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

International Journal of Business Analytics and Intelligence

Volume 4 Issue 2

Published: 2016
Author(s) Name: Riktesh Srivastava | Author(s) Affiliation: Associate Professor, Information Systems, Skyline University College, Sharjah, UAE
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Abstract

Competitive world today stresses of having virtuous marketing strategies to appeal new customers while holding longstanding customers. Organizations 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 organizations to categorize 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.

Keywords: RFM, Customer Value Pyramid (CVP), Customer Clusters, Clustering without Classification, Clustering with Classification

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