Consumer's purchasing behavior analysis based on the self-organizing feature map neural network algorithm in e-supply chain

There is a famous saying "The consumer is God". So exactly analyzing consumers' purchasing behavior is the key factor to success for assuring the profit of the whole e-supply chain. Firstly, this paper proposes and compares three kinds of research modes to analyze consumers' purchasing behavior, and then points out that the research mode driven by data is the most scientific one. Secondly, under the guidance of the idea of the research mode driven by data, this paper takes Self-Organizing Feature Map Neural Network (SOFM NN) as a tool to analyze consumers' purchasing behavior in e-supply chain of book. Lastly, based on the result of analyzing consumers' purchasing behavior, this paper gives some corresponding cyber-marketing strategies that can help to increase the loyalty of consumers and maximize the profit of the whole e-supply chain. Because consumer's purchasing behavior analysis based on SOFM NN is a comparatively novel method, the result of research in this paper is just for reference.