How the trade demand score is calculated
Our 0–100 score weighs estimated local demand — from labour-market data and city population — against how many pros already work a trade. Here is exactly how it works, and where it stops.
The trade demand score is a 0–100 opportunity index for a single city. We estimate local demand — from U.S. BLS occupational employment per capita, the city's population, and BLS growth outlook — and weigh it against local supply: how many pros already work that trade. Demand well above supply scores high (room to win clients); saturated supply scores low. It is rebuilt nightly. Demand is modeled from public data, not yet measured from first-party quote volume — a limitation we are explicit about below.
Provider count in, 0–100 score out
supplyScore = min(100, providerCount × 10) score = min(100, max(1, 2500 / supplyScore))
In plain terms: each local provider adds to a supply score that caps at 10 pros. We then invert it, so an empty market scores near 100 and a market with 10 or more pros bottoms out around 25. Provider counts come from the HireLocal directory (scraped listings plus pros who have claimed their profile), counted per city and service, then aggregated to the trade.
From pro count to band
| Local pros in the trade | Score | Band |
|---|---|---|
| 0–3 pros | 83–100 | Underserved |
| 4–8 pros | 31–62 | Balanced |
| 9+ pros | ≤28 | Crowded |
Bands: 70 and above is underserved (thin supply, easier to win clients), 30–70 is balanced, and below 30 is crowded (saturated supply). The thresholds are fixed, so scores are comparable across cities and trades.
What this score is not
Demand here is modeled, not measured. We estimate it from public labour-market data (occupational employment, population, growth outlook) — not yet from first-party signals like quote volume, search interest, or posted jobs. It captures how busy a trade should be for the local population versus how many pros serve it, which usually tracks real opportunity — but a model isn't the ground truth, so pair it with salary data and your own local knowledge. The first-party demand layer (quote and search volume) is next, and we'll document it here when it lands.
Does the score measure customer demand?
Now, yes — indirectly. The score weighs a real demand estimate against local supply. Demand is modeled from public labour-market research (U.S. BLS occupational employment), each city's population, and BLS growth outlook — i.e. how large a workforce that trade should support locally. Supply is how many pros already serve it. The honest limit: demand is modeled from public data, not yet measured from first-party quote volume or searches — that layer is next, and we'll fold it in transparently.
How often is the score updated?
The index is rebuilt nightly from the current HireLocal provider directory, so a new pro claiming or being added in a city changes that city's scores within a day.