Abstract
Consumer behavior in retail stores gives rise to product graphs based on
copurchasing
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 Erd˝os-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.