Modeling User Engagement in Mobile Content Consumption with Tapstream Data and Field Experiment

42 Pages Posted: 5 Oct 2016  

Yingjie Zhang

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management

Beibei Li

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management

Xueming Luo

Temple University

Xiaoyi Wang Sr.

Zhejiang University

Date Written: September 15, 2016

Abstract

Low engagement rates and high attrition rates have been formidable challenges for mobile apps and their long-term success, especially for those whose revenues come mainly from in-app purchases. To date, still little is known about how companies can comprehensively identify user engagement stages so as to improve business revenues. This paper proposes a structural econometric framework for modeling of consumer latent engagement stages that accounts for both the time-varying nature of engagement and consumer forward-looking consumption behavior. The present study analyzed a fine-grained mobile tapstream dataset on mobile users' continuous content consumption behavior in a popular mobile reading app. Our policy simulation enabled us to tailor, based on the model-detected engagement stages, an optimal pricing strategy to each consumer. Interestingly, we found that such an engagement-specific pricing strategy leads, simultaneously, to lower average prices for consumers and higher overall business revenues for the app. To further evaluate the effectiveness of our method, we conducted a randomized field experiment on a mobile app platform. Our experimental results provide more causal evidence that a personalized promotion strategy targeting user engagement stages can both decrease costs to app users and enhance overall business performance. Our structural-model- and field-experimentation-based findings are nontrivial and suggest, with respect to the crucial role of modeling user engagement, potential overall welfare improvements in the mobile app market.

Keywords: User engagement, Mobile content consumption, App platforms, Hidden-state model, Forward-looking behavior, Structural econometric model, Field experiment

Suggested Citation

Zhang, Yingjie and Li, Beibei and Luo, Xueming and Wang, Xiaoyi, Modeling User Engagement in Mobile Content Consumption with Tapstream Data and Field Experiment (September 15, 2016). Available at SSRN: https://ssrn.com/abstract=2847634 or http://dx.doi.org/10.2139/ssrn.2847634

Yingjie Zhang

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management ( email )

Pittsburgh, PA 15213-3890
United States

Beibei Li

Carnegie Mellon University - H. John Heinz III School of Public Policy and Management ( email )

Pittsburgh, PA 15213-3890
United States

Xueming Luo (Contact Author)

Temple University ( email )

1810 N. 13th Street
Floor 2
Philadelphia, PA 19128
United States

HOME PAGE: http://www.fox.temple.edu/mcm_people/xueming-luo/

Xiaoyi Wang Sr.

Zhejiang University ( email )

38 Zheda Road
Hangzhou, Zhejiang 310058
China

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