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Retail Renaissance: How Predictive Analytics is Transforming Site Selection
3
Discover a location's true
potential
Machine learning isn't new. And plenty of programs apply
it to site selection. The problem is that most solutions don't
give their algorithms enough datasets to work with. They're
"learning" without all the information they need. It's like
studying 60% of the material that will be on a test.
In the past decades, even the best strategists were essentially
shooting in the dark when it came to the nuances of how
traffic flow translates to business in a specific location, or
how operations and store cannibalization impact your
overall success. Not to mention your planned renewals or the
impact of closing or relocating other stores.
Each variable you add to the equation can dramatically
alter a site's profitability. And without incorporating each
consideration, you're left with a model you can't fully trust.
When you're making multi-year commitments that can
easily cost millions, you need the most reliable models.
This is where mobile data is truly remarkable. Using
advanced tools like Tango, you can track the movement of
anonymized individuals in a trade area and model customer
trip patterns. Our algorithms consider where populations
work, where they live, and where they go before and after
your store. With geofencing, you can establish boundaries
around your store, an entire shopping center, competitor
stores, and adjacent properties to glean more precise
insights about where people go.
