資料探勘技術於WIFLY客戶行為模式之研究

Analyzing Behaviors of WIFLY Customers Using Data Mining Techniques

林正榮(Cheng-Jung Lin)

指導教授 ： 蔣定安

淡江大學/工學院/資訊工程學系博士班/博士(2010年)

https://doi.org/10.6846/TKU.2010.00836

摘要

隨著通訊技術的演進, 網際網路的蓬勃發展，過去以個人電腦以及區域網路技術所主導的網際網路形態逐步轉變為通訊、娛樂、電子商務主導的網際網路型態。不再受限於有線網路連結環境的限制，透過上網熱點的連結，使得無線網路的連結更具有便利及即時性質，而多元化的時空網路連結環境使得網際網路的運用更具備實用及商業價值。

WIFLY建構於台北市，採用Wi-Fi無線網路為基礎網路架構，因取得World Teleport Association, WTA旗下的Intelligent Community Forum 所頒發的智慧城市首獎，並獲得國際認證機構JiWire評定為全球最大之無線寬頻網路城市，在2006年成為全球最大公共無線寬頻網路城市。

近年來，由於企業與顧客之關係由過去之產品發展導向，逐漸轉變為由顧客個人行為發展導向的經營模式。隨著無線寬頻網路Wi-Fi使用人數增加，提升顧客價值、維持顧客忠誠度、避免顧客流失以及增加新客源為網路經營業者之重要發展目標。區隔不同顧客的行為差異性，有助於制定適當策略預先避免顧客流失、保留既有顧客、並減少耗費不必要之企業資源成本。

本論文採用資料探勘技術進行WIFLY顧客行為分析，先運用資料探勘技術進行顧客行為區隔分析，由WIFLY顧客使用行為差異性，找出具有顯著價值之顧客族群。再根據分析之結果，執行決策樹演算分析以探討WIFLY顧戶行為特徵，提供WIFLY經營業者市場及決策部門做為擬定保留顧客以及防止顧客流失策略之參考依據。

關鍵字

顧客關係管理 ； 資料探勘 ； 群集 ； 決策樹 ； 流失(保留)

並列摘要

As communication techniques improve, Internet continues to boom. Internet leading shape gradually shifted focus from personal computer and local area network for Internet service to these used in communications, recreation, e-commerce etc. Because of wireless networks is not restricted the wired networks link environment, while broadband speeds up Internet connectivity, the wireless ratio-based networks known as Wi-Fi service untether it through hotspots to link Internet. Hence, wireless network is not only more convenient and immediate properties, but also possesses practical and commercial value.

WIFLY is a Wi-Fi service infrastructure in Taipei city, which has begun since December 20 of 2005. The Intelligent Community Forum named Taipei city as recipient of its 2006 Intelligent Community Forum of the year award and presented awards to the Intelligent Building of the year, Intelligent Community Technology and Intelligent Community Visionary of the Year as well Taipei is on the way to develop a stable wireless city following the completions of many of its related infrastructure. JiWire assessed the Taipei is the global largest city of wireless broadband network.

In recent years, the guidance of customer relationship management between enterprises and customers gradually evolved from people into product. There is huge competition for wireless networks operators. As Internet subscribers in wireless networks field are continually growing, wireless network operators have to understand the rising consumer demand and develop suitable strategies, critical to attracting repeat customers, consolidate customers loyalty and satisfaction, with continually prospects new clients etc., Therefore, the marketing strategy and CRM are becoming very important.

This dissertation applied data mining techniques to analyze WIFLY users’ behavior, and identifies the significant value of WIFLY subscribers to predict customer churn in CRM and build predicting model to prevent customer churn. The experimental evaluation results show that customer churn model is effective and efficient. It can help enterprise in predicting the customer churn, building customer loyalty and maximizing enterprise profitability.

並列關鍵字

Customer Relationship Management ； Data Mining ； Clustering ； Decision Tree ； Churn

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