Product adoption and customer behaviorEvidence check: 2/5
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
Plain-English take: 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.
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.. 11,744 observations from six biannual online-survey waves representing Germany's population aged 18–70; respondents were recruited by Respondi using quotas for age, gender, education, employment, and children.
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.
Journal of Interactive Marketing · 202410.1177/10949968231186950Publisher article page; full-text access varies and was not established in this check.
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Product adoption and customer behaviorEvidence check: 4/5
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
Plain-English take: 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.
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.. 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.
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.
Marketing Science · 202410.1287/mksc.2023.0324Publisher article page; full-text access varies and was not established in this check.
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Product adoption and customer behaviorEvidence check: 2/5
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
Plain-English take: 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.
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.. Dataset containing 457 firms classified as SMEs and large enterprises.
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.
Electronic Commerce Research · 202510.1007/s10660-023-09691-8Publisher article page; full-text access varies and was not established in this check.
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Product adoption and customer behaviorEvidence check: 2/5
Alexander Benlian, Thomas Hess, Peter Buxmann (2009). Drivers of SaaS-Adoption – An Empirical Study of Different Application Types. Business & Information Systems Engineering. https://doi.org/10.1007/s12599-009-0068-x
Plain-English take: 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.
Question: What does drivers of saas-adoption – 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.. Survey data from 297 firms in Germany, yielding 374 valid response items across different industries.
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.
Business & Information Systems Engineering · 200910.1007/s12599-009-0068-xPublisher article page; full-text access varies and was not established in this check.
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Product adoption and customer behaviorEvidence check: 3.5/5
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.
Plain-English take: 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.
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.. 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.
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.
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · 202510.1145/3706599.3706670Publisher abstract directly retrieved; full-text access not established
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