In this paper we demonstrate how to use graph matching touncover heterogeneity in the structure of preferences acrossa population of decision-makers. We propose a novel non-parametric approach to formally capture the concept of pref-erence structure using preference graphs, thereafter clusteringdecision-makers based on graph embedding methods. We ex-plore the approach with simulated choice and empirical datafrom the most common classes of economic and psychologicalmodels. The approach uncovers heterogeneity in preferencestructure across a variety of dimensions, without requiring anyprior knowledge of those structures.