Why physical-world behavior is becoming essential part of retail site selection

Retailers have long evaluated prospective locations using data to inform their decisions.

Demographic data, traffic volumes, proximity to existing stores, and competitor locations all go into building a “score” for a potential site. But two types of data are often missing from these analyses:

•Time of day by road segment traffic volume, and

•Trip data

Driving a premium customer experience starts with understanding how customers move. As competition for retail space heats up, so will the need for the best market intelligence.

Retail Space Tightens, Retailers Expand

The stakes for getting retail site selection right are getting higher. In 2023, U.S. retail space per capita shrank to 54.3 square feet, down from a 2009 peak of 56.5 square feet. In recent years, major brands like Kohl’s, Macy’s and Ulta have leaned into smaller-format stores.

This drop in space occurred, however, as retail sales and populations grew. Even as the retail footprint contracts, brands are expanding locations.

RetailStat is currently tracking more than 6,700 U.S. store openings planned for 2026, with restaurants accounting for more than half. This data shows openings are significantly outnumbering closings, representing a net increase of roughly 4,500 stores.

Many of those retailers are pursuing multi-year expansion strategies. The addition of dozens or even hundreds of new locations nationwide makes the right retail space even more valuable. Given these two competing market forces, selecting the right retail site is more important than ever.

Unseen Differences Between Two Sites

Retailers might evaluate two similar sites and see no major differences. Potential locations could have similar demographics, average traffic volumes, and proximity to existing and competitor stores. But unseen differences can cause each of these sites to perform very differently once stores are up and running.

For instance, two similar sites for a potential coffee store that relies on the regular surge of commuters might perform differently if one is on the side of a divided road that easily captures morning traffic, and the other is on the opposite side.

A location that might require drivers to cross heavy traffic to reach it, or one that might require a U-turn, might be less appealing to a passing driver than one that offers a quick diversion from their route.

The reverse might be true for two potential pizza restaurants. The site that has higher traffic volume in the evening in the direction of the evening commute will likely perform better.

Trip data can also inform these decisions. A retailer who understands the demographics of where passing drivers are coming from can determine the potential performance of a location.

For instance, the typical customer profile for a quick-service coffee shop might be different from that of a craft coffee chain. Understanding if that target demographic commutes past the potential site for either store might indicate the site’s performance.

Each of these hidden factors can turn a promising site into a costly miscalculation, all because it was on the wrong side of the road or in an area not frequented by the store’s target audience.

How to Uncover the Unseen

Using billions of current and historical mobility data points, retailers can gain insights into traffic conditions and commuting patterns, offering a true picture of how people move through potential retail locations. It’s a picture that helps retailers better predict the performance of potential sites, giving them a powerful advantage as retail space grows more and more valuable.

Once a location is selected, mobility insights can also help retailers optimize operations. Mobility data can help dial in staffing schedules to best meet peak shopping times, as well as refine delivery ETAs.

Having a real-time glimpse into how people move through physical space helps retailers align operating hours with actual customer behavior and identify where demand is building before it peaks.