I NT ERNAT I ONAL RESEARCH JOURNAL OF ISSN (Online): 2454-8499 MULTIDISCIPLINARY STUDIES Impact Factor: 0.679 Vol. 2, Issue 2, February, 2016 Online available: www.irjms.in Page 1 Data mining: Techniques for Enhancing Customer Relationship Management in Fast Moving Consumer Goods Industries Dr. Ramchandra G.Pawar Professor Research Head/Department of MCA, D.Y.Patil Institute of MCA, Akurdi, Pune-411044 ABSTRACT- Data mining is the process which uses data analysis techniques to generate new rules and patterns also describe the relationships in data that may be used to make accurate forecast for future. Customer Relationship Management (CRM) is a process which creates the business strategy to build a long term and profitable relationship with the customer and its role on enterprise management through implementing database marketing and data mining strategies, based on past information of sold goods, customer relationship management may facilitate companies to build long-term customer relationship with customers. In this study we are going to present tool based on clustering technique namely hierarchical agglomerative methods in order to measure the satisfaction of customer. This paper provides an critique of the concept of Data mining and Customer Relationship Management in Fast moving consumer goods organisation based on clustering Techniques. Keywords:-Data mining, segmentation, clustering technique, Fast moving consumer goods. I. INTRODUCTION Data mining: Data mining deals to computer-aided pattern discovery of previously unknown interrelationships and recurrences across seemingly unrelated attributes in order to predict actions, behaviours and outcomes. Data mining, in fact, helps to identify patterns and relationships in the data [1]. DM also refers as analytical intelligence and business intelligence. Because data mining is a relatively new concept, it has been defined in various ways by various authors in the recent past. Some widely used techniques in data mining include artificial neural networks, genetic algorithms, K-nearest neighbour method, decision trees, and data reduction. The data mining approach is complementary to other data analysis techniques such as statistics, on-line analytical processing (OLAP), spreadsheets, and basic data access. Data mining helps business analysts to generate hypotheses, but it does not validate the hypotheses. Customer Relation Management Customer oriented business concentrate mainly on their customers, since they knew about their customers and their needs. CRM refers to a collaborative philosophy or system of business practices implemented across an enterprise to organize the assets, aggregate, and analysis of customer profiles. Information about the customers is gathered using N number of techniques. This information is used by the organization to know about their most benefited customers for their company. The methodology that is used for collecting the information about the customers is called as “Business Intelligence System(BIS)”.Using BIS the targeted customers can be identified to maintain a long term relation. Using these method customers satisfaction is increased as well as revenue of the organisation will also be increased.