Modeling User Engagement in Mobile Content Consumption with Tapstream Data and Field Experiment
42 Pages Posted: 5 Oct 2016
Date Written: September 15, 2016
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: Suggested Citation