Confronted with flerce competition, an increasing number of telecommunication companies in China realize that they can increase proflts by reducing the rate of customer churn rather than attracting the same number of new customers. Recently, the availability of big data has increased, which has stimulated the development of data mining techniques. Identifying methods by which to maximize proflts is vital for operators based on big data. Novelly, this paper studies three key factors of the customer churn problem, namely, churn rate, prediction performance, and retention capability. We propose a proflt function that maximizes proflts under different conditions and obtain favorable results in applying it to sample data from China Mobile Communications Corporation. Theoretically, about 7.72 million Chinese Yuan per month can be obtained by applying proposed model to China Mobile Group Guangxi Company Limited, making our research of great economic value.