Recommendations Systems: Beyond Matching Products to Buyers

32 Pages Posted: 2 Apr 2021

See all articles by Pedro Gardete

Pedro Gardete

Nova School of Business and Economics

Carlos Daniel Santos

New University of Lisbon - Nova School of Business and Economics

Date Written: February 1, 2021

Abstract

The digital revolution has allowed sellers to make large assortments of products available to consumers. Recommendation systems have played a central role in this dynamic. At the core of these systems is the use of data and sophisticated algorithms to predict match values between products and buyers.

By analyzing consumer search data and product recommendations of an online used car seller, we find that there is scope for value creation by recommendation systems beyond their primary matching role. More specifically, our analysis leverages search consumption: The fact that consumers enjoy inspecting at least some of the products on sale. We identify an engagement effect such that recommending some products with high hedonic value induces additional customer engagement while keeping baseline conversion rates unchanged. The engagement effect is economically significant in our data: It explains 55% of the potential value available to recommendation systems, the remaining 45% made up by the traditional product matching mechanism.

JEL Classification: D83, L86, M31

Suggested Citation

Gardete, Pedro and Santos, Carlos Daniel, Recommendations Systems: Beyond Matching Products to Buyers (February 1, 2021). Available at SSRN: https://ssrn.com/abstract=3160247 or http://dx.doi.org/10.2139/ssrn.3160247

Pedro Gardete (Contact Author)

Nova School of Business and Economics ( email )

Rua da Holanda, 1
Carcavelos, Lisbon 2775-405
Portugal

HOME PAGE: http://pedrogardete.com

Carlos Daniel Santos

New University of Lisbon - Nova School of Business and Economics ( email )

Campus de Campolide
Lisbon, 1099-032
Portugal

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
36
Abstract Views
296
PlumX Metrics