Personalized Ranking at a Mobile App Distribution Platform

Shengjun Mao (), Sanjeev Dewan () and Yi-Jen (Ian) Ho ()
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Shengjun Mao: Faculty of Business and Economics, The University of Hong Kong, Hong Kong
Sanjeev Dewan: Paul Merage School of Business, University of California– Irvine, Irvine, California 92697
Yi-Jen (Ian) Ho: Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802

Information Systems Research, 2023, vol. 34, issue 3, 811-827

Abstract: The ease of customer data collection has enabled the widespread personalization of content and services in digital platforms. We examine personalization in a hitherto unaddressed context: that of mobile app distribution. Specifically, we develop a comprehensive framework for the personalized ranking of app impressions, leveraging revealed preferences embedded in consumer clickstream data. To improve platform revenues, the framework jointly accounts for consumer utility and cost per action (CPA) margin, which is the revenue earned by the platform per app installation. To this end, we specify a structural model of click and installation choices, jointly estimated as a function of a comprehensive set of numerical (screen rank, quality, and popularity) and textual (titles, descriptions, and reviews) covariates. Our novel data set is at the granular user-impression level and uniquely includes app CPA margins paid to the platform. We conduct a series of policy experiments to quantify the value of personalization. Specifically, we show that a personalized hybrid margin and utility margin ranking scheme outperforms other personalized methods, including those based on utilities alone or a combination of utilities and margins. Overall, our analysis demonstrates how platforms can leverage routine consumer clickstream data to personalize the ranking of app impressions, thereby more effectively monetizing mobile app distribution.

Keywords: mobile; ranking; app; platform revenue; hierarchical Bayes (search for similar items in EconPapers)
Date: 2023
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