B2B growth and sales · 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
Technology Usage and Online Sales: An Empirical Study
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.
Plain-English take
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.
How much weight to give this
3/5 Moderate evidence for a specific setting
The 1–5 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.
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.
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.
Based on the publisher-described design and comparison; see the article for complete analysis.
Publisher record was fetched directly; full text was not assumed open.
Double-blind? Blinding was not established from the retrieved publisher record.
Research question
What the authors investigated
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 and setting
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.
Reported result
What the study found
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.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
Scope and transfer
Limitations to keep in view
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.
Possible founder application
Use it as a B2B mechanism or sales-process design reference. Validate the relationship in your deal size, buying committee and sales cycle.
Evidence access
Publisher abstract/metadata retrieved; consult the linked paper for full methods and tables.
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.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.