Online Customer Segmentation Based On Lifetime Value

Abstract:

In today's fiercely competitive e-business environment, the concept of customer loyalty has gained prominent importance as companies have realized that loyal customers provide them with a variety of advantages and losing existing customers equals losing the whole value that they would have created in their lifetime relation with the company. In this regard, Customer Lifetime Value (CLV) has been a key metric in customer loyalty analysis for customer segmentation, and allocation of budgets for marketing programs. However, little work has been done on segmenting customers based on their values in the online world. In order to measure CLV, this paper proposes a modified Recency, Frequency and Monetary Value (RFM) model which takes into account important factors affecting customer value on the Internet. Thereafter, in a case study of two e-retailers, using Multilayer Feedforward Neural Network (MFNN), the proposed model is applied, and subsequently several methods, including the C 4.5 Decision Tree Algorithm, are used for further model validation