Mobile Customer Churn Management System Design And Implementation

With the telecom reforming further, the competition in telecom market becomes more and more violent. Customer resource is one of the most important assets for the telcos, and become the focus of competition. Customer retention can have more influence on the company's profit than its scale, market share, margin and other factors. Especially for telecom, almost every telco is building or is going to build customer churn predictive model. Otherwise, it will lose competitive advantage over its competitor due to lack of prediction for customer churn.In recent years, data mining technology has become one of the research hotspots in Information Industry. It mines non-trivial, implicit, previously, unknown and potentially useful information or patterns from data in large databases. In this paper, Decision Trees and BP Neural network were adopted to analyze the factors which cause customer churn and the relationship among them. Thus, customer churn trend can be predicted by means of the analytical model.From the second chapter on, the development of data mining technology is introduced, including definition, main techniques, system architecture, methodology, some practical arithmetics, and so on. After that, according to the up-to-date customer churn theory, the requirement analysis, system architecture and module design are made. In the fourth chapter, a concrete volume customer churn model is built and evaluated. Finally, summary is given to point out main difficulties faced with author's research. And a proposal for the future research is addressed.