標題: | 資料庫行銷之顧客價值分析 - 以國內A壽險公司為例 Customer Value Analysis in Database Marketing |
作者: | 錢志揚 Brett Chien 唐瓔璋 Edwin Tang 管理學院經營管理學程 |
關鍵字: | 顧客價值;RFM 分析模型;資料探勘;Customer Value;RFM;Data Mining |
公開日期: | 2007 |
摘要: | 近年來企業投入大量資源增加對顧客的瞭解並與顧客建立良好關係,希望提高顧客滿意度(Customer Satisfaction)及顧客忠誠度(Customer Loyalty),進而增加所謂的忠實顧客。顧客價值分析(CustomerValue Analysis)是顧客關係管理的基礎。對企業而言從顧客所獲得的利益越高,代表顧客的價值越高。
依據80/20 經營法則,將企業內百分之八十的資源用在最有價值的百分之二十顧客。如此依顧客價值高低區隔顧客,將大部分資源放在照顧高價值的顧客上,有助於吸引更多高價值的客戶成為忠實顧客,進而使企業獲得最大的經營效益。
本研究以顧客交易資料進行顧客價值分析。採用 Hughes(1994) 提出 RFM 分析模型為基礎,以two-way contingency tables analysis以及Analysis of Variance對自變數-靜態/動態資料做分析,並藉由分析後之結果,做為主要客戶之輪廓描述以及提供壽險業者擬定行銷策略之依據。 In recent years, many firms put in a lot of resources for understanding their customers as well as building good relationship with customers. They try to raise the percentage of customer satisfaction and loyalty and then to get more loyal customers. Hence, for achieving this objective that customer value analysis is necessary and it is the basic of customer relationship management (CRM). In terms of business, the more benefit from customer means the more value of this customer. Base on 80/20 Rule - 80% of your sales comes from 20% of your clients. That says, business should segment their customers by the value that customer can bring in. Then put more resources and look after those few but most valuable customers. By doing this way that business can gain more valuable customers to be royal customers and then to maxima their business benefit. Therefore, this study performs customer value analysis based on customer transaction data. RFM analysis model which proposed by Hughes(1994) is adopted in this study. It uses Two-way Contingency Tables Analysis and Analysis of Variance to analyze independent variable – static/dynamic data. Business can make marketing strategies base one the result after analysis. This study can be a reference for firms who want to do database marketing by customer segementation. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT009474524 http://hdl.handle.net/11536/82660 |
顯示於類別: | 畢業論文 |