The Application of Data Mining Technology for Building Customer Churn Predict Model in Mobile Telecommunication Industry

• Main Authors: Chen-Lin Kuo, 郭承林
• Other Authors: Hui-Chung Yeh
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/c6s5uq

碩士 === 國立高雄應用科技大學 === 企業管理系 === 100 === With the rapid development and popularization of information and communications technology, mobile communications technology has become an important medium of communication and transmission in our life. It’s also indirectly contributed the competition of mobile communications. Under the fierce competition, minimizing customer churn rate has become the first problem that enterprises have to face. This study used questionnaire to obtain customer information, customer mobile phone experiences and satisfaction data, and through data mining technology, including decision trees and discriminant analysis to predict customer churn, and want to find out the different features to reduce customer churn. From our empirical results can we know that the customer churn prediction ability of customer information is low than mobile phone experience and satisfaction. By the results of this study, we hope to provide the behavior that is relevant to customer churn of telecommunication industry to reduce the loss by strengthening the customer with low customer churn, to avoid becoming medium or high.