Tortoise or Hare? Quantifying the Effects of Performance on Mobile App Retention

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

Abstract

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 2019 World Wide Web Conference (WWW ’19)
EditorsLing Liu, Rhyen White
Number of pages12
PublisherInternational World Wide Web Conferences Steering Committee
Publication date2019
Pages2517-2528
ISBN (Electronic)978-1-4503-6674-8
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in conference proceedings
EventInternational World Wide Web Conference on World Wide Web (WWW 2019) - Hyatt Regency San Francisco Hotel, San Francisco, United States
Duration: 13 May 201917 May 2019
Conference number: 28
https://www2019.thewebconf.org/

Fields of Science

  • 113 Computer and information sciences
  • performance evaluation
  • crowdsensing
  • data fusion
  • mobile computing
  • apps retention
  • mobile networks
  • energy consumption
  • performance evaluation
  • crowdsensing
  • data fusion
  • mobile computing
  • apps retention
  • mobile networks
  • energy consumption
  • HOT DECK IMPUTATION
  • EXPERIENCE
  • QUALITY

Cite this

Zuniga , A., Flores, H., Lagerspetz, E., Tarkoma, S., Manner, J., Hui, P., & Nurmi, P. (2019). Tortoise or Hare? Quantifying the Effects of Performance on Mobile App Retention. In L. Liu, & R. White (Eds.), Proceedings of the 2019 World Wide Web Conference (WWW ’19) (pp. 2517-2528). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3308558.3313428