The RFMRv Model for Customer Segmentation Based on the Referral Value

Document Type : Research Paper


1 Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran


The development of social networks provides numerous venues for customers to share their views, preferences, or experiences with others. Thus, the Referral programs have become the most valuable forms of marketing. Additionally, studies have emphasized the positive impact of referral programs on consumers’ intentions to purchase products or services, which increases the need for considering referral value as part of customer value. Hence, this study analyzed customers’ behavior in social media by extending the RFM model and proposing a new RFMRv model in which Rv is the referral value of customers. First, the customer graph of invitations was used to calculate customers’ referral value. Then, the K-Mean algorithm was used to cluster customers based on the CRISP-DM methodology. Finally, the CLV for each cluster was calculated. The results indicated that the referral-acquired customers are more valuable than other customers and proved that the RFMRv model provides better clustering and valuation.


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