Identification of Customer Clusters using RFM Model: A Case of Diverse Purchaser Classification

Srivastava, R (2016) Identification of Customer Clusters using RFM Model: A Case of Diverse Purchaser Classification. International Journal of Business Analytics and Intelligence, 4 (2). pp. 46-49.

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Competitive world today stresses of having virtuous marketing strategies to appeal new customers while holding longstanding customers. Organisations use instruments to embrace both types of customers, thereby, probing better return on investments and ensuing increasing revenues. The notion of “customer clustering” is used by organisations to categorise diverse fragments of customers and offer them with varied services. The present study takes the four fragments of customers, viz., active, warm, cold, and inactive and does added exploration of these fragments. It was found that these fragments are not enough for defining marketing strategies and need further analysis. The paper magnifies the fragment using RFM analysis then performing clustering on the values obtained from this analysis. This analysis spawns the pertinent rules for each customer segment obtained after clustering.

Affiliation: Skyline University College
SUC Author(s): Srivastava, R
All Author(s): Srivastava, R
Item Type: Article
Uncontrolled Keywords: RFM, Customer Value Pyramid (CVP), Customer Clusters, Clustering without Classification, Clustering with Classification
Subjects: A Business and Management > AW Information Systems
Divisions: Skyline University College > School of Business
Depositing User: Mr SUC Library
Date Deposited: 01 Jul 2022 14:24
Last Modified: 01 Jul 2022 14:24
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