SampleIllustrative report · not your lease
Illustrative café screening using Locatalyze decision labels (PROCEED / VERIFY / AVOID). New onboarding runs for a site without trading history typically produce VERIFY, not PROCEED. Figures here are modelled, not measured at this premises.
Locatalyze
Location Intelligence Memo
Confidential · Prepared for the recipient
Subject site
214 Oxford Street, Leederville WA 6007
Specialty Café
Report ID
SAMPLE-L
Generated
12 May 2026
Data as of
12 May 2026
Prepared by
Locatalyze
Executive Summary
Specialty café at 214 Oxford Street, Leederville WA 6007 is worth continued diligence, but not a signature on this run alone. Default to VERIFY until the checks below are cleared. 4 direct specialty café competitors within 600 m — density is workable — differentiation beats generic execution. Rent at 15.9% of revenue — above the 14% caution line before economics clear PROCEED.
Bottom line: Margin-sensitive — verify before signing
Footfall: Not measured at this premises. Decision confidence: MEDIUM.
Modelled revenue
~A$78,750/mo · category estimate
MODELLED · Category-based estimate · not measured at this premises
Modelled net profit
A$-4k – A$16k
MODELLED · From category revenue · not measured P&L
Rent to modelled revenue
15.9%
MODELLED · Review against the workable band · modelled occupancy
Break-even volume
132 / day
MODELLED · At the modelled ticket · not counted covers
Labour (screening estimate)
A$26,000
MODELLED · Labour is a category screening estimate (A$26,000/mo), not a site payroll quote. It scales only when hours, seats, or a roster were supplied.
Modelled payback
25 months
MODELLED · Uses modelled profit. Not a measured recovery period.
Top risks to verify
Priority before signing
Confidence statement
The evidence basis is strong enough to support the VERIFY recommendation. Data completeness is 88%.
Quick read
Analysis
Detail panels
Reference
The decision
Margin-sensitive — verify before signing
VERIFY means confirm the checks below on site before you commit — not that the analysis failed.
Why
Confidence
MEDIUM
Key evidence is still unresolved: street activity is a neighbourhood proxy, not a door count.
The 3 things that matter most
What could change this decision?
Evidence quality
Demand — INFERRED · Footfall — PROXY · Competition — OBSERVED · Rent — USER SUPPLIED · Premises — PARTIAL
Key decision drivers
Overall 81 is driven most by competition (80/100, 28% weight). Scores are ordinal — not a guarantee of trading outcomes.
Scored against a mapped street address — still verify frontage and lease terms on site.
Competition80
4 direct competitors within 600 m drive this competition score.
Location90
Location score is structural area potential — not a lease recommendation by itself.
Location shows strong structural potential (90/100), but rent at ~15.9% of revenue blocks a PROCEED until terms improve.
Based on category benchmarks rather than verified site data — treat as directional. Gaps: street-activity proxy only.
What the numbers rest on
Evidence honesty
Missing data is labelled on purpose — nothing here is invented.
We know
We don't know yet
What could this look like financially?
Modelled operating figures — not actual store trading unless labelled SUBMITTED.
Inputs and context
Footfall
Highly relevant
73 /100 relative index — not people/hour
Not measured at this premises
What this means
Walk-in formats live or die on trading-hour covers at this door — neighbourhood proxies are not enough. Current evidence is a PROXY neighbourhood index — not a shopfront count.
Not measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday.
How to verify: Observe trade on two weeknights and one Saturday before signing.
Index values are relative neighbourhood activity — not pedestrians per hour.
Competition
4 café competitors within 600 m
moderate competitionWhat it means
4 direct café competitors sit nearby — workable if your offer fills a visible gap (price tier, day-part, or product specialty). Map the top three and note what each does better than you would on day one.
Competitor presence indicates category activity — it is not automatically good or bad for your concept.
Map evidence
Site pin and competitors within 500 m. Live map pins may differ slightly from the scored snapshot used in the recommendation.
Site fit
How this address matches your business profile.
Dimensions assessed
11
of available signals
Strong signals
4
see detail
Market fit
Strong fit
engine rating
Street visibility
Main street retail strip corridor
High — Main street retail strip corridor.
Anchor adjacency
Oxford Street dining cluster · Leederville dining precinct
Your share depends on whether anchor customers pass your frontage — not just co-location.
