The Application And Research Of Data Mining In Car Sales CRM

With the development of automobile industry and the level of consumption, Customers have become critical success factors and potential source of profit in China’s car sales industry. With the social development and the advancement of technology, especially the development of network technology, the car sales business introduces a customer relationship management (CRM) system to help manage customer information. The implementation of the CRM system can help companies better understand customer needs, improve business relationships with customers, improve customer satisfaction, thereby enhancing the competitiveness of enterprises.Due to the limitations of technology and ideas in the field of China’s car sales in CRM, customer data behind the customer information and resources can not be quickly and effectively tapped. In this paper, one kind of Data mining method-an improved K-means algorithm is applied to the field of car sales. In the conventional K-means algorithm, it is difficult to obtain the global optimal solution because of the initial cluster centers randomly selected may fall into local optimal solution.For the above problem, it made an improvement for the data mining algorithms of k-means, and made a realization of improved K-means algorithm in the data mining software of weka. Finally, this algorithm applied to the field of car sales, through an in-depth analysis the results of data mining, access to the existing rules and potential customers in the car sales process. It proves that data mining technology in the field of car sales CRM system can provide decision support for enterprise management to enhance their competitiveness and profitability.