Quick service
Quick-service restaurants, weighted toward the things a drive-thru actually lives on: traffic, access, demographics and competition.
What it weighs most
Traffic and visibility
35% of the score. The rest is on this page.
01 / The problem
A quick-service site is won or lost on traffic and access, and both are almost impossible to judge honestly from a desk. The site that looks perfect on a map is the one nobody can turn left into.
02 / The decisions it serves
Not a report. A decision somebody has to sign.
Each of these is a question your team already asks, and currently answers with a spreadsheet, a phone call and a fortnight.
Whether the traffic supports a drive-through
Twenty thousand vehicles a day, and twenty-five if the drive-through is the format rather than a feature.
Whether the category is already saturated
Not restaurants in general. The same food, within a mile.
Whether cars can actually get in
Access, stacking and the turn. The reason a site underperforms is rarely the demographics.
03 / What it asks you first
It would rather ask than assume.
The answer changes completely depending on these, so it will not guess at them in order to look fast.
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What concept: burger, chicken, Mexican, pizza, or coffee and bakery?
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Is a drive-through required?
04 / The method, in the open
Here is exactly what it weighs. Argue with it.
Most tools will not show you this, because most tools do not have it. These are the weights the playbook really uses.
Traffic and visibility
Demographics and demand
Competition
Same food category within a mile
Site access
05 / It is willing to say no
It does not hand you numbers. It gives you a verdict.
An assistant that only ever agrees with you is a mirror, not an analyst. This one holds a line, names the thing that kills the deal, and will tell you to walk away from a site you already like.
The thresholds it holds you to
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Traffic of 20,000 vehicles a day, or 25,000 if there is a drive-through.
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Population density of 3,000 people per square mile or better.
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Median household income between $35K and $80K is the sweet spot for most quick service.
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A five-minute drive-time trade area, with direct competitors inside one mile and indirect inside three.
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Peak hours analysed at 11am to 1pm and 5pm to 7pm, because that is when the money is made.
06 / Why not just ask an AI
A fluent answer and a defensible one are not the same thing.
Every model will answer a location question now, and most of the answers sound right. Ask twice and you get two of them. Ask where the number came from and the room goes quiet.
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It separates direct competitors from indirect ones, because another burger within a mile matters and a sushi place does not.
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It analyses the peak hours the business actually lives on, at lunch and at dinner, rather than an average day.
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It works to a five-minute trade area, because quick service is an impulse, not a destination.
07 / What it runs on, and what you get
The data underneath
Licensed and authoritative, and named in the output, so the number keeps its source when it travels.
- Esri GeoEnrichment
- Census
- Traffic counts
What you walk out with
A scored assessment against every factor above, on the live map, with the method beside it.
The method it used and the vintage of every number travel with it, so it still holds up when somebody asks you why in six months.
How an answer travels08 / It pairs with
Nobody makes one decision in isolation. Most teams run this alongside two or three of these.
Run Quick service on something you already decided. See if it agrees with you.
The honest test of a method is whether it reaches the conclusion your best analyst already reached, and tells you plainly when it does not.
Twenty minutes, and you can argue with the weights.