/j.sftr.2025.100971", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S2666188825005350", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "How does emerging-technology integration relate to organizational, process and product/service innovation as organizations transition from legacy systems?", "design": "Quantitative manager survey across Asian and African contexts; structural equation modeling; tests regional and gender differences.", "sample_context": "Managers from enterprises across Asian and African contexts; accessible abstract does not report sample size.", "findings": "Emerging-technology integration was positively related to organizational, process and product/service innovation across both continents; African enterprises showed stronger process-innovation adaptability despite infrastructure limits; gender differences affected product/service-innovation perceptions.", "limitations": "The accessible abstract does not state sample size or detailed limitations; manager perceptions and cross-sectional regional comparisons limit causal inference.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225a-89e9-714d-bdce-8ff86caadcb8" ], "corrections": [], "plain_english_summary": "Emerging-technology integration was positively related to organizational, process and product/service innovation across both continents; African enterprises showed stronger process-innovation adaptability despite infrastructure limits; gender differences affected product/service-innovation perceptions. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "investigating-the-experiences-of-providing-cyber-security-support-to-sma", "title": "Investigating the experiences of providing cyber security support to small- and medium-sized enterprises", "category": "Marketing capability and growth", "study_type": "Full-text qualitative empirical study", "citation": "Neeshe Khan, Steven Furnell, Maria Bada, Matthew Rand, Jason R. C. Nurse (2025). Computers & Security.", "authors": [ "Neeshe Khan", "Steven Furnell", "Maria Bada", "Matthew Rand", "Jason R. C. Nurse" ], "year": 2025, "journal": "Computers & Security", "doi": "10.1016/j.cose.2025.104448", "doi_url": "https://doi.org/10.1016/j.cose.2025.104448", "primary_url": "https://doi.org/10.1016/j.cose.2025.104448", "accessible_url": "https://www.sciencedirect.com/science/article/pii/S0167404825001373", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "What cybersecurity support do providers offer SMEs, what triggers requests, how effective is support, and how can it improve?", "design": "Semi-structured interviews with support/advice providers; qualitative synthesis of provider experiences, each drawing on exposure to many SMEs.", "sample_context": "12 participants from organizations providing cybersecurity advice or solutions in the UK; participants had cumulative exposure to numerous SMEs.", "findings": "Providers played an assistive role in education and implementation, but SME cyber hygiene and knowledge remained low; comprehension, capability, attitudes and resources constrained security; security-focused communities could improve support, collaboration and learning.", "limitations": "Provider-side perspective rather than direct SME interviews; qualitative design and UK context; each participant\u2019s experience is cumulative rather than a single-firm observation.", "founder_use": "Treat this as evidence for the specific marketing capability and growth question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225a-b987-76ff-8556-975f621eb220" ], "corrections": [], "plain_english_summary": "Providers played an assistive role in education and implementation, but SME cyber hygiene and knowledge remained low; comprehension, capability, attitudes and resources constrained security; security-focused communities could improve support, collaboration and learning. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (12); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "cybersecurity-management-an-empirical-analysis-of-dynamic-capabilities-f", "title": "Cybersecurity management: an empirical analysis of dynamic capabilities framework for enhancing cybersecurity intelligence", "category": "Marketing capability and growth", "study_type": "Abstract-supported quantitative empirical study", "citation": "Angelica Pigola, Priscila Rezende da Costa (2025). Information and Computer Security.", "authors": [ "Angelica Pigola", "Priscila Rezende da Costa" ], "year": 2025, "journal": "Information and Computer Security", "doi": "10.1108/ICS-08-2024-0185", "doi_url": "https://doi.org/10.1108/ICS-08-2024-0185", "primary_url": "https://doi.org/10.1108/ICS-08-2024-0185", "accessible_url": "https://doi.org/10.1108/ICS-08-2024-0185", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "Which dynamic capabilities contribute to organizational cybersecurity intelligence?", "design": "Develops a dynamic-capabilities-in-cybersecurity framework and tests it with hierarchical regression.", "sample_context": "207 cybersecurity experts across diverse regions.", "findings": "\u201cDoing\u201d and \u201cimproving\u201d dimensions were positively associated with cybersecurity intelligence; \u201cenabling\u201d and \u201cmanaging\u201d dimensions did not make significant contributions.", "limitations": "The accessible abstract does not state detailed limitations; expert self-report and cross-sectional regression design warrant editorial review.", "founder_use": "Treat this as evidence for the specific marketing capability and growth question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225a-dd18-7659-bd20-9fa1e60d42ec" ], "corrections": [], "plain_english_summary": "\u201cDoing\u201d and \u201cimproving\u201d dimensions were positively associated with cybersecurity intelligence; \u201cenabling\u201d and \u201cmanaging\u201d dimensions did not make significant contributions. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (207); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "the-effects-of-artificial-intelligence-on-human-resource-activities-and", "title": "The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges", "category": "Customer behavior and adoption", "study_type": "Full-text scoping review/evidence synthesis", "citation": "Justine Dima, Julie Dextras-Gauthier, Laurent Giraud (2024). Frontiers in Psychology.", "authors": [ "Justine Dima", "Julie Dextras-Gauthier", "Laurent Giraud" ], "year": 2024, "journal": "Frontiers in Psychology", "doi": "10.3389/fpsyg.2024.1360401", "doi_url": "https://doi.org/10.3389/fpsyg.2024.1360401", "primary_url": "https://doi.org/10.3389/fpsyg.2024.1360401", "accessible_url": "https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2024.1360401/full", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "What does the peer-reviewed literature show about AI\u2019s effects on HR activities and the roles of employees, line managers and HR professionals?", "design": "Scoping review of 27 years of literature; searches across four databases; 11,405 initial records, 9,413 screened after deduplication, 811 full texts assessed and 43 peer-reviewed articles included. The included empirical studies comprised 26 quantitative, 12 qualitative and five mixed-methods studies.", "sample_context": "43 articles across 38 journals covering eight HR activity categories; 95.7% intercoder agreement on 20% of coded studies.", "findings": "Synthesizes five main AI effects on HR activities and maps opportunities/challenges across the HR triad; highlights automation, decision support, bias/ethics, changing roles and need for multilevel research.", "limitations": "Scoping review does not include formal quality assessment; keyword scope and four-database search may omit studies; authors call for broader databases/disciplines and more empirical work.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225b-0fe1-77f9-925a-3c1c3438d6ec" ], "corrections": [], "plain_english_summary": "Synthesizes five main AI effects on HR activities and maps opportunities/challenges across the HR triad; highlights automation, decision support, bias/ethics, changing roles and need for multilevel research. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (43); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "employees-change-in-perception-when-artificial-intelligence-integrates-w", "title": "Employees\u2019 change in perception when artificial intelligence integrates with human resource management: a mediating role of AI-tech trust", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "Meenal Arora, Amit Mittal (2025). Benchmarking: An International Journal.", "authors": [ "Meenal Arora", "Amit Mittal" ], "year": 2025, "journal": "Benchmarking: An International Journal", "doi": "10.1108/BIJ-11-2023-0795", "doi_url": "https://doi.org/10.1108/BIJ-11-2023-0795", "primary_url": "https://doi.org/10.1108/BIJ-11-2023-0795", "accessible_url": "https://doi.org/10.1108/BIJ-11-2023-0795", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do employees\u2019 perceptions of AI-enabled changes in HR functions affect intention to adopt AI, and does AI-tech trust mediate the relationships?", "design": "Cross-sectional survey of HR professionals; two-step PLS-SEM.", "sample_context": "264 HR professionals from Indian e-commerce organizations.", "findings": "Perceptions of AI\u2019s effects on talent acquisition, training/development, performance assessment and pay/rewards predicted adoption intention; AI-tech trust positively mediated the tested relationships.", "limitations": "Cross-sectional, India/e-commerce-specific sample; self-report and nonprobability concerns are not detailed in the accessible abstract, so editorial review is required.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225b-9246-73bc-9c5d-67511c846e30" ], "corrections": [], "plain_english_summary": "Perceptions of AI\u2019s effects on talent acquisition, training/development, performance assessment and pay/rewards predicted adoption intention; AI-tech trust positively mediated the tested relationships. