以上網行為區隔潛在客戶之研究-以某電信公司為例; Segment potential customers with internet behavior for a telecommunication company

NCUIR > School of Management at National Central University > Graduate Institute of Business Administration > Electronic Thesis & Dissertation > Item 987654321/44072

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/44072

Title:	以上網行為區隔潛在客戶之研究-以某電信公司為例;Segment potential customers with internet behavior for a telecommunication company
Authors:	林冠毅;Kuan-yi Lin
Contributors:	企業管理研究所
Keywords:	聚合式的模糊 K-平均法;上網行為;集群分析;資料探勘;Agglomerative Fuzzy K-Means;Data mining;Clustering analysis;Internet behavior
Date:	2010-07-09
Issue Date:	2010-12-08 14:47:56 (UTC+8)
Publisher:	國立中央大學
Abstract:	在無線上網的人口日漸增加以及無線基礎建設的日益普及的情況下，行動上網的人數有了顯著的成長，但是對於過去習慣使用固網寬頻的使用者來說，以往只有一家電信公司的選擇，現在卻是有許多家的電信業者可以比較，而收費的方式也較以往多了很多不同的計算方法，也因為太多不同的計算方式造成許多使用者的疑惑，而使的電信業者在此部分的業績並沒有隨著使用行動上網人口增加而快速增長，因此本研究使用Agglomerative Fuzzy K-Means進行模糊集群分析，利用電信公司本身市調資料，內容包含客戶過去的上網行為，例如：上網動機、上網的頻率…等，在加上客戶的基本屬性，例如：收入、性別…等，利用敘述統計方法找出客戶族群在上網行為的差異，利用這些差異形成指標，再透過專家的比對來驗證此指標的精準度。指標可用於推測客戶行動上網的時間和適合的資費方案，因此業務行銷人員在處理案件時可先詢問構成此指標內問題，藉指標的先行判斷來避免在處理案件時因客戶回答不合理而拉長業務行銷人員在分析問題的時間，電信公司節省處理行動上網新辦續約案件的時間後就可增加每位業務行銷人員每天處理的案件數量，而藉由增加的案件數量便有機會可以使電信公司的業績有所成長。 With wireless internet access in the growing population and the increasing popularity of wireless infrastructure, the number of mobile internet has been significant growth. But for the past habit of using the fixed-line broadband users, they only have the choice of a telecommunication company. Now there are more telecommunication companies can be compared and the rate of charging are more than the past. Due to too many different calculation methods, it make user become confuse. As result of this situation, telecommunication company’s market of wireless internet does not make high profit with the use of mobile internet population growth. So this study use Agglomerative Fuzzy K-Means clustering analysis with the customer’s past internet behavior, such as: the motives of using internet、the frequency of connect internet ... and so on. Those data are collected by the telecommunication company which is the case in this study .This study also use customers basic properties, such as: income, sex ... and so on .By using descriptive statistical methods to identify customer groups of differences in internet behavior. Use those different attributes become a indicator. It will compare with telecommunication company’ expert, then we can get the recall and precision of this indicator. The indicator can supposition the time of customer may use mobile internet and suitable charging rate. So salesperson can ask the questions about the indicator in the first place. Salesperson can use this indicator analysis to avoid the Analysis of the time delay that due to the customer’s unreasonably. It can increase the quantity of case handle by salesperson by reducing the processing time of cases and the result may increase the company’s performance.
Appears in Collections:	[Graduate Institute of Business Administration] Electronic Thesis & Dissertation

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