Restaurant Site Selection
QSR and dining chains have abandoned radius circles for the same reason their site selection teams keep getting surprised: a 2-mile radius doesn't know about the highway interchange that collapses drive time to 4 minutes on one side and extends it to 18 minutes on the other. Drive-time isochrones — drawn from real road networks — define the loyalty zone your customers actually live in, the cannibalization risk a new unit actually poses, and the competition that actually shares your trade area.
Time zones
The restaurant industry's site selection methodology is built on a hierarchy of drive-time thresholds, and each threshold corresponds to a distinct customer behavior. The 5-minute zone captures the customer who doesn't think twice — an impulse stop on the commute home, a habitual lunch visit, a repeat purchase driven by proximity and availability. This customer is not loyal to the brand; they're loyal to the location. Lose them to a competitor that opens 2 minutes closer and you may not get them back.
The 10-minute zone captures the deliberate trip — a planned lunch, a family dinner on the way home, a fast-casual visit with a specific menu in mind. This customer has alternatives within the zone and is making a choice. The 15-minute zone and beyond is destination dining: the customer is going because of the concept, not the convenience. Different site selection criteria apply at each level. Conflating them — as radius-based analysis does — produces demographic profiles that mix three different customer archetypes into one misleading number.
Loyalty zone
Impulse & habitual visits — the customer who doesn't plan, just stops
Planned trip
Fast-casual primary — the customer choosing from competing options
Destination dining
Special occasion, unique concept — drive time is not a barrier
Three failure modes
You model two units as non-overlapping because they're 4 miles apart. A highway between them collapses that to 7 minutes; a river crossing doubles it to 22 minutes. The radius missed both. The first unit's revenue declines after the second opens — not because the market wasn't big enough, but because the radius analysis never showed you the real polygon overlap that your customers already knew was there.
A site near an office cluster has 20,000 people within a 10-minute drive at noon. By 7 PM that population is home — a different location 3 miles away. A radius at noon looks identical to a radius at 7 PM; it has no concept of where the population actually is. Drive-time analysis should use daypart traffic profiles, not a static circle, to capture the real trade area for each part of your operating day.
Radius circles include competitors across natural barriers that neither your customers nor theirs will cross. A competitor 1.8 miles away on the other side of a rail yard or a river may have zero actual trade area overlap with your site — but a radius flags it as a primary competitor. Drive-time polygons show only the competitors that genuinely share your reachable customer pool.
Feature breakdown
Pre-set QSR time bands, one click to draw the loyalty and planned-trip zones for any candidate address. Visualize both polygons simultaneously — the nested view that shows how your primary and secondary trade areas relate to each other and to nearby geographic barriers before you commit to a lease negotiation.
Run two origins simultaneously — visualize the trade area overlap percentage between a proposed site and your nearest existing unit. The overlap zone is the population both locations are competing for. Knowing its size before opening is the difference between confident expansion and a revenue transfer that surprises everyone at the next franchisee performance review.
Count competitor locations inside the drive-time polygon. Export the list with addresses and distances from your candidate site. The count that matters for restaurant site selection is not every competitor within a radius — it's every competitor within the polygon your actual customers can reach, including chains in adjacent categories competing for the same mealtime decision.
Median household income and population counts inside each zone. Export to CSV for your FDD filing, investment committee memo, or franchise disclosure document. The demographic read you're reporting to stakeholders should come from inside the real polygon — not from a ZIP code average or a radius that crosses the river.
FAQ · Restaurant site selection
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