Application Of Classification And Clustering In Analytical Customer Relationship Management

In the past years, the high development of data gathering and saving has derived the rapid development of database and information industry. The extensive databases come in increasing numbers. However, traditional data analysis seems to be disabled in the face of the rapid data growth and the advanced analysis, which is more complex. In that case, data mining emerges as the times require, which the CRM(Customer Relationship Management)is based on. It combines the best business practice and data mining, database, single marketing, sale automation, and other information technologies, which provides business automatic solution for sale, customer service, decision support and so on. It brings a foremost positions facing to customers based on electronic commerce and, then consequently carries out the transform from the traditional enterprise schema to modern schema based on electronic commerce. Analytical Customer Relationship Management, which is called next generation CRM, has become the study focus in application of data mining in recent years.This thesis is composed of such content: the basic function of Analytical CRM, the implement methods of preprocess and primary analyses of data, research about application of classification and clustering in Analytical CRM, the exploitation of the Analytical CRM.This thesis focuses on the classification and clustering in data mining, application of classification and clustering in Analytical CRM, then designs and develops an Analytical CRM—KDACRM. It expounds the core effect of Analytical CRM. Firstly, it analyses and apprehends the data of relative customer through report form tool that are easy to use. Secondly, customizes product, service and relevant interaction based on those data to consequently satisfy the requirement of the customer through appropriate way or channel at the appropriate time.