Based On Statistical Data Mining Techniques Applied Research In The Crm System

In the early 90s of 20th Century, with more fierce competition and shortage of customer source, companies came to realize the importance of retaining sustained relationship between customers. In these circumstances, Customer Relationship Management (CRM) came true. When companies implement CRM, they need to obtain decision support from deep analysis of numerous and complicated information. There is a large application potential of Data Mining in CRM because of its capacity of extracting useful knowledge and information from numerous data. Data mining based on statistic is more useful in extracting information. However, there is a limitation in application of data mining based on statistic in CRM.The goal of this thesis is to study application of data mining based on statistic in CRM. On the basis of reviewing relevant researches and practices, the author presents an implementation model of data mining based on statistic in CRM. Centering on the model, a data mining system for CRM is established and based on the system, a spatial data sorting model is presented.Furthermore, the thesis tests the effect of the implementation model above through empirical research. The object of empirical study is Real Estate Company. Through mining of ordinary customer data, the study resolves the problems of market segmentation, target market selection and product design.Innovations of the thesis are to present and empirically test the implementation model of data mining based on statistic in CRM. The thesis contributes to both data mining technology and CRM practices.