RFM Analysis

RFM analysis is a long-standing, behavior-based method for scoring and segmenting customers by how recently they purchased (Recency), how often they purchase (Frequency), and how much they spend (Monetary value). Rooted in catalog and direct-mail marketing and popularized in Arthur Hughes's Strategic Database Marketing, it rests on the empirical observation that customers who bought recently, buy frequently, and spend more are the most likely to respond to the next offer. The classic procedure ranks customers into quintiles on each of the three dimensions, assigns each a score from 1 to 5, and combines the scores into cells, typically a 5x5x5 grid of 125 segments. Campaign managers then measure historical response rates per cell, compare them to a break-even threshold derived from contact cost and order margin, and target only the cells that are profitable to contact. Despite its simplicity, RFM is remarkably effective and cheap to run, requiring only transaction history. It remains a workhorse for segmentation and a natural precursor to model-based customer-base analysis and lifetime-value estimation.