Many company, academic, and marketing executives have been interested in customer segmentation. Customer segmentation involves the practice of grouping or segmenting an organisation’s customer base according to comparable traits, including demographics, purchasing patterns, interests, and preferences. Finding groups of customers with similar requirements or behaviours is the goal of customer segmentation. It enables businesses to create focussed marketing campaigns and customise their goods and services to satisfy those demands. Customer cognition, which includes identifying their differences and evaluating them, is one of the significant issues faced by customer-based organisations. We can build a very effective framework using machine learning algorithms and data processing to understand customer desires and behaviours better and respond accordingly to meet those demands. The paper shows the separate study of Recency (R), Frequency (F), and Monetary (M) along with the combination of these three for the overall score. The combined RFM score is used to segment customers into three segments to predict the next purchase possibility based on a time period of 30 days.