Transit access
Leederville Station · bus corridor
Commuter and lunch dayparts depend on walk time from the stop to your door — confirm path friction on site.
Daypart pattern
Not measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday.
Daypart curve is estimated from transit stops and retail POI density — not pedestrian counts. Validate peak hours on site.
Seating capacity
38 seats submitted
Competition pressure
4 café competitors within 600 m
Thin direct competition
Rent burden
Rent 15.9% — in band, tight margin
Inside band, above ideal (8–18%)
Demand alignment
Demand ~85 (proxy) · Specialty coffee demand on Oxford Street Leederville growing with office-worker return-to-work and weekend dining cluster.
Income match
High
Median household income $96,000 (ABS 2021 Census, SA2) — 21% above Perth metro. Strong disposable income for daily specialty coffee.
Population density
14,200 in trade area
25–44 dominant (48%)
Demographic profile
25–44 dominant (48%)
Leederville trades on a young professional and student mix with above-metro income — ideal for $6.50+ specialty coffee a…
What would change this: A material rise in competition density or rent moving above the workable band would weaken the fit assessment.
Not measured at this premises
Before you sign
These are the specific captures that upgrade this report from indicative to decision-grade. Each step is a count or comparable; none requires paid research.
Deal-breakers · stop or renegotiate
The landlord will not cap total occupancy cost at A$11,025/month.
How: Ask the agent or landlord for the complete written rent schedule, outgoings, incentives and annual review clauses.
Acceptable: The written lease terms prevent this trigger for the full initial term.
Stop if: The landlord will not cap total occupancy cost at A$11,025/month.
Conservative evidence cannot support A$89,286/month at the quoted rent.
How: Ask the agent or landlord for the complete written rent schedule, outgoings, incentives and annual review clauses.
Acceptable: The written lease terms prevent this trigger for the full initial term.
Stop if: Conservative evidence cannot support A$89,286/month at the quoted rent.
Measured volume falls below 132 transactions/day at an A$17.50 average transaction.
How: Collect dated counts and comparable sales evidence across at least three weekdays and one Saturday, then rerun the model.
Acceptable: Conservative measured evidence clears the stated threshold without using the best trading window only.
Stop if: Measured volume falls below 132 transactions/day at an A$17.50 average transaction.
Priority checks
Negotiate the exact PROCEED rent
The quoted terms sit above the 14% screening limit at base revenue.
Stop if: Stop if the landlord will not reduce total occupancy cost to A$11,025/month or less.
How: Request the full occupancy-cost schedule and place the target in the heads of agreement.
Acceptable: A$11,025/month or less, requiring at least A$1,475/month concession.
Measure the path to PROCEED and AVOID
VERIFY should resolve to a measurable outcome, not open-ended investigation.
Stop if: Stop if conservative evidence misses either threshold after lease negotiation.
How: Count transactions across three weekdays and one Saturday and retain comparable price/receipt evidence.
Acceptable: A$89,286/month and at least 132 transactions/day at the modelled ticket.
Breakfast foot traffic
Breakfast ~180/hr is a category proxy, not a count at this pin. Use it as a field-check target. Missing it does not prove the door is dead — it means the breakfast thesis is unverified.
How: Count pedestrians at frontage, 7–9am, 3 separate weekdays. The threshold below is a category benchmark you need to verify here.
Acceptable: Category benchmark ~180/hr (both directions)
Lunch foot traffic
Lunch ~120/hr is a category proxy rather than a counted frontage. Missing it does not prove lunch trade is dead — it means the lunch thesis is unverified.
Why: Lunch ~120/hr is a category proxy rather than a counted frontage. Missing it does not prove lunch trade is dead — it means the lunch thesis is unverified.
How: Count pedestrians 11am–2pm, 3 weekdays. Threshold below is a category benchmark — confirm at this address.
Acceptable: Category benchmark ~120/hr
Average ticket size
Below this band the financial projections need a 15–20% downward revision; above it the model is conservative.
Stop if: The measured result does not meet ~A$14–18 weekday breakfast, ~A$24–32 weekend brunch (Australia 2026).
Why: Below this band the financial projections need a 15–20% downward revision; above it the model is conservative.
How: Visit 2 comparable cafes within 800m at 8am and 12pm. Order a typical breakfast + coffee. Note the receipt total at each.
