How Site Scouts Forecasts Fuel Volume & Inside Sales

A feasibility study is only as trustworthy as the method behind it. Most run optimistic because you can't see how the number was built. Here's exactly how we build ours — no black box.

The data we start from

Every forecast is built from public and licensed sources, not opinion:

Step 1 — Capturable traffic, not the raw count

We don't treat the traffic count as the forecast. We estimate a capture rate — the share of passing cars that can and will actually stop — from access geometry (can cars turn in?), visibility, trip purpose (commuter vs. destination), and the competitors already in the radius. The result is capturable traffic. (See how to estimate fuel volume.)

Step 2 — Competition and capture

We map the competitive set inside the capture radius and split the available demand accordingly. A great corner with two strong stores already serving its rooftops is a different forecast than the same corner with open demand.

Step 3 — Trade area and inside sales

Fuel follows the road; inside sales follow the neighborhood. We read the rooftops, daytime population, income, and daypart mix in the trade area to project inside-store and foodservice demand — a separate question from fuel, and often the one that carries the store.

Step 4 — Ranged projections

We express projections as a low / mid / high range, not a single figure. The future is a range, and a forecast that pretends otherwise is hiding its uncertainty. The range is where the honesty lives.

Step 5 — Sanity gates and frictions

Finally, we check the number against what caps a site — an approved competitor, a saturated market, a drifting trade area — so the forecast doesn't run hot. A model built to reward big inputs will always find a big number faster than the friction that limits one; the sanity gates are there to catch that.

Step 6 — Human review before delivery

Before a report reaches you, it's reviewed for accuracy. We'd rather you wait for a number we stand behind than get an instant one we don't. Speed is the advantage; trust is the product.

Why the transparency matters

You should be able to disagree with a forecast — to see the assumptions, push on the capture logic, and stress-test the range. A number you can't question isn't more credible for being confident; it's less. That's the difference between a black box and an analysis you can put in a loan file. (See will a lender accept it.)