A Heuristic Approach to a Market Segmentation Problem with Multiple Attributes

Abstract: This paper addresses a realworld customer segmentation problem from a beverage distribution firm. Given a set of customers, which share geographical and marketing attributes (volume that customers demand from a specific type of product called SKU, type of contract, and type of store), the firm wants to partition this set into segments according to certain requirements. It is desired that customers allocated to the same segment must have very similar attributes. The main reason to get a partition with these features is because the firm wants to try different product marketing strategies. In addition, the firm wishes compact segments, that is, customers within a segment must be relatively close to each other. In this work, we propose a mathematical model and a solution metodology based on an Iterated Greedy Local Seach in a variable neighborhood enviroment. Computational results are presented.