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

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorZuniga, Agustinen_US
dc.contributor.authorFlores, Huberen_US
dc.contributor.authorHui, Panen_US
dc.contributor.authorManner, Jukkaen_US
dc.contributor.authorNurmi, Petterien_US
dc.contributor.departmentDepartment of Communications and Networkingen
dc.contributor.groupauthorInternet technologiesen
dc.contributor.organizationUniversity of Helsinkien_US
dc.date.accessioned2019-07-30T07:19:41Z
dc.date.available2019-07-30T07:19:41Z
dc.date.issued2019-05-13en_US
dc.description.abstractWe 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.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationZuniga, A, Flores, H, Hui, P, Manner, J & Nurmi, P 2019, Tortoise or hare? Quantifying the effects of performance on mobile app retention. in Proceedings of the World Wide Web Conference (WWW '19). ACM, pp. 2517-2528, The Web Conference, San Francisco, California, United States, 13/05/2019. https://doi.org/10.1145/3308558.3313428en
dc.identifier.doi10.1145/3308558.3313428en_US
dc.identifier.isbn9781450366748
dc.identifier.otherPURE UUID: b522c63e-0523-4b4d-98bd-3819e00c12e1en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/b522c63e-0523-4b4d-98bd-3819e00c12e1en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85066887810&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/34936771/ELEC_zuniga_tortoise_www.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/39492
dc.identifier.urnURN:NBN:fi:aalto-201907304547
dc.language.isoenen
dc.relation.ispartofThe Web Conferenceen
dc.relation.ispartofseriesProceedings of the World Wide Web Conference (WWW '19)en
dc.relation.ispartofseriespp. 2517-2528en
dc.rightsopenAccessen
dc.subject.keywordApps retentionen_US
dc.subject.keywordCrowdsensingen_US
dc.subject.keywordData fusionen_US
dc.subject.keywordEnergy consumptionen_US
dc.subject.keywordMobile computingen_US
dc.subject.keywordMobile networksen_US
dc.subject.keywordPerformance evaluationen_US
dc.titleTortoise or hare? Quantifying the effects of performance on mobile app retentionen
dc.typeA4 Artikkeli konferenssijulkaisussafi
dc.type.versionpublishedVersion

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