Acceptable: ~A$14–18 weekday breakfast, ~A$24–32 weekend brunch (Australia 2026)
Stop if: The measured result does not meet ~A$14–18 weekday breakfast, ~A$24–32 weekend brunch (Australia 2026).
Next steps
Evidence-based actions before committing capital — not personal advice.
Verify footfall at this door Required before capital
Count pedestrians for 15 minutes across morning, lunch, afternoon and evening peaks on a weekday and a Saturday.
Confirm lease and outgoings in writing Required before capital
Ask for the full rent schedule, outgoings, incentives, and review clauses before you model a final P&L.
Inspect premises suitability Required before capital
Confirm permitted use, services, access, loading, and any fit-out constraints on a physical visit.
Negotiate the exact PROCEED rent Optional
Request the full occupancy-cost schedule and place the target in the heads of agreement.
Re-run after confirmed inputs Optional
Update rent, ticket, and staffing with verified figures so the model matches the lease you would actually sign.
Risk
The triggers that would sink this site, the competitive pressure behind them, and the assumptions the numbers rest on. Anything that lands worse than modelled here changes the recommendation.
Failure modes
Concrete tripwires from the verdict contract, ranked by how specific, fixable, and early they show up in diligence. Measurable thresholds lead; broader failure patterns follow.
Most likely tripwire —If you only fix one thing, address this first — The written concession is less than A$1,475/month.
This will fail if The downside case remains loss-making after lease negotiation.
Critical · lease-killing risk if confirmed
Watch for failure if The landlord will not cap total occupancy cost at A$11,025/month.
Material · pattern with numeric anchor
Watch for failure if Measured volume falls below 132 transactions/day at an A$17.50 average transaction.
Material · pattern with numeric anchor
Competitive intelligence
Operators you are competing against
Full competitor breakdown in Competition ↓
Key assumptions
These are the inputs the model used — not hidden defaults. Update them in Adjust assumptions or re-run with your lease quote.
Average ticket
A$18
User supplied — not independently verified
Monthly rent
A$12,500
User supplied — not independently verified
Provided at analysis time — confirm with the agent in writing before signing.
Staffing
A$26,000/mo
Category screening roster
Benchmark labour — not a site payroll quote unless you supplied a roster or staffing scale.
Monthly revenue
A$78,750
Category-based estimate
Not measured at this premises.
Lease term
Not supplied
Missing
Term and CPI review were not modelled from a written lease — confirm both before treating occupancy as stable.
Foot traffic
Not counted at this pin
Category / POI proxy
A calibrated foot-traffic index (pedestrian API or mobile heatmap) is not connected for this report — demand scores may still use category proxies.
Money
What the site earns, what it costs to run, how long the cash lasts if trade comes in light, and how much rent this deal can carry.
In short
Base-case net profit is A$6.1k/month (8% margin) — the unit economics work at this rent.
Cafe margins typically run 8-15%. Watch rent-to-revenue ratio — healthy ≤14%, watch up to 18%, risky beyond.
How your inputs compare
Your average ticket
A$18
Typical for category: A$14–A$32
Within typical band
Scenario estimate: using under the current A$18 average-ticket assumption and benchmark costs, the business may need roughly 132 paid customers per day to cover operating costs. This is not a forecast — confirm against your actual lease, staffing plan, and on-site trade observation.
Sanity check (category realism)
Operator economics
Throughput and daypart stress from your sealed cost model — not generic industry averages.
Break-even transactions
132 / day
From quoted rent, paid labour, fixed operating costs and 38% COGS.
Modelled transactions
150 / day
18 above break-even at base case.
Peak hours: Weekday commuter AM and Saturday brunch carry most covers — evening is supplementary.
Staffing: Conditional — the paid roster clears break-even by 18 transactions/day, but quoted occupancy cost is above the 14% screen.
Takeaway vs dine-in
Mixed dine-in and takeaway
Illustrative band for a specialty café on a main strip.
Illustrative band: ~58% dine-in / ~42% takeaway (not POS-measured).
Ramp-up & working capital
Survival in months 1–6 is usually a cashflow problem, not a margin problem. Adjust demand assumptions to stress how much working capital you need before steady state.
12-month cumulative cash shortfall
Cumulative deficit through ramp-up (excludes the 1-month fixed-cost buffer below).
Minimum working capital (estimate)
$102,250
Ramp-period deficits (A$63,750) plus 1 month fixed-cost buffer (A$38,500).
