数据挖掘在客户关系管理系统中的应用研究

Research on Data Mining Application in Customer Relationship Management System

随着"以客户为中心"经销模式的应用,企业越来越重视客户关系建设。企业积累了大量的客户数据,建立了客户关系管理系统,数据挖掘技术为客户关系深层次分析提供了技术保证。利用数据挖掘可以进行客户细分、客户流失率分析、客户满意度分析和市场交叉营销等分析。结合客户关系的特点,研究了基于数据挖掘的客户关系管理智能系统的体系结构,提出数据挖掘在客户关系管理系统中的实施流程,研究了ID3算法的不足和改进算法。利用K-means对客户进行聚类分析,并用改进的ID3决策树进行解释,可以更好地为管理者提供客户的有用信息,可以指导企业更好地开展有针对性的低成本服务,可以提高企业的市场竞争力和客户的满意度。

With the application of customer centered distribution mode, enterprises pay more and more attention to customer relationship building. CRM system have been built. There is a huge customer data in CRM. DM provides the technical guarantee for the deep analysis of customer relationship. IT can analysis customer segmentation, customer chum, customer satisfaction and cross marketing information. The architecture of CRM intelligent system based on data mining is studied based on the characteristics of customer relationship, and the process of DM implement in CRM is been put forward. The disadvantages of ID3 algorithm and the improved algorithm are studied. Using kmeans clustering analysis to the customer, and use improved ID3 decision tree to explain, It can provide the useful information about customers and can provide better customer service at lower cost, and improve the enterprise＇ s market competitiveness and customer satisfaction.