Customer Segmentation Using RFM Model and a New Approach to Encourage Loyal Customers

This paper focuses on customer segmentation using the recency, frequency, and monetary (RFM) model and implements strategies to reward and notify loyal customers through email notifications. We analyze customer data using the RFM model, which evaluates customer behavior based on three factors: recency (how recently a customer made a purchase), frequency (how often they make purchases), and monetary value (the amount spent). By segmenting customers based on these metrics, we can identify loyal customers who have made recent, frequent, and high-value purchases. Once loyal customers are identified, the proposed work implements a reward system to encourage their continued loyalty. Rewards include giving reward points to loyal customers based on their position. To notify loyal customers about their rewards and keep them informed, the paper integrates an email notification system. Personalized emails are sent to loyal customers, notifying them of their rewards and expressing gratitude for their loyalty. By utilizing the RFM model for customer segmentation, businesses can identify and target their most loyal customers effectively. The paper provides a framework to leverage customer data, implement reward strategies, and utilize email notifications to optimize customer loyalty management.