The Research Of Application Of Data Mining In The Bank Customer Relationship Management

In recent years,with the development of customer relationship management system(CRM)and,many entrepreneurs have focused on the data mining tools to achieve precision marketing.This method can effectively improve market share and avoid excessive costs of advertising,and enhance customer loyalty and satisfaction,as well as enhance business performance.In this paper,the main research focuses on the application of data mining technology in banking customer relationship management,which includes customer value assessment,customer segmentation and products cross-selling.The detailed content is summarized as follows:First,we review the basic theory of data mining and customer relationship management,and analysis the application of data mining in the bank CRM based on the life-cycle theory.Second,the customer's current value and potential value of consumer behavior as well as the commercial information of consumer are chosen to build the index system of customer value evaluation.And the entropy law is adopted to establish the bank customer value evaluation model.In the corresponding empirical research,different strategies and recommendations are purposed for the consumer with different value.Third,we describe the significance and method for customer segmentation.Then we address the shortcomings of K-means algorithm and modify it according to the analysis result.A customer segmentation model is built based on this improvement K-means algorithm.In the corresponding empirical research,we present different marketing strategies for different cluster of consumers.Finally,the concept of products cross-selling is described as well as the necessity of implementing it.Then a introduction of association rules and traditional Apriori algorithm are presented.A modification of Apriori algorithm is conducted to overcome the shortcoming and improve the inadequacy.Moreover,this modified Apriori algorithm is adopted to an analysis model for cross-selling of the bank financial products.In its empirical research,the association rules between online banking and other business is analyzed and some cross-selling strategies are purposed.In this study,a customer value evaluation model,customer segmentation model and product cross-selling model are developed by adopting data mining for customer relationship management of bank.As the research results show,the operational efficiency of customer relationship management can be improved outstanding based on the application of data miming.