Combining the K-means and decision tree methods to promote customer value for the automotive maintenance industry

• Main Author: Yi-Hui Liang
• Format: Conference Proceeding
• Language: English
• Subjects: Automotive engineering; automotive maintenance industry; Customer relationship management; Customer value; Data analysis; Data mining; Decision trees; Frequency; Industrial relations; Information management; Mining industry; Testing
• ISSN: 2157-3611; 2157-362X
• DOI: 10.1109/IEEM.2009.5373029

Customer value refers to the potential contribution of customers to an enterprise during specific periods. When enterprises understand the value of customers, enterprises that understand customer value can provide customized service to different customers and thus achieve effective achieve effective customer relationship management. This study focuses on the current automotive maintenance industry in Taiwan and systematically combining K-means method and decision tree theory to analyze customer value and thus promote customer value. This investigation first applies the K-means method to establish a customer value analysis model for analyzing customer value. By the results of the K-means method, the customers are divided into high, middle and low value groups. Moreover, further analysis is conducted for clustering variables using the LSD and Turkey HSD tests. Subsequently, decision tree theory is utilized to mine the characteristics of each customer segment. The analytical results in this study can provide a valuable reference with regard to customer relationship management for managers in the automotive maintenance industry.