Recognizing Real Customers in E-Supply Chain Based on SOFM Neural Network and Corresponding Marketing Strategies

Abstract

In today's buyers' market, "the customer is God", the competition is no longer enterprise to enterprise, but supply chain to supply chain. So exactly to recognize real customer in e-supply chain is the key factor to success for assuring the profit of the whole e-supply chain. There is a large amount of consuming data stored in the e-supply chain everyday. If one e-supply chain can make full use of these valuable data on the Internet to recognize its real customers and target these customers' features of consuming behaviors to produce, sell, distribute, and offer a integrated individualized service from the whole e-supply chain, this greatly increases the loyalty of customers of the e-supply chain, maximize the profit of the whole e-supply chain, and make the e-supply chain more competitive in the world. In this paper, SOFM neural network is employed as a tool to mine these valuable consuming data in the e-supply chain for recognizing its real customers. The SOFM neural network is a novel and very interesting approach that can resemble recognition function of the brain. By mean of the SOFM neural network's approach, these most-downstream customers in e-supply chain can be objectively, scientifically and automatically clustered and divided into different groups. Besides, based on the scientific recognition and analysis of customers' consuming behaviors from these different groups, there are some corresponding marketing strategies to be suggested just for references