A Prediction of the Broadband Internet Customer Churn Using Support Vector Machine

基於支持向量機的寬頻網路客戶流失預測

10.6220/joq.202302_30(1).0001

Pei-Hsi Lee(李佩熹)；Yihui Chen(陳翌惠)

broadband internet ； customer churn ； support vector machine ； genetic algorithm ； 寬頻網路 ； 客戶流失 ； 支持向量機 ； 遺傳算法

品質學報

30卷1期（2023 / 02 / 28）

1 - 12

英文;繁體中文

In the fiercely competitive broadband internet market in China, the telecom companies are facing a large amount of customer churn. If they can predict the loss of customers and propose a method to prevent it, that will help these telecom companies improve their competitive advantage. This study uses support vector machine (SVM) to predict the loss of broadband internet customers, and proposes countermeasures. The SVM is trained and tested with the real data provided by the telecom company, and its accuracy values is higher than the values of back-propagation neural network. This study also proposes a process to illustrate the use of the SVM method for predicting the customer churn, and implement the countermeasures based on the prediction results of SVM.

在競爭激烈的中國寬頻網路市場，電信企業面臨著大量的客戶流失。如果他們能夠預測客戶流失並提出預防方法，將有助於這些電信公司提高競爭優勢。本研究使用支持向量機（support vector machine, SVM）來預測寬頻網路客戶的流失，並提出對策。SVM使用電信公司提供的真實數據進行訓練和測試，其準確度值高於反向傳播神經網絡（back-propagation neural network）。本研究提出了一個流程來說明使用SVM方法預測客戶流失，並根據SVM的預測結果實施對策。

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