Cash survival
Survivable on modal-case revenue — projected A$6,100/mo net supports a viable owner wage.
Working-capital runway
—
Profitable — not drawing down reserves
Min weekly revenue
$16,778
to cover all costs
Owner wage
Viable
modelled profit supports a wage
Customers / day
150
projected modal-case throughput
WHAT WOULD CHANGE THIS
Rent burden sits in the workable band. The main sensitivity is foot traffic — a 20% drop in daily customers would push the model toward breakeven.
Scenario analysis
Same cost structure, different revenue assumptions. The spread between worst and best is your uncertainty band — the wider it is, the more your outcome depends on execution.
Scenario comparison — text summary
This location has 3 modelled scenarios. Worst case: monthly profit −A$3.7k. Base case: monthly profit A$6.1k. Best case: monthly profit A$15.9k.
| Metric | Value |
|---|---|
| Worst case | Revenue A$63k · Costs A$66.7k · Profit −A$3.7k |
| Base case | Revenue A$78.8k · Costs A$72.7k · Profit A$6.1k |
| Best case | Revenue A$94.5k · Costs A$78.6k · Profit A$15.9k |
Adjust assumptions
Move the sliders to see how the verdict shifts. Same math as the engine — your saved report stays untouched.
Still CAUTION at these inputs — rent 15.9% of revenue and 7.7% margin leave little room for a soft month.
What moves this deal most
Each +A$1 ticket is worth +A$2,790/month in net profit. Below — every lever, ranked.
Tripwire: ticket could fall to A$15 and still break even.
Tripwire: you could lose 19 customers/day and still break even.
Tripwire: rent could rise to A$18,600 and still break even.
Investor read
Compact economics and risk framing — nulls stay null when inputs are not verified.
Rent workspace
Rent negotiation
Drag the slider to see how a different rent changes your margins, profit, and break-even threshold. All other costs held constant.
NET PROFIT / MO
A$6.1k
RENT OF REVENUE
15.9%
Category typical: 12%
PROFIT MARGIN
7.7%
BREAK-EVEN / DAY
132 customers
Seasonal forecast
Monthly projection for a café based on Australian seasonal trading patterns. The dashed line marks your base monthly revenue.
Annual total
A$913,500
Projected 12-month revenue
Best month — December
A$90,563
115% of average
Weakest month — July
A$64,575
82% of average
Peak-to-trough swing
A$25,988
Revenue gap between best and weakest months
Annual projections by scenario
Cafés see a winter dip (especially outdoor seating) and peak in late spring/early summer. December holiday trade boosts revenue.
Financial detail
Cost line items and scenario sensitivities. Same model the Three Numbers strip and Simulator read from — nothing is recomputed here.
Operator read
Rent of 16% is the binding constraint here. Either negotiate it down or build an offer that defends a premium price point — there's no third path.
Competition counts: Direct café competitors within 600 m: 4. Number used in the recommendation: 4 direct. Indirect food-service competitors: 4. Broader nearby food-service scan: 18 — not all are direct competitors for your concept.
Labour assumption: Labour is a category screening estimate (A$26,000/mo), not a site payroll quote. It scales only when hours, seats, or a roster were supplied.
Monthly revenue
~A$78,750/mo · category estimate
Total monthly costs
A$67k – A$79k
Net profit
A$-4k – A$16k
Face rent vs revenue
Rent 15.9% — in band, tight margin
Break-even
132 customers/day
You need at least 132 transactions per trading day to cover all fixed and variable costs at current pricing. At this run rate, setup costs recover in approx. 25 months.
Sensitivity — customers/day at different avg tickets
| Avg ticket | Customers/day needed | |
|---|---|---|
| $13 | 177 | |
| $17 | 132 | ← engine basis |
| $23 | 100 |
Based on same fixed cost structure. Higher ticket = fewer covers needed to reach break-even.
Cost breakdown
| Rent | Face rent, excluding outgoings | A$12,500 |
| Staff | A$26,000 | |
| COGS | Cost of goods sold — scales with revenue | A$29,925 |
| Other | Utilities, marketing, insurance, etc. | A$4,225 |
| Total monthly costs | A$72,650 |
Scenarios
Worst case
−A$3,665
Revenue: A$63,000
Total costs: A$66,665
Downside revenue at 80% of base; rent, labour and other fixed costs unchanged.
Base case
A$6,100
Revenue: A$78,750
Total costs: A$72,650
Base revenue with the same rent, labour and operating-cost stack.
