ABSTRACT
In today's highly competitive landscape, businesses across various sectors, including corporations, retail, and banking, are striving to attract and retain customers. Customer segmentation has emerged as a vital strategy in this endeavor, enabling organizations to identify and cater to distinct customer groups. This study leverages the RFM (Recency, Frequency, Monetary) model to segment customers based on their purchasing behavior. Initially, an RFM analysis is conducted to quantify customer value, which is then further analyzed using the k-means clustering algorithm to identify distinct customer segments. By understanding and targeting these segments, businesses can enhance customer relationships, improve marketing strategies, and foster organizational resilience. This approach not only aids in acquiring new customers but also in retaining existing ones, ultimately contributing to sustained competitive advantage.