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (264); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "factors-influencing-artificial-intelligence-adoption-in-human-resource-m", "title": "Factors influencing artificial intelligence adoption in human resource management: a meta-synthesis and systematic review of multidimensional considerations", "category": "Customer behavior and adoption", "study_type": "Full-text open-access qualitative meta-synthesis/systematic review", "citation": "Mohammad Pedrami, Seyed Kamal Vaezi (2026). Journal of Work-Applied Management.", "authors": [ "Mohammad Pedrami", "Seyed Kamal Vaezi" ], "year": 2026, "journal": "Journal of Work-Applied Management", "doi": "10.1108/JWAM-10-2024-0158", "doi_url": "https://doi.org/10.1108/JWAM-10-2024-0158", "primary_url": "https://doi.org/10.1108/JWAM-10-2024-0158", "accessible_url": "https://doi.org/10.1108/JWAM-10-2024-0158", "access_label": "Full text retrieved from publisher or linked open repository", "access_class": "open-full-text", "research_question": "Which multidimensional factors influence AI adoption in HRM?", "design": "Qualitative meta-synthesis systematically analyzing qualitative and quantitative studies published from 2015 to 2023.", "sample_context": "Peer-reviewed AI-in-HRM studies published 2015\u20132023; the accessible article synthesizes the selected literature rather than a new respondent sample.", "findings": "Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent.", "limitations": "Qualitative meta-synthesis depends on the included literature and search/synthesis choices; the publisher article does not report a new field sample.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225b-5fbf-705a-8364-fed970eb0009" ], "corrections": [], "plain_english_summary": "Five themes organize adoption factors: organizational/strategic, technological/operational, human-centric, challenges/opportunities, and environmental/economic; ethical and legal considerations were especially prominent. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 3.5, "label": "Useful evidence with meaningful caveats", "components": [ { "name": "Design", "score": "1/2", "note": "Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions." }, { "name": "Sample", "score": "0.8/1", "note": "The reviewed source reports a sample or corpus size (2015); size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "1/1", "note": "Firecrawl retrieved a full paper or full-text publisher page for this annotation." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "harnessing-the-power-of-artificial-intelligence-ai-a-paradigm-shift-in-h", "title": "Harnessing the power of artificial intelligence (AI): a paradigm shift in HRM practices for employee sustainable performance", "category": "Customer behavior and adoption", "study_type": "Abstract-supported quantitative empirical study", "citation": "Ying Sin Chin, Abang Azlan Mohamad, May Chiun Lo (2026). Global Knowledge, Memory and Communication.", "authors": [ "Ying Sin Chin", "Abang Azlan Mohamad", "May Chiun Lo" ], "year": 2026, "journal": "Global Knowledge, Memory and Communication", "doi": "10.1108/GKMC-06-2024-0355", "doi_url": "https://doi.org/10.1108/GKMC-06-2024-0355", "primary_url": "https://doi.org/10.1108/GKMC-06-2024-0355", "accessible_url": "https://doi.org/10.1108/GKMC-06-2024-0355", "access_label": "Publisher abstract/metadata retrieved; full text not reviewed", "access_class": "abstract", "research_question": "How do AI adoption, organizational digital culture and HRM practices relate to sustainable employee performance in Malaysian luxury hotels?", "design": "Quantitative questionnaire study; psychometric validation; SPSS 28 and SmartPLS 4 analysis.", "sample_context": "Luxury hotels in Malaysia; the accessible abstract does not report the respondent n.", "findings": "Three of five hypotheses were supported: AI adoption positively related to sustainable employee performance; HRM practices and digital culture also positively related to performance; AI did not moderate the HRM\u2013performance link and AI adoption was not associated with digital culture.", "limitations": "Cross-sectional Malaysian luxury-hotel focus; authors call for longitudinal, cross-sector and cross-country comparisons.", "founder_use": "Treat this as evidence for the specific customer behavior and adoption question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.", "evidence_basis": "Publisher DOI record and accessible article/abstract directly support the bibliographic record and the summary fields; editorial review remains appropriate for duplicate checking against the unseen 300-study library. Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.", "source_ids": [ "01a1225b-bed0-7173-947e-9236698a6adb" ], "corrections": [], "plain_english_summary": "Three of five hypotheses were supported: AI adoption positively related to sustainable employee performance; HRM practices and digital culture also positively related to performance; AI did not moderate the HRM\u2013performance link and AI adoption was not associated with digital culture. For a founder, use this as a question to test in your own context, not a universal playbook.", "evidence_check": { "score": 2.5, "label": "Exploratory evidence; interpret cautiously", "components": [ { "name": "Design", "score": "1/2", "note": "The described design supports the question, but it does not establish causal effects beyond the reported setting." }, { "name": "Sample", "score": "0.4/1", "note": "The accessible source does not report a usable sample size." }, { "name": "Comparison", "score": "0.5/1", "note": "The comparison structure is limited or depends on the paper's model/context." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only publisher abstract/metadata was retrieved; full methods and robustness could not be checked." } ], "blinding": "Blinding was not established from the captured source; it may not apply to this study design." }, "reviewed_on": "2026-10-09" }, { "slug": "experimental-evidence-on-the-productivity-effects-of-generative-artificial-i", "title": "Experimental evidence on the productivity effects of generative artificial intelligence", "category": "Customer behavior and adoption", "study_type": "Preregistered online randomized experiment with incentivized, occupation-specific writing tasks.", "citation": "Noy, S. & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science.", "authors": [ "Shakked Noy", "Whitney Zhang" ], "year": 2023, "journal": "Science", "doi": "10.1126/science.adh2586", "doi_url": "https://doi.org/10.1126/science.adh2586", "primary_url": "https://doi.org/10.1126/science.adh2586", "accessible_url": "https://www.science.org/doi/10.1126/science.adh2586", "access_label": "Publisher abstract or article landing page captured; full text access not established", "access_class": "abstract", "research_question": "What is the causal effect of ChatGPT access on productivity, quality, inequality, and subsequent workplace adoption in professional writing tasks?", "design": "Preregistered online randomized experiment with incentivized, occupation-specific writing tasks.", "sample_context": "453 college-educated professionals performing midlevel professional writing tasks; half were randomly exposed to ChatGPT.", "findings": "ChatGPT reduced average time by 40% and raised output quality by 18%; inequality fell, and exposed workers were 2 times as likely to report real-job use two weeks later and 1.6 times as likely two months later.", "limitations": "Short online tasks, selected professionals, and one model/version; measured writing performance is not the same as long-run business productivity, customer value, or safe deployment.", "founder_use": "Evaluate AI features with randomized task-level tests that include quality and time, then measure sustained adoption rather than assuming a novelty effect equals retention.", "evidence_basis": "Publisher page directly retrieved with Firecrawl; scrape reference 01a1227f-03d4-711b-90ec-fe5cebeebe65. Claims are limited to the reported article record. Correction notices were not separately checked.", "source_ids": [ "01a1227f-03d4-711b-90ec-fe5cebeebe65" ], "corrections": [], "plain_english_summary": "In this study, ChatGPT reduced average time by 40% and raised output quality by 18%; inequality fell, and exposed workers were 2 times as likely to report real-job use two weeks later and 1.6 times as likely two months later. Founder use: Evaluate AI features with randomized task-level tests that include quality and time, then measure sustained adoption rather than assuming a novelty effect equals retention.", "evidence_check": { "score": 4.5, "label": "Strong experimental or quasi-experimental evidence for its stated setting", "components": [ { "name": "Design", "score": "2/2", "note": "Design description was checked against the directly fetched article source; conclusions remain specific to the studied setting." }, { "name": "Sample", "score": "1/1", "note": "Sample size or the source's lack of a reported count is stated explicitly." }, { "name": "Comparison", "score": "1/1", "note": "The comparison or identification strategy is described from the article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "Only the publisher page or abstract was confirmed." } ], "blinding": "Blinding is not stated in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "generative-ai-at-work", "title": "Generative AI at Work", "category": "Customer behavior and adoption", "study_type": "Quasi-experimental staggered introduction using workplace operational data.", "citation": "Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at Work. The Quarterly Journal of Economics.", "authors": [ "Erik Brynjolfsson", "Danielle Li", "Lindsey R. Raymond" ], "year": 2025, "journal": "The Quarterly Journal of Economics", "doi": "10.1093/qje/qjae044", "doi_url": "https://doi.org/10.1093/qje/qjae044", "primary_url": "https://doi.org/10.1093/qje/qjae044", "accessible_url": "https://arxiv.org/pdf/2304.11771", "access_label": "Open working paper PDF captured from arXiv", "access_class": "open-full-text", "research_question": "What happens when a generative-AI conversational assistant is introduced into real customer-support work, and who benefits most?", "design": "Quasi-experimental staggered introduction using workplace operational data.", "sample_context": "5,172 customer-support agents using a conversational assistant in their work.", "findings": "Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase.", "limitations": "One employer and support workflow; staggered adoption is not a pure randomized trial, and agent, customer, and tool effects may be context-specific.", "founder_use": "Prioritize AI copilot deployment where onboarding and experience gaps are largest; track quality, customer