An intelligent information system for analysing the mobile applications market

Abstract

The article considers the main advantages and disadvantages of similar information systems for the analysis of online application stores: “AppFollow”, “42matters: App Market Data & Mobile Audience Data”, and “AppAnnie”. The article presents a functional diagram of the system being developed, which includes four functional blocks responsible for monitoring online application stores, updating data in the database, obtaining aggregated data, and visualising the results of the aggregation. The visualisation block is considered in detail. This block uses the results of aggregation and custom visualisation settings to determine the parameters and to create graphs, charts, and reports. Interpolation, extrapolation, and regression analysis can be performed based on the plotted graphs. The article presents a mathematical model of the database for the developed information system. It also suggests a mathematical description of the formal language designed to describe functional dependencies between various characteristics of mobile applications. The formal language is used during the stages of data aggregation and visualisation. The language model of the formal language allows building more than 100 types of graphs and can be used in other subject areas. The article considers the functions of the developed information system, which solves the problems of monitoring, collecting, and updating information about various characteristics of mobile applications in online stores. The developed information system provides analysts with tools for automating the procedure of comprehensive analysis of the sales dynamics of online application stores. The system allows developers of mobile applications to determine the most promising directions, to estimate sales volumes in various market segments, and to obtain new knowledge. For instance, during the analysis, a correlation was found between the parameters “Rating” and “Date of last update” — the more often the application is updated, the higher its rating.