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The Customer Churn Analysis Of Mobile Based On Customer Relation Management

Posted on:2008-05-06Degree:MasterType:Thesis
Country:ChinaCandidate:C J SongFull Text:PDF
GTID:2189360218950372Subject:Business management
Abstract/Summary:PDF Full Text Request
Along with the open of telecom market, the contests for customers are getting more and more drastic. As the saturation of the telecom market, the cost of getting a new customer is much higher than maintaining an old customer. So, how to keep the customers, especially the valuable customers, came to one of the most important works for the telecom companies. As one of the important parts of the Analyzer Support System of China mobile, building the model of the churn users will allow the company to analyze the consume characters of those churned user, to find out those customers who are going to churn, so to take actions in time. So the study of this topic has very importance significance for reducing the cost of running the company and to improve the outstanding achievement of the company.According to the inquisition, Majority of mobile enterprises has established system of CRM, Operation CRM and Outlet CRM made use of more extensively, and also more maturely, Analyze CRM still be placed in the beginning stage. Making use of analyze CRM to manage the customer churn will show the trend.This thesis point out the problem of telecommunication enterprise CRM and customers churn management on the foundation of analysis competition structure of telecommunication enterprise of our country. Analyze the theories frame of CRM and the core of the Analyze CRM, Point out the importance of Data Mining to analysis the customer churn. make up of the theories of customer churn,customer value, customer classification and the customer life cycle theories to analysis the customer churn, show the familiar factor that affect customer churn and make use of the customer churn index to acquire the important churn factor. At the same time, adopt the Data Mining technique to predict the customer churn. Finally, according to customer of Possible churn that acquired in the model of predict process to reserve customer.
Keywords/Search Tags:customer churn, customer relation management, customer relation life cycle, data mining, value of reserve
PDF Full Text Request
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