Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs

Abstract
With the widespread adoption of smartphones, users now have easy access to similar services, leading to increased churn. As a result, it has become essential for service providers to prevent churn caused by customers’ switch to competing services. The most common approach for service providers to prevent their customers’ churn is to make churn predictions by monitoring customers’ usage patterns of their own services. However, despite the importance of insights concerning customers’ usage of competing services for the retention of customers, such information are yet to be integrated into churn prediction models due to the lack of suitable monitoring methods. Here, we propose an approach to predict user churn leveraging the event logs from smartphones and tablets. Instead of conventional churn prediction methods that solely rely on the users’ usage patterns of their own service, our approach predicts churn by utilizing users’ usage patterns of competing services, including their trial use of service before switch to competitor’s. We evaluated the prototyped prediction model using smartphone logs collected from NTT DOCOMO smartphone and tablet users who consented to data collection between April 2020 and March 2021. The results demonstrated that the proposed method achieved AUC values ranging from 0.844 to 0.923. Moreover, our approach improved the performance of the conventional method that predicts churn without leveraging the features of the competitor’s app by 1.8% to 7.5%.