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The study of customer classification based on self-organizing feature map neural network

Under current highly competitive market environment, an increasing number of enterprises begin to value the operation mode that changes from the traditional passive-service mode to active-service mode which provides different customers with different services, and effective customer classification is the premise and basis to implement this mode. Through constructing a SOFM model based on RFM indexes, this paper conducted a customer classification study in retail industry, and the simulation experiments using MATLAB software verified the feasibility and validity of this model. This study hopes to optimize retail enterprises' resources allocation efficiency and promote economic benefits by making personalized marketing and active-service strategies.