AI-based early detection to prevent user churn inMMORPG

Massive multiplayer online role playing game (MMORPG) is a common type of game these days. Predictinguser churn in MMORPG is a crucial task. The retention rate of users is deeply associated with the lifespan andrevenue of the service. If the churn of a specific user can be predicted in advance, targeted promotions can be usedto encourage their stay. Therefore, not only the accuracy of churn prediction but also the speed at which signs ofchurn can be detected is important. In this paper, we propose methods to identify early signs of churn by utilizingthe daily predicted user retention probabilities. We train various deep learning and machine learning modelsusing log data and estimate user retention probabilities. By analyzing the change patterns in these probabilities,we provide empirical rules for early identification of users at high risk of churn. Performance evaluations confirmthat our methodology is more effective at detecting high risk users than existing methods based on login days.Finally, we suggest novel methods for customized marketing strategies. For this purpose, we provide guidelinesof the percentage of accessed users who are at risk of churn.