The Study and Verification of Mathematical Modeling for Customer Purchasing Behavior

Abstract

Recent information technology developments have forced companies to face stiff competition while the lines between industries have disappeared, giving rise to the possibility of cooperative partnerships. Current industries have already entered the era of cross-industry competition, and only by cooperating with other industries can they quickly take advantage of all kinds of competitive opportunities. Data mining plays a decisive role in enabling firms get a better grasp of market trends, formulate strategies, suggest action plans, and improve competitive advantage. This study uses RFM analysis and data mining techniques with the focus on banks and other industrial partners as examples, and analyzes the behavior of banks' credit card customers. Since the buying behavior of credit card customers encompasses several industry products, this research proposes a potential customer mechanism, analyzing the interests of credit card customers and their need for all types of products in order to predict the next chance of a possible purchase. The cooperating firms can use bank credit card customer analysis to develop potential customers in the hope of providing for the real needs, in terms of products and services, to customers at the opportune time.