I'll Be Back: On the Multiple Lives of Users of a Mobile Activity Tracking Application
Mobile health applications that track activities, such as exercise, sleep, and diet, are becoming widely used. While these activity tracking applications have the potential to improve our health, user engagement and retention are critical factors for their success. However, long-term user engagement...
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| Vydáno v: | Proceedings of the ... International World-Wide Web Conference. International WWW Conference Ročník 2018; s. 1501 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Netherlands
01.04.2018
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| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | Mobile health applications that track activities, such as exercise, sleep, and diet, are becoming widely used. While these activity tracking applications have the potential to improve our health, user engagement and retention are critical factors for their success. However, long-term user engagement patterns in real-world activity tracking applications are not yet well understood. Here we study user engagement patterns within a mobile physical activity tracking application consisting of 115 million logged activities taken by over a million users over 31 months. Specifically, we show that over 75% of users return and re-engage with the application after prolonged periods of inactivity, no matter the duration of the inactivity. We find a surprising result that the re-engagement usage patterns resemble those of the
of the initial engagement period, rather than being a simple continuation of the
of the initial engagement period. This evidence points to a conceptual model of
of user engagement, extending the prevalent
view of user activity. We demonstrate that these multiple lives occur because the users have a variety of different
for using the app. These primary intents are associated with how long each life lasts and how likely the user is to re-engage for a new life. We find evidence for users being more likely to stop using the app once they achieved their primary intent or goal (
, weight loss). However, these users might return once their original intent resurfaces (
, wanting to lose newly gained weight). We discuss implications of the
and propose a novel prediction task of predicting the number of lives of a user. Based on insights developed in this work, including a marker of improved primary intent performance, our prediction models achieve 71% ROC AUC. Overall, our research has implications for modeling user re-engagement in health activity tracking applications and has consequences for how notifications, recommendations as well as gamification can be used to increase engagement. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| DOI: | 10.1145/3178876.3186062 |