Abstract 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 defning marketing strategies and need further analysis. The paper magnifes 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. JEL Codes: G31, G32 Keywords: RFM, Customer Value Pyramid (CVP), Customer Clusters, Clustering without Classifcation, Clustering with Classifcation Identifcation of Customer Clusters using RFM Model: A Case of Diverse Purchaser Classifcation Riktesh Srivastava* * Associate Professor, Information Systems, Skyline University College, Sharjah, UAE. Email: riktesh.srivastava@gmail.com Introducton RFM model is an apparatus of clustering customers into 3-dimensions, specifcally, recency (R), frequency (F), and monetary value (M). In added arguments, RFM model helps to determine the top 20% of customers, who bring in 80% of revenue. In RFM model, recency (R) is defned as the intermission from the time when the latest consumption happens to the present, frequency (F) is the number of consumption within a certain period, and monetary (M) is the amount of money spent within a certain period. An earlier study showed that customers with bigger R, F, and M values are more likely to make a new transaction (Wu& Lin, 2002). In order to group customers and perform analysis, a customer segmentation model-Customer pyramid model is used (Curry & Curry, 2000). Allowance of customer pyramid to model group customers by the revenue they generate is shown in Fig.1 (http://mnama.blogspot.ae). Fig. 1: % of Customers v/s % of Revenue As stated in Fig. 1, the uppermost 10% of customers epitomizes amid 50-60% of revenue, next 30% embodies 30-35% of revenue. The bottom 60% of customers has awfully low value, and gives less than 15% of total revenue. These three stages of the customer value pyramid can be divided as active, warm, and cold. Added elaboration of the pyramid into 4 dimensions comprises the following four customer types– active, warm, cold, and inactive (https://lawsonhembree.wordpress.com). Both the studies (http://mnama.blogspot.ae, https:// lawsonhembree.wordpress.com) suggest that the customer exhibiting high RFM score should normally conduct more transactions and result in higher revenue. RFM analysis (Im, & Park, 1999; Madeira, 2002) is Article can be accessed online at http://www.publishingindia.com