In this empirical study, an attempt is made to show how the Customer Lifetime Value (CLV) can be computed by modeling multiple components of the customer and firm behavior. Specifically, attention will be given to modeling (1) the probability that a customer is likely to buy, (2) the quantity of purchase given that they will buy, and (3) the cost of marketing to each customer. Once the authors compute each of these inputs, they combine them to compute CLV using the net present value concept. The authors will examine multiple ways of computing purchase probabilities depending on the customer’s buying pattern. They will also discuss the estimation challenges in obtaining such inputs for computing CLV. The authors will demonstrate the implementation with a case study for a fashion retailer and what kind of managerial actions can be taken. Finally, a generalizable framework for all fashion retailers to maximize profits will be presented and discussed.

• Anita Pansari(Georgia State University, USA)
• V. Kumar(Georgia State University, USA)