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A Study on the Analysis of Comparison of Churn Prediction Models in Mobile Telecommunication Services  

Kim, Choong-Nyoung (서울시립대학교 경영학부)
Chang, Nam-Sik (서울시립대학교 경영학부)
Kim, Jun-Woo (인천시립대학교)
Publication Information
Asia pacific journal of information systems / v.12, no.1, 2002 , pp. 139-158 More about this Journal
Abstract
As the telecommunication market becomes mature in Korea, severe competition has already begun on the market. While service providers struggled for the last couple of years to acquire as many new customers as possible, nowadays they are making more efforts on retaining the current customers. The churn management by analyzing customers' demographic and transactional data becomes one of the key customer retention strategies which most companies pursue. However, the customer data analysis has still remained at the basic level in the industry, even though it has considerable potential as a tool for understanding customer behavior. This paper develops several churn prediction models using data mining techniques such as logistic regression, decision trees, and neural networks. For model-building, real data were used which were collected from one of the major telecommunication companies in Korea. This paper explores various ways of comparing model performance, while the hit ratio was mainly focused in the previous research. The comparison criteria used in this study include gain ratio, Kolmogorov-Smirnov statistics, distribution of the predicted values, and explanation ability. This paper also suggest some guidance for model selection in applying data mining techniques.
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