Development of RFM strategies for customer segmentation using algorithmic methods

The paper is devoted to studying consumer behavior using RFM analysis and an algorithm for providing personalized discounts, using algorithmic methods. The essence of the customer base, the concept of RFM analysis, and machine learning models that can be effectively used to analyze the customer base and further develop marketing strategies are considered. Customer segmentation is carried out using RFM analysis. Particular attention is paid to the RFM analysis algorithm and calculating personalized discounts for retail chain customers using algorithmic methods considering the price elasticity coefficient. The paper offers a deeper understanding of RFM segments for a more personalized approach using algorithmic methods.