This paper introduces product relation correlation, a measure of product relatedness that assesses the extent to which products may function as substitutes or complements through analysis of shared purchasing patterns. Product relation correlation can be used for tasks such as product clustering and shelf space optimization, enabling retailers to arrange items in ways that enhance customer experience. Applied to data from a retail drugstore chain, the measure demonstrates an alignment with cross-price elasticity, increasing as products diverge from independence. With computational simplicity, requirement for only commonly available data, and a robust theoretical interpretation, product relation correlation serves as a practical and efficient tool for deriving useful product insights.
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