sentiment, escalation, and retention together.", "evidence_basis": "Publisher page directly retrieved with Firecrawl; scrape reference 01a1227f-0fec-77ae-b61b-74f5f6c2b64c. Claims are limited to the reported article record. Correction notices were not separately checked.", "source_ids": [ "01a1227f-0fec-77ae-b61b-74f5f6c2b64c", "01a1227f-9e00-759c-808d-4c5f0a1b7af2" ], "corrections": [], "plain_english_summary": "In this study, Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase. Founder use: Prioritize AI copilot deployment where onboarding and experience gaps are largest; track quality, customer sentiment, escalation, and retention together.", "evidence_check": { "score": 4.5, "label": "Strong experimental or quasi-experimental evidence for its stated setting", "components": [ { "name": "Design", "score": "2/2", "note": "Design description was checked against the directly fetched article source; conclusions remain specific to the studied setting." }, { "name": "Sample", "score": "1/1", "note": "Sample size or the source's lack of a reported count is stated explicitly." }, { "name": "Comparison", "score": "1/1", "note": "The comparison or identification strategy is described from the article record." }, { "name": "Can we check it?", "score": "1/1", "note": "A directly retrieved full paper is available." } ], "blinding": "Blinding is not stated in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "navigating-the-jagged-technological-frontier-field-experimental-evidence-of", "title": "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality", "category": "Customer behavior and adoption", "study_type": "Preregistered randomized controlled laboratory-in-the-field experiment, with realistic consulting tasks and a no-AI, GPT-4, and GPT-4-plus-prompt-engineering condition.", "citation": "Dell'Acqua, F., III, E. M., Mollick, E., Lifshitz, H., Kellogg, K. C., Rajendran, S., Krayer, L., & Candelon, F. (2026). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality. Organization Science.", "authors": [ "Fabrizio Dell\u2019Acqua", "Edward McFowland III", "Ethan Mollick", "Hila Lifshitz", "Katherine C. Kellogg", "Saran Rajendran", "Lisa Krayer", "Fran\u00e7ois Candelon" ], "year": 2026, "journal": "Organization Science", "doi": "10.1287/orsc.2025.21838", "doi_url": "https://doi.org/10.1287/orsc.2025.21838", "primary_url": "https://doi.org/10.1287/orsc.2025.21838", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/orsc.2025.21838", "access_label": "Open full text captured directly", "access_class": "open-full-text", "research_question": "When does GPT-4 improve versus degrade the productivity and quality of complex knowledge work?", "design": "Preregistered randomized controlled laboratory-in-the-field experiment, with realistic consulting tasks and a no-AI, GPT-4, and GPT-4-plus-prompt-engineering condition.", "sample_context": "758 knowledge workers performing 18 realistic management-consulting tasks developed with Boston Consulting Group, plus a separate out-of-frontier managerial task.", "findings": "Within the AI capability frontier, AI users completed 12.2% more tasks, 25.1% faster, with higher quality; on an out-of-frontier managerial task they were 19% less likely to be correct.", "limitations": "Consulting tasks and GPT-4-era capabilities may not represent other work or later models; task performance is not a direct measure of product adoption, revenue, or organizational learning.", "founder_use": "Design AI product analytics around task-level success and verification, not aggregate usage; expose where the model helps and require review where it can degrade decisions.", "evidence_basis": "Publisher page directly retrieved with Firecrawl; scrape reference 01a1227f-1ac8-74ec-9bba-2a65012e56ec. Claims are limited to the reported article record. Correction notices were not separately checked.", "source_ids": [ "01a1227f-1ac8-74ec-9bba-2a65012e56ec" ], "corrections": [], "plain_english_summary": "In this study, Within the AI capability frontier, AI users completed 12.2% more tasks, 25.1% faster, with higher quality; on an out-of-frontier managerial task they were 19% less likely to be correct. Founder use: Design AI product analytics around task-level success and verification, not aggregate usage; expose where the model helps and require review where it can degrade decisions.", "evidence_check": { "score": 4.5, "label": "Strong experimental or quasi-experimental evidence for its stated setting", "components": [ { "name": "Design", "score": "2/2", "note": "Design description was checked against the directly fetched article source; conclusions remain specific to the studied setting." }, { "name": "Sample", "score": "1/1", "note": "Sample size or the source's lack of a reported count is stated explicitly." }, { "name": "Comparison", "score": "1/1", "note": "The comparison or identification strategy is described from the article record." }, { "name": "Can we check it?", "score": "1/1", "note": "A directly retrieved full paper is available." } ], "blinding": "Blinding is not stated in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "how-apis-create-growth-by-inverting-the-firm", "title": "How APIs Create Growth by Inverting the Firm", "category": "B2B growth and sales", "study_type": "Difference-in-differences, synthetic control, instrumental variables using API-network variation, and private API data.", "citation": "Benzell, S. G., Hersh, J., & Alstyne, M. (2023). How APIs Create Growth by Inverting the Firm. Management Science.", "authors": [ "Seth G. Benzell", "Jonathan Hersh", "Marshall Van Alstyne" ], "year": 2023, "journal": "Management Science", "doi": "10.1287/mnsc.2023.4968", "doi_url": "https://doi.org/10.1287/mnsc.2023.4968", "primary_url": "https://doi.org/10.1287/mnsc.2023.4968", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4968", "access_label": "Open full text captured directly", "access_class": "open-full-text", "research_question": "Do public APIs create firm growth by enabling third-party complementors, and what are the security trade-offs?", "design": "Difference-in-differences, synthetic control, instrumental variables using API-network variation, and private API data.", "sample_context": "Public firms adopting public APIs, API-network data from 2005 onward, and a private API development firm's data.", "findings": "Public API adopters grew an additional 38.7% over 16 years relative to similar nonadopters; growth was stronger with more complementors and network centrality. Internal-only API use had no significant effect, while public APIs increased breach risk.", "limitations": "Firm-level observational designs still depend on identification assumptions; public-company/API adopters and market-value outcomes may not map to early-stage private SaaS.", "founder_use": "Treat an API as an ecosystem product: measure active complementors, connected apps, centrality, and partner value\u2014not only API calls\u2014and budget for security controls.", "evidence_basis": "Publisher page directly retrieved with Firecrawl; scrape reference 01a1227f-25d8-722f-8628-9d5191c591cd. Claims are limited to the reported article record. Correction notices were not separately checked.", "source_ids": [ "01a1227f-25d8-722f-8628-9d5191c591cd" ], "corrections": [], "plain_english_summary": "In this study, Public API adopters grew an additional 38.7% over 16 years relative to similar nonadopters; growth was stronger with more complementors and network centrality. Internal-only API use had no significant effect, while public APIs increased breach risk. Founder use: Treat an API as an ecosystem product: measure active complementors, connected apps, centrality, and partner value\u2014not only API calls\u2014and budget for security controls.", "evidence_check": { "score": 4.0, "label": "Useful empirical evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "2/2", "note": "Design description was checked against the directly fetched article source; conclusions remain specific to the studied setting." }, { "name": "Sample", "score": "1/1", "note": "Sample size or the source's lack of a reported count is stated explicitly." }, { "name": "Comparison", "score": "1/1", "note": "The comparison or identification strategy is described from the article record." }, { "name": "Can we check it?", "score": "1/1", "note": "A directly retrieved full paper is available." } ], "blinding": "Blinding is not stated in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "examining-the-use-and-impact-of-an-ai-code-assistant-on-developer-productiv", "title": "Examining the Use and Impact of an AI Code Assistant on Developer Productivity", "category": "Product adoption and customer behavior", "study_type": "Mixed-methods case study of an IBM AI code assistant under development: surveys of two user cohorts and unmoderated usability testing.", "citation": "Weisz, J. D., Kumar, S. V., Muller, M., Browne, K., Goldberg, A., Heintze, K. E., & Bajpai, S. (2025). Examining the Use and Impact of an AI Code Assistant on Developer Productivity. