Developing W-RFM model for customer value: An electronic retailing case study

In every business, firms are facing with several kinds of customer groups. By considering limited resource, companies should rank customers according to their values and allocate them proper portion of marketing resources. If firms allocate resources to valuable customers, they earn more profit. Although there are many methods for customer value calculation such as Share of Wallet, Past Customer Value, RFM, and Life Time Value, we have used weighted REM analysis to obtain customer values, because of good flexibility and adaption to each business situation. After that we used data mining technique for clustering customer into different groups according to their values. The proposed method was examined in electronic retailing company with flower type products.