Abstract—Electronic commerce has developed a lot in the last few years. Product recommendation helps to satisfy customers as one of useful applications of electronic commerce. Recommending right products to right customers enhances the customer’s utility and firm profitability. Different types of customers have different interests, so firms should firstly segment customers in to groups and recommend right product to them. A very useful method for grouping customers is customer lifetime value model, which identifies the value of each customer by various parameters. The main purpose of this paper is to clustering customers based on customer lifetime value and then recommending product to different groups of customers with using association rule mining technique. We use one electronic retailing in our study. One useful result of this survey indicates that the rules which are generated for the most loyal customers have more confidence.

Index Terms—Product recommendation; customer Lifetime Value; electronic commerce;data mining; customer loyalty.

Z. Tabaei and M. Fathian are with Department of Industrial Engineering, Iran University of Science and Technology (email: Zahra_Tabaei@ind.iust.ac.ir, Fathian@iust.ac.ir).

Cite: Zahra Tabaei and Mohammad Fathian , "Using Customer lifetime Value Model for Product Recommendation: An Electronic Retailing Case Study ," International Journal of e-Education, e-Business, e-Management and e-Learning vol. 2, no. 1, pp. 077-082, 2012.