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Building Customer Relationship Management System, Based On Data Mining

Posted on:2003-07-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y YanFull Text:PDF
GTID:2208360065961411Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
Customer Relationship Management(CRM) is a kind of new management systems aiming at improving the relationship between corporations and their customers. It can keep touch with and attract more and more customers through efficient and kind services. Meanwhile, it can decrease the corporations' costs through complete management of the operation flow.Data is the foundation for making out a good CRM. There is a great deal of important information concealed under the mass of data relevant to customers in corporation. But at the present time it can not be found out speedily and availably because of the disabality of method being used by people. Data Mining can set up the model which can forecast the trend of behavior of customers, help people to pick up the useful business information from mass of data and thereby nicely support people's decision. Data Mining is a new valuable field in database research.Aiming at the characters above, we accentuate importing the technology of Data Mining to the application of CRM. This technology is helpful to all the stages in a customer's life, including getting new customers, making more profits from your present customers and keeping your contact with important customers.In order to validate our theory and methods, we designed and implemented a demo. It comes from a CRM system for a big supermarket. It embodies CRM ideas, realizes the access to data warehouse and implements the data forecast owed to the technology of Data Mining. And it solves many ubiquitous problems in today's corporations, and validates the correctness of the optimization . It performs a helpful attempt to make Data Mining in CRM practical and shows a way to enhance the availability and real-time capability of CRM.
Keywords/Search Tags:Customer Relationship Management, information, forecast, Data Mining
PDF Full Text Request
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