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Retail Renaissance: How Predictive Analytics is Transforming Site Selection
8
Accurately compare different
locations
There really is a best location. But most retailers are
woefully ill-equipped to compare sites. Even when you
have tens of thousands of locations, each one is surprisingly
unique. And if your site models don't account for as many
variables as possible, you can't produce an accurate
comparison.
With a robust predictive analytics system, you can
comfortably compare a location in a high-income area
with two nearby competitors to one in a low-income area
with no competition. You can account for any variations in
store formats—is it inside a mall, part of a strip center, or a
standalone store? And you can actually compare traffic flow
and access to demand.
Another variable retailers often forget to compare is
differences in business operations. Place your top store
manager at an inferior location, and they could cause the
store to outperform a much better location operated by a
less effective employee. This could easily lead you to close
the wrong store, or overlook or even overestimate a potential
location. And it happens all the time.
