Segmenting your Customers in Recommender System

M. Xu, Y. Qiu, J. Qiu, and X. Wang (PRC)


Customer Segmentation, Profitability,Recommender System


That customers vary in profitability is not exactly new. However, segmenting customers in terms of their profit contribution remains an underutilized approach in many recommender systems nowadays. In such systems, they are likely to believe every browser might be a buyer later, so they give the same care to all of the customers without calculating whether the expected profit from a customer is greater than the cost of marketing to her or not. Providing a high quality recommendation service to all customers is totally not economically logical. So in this paper, our research is based on the understanding of individual customer profitability, Pareto's principle and the customer pyramid. A segmenting algorithm based on decision tree and RFM (Recency, Frequency, and Monetary) Model has been proposed here. Network value has also been considered in the segmenting algorithm.

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