Product Relation Correlation and Its Use in Product Clustering

TL;DR

This paper proposes product relation correlation, a simple and robust measure of product relatedness based on shared purchasing patterns, useful for clustering and shelf space optimization in retail.

Contribution

It introduces a novel, computationally simple measure of product relatedness that aligns with cross-price elasticity and aids retail decision-making.

Findings

Correlation increases as products diverge from independence

Aligns well with cross-price elasticity measures

Effective for product clustering and shelf space planning

Abstract

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.