The Application Of Customer Relationship Management Base On Data Mining

With the increasingly fierce market competition, the initiative of market has gradually delivered to the customers, so if the customers are not satisfied with the product or service business, they can easily choose other suppliers. Especially in the times of high-speed development of information technology, whether the enterprise has sufficient customers resources or not, whether the customers satisfaction or not, have become key factors to impact the enterprise'survival and development.Customer is God; the customers are the resource of enterprise efficiency. With the diversification and personalized of customers'needs, if the enterprises want to succeed in the fierce market competition, it is necessary to according to the customers'different needs to conduct customers segmentation, and targeting the different customers'bases, to provide different services. The data mining technology can be very good at screening the different customers'information from a large number of complex customers'information, so enterprises can be enable to conveniently designing different products and marketing modes for the different customers'bases. At present, the research about the application of customer relationship management base on data mining is not too much, also its application in reality is rare, so this paper which will study this subject from theory on the one hand, and on the other hand from practice, will has more important significance.In this paper, it is divided into four chapters: at first, it describes the development history and concepts of customers'relationship management, the new styles of customers'relationship management, as well as the research background and significance of this paper, and then describes the research situation of customers'relationship management and data mining at home and abroad, respectively pointing out the research ideas and innovation points of this paper. Thirdly, at the technical level, focusing on data mining technology, especially the decision-making tree, respectively analysis of the customers'class, the potential customers'found, the loyal customers'maintain and the early warning building of losing customers, and respectively establish the analytical models for them. At the same time, it provides some proposals for enterprises on how to improve customers'loyalty and prevent customers'churn. Finally, it puts forward the limitations and deficiencies of this subject study under the present conditions, as well as the vision of this subject study for the future.