Abstract

https://ssrn.com/abstract=2847634
 


 



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


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

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.

Number of Pages in PDF File: 42

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


Open PDF in Browser Download This Paper

Date posted: October 5, 2016  

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

Contact Information

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
Feedback to SSRN


Paper statistics
Abstract Views: 293
Downloads: 116
Download Rank: 190,720