Data mining approach in customer relationship management: case study of a Taiwanese household exporter

淡江大學機構典藏 > 商管學院 > 國際企業學系暨研究所 > 學位論文 > Item 987654321/51642

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题名:	Data mining approach in customer relationship management: case study of a Taiwanese household exporter
其它题名:	資料挖掘應用於客戶關係管理：臺灣家用品出口商個案研究
作者:	陳美琴;Chen, Mei-chin
贡献者:	淡江大學國際商學碩士在職專班廖述賢;Liao, Shu-hsien
关键词:	顧客關係管理;關係行銷;企業對企業;資料挖掘;關聯性法則;Customer Relationship Management;Relationship Marketing;Business-to-Business;data mining;Association rules
日期:	2010
上传时间:	2010-09-23 15:34:55 (UTC+8)
摘要:	客戶關係管理(CRM, Customer Relationship Management)在學術上已被廣泛地探討。先進科技發達的今天，雖然給企業帶來了很大的衝擊與競爭，卻也助長了CRM的應用。資料挖掘的技術在CRM扮演很重要的角色，最常見的例子是關聯性法則應用在零售業及電子商務，挖掘隱藏性的產品關聯作為CRM的行銷決策，如店內陳列、交叉銷售、客戶分群等等，證實有顯著的成效與報酬率。然而，以關係行銷為主的企業對企業B2B (Business-to-Business)產業在採用客戶關係管理的同時，因為商業模式的不同，應用資料挖掘技術在B2B CRM系統上卻不多，甚至有些經理人員認為觀念上是不可行的。本研究將透過理論文獻上的參考結合實務上的探討，針對個案公司目前在客戶關係管理的運作，進行診斷並提出建議。另外本研究嘗試性將資料挖掘技術應用在個案公司的交易資料庫，試圖以關聯性法則挖掘跨不同品類的產品關聯知識，作為個案公司推薦相關產品給同性質或來自同一區(有相同的文化)的客戶，並作為其樣品間的商品展示陳列參考。實驗結果是資料挖掘也是可以應用在CRM B2B的環境下，惟對文字或資料的處理與資料倉儲建置需要產業的知識與經驗來定義資料變數，再將挖掘結果整合併入行銷決策系統。資料挖掘尚有更多的技術可以運用在CRM B2B，CRM的目標為收集訊息、分析客戶與產品知識，將有助訂定一對一行銷策略、客製化客服策略來增加客戶價值，提高客戶忠誠度，最終目標提高企業收益，創造競爭優勢。本篇論文強調CRM在貿易產業也很重要，資料挖掘更是可以作為CRM分析工具。在末章將提出管理上的意函與對未來的研究方向建議。 Customer Relationship Management (CRM) has been addressed with great interest among scholars and executives. The advanced technology brings tremendous impact and competition in nowadays business environment. At the same time, it facilitates the application of CRM. Data mining acts one of components to CRM system. Among many techniques, Association Rule is one of techniques to be evident effective with best return in retailing and e-commerce as marketing decision support. The new marketing strategy includes: in-store merchandising shelf display, cross-selling, customer segmentation, and supply chain management etc. Nevertheless, data mining approach in B2B (Business-to-Business) industry has been seen impossible by some managers in conception wise. Only a few CRM vendors act as a catalyst. Firstly, this research attempts to diagnose CRM in the case study with literature review and practical experience, moreover, to propose managerial implication and suggestion for the topic. Secondly, with data mining approach to its transaction database to find the relation between sub-sub categories for product recommendation and showroom merchandising display. According to the result of experiment, it proves applicable in CRM B2B. The concern raised shall be the information collection and data format that stored in the database. Then by giving variables and attributes with practical insights in the field to construct the database for better analysis. However, the case company is used to rely on personal judgment and seems lack of analytic tools for decision making system. The ultimate objective of CRM in B2B is to create customized marketing strategy to increase customer value, enhance customer royalty and satisfaction to gain business revenue with competitive advantages. This research aims to demonstrate a logical analysis for case study’s marketing strategy decision support. CRM is obviously necessary in trading industry, while an analytical tool is also vital to have a logical base for CRM strategy rather than personal bias and judgment when dealing with large amount of information and data. Managerial implication for the case company has been concluded in chapter five. Suggestions both for case company in aspect of Data Mining and future study will be proposed in the last chapter.
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