Open AccessEstablishing Continuous App Improvement by Considering Heterogenous Data Sources
Author(s) -
Simon André Scherr,
Steffen Hupp,
Frank Elberzhager
Publication year - 2021
Publication title -
international journal of interactive mobile technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 16
ISSN - 1865-7923
DOI - 10.3991/ijim.v15i10.20613
Subject(s) - computer science , scheduling (production processes) , mobile apps , product (mathematics) , quality (philosophy) , architecture , world wide web , engineering , operations management , philosophy , geometry , mathematics , epistemology , art , visual arts
Mobile apps have penetrated the market and are being used everywhere. Companies developing apps face increasing challenges such as short time to market or demand for high quality. Furthermore, the success of an app also depends on how users perceive its quality. Feedback provided by users influences other potential users and provides new opportunities for identifying features. Consequently, it is a valuable source of input for app developers with respect to product improvements. One form is textual feedback. This kind of feedback is usually distributed across various data sources. Therefore, it must be captured from these sources and put into one single pool of data before it can be analyzed. The analysis must take into account the peculiarities of the short release cycles and high change rate of features for mobile apps. In this article, we present User Echo Service (UES), which was built to address heterogeneous data sources. The aim of UES is to allow product managers to be able to be always up to date with the latest feedback data. Therefore, we have created an extensible architecture aimed at supporting different data sources and present the feedback collection scheduling system. This forms the prerequisite for subsequent analyses of the collected data. We discuss our solution and provide ideas for future development.