Customer segmentation based on a collaborative recommendation system: application to a retail company

Vandenbulcke, Virginie [UCL] Lecron, Fabian [UMons] Ducarroz, Caroline [UCL] Fouss, François [UCL]

Identifying customer segments has been arousing interest in the literature for decades, for various reasons. This paper introduces a different way of segmenting customers in the retail sector based on shopping behaviors: unlike traditional criteria, our segmentation criterion lies on items that we recommend shoppers to buy in the future, these recommendations being defined on what other shoppers, who act similarly in terms of shopping basket, buy. Our approach is thus made of two steps: first, products to be recommended to each specific customer are determined and second, customers are segmented following these recommendations. A first analysis on real data has been performed and preliminary results are shown in this paper. A possible application lies in the area of targeted promotional material, for example advertising folders or brochures adapted for each segment.