콘텐츠 본문
논문 해외 국제전문학술지(SCI급) CRM Strategies for a Small-Sized Online Shopping Mall Based on Association Rules and Sequential Patterns
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2012
- 저자명 Beomsoo Shim, Keunho Choi, and Yongmoo Suh
- 학술지명 Expert Systems with Applications
- 발행처명 PERGAMON-ELSEVIER SCIENCE LTD
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 3
논문 초록 (Abstract)
As dot-com bubble burst in 2002, an uncountable number of small-sized online shopping malls have emerged every day due to many good characteristics of online marketplace, including significantly reduced search costs and menu cost for products or services and easily accessing products or services in the world. However, all the online shopping malls have not continuously flourished. Many of them even vanished because of the lack of customer relationship management (CRM) strategies that fit them. The objective of this paper is to propose CRM strategies for small-sized online shopping mall based on association rules and sequential patterns obtained by analyzing the transaction data of the shop. We first defined the VIP customers in terms of recency, frequency and monetary (RFM) value. Then, we developed a model which classifies customers into VIP or non-VIP, using various data mining techniques such as decision tree, artificial neural network, logistic regression and bagging with each of these as a base classifier. Last, we identified association rules and sequential patterns from the transactions of VIPs, and then these rules and patterns were utilized to propose CRM strategies for the online shopping mall.
