Development of big data analiysis methods in lifecycle management for user continuity on mobile applications

Mobile applications are a kind of application software designed to work on a mobile device such as a smartphone or tablet. Developed mobile applications are offered to users in mobile application virtual stores provided by different platforms, depending on the operating system. A variety of studies are being conducted to improve the user continuity of mobile applications within the mobile lifecycle. This is very important for mobile applications to be placed on the market. In this thesis, application of A / B tests for a big data analysis method defined in mobile application lifecycle management has been developed to ensure user continuity in mobile applications. For this purpose, two versions of the A / B test have been prepared for the orientation step in the flow of an individual's transfer of money to another individual on an individual messaging chat window based on a mobile application that has individual and group instant messaging features. Firstly, for the devices with iOS and Android operating system, A / B test integration is completed by installing appropriate software development kits of Mixpanel analytical tool. Then the AARRR metrics used for the mobile application lifecycle and the business model of this lifecycle were examined and the current studies in the literature for each of these metrics were examined. Then a method for activation metrics was developed and analyzes were performed to increase user continuity with A / B test on big data in selected application. As a result of these analyzes, all users who use instant messaging application were determined to be valuable in two versions prepared according to A / B test report results and distributed to all users.