In today's competitive business environment faster than competitors to grasp the needs of customers is the key to create corporate profits. In order to understand customers’ needs and consumption patterns, enterprises usually using Data Mining and association rules to analyze customers' buying habits, also known as market basket analysis. We can use market basket analysis to understand what the customers' want and carry on propriety promotion plans, furthermore we can develop a customer relationship management strategy. Ordinary thesis about basket analysis may be able to accurately identify the customer's property, but the contribution of the customer for the enterprise is no mention. By using the aforementioned method In this paper, we total find a of four key commodities. Each key products in the testing data for VIP customers distinction ratios are more than 60%, of which two key products but also up to 70% or more. This means that customers buy key products, which are more than 60% probabilities who we want to develop a VIP customer. Because this thesis requires only recognizable membership number, so the only member number anonymous data mining methods are also considerable contributions.
