Personalized Ranking at a Mobile App Distribution Platform

Information Systems Research (forthcoming)

44 Pages Posted: 18 Jun 2019 Last revised: 10 Jul 2022

See all articles by Shengjun Mao

Shengjun Mao

University of Hong Kong - Faculty of Business and Economics

Sanjeev Dewan

University of California, Irvine - Paul Merage School of Business

Yi-Jen (Ian) Ho

Tulane University - A.B. Freeman School of Business

Date Written: May 29, 2019

Abstract

The ease of customer data collection has enabled the widespread personalization of content and services on 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 could 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

JEL Classification: M15

Suggested Citation

Mao, Shengjun and Dewan, Sanjeev and Ho, Yi-Jen (Ian), Personalized Ranking at a Mobile App Distribution Platform (May 29, 2019). Information Systems Research (forthcoming), Available at SSRN: https://ssrn.com/abstract=3396085

Shengjun Mao

University of Hong Kong - Faculty of Business and Economics ( email )

KKL 813
The University of Hong Kong, Pokfulam
Hong Kong, Hong Kong
Hong Kong

Sanjeev Dewan

University of California, Irvine - Paul Merage School of Business ( email )

Paul Merage School of Business
Irvine, CA 92697-3125
United States

Yi-Jen (Ian) Ho (Contact Author)

Tulane University - A.B. Freeman School of Business ( email )

7 McAlister Drive
New Orleans, LA 70118
United States

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