Mapping E-Commerce Customer Profiles with RFM and K-Means

• Ewerthon J. Kutz UEL http://orcid.org/0009-0000-3786-1320
• Helen C. M. Senefonte UEL

DOI: https://doi.org/10.5753/courb.2025.8768

Abstract

Understanding consumers is essential for effective decision-making in an integrated and competitive ecosystem. However, obtaining their characteristics and leveraging them to personalize services and allocate resources efficiently is a non-trivial challenge. This article analyzes data from an e-commerce business with the objective of segmenting its customers using the RFM (Recency, Frequency, Monetary) method combined with the K-Means machine learning algorithm, aiming to interpret these groups for actionable strategies and explore the segmentation process. As a result, four distinct behavioral segments are identified, providing strategic insights into retail consumption in the digital environment.

Keywords: RFM, K-Means, E-Commerce, Customers, Clustering

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