RFM-Based Customer Segmentation: A Pedagogical Case Study for Marketing Analytics Education

Purpose of the Study This paper addresses the gap between marketing theory and practice by presenting a pedagogical framework to improve students’ analytical skills. It details a hands-on case study for teaching customer segmentation, a core competency in marketing analytics. Method/Design and Sample A robust analytical pipeline, including K-Means clustering and PCA visualization, is applied to a real-world transactional dataset of over 189,000 records from a Brazilian bakery. Results The analysis identifies four distinct customer segments. These findings are transformed into a replicable teaching module with practical classroom activities, such as persona creation and campaign simulations, designed to foster critical thinking and data interpretation skills. Value to Marketing Educators This work provides educators with a ready-to-use case study and supplementary materials (dataset and Python code) to teach complex analytics concepts. The framework is a practical tool to enhance student engagement and prepare them for data-driven industry challenges.