How To Calculate “Trade Area” in 2021

With recent advancements in mobile data technologies, retailers now have the ability to be much more precise and granular with their trade area calculations by studying the hour-by-hour movement patterns of their customers.  


How To Calculate “Trade Area” in 2021

Where are your customers actually coming from?

“Trade area” is one of the most important age-old concepts in retail site selection because a correct measurement ensures that you’re selecting sites with high demand for your product and low supply.  Getting your trade area right is pivotal for accurate site selection, leading to more profitable sites, less cannibalization amongst nearby stores, and maximum expansion opportunities in your market. Here are important concepts for you or your broker to consider when examining the trade area for your next retail or restaurant location.

Using traditional trade area rings is risky.

We’ve all seen the 1-3-5 mile radius map before, but this traditional approach may be killing your expansion strategy for a couple of reasons:
  • Rings don’t show how your customers are traveling to your site. Are your customers walking to your store or driving?  Are they coming from home or work?  Rings give little to no indication.
  • Rings don’t standardize across sites or markets.  A 3-mile radius in Nashville could arguably make sense, but is ludicrous for NYC. Furthermore, even two different sites within Manhattan may have a difference of 0.5 miles in trade area size, but in a city reporting 67,000 people per square mile, this small difference can make or break your next location.  

Drive times (and walk times) are better, but provide an incomplete picture.

Analyzing drive times and walk times over distance rings can be immensely helpful, but the devil’s in the details.  Consider below a 6-minute walk time trade area of a downtown site, compared to where its customers are located during the day, as shown by Locate’s mobile data analysis in the next image. Drive times and walk times can be necessary for modeling purposes, but it fails to answer some core questions: Are your customers coming from home vs. work? How are your customers distributed within your trade area? Does your de facto trade area size correctly capture where your customers are in your neighborhood?

Using mobile data is the most accurate way to measure your trade area.

With recent advancements in mobile data technologies, retailers now have the ability to be much more precise and granular with their trade area calculations by studying the hour-by-hour movement patterns of their customers.   Here are 3 ways to immediately improve your trade area analysis today using mobile data:
  1. Examine your customers’ “before and after” locations instead of home addresses. The only way to do this is by analyzing the locations of your customers through mobile data analysis. By plotting the GPS coordinates of your customers’ devices, you can draw a trade area that represents the true “geographic pull” that brings your customers into your store.
  3. Outline the shape that contains most, but not all, of your customers. For optimal planning, you’ll want to choose the shape that captures most, but not all, of your customers. After a certain shape, you’ll start to get diminishing returns on how many incremental customers you’re able to capture.  Our recommendation for general rule of thumb is to find the trade area size that captures 70% of your customers, but this number may vary depending on the consumer behavior of the given location.
  5. Calibrate your trade area sizes from location to location.  Not only does the urbanity  level of a location influence the size of the trade area, but the consumer behavior patterns may differ from one street corner to the next. If you’re entering an expansion market, we recommend the trade area of synergistic brands (or shopping centers) in the new market to best calibrate your own trade area to new market conditions.

How Locate can help you with trade area calculation and site selection

Locate is the first tech-enabled brokerage in the retail industry that combines unparalleled artificial intelligence with brokerage expertise to create the most accurate site selection process possible for a fast-growing number of retailers like Allbirds, Barry’s, and Clean Juice. Using A.I. and data from over 180 million anonymous mobile devices across the U.S., Locate’s team of Stanford engineers helps retailers accurately define their trade areas, predict revenue streams, and make risk-adjusted decisions in opening successful store locations.


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