Knowledge acquisition of association rules from the customer-lifetime-value perspective
ISSN: 0368-492X
Article publication date: 15 January 2018
Issue publication date: 23 February 2018
Abstract
Purpose
Customer lifetime value (CLV) scoring is highly effective when applied to marketing databases. Some researchers have extended the traditional association rule problem by associating a weight with each item in a transaction. However, studies of association rule mining have considered the relative benefits or significance of “items” rather than “transactions” belonging to different customers. Because not all customers are financially attractive to firms, it is crucial that their profitability be determined and that transactions be weighted according to CLV. This study aims to discover association rules from the CLV perspective.
Design/methodology/approach
This study extended the traditional association rule problem by allowing the association of CLV weight with a transaction to reflect the interest and intensity of customer values. Furthermore, the authors proposed a new algorithm, frequent itemsets of CLV weight (FICLV), to discover frequent itemsets from CLV-weighted transactions.
Findings
Experimental results from the survey data indicate that the proposed FICLV algorithm can discover valuable frequent itemsets. Moreover, the frequent itemsets identified using the FICLV algorithm outperform those discovered through conventional approaches for predicting customer purchasing itemsets in the coming period.
Originality/value
This study is the first to introduce the optimum approach for discovering frequent itemsets from transactions through considering CLV.
Keywords
Acknowledgements
The authors would like to thank the Editor, Prof. Gandolfo Dominici, and the anonymous referees for their helps and valuable comments to improve this paper. This research was supported by the Ministry of Science and Technology of the Republic of China under contract MOST 104-2410-H-166-003 and MOST 106-2410-H-194-026-MY2.
Citation
Weng, C.-H. and Huang, T.C.-K. (2018), "Knowledge acquisition of association rules from the customer-lifetime-value perspective", Kybernetes, Vol. 47 No. 3, pp. 441-457. https://doi.org/10.1108/K-03-2016-0042
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited