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Predicting customer value per product: From RFM to RFM/P

Author

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  • Heldt, Rodrigo
  • Silveira, Cleo Schmitt
  • Luce, Fernando Bins

Abstract

Recency, frequency, and monetary (RFM) models are widely used to estimate customer value. However, they are based on the customer perspective and do not take the product perspective into account. Furthermore, predictability decreases when recency, frequency, and monetary values vary among product categories. A RFM per product (RFM/P) model is proposed to first estimate customer values per product and then aggregate them to obtain the overall customer value. Empirical applications for a financial services company and a supermarket demonstrate that RFM/P opens up the possibility to combine customer and product perspectives. Additionally, when there are changes in customer purchase behavior regarding recency per product and frequency per product, which is usual, RFM/P prediction accuracy was found to be better than traditional RFM.

Suggested Citation

  • Heldt, Rodrigo & Silveira, Cleo Schmitt & Luce, Fernando Bins, 2021. "Predicting customer value per product: From RFM to RFM/P," Journal of Business Research, Elsevier, vol. 127(C), pages 444-453.
    • Handle: RePEc:eee:jbrese:v:127:y:2021:i:c:p:444-453
    DOI: 10.1016/j.jbusres.2019.05.001
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    Citations

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    Cited by:

    1. Ho Thanh & Nguyen Suong & Nguyen Huong & Nguyen Ngoc & Man Dac-Sang & Le Thao-Giang, 2023. "An Extended RFM Model for Customer Behaviour and Demographic Analysis in Retail Industry," Business Systems Research, Sciendo, vol. 14(1), pages 26-53, September.
    2. Jihoon Cho & Swinder Janda, 2023. "Perception carryover in cross-buying: the role of interpurchase time and product locus," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 809-819, December.
    3. Gabriel Marín Díaz & Ramón Alberto Carrasco & Daniel Gómez, 2021. "RFID: A Fuzzy Linguistic Model to Manage Customers from the Perspective of Their Interactions with the Contact Center," Mathematics, MDPI, vol. 9(19), pages 1-27, September.
    4. Mei, Yupeng & Jing, Kunpeng, 2024. "Customer concentration and management earnings forecast," Finance Research Letters, Elsevier, vol. 65(C).
    5. Rocío G. Martínez & Ramon A. Carrasco & Cristina Sanchez-Figueroa & Diana Gavilan, 2021. "An RFM Model Customizable to Product Catalogues and Marketing Criteria Using Fuzzy Linguistic Models: Case Study of a Retail Business," Mathematics, MDPI, vol. 9(16), pages 1-31, August.
    6. Marcel Röser, 2024. "More certainty in uncertainty: a special life-cycle approach for management decisions in volatile markets," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 35(1), pages 165-197, March.

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