Recency Frequency Monetary Analysis for Segmenting Milk Suppliers of a Dairy Organisation

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Authors: Subir Mitra
Cited by: 0

Abstract

The dairy supply chain encompasses a complex network of stakeholders, including milk producers, processors, distributors and retailers. Effective management of this supply chain is essential for ensuring the continuous supply of high-quality milk and milk products to consumers. Milk suppliers, as the primary source of milk, play a critical role in the dairy supply chain. Understanding and segmenting milk suppliers based on their milk-supplying behaviour can provide dairy organisations with valuable insights for optimising supply chain management strategies. It will also improve supplier relationships and enhance overall profitability. At present, all transactions of individual milk suppliers are digitally recorded immediately at the point of their supply on a daily basis, creating a massive database that can be used for dynamic data analysis by fast computing facilities available in information technology today. Recency frequency monetary (RFM) analysis is a powerful tool that can be used to segment milk suppliers based on their milk-supplying behaviour. Further, based upon the initial RFM analysis, machine learning-based algorithms may be utilised to give interesting insights into the supply patterns, which may be missed by normal statistical analysis. This article explores the benefits of RFM application for segmenting milk suppliers of a dairy organisation for managing the supply chain effectively with a real case example.

Fields of Study & Subjects

Customer churn and segmentation Data Mining and Machine Learning Applications Supply Chain and Inventory Management

Publication details

Publication date
6 February 2026
Language
EN