Capital investment in retail sector and competition in the market has changed the style of marketing. At the same time the enhancements in the field of information technology provided an upper hand to the marketer to know the exact need, preference and perches trend of the customer. By knowing the actual need, preference and purchase trend of customers the marketer can make a future business plan to increase the sale and earn more profit. This paper provides a framework to the retail marketer to find the potential customer by analyzing the previous purchase history of the customer. This task can be accomplished by the use of data mining technique. In this paper we have used k-mean clustering algorithm and Naive Bayes’ classifier for in identifying potential customer for a particular section of products of the retailer.

Naive Bayes,Cluster, Centroid,Foreign Direct Investment(FDI)

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