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.", "authors": [ "Justin D. Weisz", "Shraddha Vijay Kumar", "Michael Muller", "Karen-Ellen Browne", "Arielle Goldberg", "Katrin Ellice Heintze", "Shagun Bajpai" ], "year": 2025, "journal": "Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems", "doi": "10.1145/3706599.3706670", "doi_url": "https://doi.org/10.1145/3706599.3706670", "primary_url": "https://doi.org/10.1145/3706599.3706670", "accessible_url": "https://dl.acm.org/doi/10.1145/3706599.3706670", "access_label": "Publisher abstract directly retrieved; full-text access not established", "access_class": "abstract", "research_question": "How does use of an AI code assistant affect developers' perceived productivity, usage choices, and concerns about generated-code responsibility?", "design": "Mixed-methods case study of an IBM AI code assistant under development: surveys of two user cohorts and unmoderated usability testing.", "sample_context": "IBM developer users of a general-purpose assistant supporting common programming languages; publisher abstract reports survey cohorts totaling N=669 and unmoderated usability testing N=15.", "findings": "The assistant generally produced net perceived productivity increases, but benefits were not experienced equally; the study also surfaced motivations, expectations about speed/quality, and questions about ownership and responsibility for generated code.", "limitations": "This is an organizational case study using self-reported perceptions plus usability testing, not a randomized productivity trial; it concerns one assistant and IBM context, and the abstract cautions that gains vary across users.", "founder_use": "For developer-tool founders, measure perceived and behavioral productivity together, segment by user, and make provenance, ownership, responsibility, and output-quality workflows explicit. Avoid assuming that aggregate positive sentiment means every team or task benefits.", "evidence_basis": "Direct publisher scrape verified title/record and available text; Firecrawl source ID 01a1228d-e249-7029-8a2f-e072d63d2379. Correction notices were not separately checked.", "source_ids": [ "01a1228d-e249-7029-8a2f-e072d63d2379" ], "corrections": [], "plain_english_summary": "The assistant generally produced net perceived productivity increases, but benefits were not experienced equally; the study also surfaced motivations, expectations about speed/quality, and questions about ownership and responsibility for generated code. For a SaaS founder: For developer-tool founders, measure perceived and behavioral productivity together, segment by user, and make provenance, ownership, responsibility, and output-quality workflows explicit. Avoid assuming that aggregate positive sentiment means every team or task benefits.", "evidence_check": { "score": 3.5, "label": "Context-specific or model-based evidence; use as a hypothesis", "components": [ { "name": "Design", "score": "1/2", "note": "The design type and its limits are described from the directly fetched article." }, { "name": "Sample", "score": "1/1", "note": "Reported sample details are included; when the source does not give a count, that is stated." }, { "name": "Comparison", "score": "0.5/1", "note": "The experimental, review, observational, or model comparison is identified without converting it into a causal claim." }, { "name": "Can we check it?", "score": "0.5/1", "note": "The publisher abstract or record was directly retrieved." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "interventions-to-promote-technology-adoption-in-firms-a-systematic-review", "title": "Interventions to promote technology adoption in firms: A systematic review", "category": "Customer behavior and adoption", "study_type": "Campbell systematic review of experimental and quasi-experimental evaluations of exogenous incentives/interventions affecting firm technology adoption; standardized effects were synthesized across included studies.", "citation": "Alfaro-Serrano, D., Balantrapu, T., Chaurey, R., Goicoechea, A., & Verhoogen, E. (2021). Interventions to promote technology adoption in firms: A systematic review. Campbell Systematic Reviews.", "authors": [ "David Alfaro-Serrano", "Tanay Balantrapu", "Ritam Chaurey", "Ana Goicoechea", "Eric Verhoogen" ], "year": 2021, "journal": "Campbell Systematic Reviews", "doi": "10.1002/cl2.1181", "doi_url": "https://doi.org/10.1002/cl2.1181", "primary_url": "https://doi.org/10.1002/cl2.1181", "accessible_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8988818/", "access_label": "Open full text directly retrieved", "access_class": "open-full-text", "research_question": "Which types of intervention have been evaluated to promote technology adoption in firms, and how consistent are their effects?", "design": "Campbell systematic review of experimental and quasi-experimental evaluations of exogenous incentives/interventions affecting firm technology adoption; standardized effects were synthesized across included studies.", "sample_context": "Firms in manufacturing, services, and agriculture across varied countries and contexts; the review reports 1,108 regression coefficients from selected studies and separately analyzes sectors. It does not describe one single pooled SaaS sample.", "findings": "Some interventions produced positive technology-adoption effects, but results varied substantially by context and methodology. Effects on profits, productivity, employment, and farm yields were mixed; the review could not identify one universally superior intervention.", "limitations": "Very broad intervention, sector, outcome, and country heterogeneity limits generalization; the authors call results suggestive rather than definitive, did not conduct heterogeneity analysis, and note reporting gaps (including needing to contact authors for information). This is not SaaS-specific evidence.", "founder_use": "Use the review as a reason to run context-specific experiments: compare guided onboarding, training, incentives, peer learning, and support while measuring activated accounts and sustained usage. Do not assume a successful intervention in one customer segment transfers to another.", "evidence_basis": "Direct publisher scrape verified title/record and available text; Firecrawl source ID 01a1228d-b061-74d9-ae40-2a828d88b89b. Correction notices were not separately checked.", "source_ids": [ "01a1228d-b061-74d9-ae40-2a828d88b89b" ], "corrections": [], "plain_english_summary": "Some interventions produced positive technology-adoption effects, but results varied substantially by context and methodology. Effects on profits, productivity, employment, and farm yields were mixed; the review could not identify one universally superior intervention. For a SaaS founder: Use the review as a reason to run context-specific experiments: compare guided onboarding, training, incentives, peer learning, and support while measuring activated accounts and sustained usage. Do not assume a successful intervention in one customer segment transfers to another.", "evidence_check": { "score": 4.0, "label": "Useful synthesis or empirical evidence with transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "The design type and its limits are described from the directly fetched article." }, { "name": "Sample", "score": "1/1", "note": "Reported sample details are included; when the source does not give a count, that is stated." }, { "name": "Comparison", "score": "1/1", "note": "The experimental, review, observational, or model comparison is identified without converting it into a causal claim." }, { "name": "Can we check it?", "score": "1/1", "note": "The full article was directly retrieved." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "self-selected-sales-incentives-evidence-of-their-effectiveness-persistence", "title": "Self-Selected Sales Incentives: Evidence of their Effectiveness, Persistence, Durability, and Underlying Mechanisms", "category": "B2B growth and sales", "study_type": "Two field experiments at Fortune 500 companies, plus two online experiments testing mechanisms.", "citation": "Bommaraju, R. & Hohenberg, S. (2018). Self-Selected Sales Incentives: Evidence of their Effectiveness, Persistence, Durability, and Underlying Mechanisms. Journal of Marketing.", "authors": [ "Raghu Bommaraju", "Sebastian Hohenberg" ], "year": 2018, "journal": "Journal of Marketing", "doi": "10.1509/jm.17.0002", "doi_url": "https://doi.org/10.1509/jm.17.0002", "primary_url": "https://journals.sagepub.com/doi/10.1509/jm.17.0002", "accessible_url": "https://journals.sagepub.com/doi/10.1509/jm.17.0002", "access_label": "Publisher abstract directly retrieved; full-text access not established", "access_class": "abstract", "research_question": "What happens when sales employees choose their own goal\u2013reward incentive combination?", "design": "Two field experiments at Fortune 500 companies, plus two online experiments testing mechanisms.", "sample_context": "Sales employees at two Fortune 500 companies; the publisher page does not state the field-experiment sample sizes in the fetched abstract.", "findings": "Compared with equivalent quota systems, allowing employees to select a goal\u2013reward combination increased sales performance substantially. Effects were larger for employees with highly variable past performance and lower past performance; effects persisted when the scheme was discontinued and were durable when offered again.", "limitations": "The abstract does not report sample sizes; the field evidence comes from two companies and a specific incentive menu, so generalization to small SaaS sales teams, different compensation systems, or non-sales roles is uncertain.", "founder_use": "A founder could cautiously pilot employee-selected quota/reward menus in a randomized or phased rollout, tracking revenue quality and retention as well as bookings. Do not assume the observed effects transfer across roles or that self-selection is always superior to a well-designed fixed plan.", "evidence_basis": "Direct publisher scrape verified title/record and available text; Firecrawl source ID 01a1228d-cc56-7274-a66e-712b4091bb1e. Correction notices were not separately checked.", "source_ids": [ "01a1228d-cc56-7274-a66e-712b4091bb1e" ], "corrections": [], "plain_english_summary": "Compared with equivalent quota systems, allowing employees to select a goal\u2013reward combination increased sales performance substantially. Effects were larger for employees with highly variable past performance and lower past performance; effects persisted when the scheme was discontinued and were durable when offered again. For a SaaS founder: A founder could cautiously pilot employee-selected quota/reward menus in a randomized or phased rollout, tracking revenue quality and retention as well as bookings. Do not assume the observed effects transfer across roles or that self-selection is always superior to a well-designed fixed plan.", "evidence_check": { "score": 4.5, "label": "Strong evidence in its stated setting", "components": [ { "name": "Design", "score": "2/2", "note": "The design type and its limits are described from the directly fetched article." }, { "name": "Sample", "score": "1/1", "note": "Reported sample details are included; when the source does not give a count, that is stated." }, { "name": "Comparison", "score": "1/1", "note": "The experimental, review, observational, or model comparison is identified without converting it into a causal claim." }, { "name": "Can we check it?", "score": "0.5/1", "note": "The publisher abstract or record was directly retrieved." