RETAIL SEGMENTATION ANALYSIS: INTEGRATING GEOVISUALIZATION AND STRATEGIC INSIGHTS INTO THE RFM AND K-MEANS MODEL

In response to the need for optimization in the retail sector, this paper proposes the RFMKIG (RFM, K-Means, Insights, Geovisualization) framework for the strategic segmentation of retail stores. The methodology combines the RFM model and the K-Means algorithm, applied to a public dataset of 100 North American stores, with its originality lying in the addition of two layers: geovisualization, which reveals spatial patterns, and qualitative analysis, which translates data into named profiles with actionable strategic insights. The RFMKIG framework proves to be a robust tool for data-driven decision-making, integrating the quantitative, spatial, and strategic dimensions.