The Telecommunications Mobile Customer Churn Prediction Cn Model

Mobile phone users have been rising in a stable way in recent years. Customers have become valuable resources of telecommunications operators, competition between the telecommunications operators become drastic. How to avoid customers churn, retain customers, make scientific and rational marketing and services strategy to reduce customer churn ratio at the greatest extent, has become one of the focus telecommunication operators should pay attention to.After years of development, telecommunication operators have many mature database systems, which accumulated large amounts of business data. However, faced with massive data, if we want to obtain useful information, to predict churn tendency of customer in the near future, and how to take proper measures to retain customers, traditional analysis method which Based on the customer behavior has been unable to meet this demand.Some Foreign telecom companies have already used data mining for customer churn predicting. Domestic telecommunication enterprises focus on establishing customer relationship management system to maintain and retain customers, few predict customer churn according to existing literature.The research on customer churn prediction focus on using single data mining method to build predictive model, these methods always only give the probability of customer churn, and they don not represent better effect in practice. Based on former research, combining the mobile communications industry status in customer hold management, this paper builds C-N hybrid model for customer churn prediction using decision tree and neural network method .In this paper, a theoretical research and empirical study method is used. Based on China Unicom G branch's customer data, this paper builds C-N hybrid model, including a detailed explanation of the whole process such as attributes choosing, data preparation, construction of the model and model evaluation and application. In this paper, a more reasonable evaluation method - numerical indicators and the graphic indicators are used to evaluate the result of the model. The result indicates that the hybird model has better accuracy and hit rates. Meanwhile, the C-N model presents better results than the existing method used by telecom industry at home.Finally, using the results of the C-N model, this paper analyses the probability of the G Unicom's customer churn in the next month, and the churning customer's characteristics, such as average fee, length of service, gender, total number of outgoing calls and so on, and sum up the reason for the loss of customers, and give the corresponding measures to retain customers. The customers predicting hybird mobile proposed in this paper may provide some references to the analysis of the customer churn in the telecommunication industry.