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "optimal-software-free-trial-strategy-limited-version-time-locked-or-hybrid", "title": "Optimal Software Free Trial Strategy: Limited Version, Time-locked, or Hybrid?", "category": "Pricing and product adoption", "study_type": "Analytical model of software free-trial design incorporating network externalities and consumer uncertainty; compares limited-version, time-locked and hybrid trials.", "citation": "Cheng, H. K., Li, S., & Liu, Y. (2015). Optimal Software Free Trial Strategy: Limited Version, Time-locked, or Hybrid?. Production and Operations Management.", "authors": [ "Hsing Kenneth Cheng", "Shengli Li", "Yipeng Liu" ], "year": 2015, "journal": "Production and Operations Management", "doi": "10.1111/poms.12248", "doi_url": "https://doi.org/10.1111/poms.12248", "primary_url": "https://onlinelibrary.wiley.com/doi/10.1111/poms.12248", "accessible_url": "https://onlinelibrary.wiley.com/doi/10.1111/poms.12248", "access_label": "Publisher abstract directly retrieved; full-text access not established", "access_class": "abstract", "research_question": "Under what product and network conditions should a software company use a feature-limited, time-limited, or hybrid free trial?", "design": "Analytical model of software free-trial design incorporating network externalities and consumer uncertainty; compares limited-version, time-locked and hybrid trials.", "sample_context": "Theoretical software-product market; no human or firm sample.", "findings": "The optimal trial format depends on network externalities, consumer uncertainty and product characteristics; the paper derives conditions under which limited, time-locked or hybrid trials are preferred.", "limitations": "Analytical assumptions rather than field validation; outcomes depend on modeled network effects, uncertainty and conversion behavior.", "founder_use": "Treat trial format as a product-design choice, not merely a duration choice; map whether collaboration/network value and uncertainty favor feature limits, time limits or a hybrid, then test empirically.", "evidence_basis": "Direct publisher scrape verified title/record and available text; Firecrawl source ID 01a1228d-fa20-739e-b452-94d1d9a54d59. Correction notices were not separately checked.", "source_ids": [ "01a1228d-fa20-739e-b452-94d1d9a54d59" ], "corrections": [], "plain_english_summary": "The optimal trial format depends on network externalities, consumer uncertainty and product characteristics; the paper derives conditions under which limited, time-locked or hybrid trials are preferred. For a SaaS founder: Treat trial format as a product-design choice, not merely a duration choice; map whether collaboration/network value and uncertainty favor feature limits, time limits or a hybrid, then test empirically.", "evidence_check": { "score": 3.5, "label": "Context-specific or model-based evidence; use as a hypothesis", "components": [ { "name": "Design", "score": "1/2", "note": "The design type and its limits are described from the directly fetched article." }, { "name": "Sample", "score": "0.5/1", "note": "Reported sample details are included; when the source does not give a count, that is stated." }, { "name": "Comparison", "score": "0.5/1", "note": "The experimental, review, observational, or model comparison is identified without converting it into a causal claim." }, { "name": "Can we check it?", "score": "0.5/1", "note": "The publisher abstract or record was directly retrieved." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "pricing-services-subject-to-congestion-charge-per-use-fees-or-sell-subscrip", "title": "Pricing Services Subject to Congestion: Charge Per-Use Fees or Sell Subscriptions?", "category": "Pricing and monetization", "study_type": "Analytical queueing/pricing model comparing per-use fees with subscriptions under congestion, consumer heterogeneity and fixed capacity.", "citation": "Cachon, G. P. & Feldman, P. (2011). Pricing Services Subject to Congestion: Charge Per-Use Fees or Sell Subscriptions?. Manufacturing & Service Operations Management.", "authors": [ "G\u00e9rard P. Cachon", "Pnina Feldman" ], "year": 2011, "journal": "Manufacturing & Service Operations Management", "doi": "10.1287/msom.1100.0315", "doi_url": "https://doi.org/10.1287/msom.1100.0315", "primary_url": "https://pubsonline.informs.org/doi/10.1287/msom.1100.0315", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/msom.1100.0315", "access_label": "Publisher abstract directly retrieved; full-text access not established", "access_class": "abstract", "research_question": "When do subscriptions outperform per-use fees for services with limited capacity and congestion?", "design": "Analytical queueing/pricing model comparing per-use fees with subscriptions under congestion, consumer heterogeneity and fixed capacity.", "sample_context": "Theoretical service-pricing setting; no human or firm sample.", "findings": "Subscription pricing can earn more revenue than per-use pricing even when congestion is costly; its relative appeal rises with high potential utilization, fixed capacity and sufficiently different heavy/light usage rates.", "limitations": "Model-based results depend on assumptions about congestion, demand, capacity and consumer information; not a causal field test and not SaaS-specific.", "founder_use": "Use as a pricing hypothesis: compare seat/usage subscriptions with metered pricing while stress-testing capacity and heavy-user economics; validate with controlled pilots because real SaaS marginal costs and network effects differ.", "evidence_basis": "Direct publisher scrape verified title/record and available text; Firecrawl source ID 01a1228e-1136-75fb-83d9-346fd599e015. Correction notices were not separately checked.", "source_ids": [ "01a1228e-1136-75fb-83d9-346fd599e015" ], "corrections": [], "plain_english_summary": "Subscription pricing can earn more revenue than per-use pricing even when congestion is costly; its relative appeal rises with high potential utilization, fixed capacity and sufficiently different heavy/light usage rates. For a SaaS founder: Use as a pricing hypothesis: compare seat/usage subscriptions with metered pricing while stress-testing capacity and heavy-user economics; validate with controlled pilots because real SaaS marginal costs and network effects differ.", "evidence_check": { "score": 3.5, "label": "Context-specific or model-based evidence; use as a hypothesis", "components": [ { "name": "Design", "score": "1/2", "note": "The design type and its limits are described from the directly fetched article." }, { "name": "Sample", "score": "0.5/1", "note": "Reported sample details are included; when the source does not give a count, that is stated." }, { "name": "Comparison", "score": "0.5/1", "note": "The experimental, review, observational, or model comparison is identified without converting it into a causal claim." }, { "name": "Can we check it?", "score": "0.5/1", "note": "The publisher abstract or record was directly retrieved." } ], "blinding": "Blinding is not reported in the source reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "e-service-quality-a-meta-analytic-review", "title": "E-Service Quality: A Meta-Analytic Review", "category": "Customer behavior and adoption", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Blut, M., Chowdhry, N., Mittal, V., & Brock, C. (2015). E-Service Quality: A Meta-Analytic Review. Journal of Retailing, 91(4), 679-700.", "authors": [ "Markus Blut", "Nivriti Chowdhry", "Vikas Mittal", "Christian Brock" ], "year": 2015, "journal": "Journal of Retailing, 91(4), 679-700", "doi": "10.1016/j.jretai.2015.05.004", "doi_url": "https://doi.org/10.1016/j.jretai.2015.05.004", "primary_url": "https://doi.org/10.1016/j.jretai.2015.05.004", "accessible_url": "https://doi.org/10.1016/j.jretai.2015.05.004", "access_label": "Publisher abstract or article landing page captured; full-text access not established.", "access_class": "abstract", "research_question": "Which dimensions of e-service quality relate to customer evaluations and behavioral outcomes across online-service research?", "design": "Meta-analytic review synthesizing empirical e-service-quality research across online service settings.", "sample_context": "Meta-analytic review synthesizing empirical e-service-quality research across online service settings.", "findings": "E-service-quality dimensions have meaningful relationships with customer evaluations and behavioral outcomes, but effects depend on measurement and context.", "limitations": "Primarily consumer online-service evidence; construct definitions and samples vary; meta-analysis cannot remove limitations of underlying correlational studies.", "founder_use": "Use as a measurement/design checklist for onboarding and support, then validate which service-quality dimensions predict SaaS activation, expansion, and renewal in your segment.", "evidence_basis": "Publisher article page directly retrieved with Firecrawl (reference 01a122bc-7154-732c-9b26-1f890c1241f5). The annotation follows the retrieved title/abstract or landing-page record; full methods and correction notices were not independently reviewed.", "source_ids": [ "01a122bc-7154-732c-9b26-1f890c1241f5" ], "corrections": [], "plain_english_summary": "E-service-quality dimensions have meaningful relationships with customer evaluations and behavioral outcomes, but effects depend on measurement and context. Founder-use interpretation: Use as a measurement/design checklist for onboarding and support, then validate which service-quality dimensions predict SaaS activation, expansion, and renewal in your segment.", "evidence_check": { "score": 4.0, "label": "Useful empirical or synthesis evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Scored from the described study design; an analytical or review design is not treated as a randomized field estimate." }, { "name": "Sample", "score": "0.5/1", "note": "The setting and reported sample detail are stated explicitly; size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The reported comparison or synthesis method is described from the retrieved article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "A publisher page or abstract was directly retrieved; full methods access was not established." } ], "blinding": "Blinding is not stated in the publisher record reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "optimal-software-free-trial-strategy-the-impact-of-network-externalities-and", "title": "Optimal Software Free Trial Strategy: The Impact of Network Externalities and Consumer Uncertainty", "category": "Pricing and