Analysis of E-Commerce Product Graphs

04/26/2020

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Consumer behavior in retail stores gives rise to product graphs based on co-purchasing or co-viewing behavior. These product graphs can be analyzed using the known methods of graph analysis. In this paper, we analyze the product graph at Target Corporation based on the Erdos-Renyi random graph model. In particular, we compute clustering coefficients of actual and random graphs, and we find that the clustering coefficients of actual graphs are much higher than random graphs. We conduct the analysis on the entire set of products and also on a per category basis and find interesting results. We also compute the degree distribution and we find that the degree distribution is a power law as expected from real world networks, contrasting with the ER random graph.