Research On Personalized Recommendation Based On Mobile User Behavior Information From Prospective Marketing Perspective

On the environment of Internet +, China's electricity supplier market has developed rapidly. In 2016, China's electricity supplier market has exceeded 2 billion in total.Network has become the backbone of the development of China's electricity supplier market. As of the first half of 2016, China's Internet users have more than 700 million,there're more than 600 million mobile phone users. China's online shopping users have more than 400 million, online shopping usage rate is 63%. Traditional enterprises are facing transformation. In the face of intense competition coupled with the lack of experience in the transformation of the traditional enterprises in the electricity supplier operations and product promotion unsatisfactory, compared with JingDong and TianMao,it has a lot of room to improve. leading electricity supplier market share,is the most important thing for traditional business company.Based on the perspective of precise marketing, the paper focused on personalized recommendation based on user behavior information. Firstly, we got a foreign research review to make clear the research goal of the thesis; then, carries on the related basic theory and the basic theoretical analysis to the mobile user behavior, the precise marketing and the individuation recommendation, the research on the domestic and foreign study actuality, understands the current research hotspot and the frontier;Focusing on the key processes and issues in precise marketing, based on the analysis of user's value, user preferences, consumer habits and user churn, the author constructs the user behavior analysis model of precise marketing, and then establishes the personalized recommendation scheme based on the mobile User behavior information analysis through the precise marketing user behavior analysis model. Based on the personalized recommendation of mobile user behavior information analysis, the feasibility analysis and the goal and principle of the scheme are proposed, and the personalized recommendation scheme for the analysis of mobile user behavior information is presented, and the personalized recommendation strategy based on mobile user behavior information is put forward in the case of a company online mall. In describing a company online mall on the basis of the survey, analysis a company online mall current development status and existing problems, from products, prices, promotions, channels to formulate a variety of precise marketing perspective based on mobile user behavior information personalized recommendation strategy.