monetization", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Cheng, H. K. & Liu, Y. (2012). Optimal Software Free Trial Strategy: The Impact of Network Externalities and Consumer Uncertainty. Information Systems Research, 23(2), 488-504.", "authors": [ "Hsing Kenneth Cheng", "Yipeng Liu" ], "year": 2012, "journal": "Information Systems Research, 23(2), 488-504", "doi": "10.1287/isre.1110.0348", "doi_url": "https://doi.org/10.1287/isre.1110.0348", "primary_url": "https://doi.org/10.1287/isre.1110.0348", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/isre.1110.0348", "access_label": "Publisher abstract or article landing page captured; full-text access not established.", "access_class": "abstract", "research_question": "How do network effects and consumer uncertainty affect the optimal free-trial strategy for software?", "design": "Formal analytical model of software free-trial strategy incorporating network externalities and consumer uncertainty; compares time-locked, limited-version, and related trial choices.", "sample_context": "Formal analytical model of software free-trial strategy incorporating network externalities and consumer uncertainty; compares time-locked, limited-version, and related trial choices.", "findings": "The value and optimal form of a free trial depend on network effects and uncertainty; a one-size-fits-all trial policy is not optimal.", "limitations": "Model assumptions rather than a randomized field trial; parameter/results require calibration to a product's network effects, uncertainty, and conversion economics.", "founder_use": "Use to frame trial-design experiments; do not infer that longer, unlimited, or time-locked trials universally win for SaaS.", "evidence_basis": "Publisher article page directly retrieved with Firecrawl (reference 01a122bc-5847-70bb-b862-8e17fb054692). The annotation follows the retrieved title/abstract or landing-page record; full methods and correction notices were not independently reviewed.", "source_ids": [ "01a122bc-5847-70bb-b862-8e17fb054692" ], "corrections": [], "plain_english_summary": "The value and optimal form of a free trial depend on network effects and uncertainty; a one-size-fits-all trial policy is not optimal. Founder-use interpretation: Use to frame trial-design experiments; do not infer that longer, unlimited, or time-locked trials universally win for SaaS.", "evidence_check": { "score": 4.0, "label": "Useful empirical or synthesis evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "1/2", "note": "Scored from the described study design; an analytical or review design is not treated as a randomized field estimate." }, { "name": "Sample", "score": "0.5/1", "note": "The setting and reported sample detail are stated explicitly; size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The reported comparison or synthesis method is described from the retrieved article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "A publisher page or abstract was directly retrieved; full methods access was not established." } ], "blinding": "Blinding is not stated in the publisher record reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "software-developers-perceptions-of-productivity", "title": "Software developers' perceptions of productivity", "category": "Developer productivity and AI", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Meyer, A. N., Fritz, T., Murphy, G. C., & Zimmermann, T. (2014). Software developers' perceptions of productivity. Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2014).", "authors": [ "Andr\u00e9 N. Meyer", "Thomas Fritz", "Gail C. Murphy", "Thomas Zimmermann" ], "year": 2014, "journal": "Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2014)", "doi": "10.1145/2635868.2635892", "doi_url": "https://doi.org/10.1145/2635868.2635892", "primary_url": "https://doi.org/10.1145/2635868.2635892", "accessible_url": "https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/meyer-fse-2014.pdf", "access_label": "Publisher abstract or article landing page captured; full-text access not established.", "access_class": "abstract", "research_question": "How do professional software developers perceive productive and unproductive work?", "design": "Two studies, including a survey and an observational study, examining professional developers' perceptions of productive and unproductive work.", "sample_context": "Two studies, including a survey and an observational study, examining professional developers' perceptions of productive and unproductive work.", "findings": "Developers perceive days as productive when completing many or large tasks without significant interruptions/context switches, although substantial task/activity switching can coexist with feeling productive.", "limitations": "Perceived rather than objective productivity; observational/self-report bias; developer and workplace context may not represent all teams.", "founder_use": "Useful for product/engineering workflow hypotheses and user research, not proof that a tool improves delivery metrics; pair perceived productivity with cycle time, quality, and wellbeing measures.", "evidence_basis": "Publisher article page directly retrieved with Firecrawl (reference 01a122bc-2599-72ce-b1ae-8d126dcda4a4). The annotation follows the retrieved title/abstract or landing-page record; full methods and correction notices were not independently reviewed.", "source_ids": [ "01a122bc-2599-72ce-b1ae-8d126dcda4a4" ], "corrections": [], "plain_english_summary": "Developers perceive days as productive when completing many or large tasks without significant interruptions/context switches, although substantial task/activity switching can coexist with feeling productive. Founder-use interpretation: Useful for product/engineering workflow hypotheses and user research, not proof that a tool improves delivery metrics; pair perceived productivity with cycle time, quality, and wellbeing measures.", "evidence_check": { "score": 3.5, "label": "Useful empirical or synthesis evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Scored from the described study design; an analytical or review design is not treated as a randomized field estimate." }, { "name": "Sample", "score": "0.5/1", "note": "The setting and reported sample detail are stated explicitly; size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The reported comparison or synthesis method is described from the retrieved article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "A publisher page or abstract was directly retrieved; full methods access was not established." } ], "blinding": "Blinding is not stated in the publisher record reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "a-systematic-literature-review-to-uncover-saas-adoption-issues-by-smes-reaso", "title": "A Systematic Literature Review to Uncover SaaS Adoption Issues by SMEs \u2013 Reasons and Solutions to the Adoption Problem", "category": "SaaS adoption and onboarding", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Adenuga, O. A., Kekwaletswe, R. M., & Adenuga, O. T. (2020). A Systematic Literature Review to Uncover SaaS Adoption Issues by SMEs \u2013 Reasons and Solutions to the Adoption Problem. International Journal of Data and Information Systems (IJDIS).", "authors": [ "Olugbenga A. Adenuga", "Ray M. Kekwaletswe", "Olukorede T. Adenuga" ], "year": 2020, "journal": "International Journal of Data and Information Systems (IJDIS)", "doi": "10.20533/ijds.2040.2570.2020.0205", "doi_url": "https://doi.org/10.20533/ijds.2040.2570.2020.0205", "primary_url": "https://dx.doi.org/10.20533/ijds.2040.2570.2020.0205", "accessible_url": "https://dx.doi.org/10.20533/ijds.2040.2570.2020.0205", "access_label": "Publisher abstract or article landing page captured; full-text access not established.", "access_class": "abstract", "research_question": "Which issues are reported in research on SaaS adoption by small and medium enterprises, and what responses are proposed?", "design": "Systematic literature review across six academic databases: 682 records retrieved and 42 SaaS-adoption articles selected, focused on SME adoption.", "sample_context": "Systematic literature review across six academic databases: 682 records retrieved and 42 SaaS-adoption articles selected, focused on SME adoption.", "findings": "The review coded 58 issues, 32 causal associations, and 26 treatments; security and operational/support problems were especially frequent and important.", "limitations": "Evidence is secondary literature rather than a new firm-level causal sample; findings depend on database search, inclusion, and coding choices.", "founder_use": "Useful as a risk and onboarding checklist, not as an estimate of SaaS conversion or churn effects; validate locally by segment, geography, and product category.", "evidence_basis": "Publisher article page directly retrieved with Firecrawl (reference 01a122bc-9402-767b-9e18-21a6789d656d). The annotation follows the retrieved title/abstract or landing-page record; full methods and correction notices were not independently reviewed.", "source_ids": [ "01a122bc-9402-767b-9e18-21a6789d656d" ], "corrections": [], "plain_english_summary": "The review coded 58 issues, 32 causal associations, and 26 treatments; security and operational/support problems were especially frequent and important. Founder-use interpretation: Useful as a risk and onboarding checklist, not as an estimate of SaaS conversion or churn effects; validate locally by segment, geography, and product category.", "evidence_check": { "score": 3.5, "label": "Useful empirical or synthesis evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "1/2", "note": "Scored from the described study design; an analytical or review design is not treated as a randomized field estimate." }, { "name": "Sample", "score": "1/1", "note": "The setting and reported sample detail are stated explicitly; size alone does not establish representativeness." }, { "name": "Comparison", "score": "0.5/1", "note": "The reported comparison or synthesis method is described from the retrieved article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "A publisher page or abstract was directly retrieved; full methods access was not established." } ], "blinding": "Blinding is not stated in the publisher record reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "the-effects-of-generative-ai-on-high-skilled-work-evidence-from-three-field", "title": "The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers", "category": "Developer