Tortoise or hare? Quantifying the effects of performance on mobile app retention

Agustin Zuniga, Huber Flores, Pan Hui, Jukka Manner, Petteri Nurmi

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

19 Citations (Scopus)
211 Downloads (Pure)


We contribute by quantifying the effect of network latency and battery consumption on mobile app performance and retention, i.e., user's decisions to continue or stop using apps. We perform our analysis by fusing two large-scale crowdsensed datasets collected by piggybacking on information captured by mobile apps. We find that app performance has an impact in its retention rate. Our results demonstrate that high energy consumption and high latency decrease the likelihood of retaining an app. Conversely, we show that reducing latency or energy consumption does not guarantee higher likelihood of retention as long as they are within reasonable standards of performance. However, we also demonstrate that what is considered reasonable depends on what users have been accustomed to, with device and network characteristics, and app category playing a role. As our second contribution, we develop a model for predicting retention based on performance metrics. We demonstrate the benefits of our model through empirical benchmarks which show that our model not only predicts retention accurately, but generalizes well across application categories, locations and other factors moderating the effect of performance.

Original languageEnglish
Title of host publicationProceedings of the World Wide Web Conference (WWW '19)
Number of pages12
ISBN (Electronic)9781450366748
Publication statusPublished - 13 May 2019
MoE publication typeA4 Conference publication
EventThe Web Conference - San Francisco, United States
Duration: 13 May 201917 May 2019


ConferenceThe Web Conference
Abbreviated titleWWW
Country/TerritoryUnited States
CitySan Francisco
Internet address


  • Apps retention
  • Crowdsensing
  • Data fusion
  • Energy consumption
  • Mobile computing
  • Mobile networks
  • Performance evaluation


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