Customer's Time-Variant Purchase Behavior and Corresponding Marketing Strategies: An Online Retailer's Case

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The traditional customer relationship management (CRM) studies are mainly focused on CRM in a specific point of time. The static CRM and derived knowledge of customer behavior could help marketers to redirect marketing resources for profit gain at the given point in time. However, as time goes on, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date. In this paper, we propose a dynamic CRM model utilizing data mining and a monitoring agent system to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the retailer. Furthermore, we show that longitudinal CRM could be usefully applied to solve several managerial problems, which any retailer may face. (C) 2002 Elsevier Science Ltd. All rights reserved.
Publisher
Pergamon Press Ltd.
Issue Date
2002-09
Language
ENG
Article Type
Article
Citation

COMPUTERS AND INDUSTRIAL ENGINEERING, v.43, no.4, pp.801 - 820

ISSN
0360-8352
URI
http://hdl.handle.net/10203/79893
Appears in Collection
NE-Journal Papers(저널논문)
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