英文摘要 |
Due to the maturity of IP network technology and the provision of 4G mobile high speed networks, Internet-based services have become more popular. Nevertheless, the revenue of voice services for telecom operators has been substantially reduced. Yet the construction cost of broadband network and mobile phone base station remain the same. As a result, the profit of telecom operators has been drastically reduced. In addition, reports from the NCC shows that Taiwan's telecommunications market has been saturated. Therefore, customer retention and customer churn management become important issues for telecom operators. In this work, we engage in the study of predicting enterprise customer churns in telecommunication industry because enterprise customers contribute more revenues to telecom service providers. Various variables, including the enterprise customers' unique variables, have been identified, and the Xgboost algorithm is used to establish the prediction model. Our experimental results based on the real telecom customer data show that three enterprise customers' unique variables are among the top 10 most important variables. In addition, our proposed prediction model is able to increase AUC and recall rate by 3% and 5.4% respectively, when compared to the prediction model that simply incorporates variables identified by previous work. We further try to minimize revenue loss by setting the most appropriate threshold. The experimental results show that by setting the threshold at 0.72 and applying customer retention strategy to the predicted customers, we are able to reduce the revenue loss by 525 units per customer. |