A new framework for increasing user engagement in mobile applications using machine learning techniques

Authors:
Merve Gençer;Gökhan Bilgin;Özgür Zan;Tansel Voyvodaoğlu
Affiliations:
Done Info. and Com. Systems Istanbul, Turkey;Dept. of Computer Engineering, Yildiz Technical University, Istanbul, Turkey;Done Info. and Com. Systems Istanbul, Turkey;Done Info. and Com. Systems Istanbul, Turkey
Venue:
DUXU'13 Proceedings of the Second international conference on Design, User Experience, and Usability: web, mobile, and product design - Volume Part IV
Year:
2013

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Abstract

In this paper, it is proposed to build a new framework which anticipates mobile user status and behavior characteristics with the aim of increasing user engagement and provide stickiness in mobile applications (iOS-Android) by using machine learning techniques. Motivation of this study is based on the idea of collecting data from users by non-survey methods because data collection from surveys may mislead the system model according to the literature researches on user experience. User behavior includes forecasting next usage time of the user, user motivation type, user mastery level and current context of the user. In order to find relevant patterns, usage data is obtained from pilot mobile applications at first and then they are processed according to the chosen machine learning algorithm.