Every Locatalyze report is built on real data — not guesses. Here's exactly what we analyse, where the data comes from, and how we calculate your score.
The process
Address + coordinate pinning
Competitor mapping
Demographic analysis
Rent vs comps
Model calibration (optional but impactful)
Deterministic financial model
Written analysis & verdict
Data sources
Google Maps Platform
Competitor locations, ratings, review counts, and price levels queried live for your specific coordinates within a 500m radius.
ABS Census Estimates
Population demographics, median income, household size and age distribution anchored to ABS 2021 Census with rolling estimate updates where available.
Commercial Rent Database
Suburb-level rent comps built from publicly available property listings. Sources vary by state: REIWA for WA, RealCommercial and Domain for NSW/VIC/QLD/SA/ACT. Your submitted rent is validated against the relevant state band.
Category trade norms
Daily customers baseline, average ticket size, COGS %, gross margin, and staffing cost ratios segmented by business type. Used as the fallback when you do not provide your own figures.
Deterministic Compute Engine
A rules-based financial model (not AI) that builds the P&L from your calibrated inputs. Formulas are deterministic and documented — no black box outputs.
Narrative layer
Generates the prose sections only — SWOT, market narrative, risk scenarios, and 3-year projection. Financial figures come from the compute engine.
Scoring system
The Location Score (0–100) is a weighted composite of five dimensions. Each dimension is scored independently then combined into a final score that determines your GO / CAUTION / NO verdict. Every report also shows a separate Data Completeness % and Model Confidence label so you can see how much of the analysis relied on your own inputs versus fallback category norms.
20%
weight
Rent Affordability
Rent as a percentage of projected revenue. Under 14% = GO band; 14–20% = caution; at or above 20% = danger zone (typically NO). Competition and demand scores still matter — this dimension is the single biggest predictor of long-term viability.
25%
weight
Competition
Competitor density within 500m, weighted by their threat level (ratings, review volume, proximity). Fewer strong competitors = higher score.
20%
weight
Market Demand
Search demand signals, population density, income fit, household growth and demographic alignment for your business category.
25%
weight
Profitability
Net profit margin after all costs. Calculated from your revenue estimate minus rent, COGS, labour and fixed costs.
10%
weight
Location Quality
Physical location signals: access quality, anchor proximity, and local activity conditions around your specific site.
All key dimensions support this location. The data gives you a basis to act — proceed to lease negotiation and site visits with confidence.
Mixed signals. Viable with the right execution, but specific risks need mitigation.
Significant concerns identified. The risk profile does not support proceeding at this time.
Financial model
Our financial model combines your inputs with category baseline data to build a realistic P&L. Here's the logic behind each number.
Base revenue (category norm)
daily_customers_base × hours_multiplier × access_multiplier × avg_ticket × 26
The baseline revenue from which all scenarios are built. We use 26 service days per month (standard Australian hospitality six-day trading: closed one day a week for owner-operated formats). hours_multiplier ranges from 0.45× (weekends only) to 1.35× (all-day). access_multiplier ranges from 0.70× (arcade) to 1.10× (transport hub). avg_ticket uses your entered value if provided, otherwise the category typical.
COGS (Cost of Goods)
28–40% of revenue
Typical band varies by category: cafes ~30%, restaurants ~32%, retail ~40%. Based on common gross margins for Australian operators.
Labour Costs
Staffing tiers by business type and size
Calculated from typical staffing requirements: cafe (2 FT + 2 casual) = $25,000–35,000/mo; restaurant = $35,000–55,000/mo; retail = $15,000–25,000/mo. Does not include owner salary.
Fixed Costs (for break-even)
Monthly rent + Estimated staffing costs
Only fixed costs are used in the break-even calculation — not COGS, which is variable. This is the contribution margin break-even formula, which avoids double-counting variable costs.
Break-even Customers / Day
Fixed costs ÷ (avg_ticket × (gross_margin% − other_variable_costs%) × 26)
The minimum daily customers needed to cover rent and staffing over the 26 service days per month (matching the revenue formula). Compared against your projected daily demand. If projected > break-even, the location is viable at current inputs. The zero-profit survival floor (rent + overheads only, excluding staff cost) is lower than this number.
Payback Period
Setup cost ÷ Monthly net profit
Months to recover your initial investment. Only shown when monthly net profit is positive and setup cost is greater than $0. Under 12 months is excellent. Over 24 months carries meaningful risk.
3-Year Projection Assumption
Year2 = Year1 × 1.08, Year3 = Year2 × 1.10
Projection growth assumptions use a two-step rate: +8% then +10% when sufficient live revenue signals are available.
Important: Use as a decision-support tool
Locatalyze reports are designed to help you make better-informed decisions — not to replace professional due diligence. Our revenue and profit estimates are based on statistical benchmarks and AI modelling, not guaranteed outcomes.
Before signing a lease or committing capital, we recommend:
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