Personal Behavior Composite Data Analysis Based on Mobile Networks

Abstract

The paper mainly proposes the research of solving the analysis of APP operation behavior and social personal behavior preference. Through the paper put forward that the three modules implementation for data collection and analysis, which are processed according to the algorithm of each module, and its effective in the analysis of the personalized data overlapping of APP operation behavior and social network platform (Facebook). The planning of the modules presented in the paper. After the system actual verification, on the APP, the total average stay time of assignment increased by 55.96%, total average bounce rate of assignment reduced 53.44%, total average click through rate of assignment increased 1.1 times, total average click through rate of commodity increased 1.3 times, total average redemption rate of commodity increased 2.29 times, total average purchase rate of the commodity increased 12 times.