Sun Yat-Sen Management Review

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Title
企業客戶語音業務流失預測之研究
The Research on the Prediction of Enterprise Customer Churn on Voice Services
(156_M625787dfc06ce_Full.pdf 7,131KB)

Author
黃三益、林彥君、賴佳瑜/國立中山大學資訊管理系、國立中山大學資訊管理研究所、國立屏東科技大學資訊管理系
San-Yih Hwang, Yen-Chun Lin, Chia-Yu Lai/

Department of Information Management, National Sun Yat-sen University;Department of Information Management, National Sun Yat-sen University;Department of Management Information Systems, National Pingtung University of Science and Technology


Abstract(Chinese)

網際網路技術成熟及行動網路速度提升,使得電信業者提供之語音服務被網路服務取代。以營收貢獻來說,企業客戶遠大於一般消費客戶,且若企業客戶部分業務一旦流失至競業,其他相關業務皆可能轉至競業,期能保留目前使用語音服務的客戶,維持現有客戶之語音服務營收。本研究主題為企業客戶語音流失預測,為找出可能流失客戶,運用機器學習之方法建立預測模型,並考量企業客戶特性,納入企業客戶專有變數,以提升預測準確率。根據真實的電信客戶資料的研究結果顯示,企業客戶專有變數在前十大重要變數裡佔了三個;此外,依據預測結果對可能流失之客戶進行挽留,透過設定最適合閾值後,使營收損失最小化,相較於單純不作為,則可有效降低營收損失。

(156_M625787dfc06ce_Abs.pdf(File does not exist))

KeyWord(Chinese)

電信業客戶流失、客戶流失預測、客戶固守、機器學習、行銷預測


Abstract(English)

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.

(156_M625787dfc06ce_Abs.pdf(File does not exist))

KeyWord(English)

Customer Churn in Telecom, Customer Retention, Machine Learning, Churn Prediction, Marketing


Policy and management implications
(Available only in Chinese)

現今由於網際網路技術成熟及行動網路速度提升,電信語音服務已大量被網路服務取代,然而在電信業者的高度競爭與市場飽和壓力下,電信業者所提供給企業客戶之語音業務則轉變成減價轉換的模式,使電信業者可獲得之利潤大幅減少。由於企業客戶之營收貢獻通常遠大於一般型消費使用者,倘若企業客戶的語音業務若流失至其他競爭業者,將可能流失所有電信相關業務,因而如何預防重要企業客戶流失與客戶保留為提升電信市場競爭力的重要議題。本研究旨在為電信業者提出有效之企業客戶語音流失預測模型,以利提供企業客戶即時的服務決策支援,本研究考慮電信業者之企業客戶特性,納入企業客戶特有重要類別變數,包括企業客戶服務等級、專人服務及優惠折扣申請,透過模型預測我們可以找出企業客戶中的可能潛在語音業務流失之客戶,並因而制定相關行銷策略:(一)企業客戶服務等級:月營收貢獻最高之客群,其流失比例最高,而月營收貢獻最低之客群,其流失家數最多,兩種客群差異極大,產品包裝及服務應有所不同,且基於80/20法則,應優先照顧月營收貢獻最高但流失比例最高之客群。(二)專人服務︰指派專人服務之客戶流失比例高且流失家數多,建議應考量服務流程及品質是否需要加強及改善。(三)優惠折扣申請︰有申請優惠之客群流失比例反而較高,顯示優惠內容可能不符合客戶需求,後續應進行優惠內容檢討。本研究之相關研究成果,可提供未來電信業在針對潛在企業客戶語音業務流失提出解決方案與管理經營方向,透過資訊系統可自動偵測客戶訊務量及門號數成長率變化,當其降低至某個警戒值之下,可主動通知專人以主動關懷客戶及提供固守方案,並協助企業客戶服務團隊有效的掌握客戶動向,及早偵測客戶流失的可能性,才能使客戶流失率降至最低,大幅減少招攬新客戶的成本,並可增加企業總體盈利。


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