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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 5 Rapidly adjust models to changing circumstances Since March of 2020, just about everything has been in flux. Stores have closed left and right, and businesses are constantly modifying the in-person shopping experience to accommodate new guidelines and expectations. Consumer behavior has changed, too. Traditionally, historical data has played an essential role in site selection. But now, retailers are being forced to make long-term decisions based on rapidly changing data. In the past, sales forecasts and site models have taken months to develop. They've been built on years or even decades of data, and producing a new iteration could take just as long. That doesn't cut it in an environment where last year's data has such little bearing on the present. The variables are changing too quickly for most retailers to keep up. If you want to survive COVID and thrive in a post-COVID economy, you need the ability to pivot quickly and recalibrate your models based on current data. How do shifting health guidelines and consumer behavior impact ecommerce and brick-and-mortar sales? As businesses reopen and employees return to campus, how does that change traffic patterns and where your target demographic spends most of their time? What if everyone keeps working f rom home forever? With Tango, you can quickly and easily reconfigure your model and adapt your forecast to fit what you're currently seeing in the trade area, not just historical patterns. In such a fast-paced environment, this is especially critical as you consider upcoming lease renewals, store closures, and relocation projects.

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