A REVIEW ON DATA MINING TECHNIQUES USED TO IMPROVE THE CUSTOMER RELATIONSHIP MANAGEMENT THAT HELPS TO IMPROVE THE BUSINESS REVENUE

In recent years many organizations have identified the need to become more customers facing with increased global competition. As a consequence, customer relationship management (CRM) has risen to the agenda of many organizational strategies. The past decade has witnessed a shift from the need to manage transactions to that of the need to manage relationships. Where Enterprise Resource Planning software dominated the management of transactions era, CRM software leads in regard to relationships. At present, a balanced view of CRM software is scantly presented instead relying on vendor oratory. The number of customer relationship management (CRM) implementations has grown dramatically in recent years. Data Mining is the process that uses a variety of data analysis and modeling techniques to discover patterns and relationships in data that may be used to make accurate predictions. It can help you to select the right prospects on whom to focus. The essence of the information technology revolution and, in particular, the World Wide Web is the opportunity to build better relationships with customers than has been previously possible in the offline world. For instance, as part of their CRM strategy, a business might use a database of customer information to help construct a customer satisfaction survey, or decide which new product their customers might be interested in. In this paper, we are introducing the data mining techniques to improve the customer relationship management.