A development team looking at 4 sites will usually rank them on rent, visibility, and how the buildout pencils. Those 3 questions are answerable from a broker package in an afternoon. The questions that decide the outcome are harder and rarely appear in the package: how many of the right households sit inside a 10 minute drive, what comparable units in the region already earn, and which of the brand's own restaurants the new one will take sales from.
Build the Trade Area Before the Comparison
A site is only as good as the population that can reach it, and reach is measured in minutes. Drawing 5, 10, and 15 minute drive time polygons around each candidate address gives a set of comparable containers. Then fill them with the same data for every site: households, median income, daytime employment, and the count of competing restaurants in the category.
Candidate addresses and existing units belong on one map, and franchise mapping software holds both so the containers can be compared side by side. The shape of the polygon separates the sites more often than the household count does. A site on the wrong side of a divided highway can lose half its apparent trade area to a median with no crossing for 2 miles.
6 Data Layers for Every Candidate
The polygons are containers, and what goes inside them decides the comparison. Most restaurant concepts need 6 layers. Household count and median income describe the residential base. Daytime employment describes the lunch trade, and in an office corridor it can be triple the residential number. Competing units in the category show how much of that demand is already claimed.
The last 2 layers are the ones development teams leave out. Traffic counts on the adjacent roads are published by state transportation departments and describe how many cars pass rather than how many stop. Existing units of the same brand show where the trade area is already served, which is the single most expensive thing to get wrong.
Every layer should be loaded for all candidate sites at once. Pulling data one site at a time invites a subtle bias, because the first site becomes the reference point and the others get judged against it rather than against the concept's requirements.
Keeping the layers comparable takes 2 conventions. Use the same drive time bands for every site, since a 10 minute polygon in a dense grid and a 10 minute polygon on a highway corridor already differ enormously in area, and switching to a mileage radius for one site quietly changes the question being asked. And date every layer. Household counts revised 4 years ago and traffic counts collected last spring will disagree about the same intersection, and knowing which number is older decides which one to trust when they conflict.
Concept Fit and Site Ranking
Population alone does not qualify a site. The households have to be the ones the brand sells to, and a trade area holding 40,000 people can be an excellent site for one concept and a poor one for another at the same address. That is why large operators segment their markets before they build anything. Wal-Mart's move to tailor store assortments by community, reported under the heading of six degrees of demographics, sorted its US stores into 6 customer profiles rather than treating every market as the same store.
A restaurant brand does this arithmetic at a smaller scale. A fast casual concept with a $14 check and a lunch-heavy daypart needs daytime employment density more than household income. A family dining concept needs households with children inside a 12 minute drive. Those 2 profiles rank the same 4 sites in different orders, and the ranking that matters is the one built from the concept's actual customer.
Comparable Units for the AUV Benchmark
Before any site is scored, establish what a normal unit earns in this system. Average unit volume is the standard yardstick and also the number most often quoted loosely. The publication that compiles average unit volumes for its Top 200+ ranking defines the figure as average gross annual revenue across all units divided by the number of units, and warns that advertised AUVs in franchisor promotions deserve a look at the fine print.
The system-wide figure is the wrong comparison anyway. A brand with a $1.4 million system AUV can hold suburban units at $2 million and small-town units at $700,000. The candidate site should be measured against units in markets with similar density, daypart mix, and competition, and if the brand has fewer than 3 such units, the projection is a guess wearing a decimal point.
Measure the Overlap Before Signing
For any brand with existing units nearby, the honest comparison includes sales moved rather than created. Overlay the new site's drive time polygon on the polygons of existing units and measure the intersection. A 30% overlap with a unit doing $1.6 million is a different proposition from a 5% overlap with a unit doing $900,000.
Delivery has made that overlap harder to see and more contentious. A third-party provider's delivery zone frequently fails to line up with the territories a franchisor drew, which leaves 2 operators of the same brand competing for the same customers inside one restaurant delivery radius, and franchisors have responded by rewriting operations manuals and system standards to settle it. A site comparison that ignores delivery zones is comparing 2 restaurants that no longer exist in that form.
Territory Rights Attached to Each Site
Territory rights belong on the map next to the drive time polygons. In a multi-unit deal, the developer typically signs a development agreement committing to open an agreed number of units in a defined territory, and in exchange the franchisor agrees not to open a company-owned restaurant or grant a franchise to anyone else there while the agreement holds, as a legal explainer on structuring a multi-unit operation sets out.
That protection is bounded in both time and area. A candidate site sitting outside the protected zone by half a mile is a site where another operator of the same brand can open across the street once the development schedule ends.
The Structured Site Visit
Data narrows 12 candidates to 3. The visit decides among the 3, and it should be structured rather than impressionistic. Go at the daypart that matters most for the concept, count cars in the anchor tenant's lot, time the left turn into the site, and watch where people park when the lot is 70% full.
Write those observations into the same comparison table as the demographic figures. A site with the best trade area and a 4 minute wait to turn left across traffic loses to the second best trade area with an easy right in and right out, and no spreadsheet built from broker data will show that.
Score Every Site on One Sheet
Put every candidate in one table with the same 8 columns: 10 minute households, median income, daytime employment, category competitors inside the polygon, overlap with existing units, rent per square foot, projected AUV from comparable markets, and a note on access. Rank each column, then look at where the sites disagree.
A site that wins 6 columns and loses badly on 2 is usually the answer. A site that wins on rent alone is the one development committees talk themselves into, and the one that turns up 2 years later on a closure list.
A Week of Work and a 10 Year Lease
The full comparison for 4 sites takes roughly a week, most of it assembling data the brand already owns. A 10 year lease at $8,000 a month commits the operator to about $960,000 before escalations, and that is before equipment, buildout, and the working capital to survive a slow first year. A week of analysis against a million dollar commitment is the cheapest step in the entire development process, and it is the one most often skipped because the broker package looked complete.
