Abstract
Personalization is an emerging digital strategy to engage users across different business domains. It is defined as the capability to match content, products, and services to individual users based on the knowledge of their past behaviors and revealed preferences. It has shown its great potential across a variety of contexts, including search engines, recommender systems, targeted marketing, and more. In this study, we examine personalization on third-party mobile app platforms, which account for a $36 billion market in 2021. We develop a comprehensive structural 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 margin. A series of policy experiments highlights the value of personalization to various extent. Remarkably, personalized rankings at the individual level outperform the current practice by 16.73%. This cost-efficient approach showcases how platforms can leverage routine consumer clickstream data to personalize the ranking of app impressions, thereby more effectively monetizing mobile app distribution.
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