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Retail Renaissance

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Copyright ©2022 Tango. All rights reserved. Retail Renaissance: How Predictive Analytics is Transforming Site Selection 7 Turn consumer behavior into actionable data In retail, we often recognize patterns in consumer behavior that we can't measure or analyze in tangible, meaningful ways. The farther away your store is f rom a population, the less people will be willing to buy f rom that location. If people have to fight bumper-to-bumper traffic, cross over three lanes of a busy street, or navigate congestion in the parking lot in order to shop at a location, they'll avoid you at all costs. You already know your store needs to be convenient and accessible. There's only so much f riction people are willing to put up with, even if they're loyal to your brand. When machine learning has enough datasets to work with, you can turn obvious consumer behavior into actionable data. You can see why one site is near demand but not in a position to take advantage of it. Or find out how being on an endcap of a shopping center with poor visibility translates into low traffic. And see exactly how much a store's capacity depends on parking availability. Tango makes it easy to translate "the obvious" into data your models can actually use, so you never feel like you're making costly decisions based on assumptions.

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