Data Mining Techniques In Customer Relationship Management Applications

Data mining is largely used by the process of filtering and modeling from a great deal of data to find out unknown rules and relations in advance, so that the clear and useful information can be gained for the owner of database. In the field of business, the result of data mining has evolved into the business profits. Therefore, data mining is not only the application of algorithms and statistics, but also the businesses intelligentize process, which supports business decision-making with the information technique. As one of management information system, the core of the customer relationship management is mining potential market and customers, increasing dominant position in market competition and profits by collecting available data from relevant customers and their operations. In the field of customer relationship management, data mining has prodigious application space: customers' retentionand, cross sales, distinctive marketing, new customer acquisition and customers' profits ability analysis.There are many techniques for data mining. The paper introduces the decision tree and Bayesian classifiers menthods to do the research on customer relationship managing. Decision is one of the most important parts of company management. So is customer value evaluation in decision-making. This paper chooses member card evaluation as classification attribute.As an application example, the books customer relationship management system has many functions besides the ones mentioned above, such as data inputing module, inquery module, system maintaining module and the basic operation of records tables printing etc. The system is secure, practicably and can be operated easily. It can not only do generally data operation, but also keep the data information secret. To different kinds of customers, the system can provide decisions by the customer value evaluation attribute, so as to increase customers' loyalties, help to make market subdivision decision, provide individual survices and ensuer the most...