productivity and AI", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Peng, S. & Demirer, M. (2026). The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers. Management Science (Articles in Advance).", "authors": [ "Sida Peng", "Mert Demirer" ], "year": 2026, "journal": "Management Science (Articles in Advance)", "doi": "10.1287/mnsc.2025.00535", "doi_url": "https://doi.org/10.1287/mnsc.2025.00535", "primary_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2025.00535", "accessible_url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2025.00535", "access_label": "Publisher abstract or article landing page captured; full-text access not established.", "access_class": "abstract", "research_question": "What effect did access to generative AI have on software developers\u2019 task completion in three company field experiments?", "design": "Three randomized field experiments run in ordinary business operations at Microsoft, Accenture, and an anonymous Fortune 100 company; 4,867 software developers received randomized access or no access to an AI coding assistant.", "sample_context": "Three randomized field experiments run in ordinary business operations at Microsoft, Accenture, and an anonymous Fortune 100 company; 4,867 software developers received randomized access or no access to an AI coding assistant.", "findings": "Pooling the experiments, AI access increased completed tasks by 26.08% (SE 10.3%); less-experienced developers adopted more and had larger gains, while individual experiments were noisy and heterogeneous.", "limitations": "Company-specific coding assistant, firms, tasks, and outcome metric limit external validity; pooled estimate masks variation and does not establish effects on product quality, revenue, or long-run retention.", "founder_use": "Strong evidence for testing AI-assisted engineering productivity, not a promise of proportional headcount or SaaS growth; run a controlled rollout with quality, security, rework, and customer outcomes.", "evidence_basis": "Publisher article page directly retrieved with Firecrawl (reference 01a122bc-9e6a-738d-9df6-6070598d013e). The annotation follows the retrieved title/abstract or landing-page record; full methods and correction notices were not independently reviewed.", "source_ids": [ "01a122bc-9e6a-738d-9df6-6070598d013e" ], "corrections": [], "plain_english_summary": "Pooling the experiments, AI access increased completed tasks by 26.08% (SE 10.3%); less-experienced developers adopted more and had larger gains, while individual experiments were noisy and heterogeneous. Founder-use interpretation: Strong evidence for testing AI-assisted engineering productivity, not a promise of proportional headcount or SaaS growth; run a controlled rollout with quality, security, rework, and customer outcomes.", "evidence_check": { "score": 4.5, "label": "Useful empirical or synthesis evidence with context-specific transfer limits", "components": [ { "name": "Design", "score": "2/2", "note": "Scored from the described study design; an analytical or review design is not treated as a randomized field estimate." }, { "name": "Sample", "score": "1/1", "note": "The setting and reported sample detail are stated explicitly; size alone does not establish representativeness." }, { "name": "Comparison", "score": "1/1", "note": "The reported comparison or synthesis method is described from the retrieved article record." }, { "name": "Can we check it?", "score": "0.5/1", "note": "A publisher page or abstract was directly retrieved; full methods access was not established." } ], "blinding": "Blinding is not stated in the publisher record reviewed; that does not establish whether blinding was or was not used." }, "reviewed_on": "2026-10-09" }, { "slug": "the-cost-of-free-the-effects-of-wait-for-free-pricing-schemes-on-the-monetiz", "title": "The Cost of Free: The Effects of \u201cWait-for-Free\u201d Pricing Schemes on the Monetization of Serialized Digital Content", "category": "SaaS adoption and monetization", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Choi, A. A., Rhee, K. E., Yoon, C., & Oh, W. (2023). The Cost of Free: The Effects of \u201cWait-for-Free\u201d Pricing Schemes on the Monetization of Serialized Digital Content. MIS Quarterly: Management Information Systems.", "authors": [ "Angela Aerry Choi", "Ki Eun Rhee", "Chamna Yoon", "Wonseok Oh" ], "year": 2023, "journal": "MIS Quarterly: Management Information Systems", "doi": "10.25300/MISQ/2022/17196", "doi_url": "https://doi.org/10.25300/MISQ/2022/17196", "primary_url": "https://doi.org/10.25300/MISQ/2022/17196", "accessible_url": "https://doi.org/10.25300/MISQ/2022/17196", "access_label": "Publisher article or abstract page directly retrieved with Firecrawl; full methods access varies.", "access_class": "abstract", "research_question": "The Cost of Free: The Effects of \u201cWait-for-Free\u201d Pricing Schemes on the Monetization of Serialized Digital Content?", "design": "Combination of analytical/economic modeling and empirical assessment of wait-for-free consumer behavior, including switching from waiting to immediate purchase.", "sample_context": "Serialized digital entertainment content on online platforms, where users can wait to obtain an episode free or pay immediately. The publisher record does not disclose the platform identity or a respondent count.", "findings": "Wait-for-free pricing generated new demand and increased serialized-content sales, with sustained long-run profits in the reported setting. As users accumulated free episodes, conversion to instant purchase rose up to a threshold and then declined; one free episode could raise purchase likelihood by up to 13%.", "limitations": "The publisher describes digital entertainment rather than B2B software and does not disclose the platform/sample count in the record. Thus transfer to SaaS trial design, usage limits, and enterprise pricing is an open empirical question.", "founder_use": "Use this as a question to test in your own product context, not as a universal benchmark. The publisher describes digital entertainment rather than B2B software and does not disclose the platform/sample count in the record. Thus transfer to SaaS trial design, usage limits, and enterprise pricing is an open empirical question.", "evidence_basis": "Publisher record directly retrieved with Firecrawl (reference 01a122ca-77a7-7024-b16c-30ca56d78a4a); summary is a careful paraphrase of the accessible record.", "source_ids": [ "01a122ca-77a7-7024-b16c-30ca56d78a4a" ], "corrections": [], "plain_english_summary": "Wait-for-free pricing generated new demand and increased serialized-content sales, with sustained long-run profits in the reported setting. As users accumulated free episodes, conversion to instant purchase rose up to a threshold and then declined; one free episode could raise purchase likelihood by up to 13%. Founder-use interpretation: Use this as a question to test in your own product context, not as a universal benchmark. The publisher describes digital entertainment rather than B2B software and does not disclose the platform/sample count in the record. Thus transfer to SaaS trial design, usage limits, and enterprise pricing is an open empirical question.", "evidence_check": { "score": 3.5, "label": "Relevant empirical or synthesis evidence with transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Based on the reported design." }, { "name": "Sample", "score": "0.5/1", "note": "Context and reporting are stated; representativeness is bounded." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison detail varies by publisher access." }, { "name": "Can we check it?", "score": "1/1", "note": "Publisher record directly retrieved; full methods may not be accessible." } ], "blinding": "Not established in this retrieval." }, "reviewed_on": "2026-10-09" }, { "slug": "making-a-first-impression-as-a-start-up-strategies-to-overcome-low-initial-t", "title": "Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption", "category": "Customer acquisition and trust", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Konya-Baumbach, E., Schuhmacher, M. C., Kuester, S., & Kuharev, V. (2019). Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption. International Journal of Research in Marketing.", "authors": [ "Elisa Konya-Baumbach", "Monika C. Schuhmacher", "Sabine Kuester", "Victoria Kuharev" ], "year": 2019, "journal": "International Journal of Research in Marketing", "doi": "10.1016/j.ijresmar.2019.01.008", "doi_url": "https://doi.org/10.1016/j.ijresmar.2019.01.008", "primary_url": "https://doi.org/10.1016/j.ijresmar.2019.01.008", "accessible_url": "https://doi.org/10.1016/j.ijresmar.2019.01.008", "access_label": "Publisher article or abstract page directly retrieved with Firecrawl; full methods access varies.", "access_class": "abstract", "research_question": "Making a first impression as a start-up: Strategies to overcome low initial trust perceptions in digital innovation adoption?", "design": "Five experiments, including randomized online between-subjects experiments and a quasi-field experiment with a start-up; mediation analyses test initial trust as the mechanism between business-model signals and adoption intentions.", "sample_context": "Digital-innovation launch scenarios including an augmented-reality city-guide app, a smart-insurance app, and an interior-design planner; publisher methods report final samples of 174, 90, 91, 173, and 200 across the experiments, using European online-panel participants and business-school students.", "findings": "Customer ratings, benefit communication, and revenue model were effective design signals for increasing adoption of digital innovations by improving initial trust. Revenue model also affected privacy concerns, which mediated its relationship with initial trust; the publisher discussion reports that positive-rating quantity itself did not significantly affect initial trust/adoption in one test.", "limitations": "The article\u2019s discussion notes that negative ratings were not tested, alternative revenue models such as freemium/subscription/advertising remain for future work, and additional mediators/moderators may exist. Simulated digital-innovation presentations and mostly European samples limit direct evidence about long-run real-product usage.", "founder_use": "Use this as a question to test