1 research outputs found
A State Transition Model for Mobile Notifications via Survival Analysis
Mobile notifications have become a major communication channel for social
networking services to keep users informed and engaged. As more mobile
applications push notifications to users, they constantly face decisions on
what to send, when and how. A lack of research and methodology commonly leads
to heuristic decision making. Many notifications arrive at an inappropriate
moment or introduce too many interruptions, failing to provide value to users
and spurring users' complaints. In this paper we explore unique features of
interactions between mobile notifications and user engagement. We propose a
state transition framework to quantitatively evaluate the effectiveness of
notifications. Within this framework, we develop a survival model for badging
notifications assuming a log-linear structure and a Weibull distribution. Our
results show that this model achieves more flexibility for applications and
superior prediction accuracy than a logistic regression model. In particular,
we provide an online use case on notification delivery time optimization to
show how we make better decisions, drive more user engagement, and provide more
value to users.Comment: 9 pages, 7 figures. Published in WSDM 19