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Mobile health applications that track activities, such as exercise, sleep,and diet, are becoming widely used. While these activity tracking applicationshave the potential to improve our health, user engagement and retention arecritical factors for their success. However, long-term user engagement patternsin real-world activity tracking applications are not yet well understood. Herewe study user engagement patterns within a mobile physical activity trackingapplication consisting of 115 million logged activities taken by over a millionusers over 31 months. Specifically, we show that over 75% of users return andre-engage with the application after prolonged periods of inactivity, no matterthe duration of the inactivity. We find a surprising result that there-engagement usage patterns resemble those of the start of the initialengagement period, rather than being a simple continuation of the end of theinitial engagement period. This evidence points to a conceptual model ofmultiple lives of user engagement, extending the prevalent single life view ofuser activity. We demonstrate that these multiple lives occur because the usershave a variety of different primary intents or goals for using the app. We findevidence for users being more likely to stop using the app once they achievedtheir primary intent or goal (e.g., weight loss). However, these users mightreturn once their original intent resurfaces (e.g., wanting to lose newlygained weight). Based on insights developed in this work, including a marker ofimproved primary intent performance, our prediction models achieve 71% ROC AUC.Overall, our research has implications for modeling user re-engagement inhealth activity tracking applications and has consequences for hownotifications, recommendations as well as gamification can be used to increaseengagement.

I'll Be Back: On the Multiple Lives of Users of a Mobile Activity Tracking Application