in your own product context, not as a universal benchmark. The article\u2019s discussion notes that negative ratings were not tested, alternative revenue models such as freemium/subscription/advertising remain for future work, and additional mediators/moderators may exist. Simulated digital-innovation presentations and mostly European samples limit direct evidence about long-run real-product usage.", "evidence_basis": "Publisher record directly retrieved with Firecrawl (reference 01a122ca-8d7a-755c-92a3-8120f79f73c2); summary is a careful paraphrase of the accessible record.", "source_ids": [ "01a122ca-8d7a-755c-92a3-8120f79f73c2" ], "corrections": [], "plain_english_summary": "Customer ratings, benefit communication, and revenue model were effective design signals for increasing adoption of digital innovations by improving initial trust. Revenue model also affected privacy concerns, which mediated its relationship with initial trust; the publisher discussion reports that positive-rating quantity itself did not significantly affect initial trust/adoption in one test. Founder-use interpretation: Use this as a question to test in your own product context, not as a universal benchmark. The article\u2019s discussion notes that negative ratings were not tested, alternative revenue models such as freemium/subscription/advertising remain for future work, and additional mediators/moderators may exist. Simulated digital-innovation presentations and mostly European samples limit direct evidence about long-run real-product usage.", "evidence_check": { "score": 3.5, "label": "Relevant empirical or synthesis evidence with transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Based on the reported design." }, { "name": "Sample", "score": "0.5/1", "note": "Context and reporting are stated; representativeness is bounded." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison detail varies by publisher access." }, { "name": "Can we check it?", "score": "1/1", "note": "Publisher record directly retrieved; full methods may not be accessible." } ], "blinding": "Not established in this retrieval." }, "reviewed_on": "2026-10-09" }, { "slug": "impacts-of-license-choice-and-organizational-sponsorship-on-user-interest-an", "title": "Impacts of License Choice and Organizational Sponsorship on User Interest and Development Activity in Open Source Software Projects", "category": "Developer ecosystems and adoption", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Stewart, K. J., Ammeter, A. P., & Maruping, L. M. (2006). Impacts of License Choice and Organizational Sponsorship on User Interest and Development Activity in Open Source Software Projects. Information Systems Research.", "authors": [ "Katherine J. Stewart", "Anthony P. Ammeter", "Likoebe M. Maruping" ], "year": 2006, "journal": "Information Systems Research", "doi": "10.1287/isre.1060.0082", "doi_url": "https://doi.org/10.1287/isre.1060.0082", "primary_url": "https://doi.org/10.1287/isre.1060.0082", "accessible_url": "https://doi.org/10.1287/isre.1060.0082", "access_label": "Publisher article or abstract page directly retrieved with Firecrawl; full methods access varies.", "access_class": "abstract", "research_question": "Impacts of License Choice and Organizational Sponsorship on User Interest and Development Activity in Open Source Software Projects?", "design": "Archival/observational empirical study using project data from Freshmeat.net and project home pages; the authors develop and test models of user interest and developer activity.", "sample_context": "Open-source software projects listed on Freshmeat.net, with project-home-page information; outcomes are user interest and development activity. The publisher abstract does not report a project count.", "findings": "License restrictiveness and organizational sponsorship interacted: users were most attracted to projects sponsored by nonmarket organizations and using nonrestrictive licenses. Licensing and sponsorship also addressed complementary developer motivations, so licensing\u2019s relationship with development activity depended on sponsor type.", "limitations": "The publisher abstract does not provide an explicit limitations section or a causal identification strategy. Because the evidence is observational and tied to Freshmeat.net/project-home-page listings, representativeness and causal interpretation beyond those projects remain uncertain.", "founder_use": "Use this as a question to test in your own product context, not as a universal benchmark. The publisher abstract does not provide an explicit limitations section or a causal identification strategy. Because the evidence is observational and tied to Freshmeat.net/project-home-page listings, representativeness and causal interpretation beyond those projects remain uncertain.", "evidence_basis": "Publisher record directly retrieved with Firecrawl (reference 01a122ca-e3e8-769a-8d79-d09f4d5f3992); summary is a careful paraphrase of the accessible record.", "source_ids": [ "01a122ca-e3e8-769a-8d79-d09f4d5f3992" ], "corrections": [], "plain_english_summary": "License restrictiveness and organizational sponsorship interacted: users were most attracted to projects sponsored by nonmarket organizations and using nonrestrictive licenses. Licensing and sponsorship also addressed complementary developer motivations, so licensing\u2019s relationship with development activity depended on sponsor type. Founder-use interpretation: Use this as a question to test in your own product context, not as a universal benchmark. The publisher abstract does not provide an explicit limitations section or a causal identification strategy. Because the evidence is observational and tied to Freshmeat.net/project-home-page listings, representativeness and causal interpretation beyond those projects remain uncertain.", "evidence_check": { "score": 3.5, "label": "Relevant empirical or synthesis evidence with transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Based on the reported design." }, { "name": "Sample", "score": "0.5/1", "note": "Context and reporting are stated; representativeness is bounded." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison detail varies by publisher access." }, { "name": "Can we check it?", "score": "1/1", "note": "Publisher record directly retrieved; full methods may not be accessible." } ], "blinding": "Not established in this retrieval." }, "reviewed_on": "2026-10-09" }, { "slug": "how-peripheral-developers-contribute-to-open-source-software-development", "title": "How Peripheral Developers Contribute to Open-Source Software Development", "category": "Developer ecosystems and adoption", "study_type": "Peer-reviewed empirical study or research synthesis", "citation": "Setia, P., Rajagopalan, B., Sambamurthy, V., & Calantone, R. (2012). How Peripheral Developers Contribute to Open-Source Software Development. Information Systems Research.", "authors": [ "Pankaj Setia", "Balaji Rajagopalan", "Vallabh Sambamurthy", "Roger Calantone" ], "year": 2012, "journal": "Information Systems Research", "doi": "10.1287/isre.1100.0311", "doi_url": "https://doi.org/10.1287/isre.1100.0311", "primary_url": "https://doi.org/10.1287/isre.1100.0311", "accessible_url": "https://doi.org/10.1287/isre.1100.0311", "access_label": "Publisher article or abstract page directly retrieved with Firecrawl; full methods access varies.", "access_class": "abstract", "research_question": "How Peripheral Developers Contribute to Open-Source Software Development?", "design": "Longitudinal observational study of open-source products using hierarchical linear modeling to estimate how peripheral-developer involvement relates to product quality and diffusion over product-development stages.", "sample_context": "147 open-source software products; peripheral developers are external volunteers whose contributions include product-quality work and word-of-mouth advocacy/diffusion.", "findings": "Peripheral developers made significant contributions to product quality and diffusion, especially when projects were in more mature product-development stages.", "limitations": "The publisher abstract does not report a dedicated limitations section. The study is observational and its sample consists of 147 open-source products, so representativeness, measurement validity, and causal interpretation beyond the sampled projects cannot be established from the publisher record alone.", "founder_use": "Use this as a question to test in your own product context, not as a universal benchmark. The publisher abstract does not report a dedicated limitations section. The study is observational and its sample consists of 147 open-source products, so representativeness, measurement validity, and causal interpretation beyond the sampled projects cannot be established from the publisher record alone.", "evidence_basis": "Publisher record directly retrieved with Firecrawl (reference 01a122cb-0315-7609-866e-c5ea0a7a6079); summary is a careful paraphrase of the accessible record.", "source_ids": [ "01a122cb-0315-7609-866e-c5ea0a7a6079" ], "corrections": [], "plain_english_summary": "Peripheral developers made significant contributions to product quality and diffusion, especially when projects were in more mature product-development stages. Founder-use interpretation: Use this as a question to test in your own product context, not as a universal benchmark. The publisher abstract does not report a dedicated limitations section. The study is observational and its sample consists of 147 open-source products, so representativeness, measurement validity, and causal interpretation beyond the sampled projects cannot be established from the publisher record alone.", "evidence_check": { "score": 3.5, "label": "Relevant empirical or synthesis evidence with transfer limits", "components": [ { "name": "Design", "score": "1.5/2", "note": "Based on the reported design." }, { "name": "Sample", "score": "0.5/1", "note": "Context and reporting are stated; representativeness is bounded." }, { "name": "Comparison", "score": "0.5/1", "note": "Comparison detail varies by publisher access." }, { "name": "Can we check it?", "score": "1/1", "note": "Publisher record directly retrieved; full methods may not be accessible." } ], "blinding": "Not established in this retrieval." }, "reviewed_on": "2026-10-09" } ], "assessment_note": "The 1\u20135 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design." }