An Integrated Pareto/NBD- fuzzy weighted RFM model for customer segmentation in non-contractual setting

Document Type : Research Paper

Authors

1 Prof. Amir Albadvi, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

2 PhD. Candidatein Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

3 Associate Prof., Mohammad Mehdi Sepehri, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

4 Associate Prof., Mohammad Reza Amin Naseri, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Companies create revenue through creating customer relationships and sustenance of these relations in long-term. Therefore, an appropriate prediction of customer relationships is central for CRM. Segmentation divides the customer base into homogenous parts where every group of customers has similar characteristics of buying behavior and therefore has similar expected value. One of the most popular segmentation techniques is RFM analysis which uses transactional databases to provide predictions about customer lifetime value. This study aims to combine Pareto/NBD model, as a powerful tool in predicting customer’s future behavior with RFM analysis to improve the segmentation quality. The Pareto/NBD model is used to estimate the probability of customers’ activity in future periods, the expected number of transactions and the expected average monetary value. The result of this segmentation is being compared to the application of traditional RFM technique. Experimental results indicate that the proposed approach improves the quality of segmentation in order to estimate the customer’s future value, especially in the case of more valuable segments.

Keywords

Main Subjects

References

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Journal of Business Management
Volume 6, Issue 3 - Serial Number 3
October 2014
Pages 417-440

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