The analysis of customers´ satisfaction degree based on decision tree model

Customers are resources of the enterprises´ profits, Customer satisfaction degree is defined as a measure of how a firm´s product or service performs compared to customer´s expectations. With the market developing quickly, how to improve the customers´ satisfaction degree has become the main task and object for one company. It has been a subject of research due to its importance for measuring marketing and business performance. A lot of models have been developed for its measurement. In this paper, a decision tree model is used to analyze the main factors that affect Customers´ satisfaction degree. Data mining has made data processing into a more advanced stage, which is playing an important role in the science research and economic fields. The decision tree as a classification method has the advantage of processing large data quickly and accurately. We use ID3 algorithm, one of the algorithms of decision tree analysis, to analyze these key factors and resolve some important questions. Data obtained from a technology-supported company were used. Finally, we conclude that if one company wants to improve its Customers´ Satisfaction degree, managers should try their best to improve the level of technology and the employees´ professional skills, innovate their products continuously to satisfy more customers´ needs.