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Comparative Analysis on Customer Relationship Management with Data Mining Techniques

B. Arivazhagan, R. SankaraSubramanian


Customer Relationship Management (CRM) is an area that administers company's interaction with fresh and promising customers. It analyses the data about customers' history with a company for improving business relationships with customers, retention of customers and to promote sales growth. Through the CRM approach and the systems used to facilitate it, businesses learn more about their target audiences and how to best cater to their needs. Customer Relationship Management (CRM) possesses Business Intelligence by incorporating information acquisition, decision support functions and information storage to provide customized service. CRM enables to analyze and classify data in order to satisfy the customer needs. CRM takes customer as the main point and optimizes the business process around them.  With the rapid increase of data accumulated in the database or data warehouse of enterprises, analyzes about customer manually is a tedious job. Data mining ease this process by using various techniques such as Classification, Clustering and Association mining in decision support system. Data mining extracts hidden information from large databases and provide valuable information about customers and enable business firms to make proactive decisions. The outcome of these techniques aids the organizations to track their customers purchasing patterns and demands thus making their tactical decision more effective for the advancement of the business. This paper analyses the data mining techniques available for customer relationship management.

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