Methodology
Store Location Analysis Methodology
ShopLocation AI is designed for preliminary site screening. The score combines demand indicators, competitive pressure, convenience signals, business-type fit, and risk factors into a practical first-pass report.
What the preview can assess
The free preview shows a demographic snapshot only. Competition, nearby-place demand and the composite location assessment are not assessed until the required inputs are available. Unrequested or failed data is unknown, not zero.
ACS demographics describe the recorded census tract or county, not the selected competition-search radius. A county fallback is broad context. Resident population is not measured daytime foot traffic.
Population and demand base
Uses the recorded Census geography population and median age as heuristic inputs. It does not measure radius population or population density.
Income and customer fit
Compares local income and demographic signals against the expected business model.
Competition
Counts same-category operators and treats density as both demand proof and saturation risk.
Nearby POI convenience
Reviews offices, apartments, schools, parking, transit, gyms, retail, hotels, and parks. It is not measured pedestrian or vehicle traffic.
Business-type fit
Weights nearby signals differently for coffee shops, restaurants, salons, pet grooming, and other local concepts.
Risk resilience
Higher is better: it reflects resilience against the model's observed risk signals, not an absence of business risk.
Composite weights and assumptions
Population 20%, income 15%, competition 25%, nearby places 15%, business fit 15%, risk resilience 10%. Business fit reuses several of these inputs. Scores are heuristic indexes, not calibrated probabilities of business success.
The income reference is $85,000 for upper-income concepts and $65,000 for other concepts. Population is scaled against 32,000 residents, with an age bonus between 28 and 45. Competition scores peak at 3–8 returned competitors. These constants are model assumptions, not universal requirements for a viable site. Missing required inputs prevent a composite score.
How the Overall Score Is Interpreted
The overall score is a screening signal, not a prediction. A higher score means the available inputs appear directionally supportive for deeper diligence. A lower score means the location may still work, but the user should be more cautious about rent, positioning, access, or demand assumptions.
85-100
Excellent
70-84
Good
55-69
Moderate
40-54
Risky
0-39
Poor
Example Score Reading
A coffee shop with strong apartment density, offices, transit, and moderate competition may receive a good score because the trade area supports repeat morning demand. If the same site has several highly reviewed competitors, the score should lead to positioning and fieldwork questions rather than automatic approval.
Why No Competition Is Not Always Good
An empty market can mean opportunity, but it can also mean weak demand, poor access, low visibility, or unsuitable customer routines. The model treats balanced competition as stronger than either an unproven market or an overcrowded one.
Industry-Specific Weighting Logic
Different business types depend on different nearby signals. Coffee shops depend heavily on offices, apartments, schools, transit, and gyms. Restaurants may rely more on offices, apartments, hotels, parking, and delivery-friendly density. Nail salons and hair salons need repeat convenience, parking, retail co-tenancy, and neighborhood fit. Pet grooming needs apartment density, parks, veterinarians, and drop-off access.
Common Sources of Error
- Public or provider data may be incomplete, delayed, or categorized incorrectly.
- Competitor quality can change faster than public listings update.
- A strong neighborhood can still have a weak block, side of street, or storefront entrance.
- Rent, build-out cost, permits, utilities, and zoning are not fully captured by location signals.
Why This Is Not a Revenue Forecast
Revenue depends on concept quality, pricing, operations, staffing, marketing, lease economics, seasonality, customer retention, and execution. ShopLocation AI screens whether a site deserves deeper review; it does not estimate sales, profit, foot traffic, or financing outcomes.
Important limitation
The score is not a revenue forecast, investment recommendation, or lease approval. Users should verify rent, permits, zoning, traffic, access, build-out costs, and local conditions independently.
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