Real-time mobility analytics helps developers and retailers pursue data-backed decision-making.
Modern retail success depends not just on where it’s sited, but on how, when and why people engage with it. In today’s challenging retail landscape, the difference in performance between an accessible site and a less viable one is more important than ever, particularly for retailers that depend on vehicle traffic. Postpandemic shifts in consumer behavior and tighter margins have added new layers of complexity to site selection. While traditional resources such as radius maps and aggregated footfall counts are still useful, they fall short in understanding the potential for retail sites that depend on vehicle traffic.
In 2024, U.S. retailers shuttered more than 7,300 stores, the highest number of closures since 2020, and analysts projected that closures could more than double to 15,000 in 2025. Although e-commerce continues to grow — with forecasts reaching $6.8 trillion in global online consumer spending by 2028 — 80% or more of U.S. retail transactions still occur in physical stores.
Given these pressures, forward-looking developers and retailers are leveraging real-time mobility data to understand where potential customers are coming from when they go to a particular vendor or store, how they move through a market and how accessible a site is at different times of day. The result: data-backed decisions that reduce risk, increase store performance and align more closely with modern consumer patterns.
Understanding Vehicle Movement at Specific Times of the Day
Traditional determinations that rely on mobile or footfall traffic, often aggregated at a daily level, do not usually apply to retailers that need to understand how consumers reach their stores by car. And vehicle volume alone is a blunt metric. What truly drives understanding is the quality of that traffic: who the people are, where they originate and what time of day they pass by a site.
For instance, a breakfast-focused restaurant needs to understand the volume of traffic that can easily access a potential location from the side of the road that morning commuters take. A location in the opposite direction from the commuter flow might not perform as well if drivers need to make a U-turn or cross traffic. Similarly, a national coffee chain has used real-time mobility data to identify intersections where pedestrian counts spike during early morning and late afternoon commutes, ensuring store placement directly along those walking routes. Another example is a major big-box retailer that leveraged traffic flow data to avoid opening near a competitor whose parking lot consistently captured the majority of weekend shoppers — a nuance that static demographic reports failed to reveal.
This is where real-time mobility data becomes indispensable. Leveraging aggregated, anonymized location intelligence equips retailers and their development partners to make investment decisions that align with real-world consumer behavior. They can evaluate traffic both in terms of volume and intent, identifying patterns that reveal whether passersby are potential customers, how often they return and how far they’re willing to travel. In short, movement data allows teams to assess a site’s actual commercial gravity rather than relying on assumptions rooted in visibility alone.
A Smarter Approach to Site Selection
With mobility data integrated into the decision-making process, site evaluations can now include:
Traffic volume analysis: Identifying not just high-traffic areas but the type and timing of traffic on the specific roads that lead to the retail site.
Trip movement data: Tracking how customers and competitors move through trade areas.
Real-time catchment areas: Defining accurate drive-time zones based on actual origin-destination patterns, not assumptions.
Side-of-the-road bias analysis: Revealing how the direction of travel and the ease of turn-in affect drive-through and storefront performance.
Origin and destination analysis: Identifying where potential customers originate from and whether a location is in the right demographic area.
These insights empower retailers and developers to compare actual visit volumes between candidate sites and top-performing stores; understand how traffic flows shift depending on time of day, day of week or seasonality; and evaluate accessibility to the site from key anchors, competitors and commuting corridors.
Best Practices
Retailers seeking to modernize their site selection strategy can adopt several best practices rooted in mobility intelligence:
Analyze origin-destination patterns early. Before narrowing in on a site, use mobility data to analyze where current customers are coming from and how they interact with an existing footprint. Understanding origin-destination flows helps predict whether a new site will attract similar high-value traffic or dilute performance at an adjacent location.
Go beyond vehicle counts. Static traffic data alone lacks context. Retailers should look for insights into dwell time, trip purpose and daypart traffic to identify, for example, whether visitors are commuters, lunch-hour shoppers or weekend family groups. This allows for more precise forecasting and merchandising strategy.
Segment customers by visit frequency and loyalty. Not all visitors contribute equally to a store’s success. Frequent repeat visitors often drive outsized revenue. Use mobility data to identify high-loyalty cohorts and determine whether a new site lies within their travel patterns.
Understand competitive overlap. Evaluating where customers stop before or after visiting a location allows CRE professionals to detect potential synergies or threats. For instance, a site near complementary retailers may benefit from cross-shopping patterns, while proximity to strong competitors may reduce performance potential.
Assess real-time accessibility and infrastructure impact. Some locations may appear promising but suffer from congestion, poor ingress/egress or inconsistent traffic flow. By layering mobility data with real-time traffic analytics, retailers can identify potential friction points that may affect accessibility and, ultimately, revenue.
Simulate “what if?” scenarios. With predictive analytics tools, retailers can simulate future performance based on changes in traffic infrastructure, seasonal travel patterns or even local development plans. This helps stress-test assumptions before committing to a large investment.
Modernizing Site Strategy
As the CRE landscape grows more complex, access to accurate, real-time mobility data provides a competitive edge. Retailers who once relied on instinct or anecdotal trends can now ground their decisions in verifiable insights, reducing risk and boosting confidence for investors, developers and internal stakeholders.
For example, consider a retailer deciding between two potential storefronts in a busy commercial corridor. By analyzing mobility data, they might discover that one location sees a far higher volume of lunchtime foot traffic from nearby office workers, while the other attracts more evening and weekend visitors from surrounding neighborhoods. Depending on whether the retailer’s target customer skews toward office commuters or families, this insight could make the difference in choosing the site that delivers the best long-term performance.
Adopting this approach requires a mindset shift. Retailers must be willing to question legacy assumptions, integrate data-driven decision-making into their workflows, and partner more closely with data science and analytics teams.
A More Predictable Future
Retail success has traditionally hinged on foot traffic and visibility. But with e-commerce competing with brick-and-mortar stores and consumer routines being more fluid than ever, a high-traffic corridor doesn’t automatically guarantee high conversion rates.
In an era when physical footprint decisions are make-or-break for retail brands, site selection requires more than instinct or experience. It demands a data-driven approach grounded in real-world movement patterns. Embedding mobility intelligence into the development process empowers retailers to improve location performance and future-proof their expansion strategies.
Michael Cottle is the senior vice president for INRIX Enterprise.
