Today's businesses have large quantity of demographic, economic and behavioral data on their customers with the rapid development of computer and internet technologies. Customer segmentation analyzes are carried out on the basis of various parameters in order to identify and group consumers with different needs and wishes and to develop marketing applications and solutions specific to each group. RFM analysis is a commonly used and well-known customer value evaluation tool for analyzing and classifying vast volumes of customer data quickly and effectively. It is used to numerically identify the correct customers by examining how recently, how often and to which monetary value a customer has made purchases. This study proposes a new model to be used in customer segmentation. In this model called RFM-V, the "V" parameter indicates the diversity of the customer's purchases, which can define customer depth in terms of customer relationship management literature. The study also proposes a new matrix, Customer-Product Depth Matrix, with this new variable V added to the model. With this matrix created by using M and V parameters, customers can be examined in four quadrants according to their depth. Analysis findings can also be associated with basket analysis data in order to develop healthier marketing strategies and realize effective promotional suggestions.
Ozkan, P., & Deveci-Kocakoc, I. (2021). A customer segmentation model proposal for retailers: RFM-V. In C. Cobanoglu, & V. Della Corte (Eds.), Advances in global services and retail management (pp. 1–12). USF M3 Publishing. https://www.doi.org/10.5038/9781955833035
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License