由於網際網路與電子商務的快速發展，使顧客期望較以往要有更高品質及效率交流服務，一般認為公司之間的來往最重要的關鍵在於有良好的溝通管道，這也是企業追求永續發展不得不考慮的重要因素。面對國際化及競爭白熱化，企業在經營上必需面對低忠誠度的顧客及經營環境的惡化，要如何及時反應滿足顧客需求及經營環境的快速變化，都是企業必須面對的重要課題。為有效利用與分析企業資料庫中所擁有的顧客資料及交易資料，企業必須有效的利用資訊科技改善企業流程管理，進而作成決策制定以及時反應市場及顧客的需求。顧客關係管理是一經營管理的概念，要求企業將焦點放在企業營運最重要的核心「顧客」之上，試著與顧客間建立一種學習關係，從顧客對企業所提供產品與服務之表現，來學習如何加強提供更佳的產品與服務品質，進而以顧客為中心，訂定有效的經營管理與營運目標，以建立企業與顧客間之關係。
　　本研究透過資料探勘工具，針對知識的創造、獲取、管理前置處理加以探討，希望在顧客關係管理中導入管理因子，利用最終所萃取出來的知識，應用到顧客關係管理中，回饋給顧客群，提供顧客快速且高質感的服務，藉以持顧客的忠誠度及吸引新的客源，提升企業的競爭優勢，創造企業的新契機，達到企業永續經營的目標。

　　Due to the Internet and Electronic Commerce have been developed rapidly, the customers expected to get higher quality and efficient services from company. The establishment of “Customer Relationship Management(CRM)”becomes as an important workload for an enterprise. Usually, a company keeps a lot of customer data which included customer basic data such as customer name, corresponding address etc., and the transaction data of the customer. How to get valuable information, such as the expenditure characteristics, from these data is a nontrivial work. To keep the business increasing of a company, it is very important to retain the old “good” customers and create the new potential customers. Data mining, which is also referred to as knowledge discovery in data bases, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information(such as knowledge rules, constraints, regularities) from data in databases. In this is thesis. Data mining technique was used to develop the CRM system for a company for manufacturing sport facilities. The company existing data bases are used as a testing sample. And the decision rules are made by the manager of the company. The package of MS-SQL2000 analysis Service was used as the implementation tools. The simulation result is helpful for the company to make the marketing strategies.

[1] 尹相志 編著，資料採礦服務SQL 2000Analysis Services，維科，台北，2003。
[2] 安迅資訊，整合企業經營策略與顧客關係管理，電子化企業經理人報告-電子化顧客關係
管理，安迅資訊，2000.1，第5期，20-25頁。
[3] 呂執中,林懿貞，顧客關係管理之策略應用，品質管制月刊，第37卷第3期，2001.03，20
-23頁。
[4] 沈兆陽 編著，資料倉儲與Analysis Services SQL:SQL 2000的OLAP解決方案，文魁，台
北，2001。
[5] 林宏諭 編著，SQL 2000之決策分析:OLAP建置與應用，博碩文化，台北，2001。
[6] 狀態網際網路公司網址:http//www.status.com.tw/intranet4_crm.asp。
[7] 英孚美，如何建制成功的資料倉儲，資訊與電腦，第240期，2000.7，62-64頁。
[8] 葉怡成，「應用類神經網路」，儒林書局，台北，1998。
[9] 組合國際，資料倉儲應用新一章-CRM，資訊與電腦，第240期，2000.7，54-57頁。
[10] 劉熒潔 編著，從ERP、SCM、CRM到電子商務，文魁，台北，2002。
[11] 劉慧瑜，資料提煉技術在虛擬商店之運用，中興大學應用數學系碩士論文，2000。
[12] 羅曉慧，應用資料提煉技術客戶端個人化網頁，中興大學應用數學系碩士論文，2001。
[13] 羅志明，運用CRM來實現管理大師的夢，品質管制月刊， 2001.04，57-61頁。
[14] 蘇代成，e世代顧客關係管理，品質管制月刊，第37卷第3期，2001.03，34-37頁。
[15] Berson Smith Thearling, Building Data Mining Applications for CRM,
McGraw-Hill
[16] Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth: Statistical
Inference and Data Mining. CACM 39(11): 35-41 (1996)
[17] C.C. Wong, C.C. Chen, and S.L. Yeh, “K-means-based fuzzy classifier
design,” IEEE International Conference on Fuzzy Systems, (Texas, U.S.A.,
May 7-10), pp.48-52, 2000.
[18] C. T. Hsieh, Eugene Lai and Jin-Ruong Ye, "Handwritten Numeral Recognition
Using Fuzzy Agglomeration Kohonen Clustering Networks", IASTED International
Conference on Artificial Intelligence and Soft Computing, USA, Aug. 1999.
[19] Don Peppers & Martha Rogers, Enterprise One to One, Kluwer, 1999
[20] Fayyad et al., 1996a Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P.
(1996a) Knowledge discovery and data mining: towards a unifying framework.
In Simoudis, E., Han, J., and Fayyad U., editors, Proceedings of KDD'96,
Second International Conference on Knowledge Discovery & Data Mining, pages
82-88. AAAI Press, Menlo Park, CA.
[21] Phillip Kotler, Marketing Management-Analysis, Planning, Implementation and
Control, 1991, 7th Ed, Prentice-Hall International, Inc.
[22] P. Adler, Shared learning, Management Science 36 (8) (1990) 938–957.
[23] Q.Chen,U. Datal and M.Hsu,”A Distributed OLAP Infrastructure for
E-commerce,”Proc.IFCIS International Conference on Cooperative Information
Systems,1999,pp:209-220.