To mine association rules of customer values via a data mining procedure with improved model: An empirical case study

Authors:
Wen-Yu Chiang
Affiliations:
Department of Industrial and Business Management, Aletheia University, Taiwan
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 4
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Abstract

This paper proposes a new procedure and an improved model to mine association rules of customer values. The market of online shopping industry in Taiwan is the research area. Research method adopts Ward's method to partition online shopping market into three markets. Customer values are refined from an improved RFMDR model (based on RFM/RFMD model). Supervised Apriori algorithm is employed with customer values to create association rules. These effective rules are suggested to apply on a customized marketing function of a CRM system for enhancing their customer values to be higher grades.