Best case
A$15,865
Revenue: A$94,500
Total costs: A$78,635
Upside revenue at 120% of base; rent, labour and other fixed costs unchanged.
Multi-year revenue projection
Year 1
A$945,000
Year 2
A$1,039,500
Year 3
A$1,143,450
Market
Who else competes for the same spend, whether category demand is real at this pin, and whether the premises and the catchment suit the offer. Forward supply and licensing close the chapter.
In short
4 café competitors within 600 m — moderate competition.
In cafe-dense areas, differentiation matters more than location. Look for specialty gaps.
4 café competitors within 600 m
moderate competition4 café competitors within 600 m
4 indirect spend competitors may still compete for nearby trade.
The five competitors that matter most
These 4 operators matter most for your concept — ranked by threat, reviews, and overlap with your format. Review count is a popularity proxy, not monthly velocity.
520 reviews · 420 m
Competes for nearby spend but is not like-for-like (specialty coffee).
310 reviews · 370 m
Competes for nearby spend but is not like-for-like (food service).
142 reviews · 180 m
Competes for nearby spend but is not like-for-like (food service).
87 reviews · 240 m
Competes for nearby spend but is not like-for-like (food service).
How competitor counts are defined
Direct café competitors within 600 m: 4. Number used in the recommendation: 4 direct. Indirect food-service competitors: 4. Broader nearby food-service scan: 18 — not all are direct competitors for your concept.
Format mix within 600m: 3 other food service · 1 specialty coffee.
1 premium tier · 1 mid tier · 2 budget tier
Most nearby operators are adjacent formats (bakery, hybrid restaurant, takeaway) — 3 partial overlap; direct coffee/brunch competition is lighter than the raw count suggests.
4 in 600 m — thin mapped competition. Validate weekend covers on site before treating demand as proven. Lead incumbent: Oxford Espresso · 4.6★ · 520 reviews · 420 m.
0 direct competitors · 4 indirect spend competitors · 4 food-service venues scored
See pin positions in the map view ↓
WHAT WOULD CHANGE THIS
If Oxford Espresso at 420 m closes or weakens, the threat distribution shifts in your favour — re-running is worth it within 30 days.
In short
Trade-area demand is rising; tracks above the industry estimate (score 85/100).
For cafes, morning foot traffic and proximity to offices/transit are the strongest demand signals.
Market fit
Strong fit
Active operators
4 direct café competitors within 600 m · 4 indirect spend competitors
Catchment density
Thin direct competition
Demand is category-estimated — see Market for the proxy read.
Street activity
Proxy-basedFoot-traffic signal — see Data confidence for the full gap detail.
See data confidence for foot-traffic gaps.
Not measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday.
Estimated daypart curve (transit + POI)
Not pedestrian counts — validate peak hours on site.
6am · 9am · 12pm · 3pm · 6pm · 9pm
In short
Structural outlook — category index above median (composite score 81/100 · 4 competitors mapped). Demand trend is specialty coffee demand on oxford street leederville growing with office-worker return-to-work and weekend dining cluster. (qualitative signal — not measured).
Competitor count — see Competition.
Re-run triggers
In short
Split read — 4 dimensions favour the profile, 0 raise concerns, and 1 dimension needs on-site checks (e.g. low rent vs foot traffic) before committing.
Ideal cafe sites have: morning foot traffic, seating capacity for turnover, visible street frontage.
Street visibility
ModerateMain street retail strip corridor
Anchor adjacency
StrongOxford Street dining cluster · Leederville dining precinct
Your share depends on whether anchor customers pass your frontage — not just co-location.
Transit access
ModerateLeederville Station · bus corridor
Commuter and lunch dayparts depend on walk time from the stop to your door — confirm path friction on site.
Daypart pattern
Requires validationNot measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday.
Daypart curve is estimated from transit stops and retail POI density — not pedestrian counts. Validate peak hours on site.
Seating capacity
Moderate38 seats submitted
Competition pressure
Light4 café competitors within 600 m
Thin direct competition
Rent burden
ModerateRent 15.9% — in band, tight margin
Inside band, above ideal (8–18%)
Demand alignment
StrongDemand ~85 (proxy) · Specialty coffee demand on Oxford Street Leederville growing with office-worker return-to-work and weekend dining cluster.
Income match
StrongHigh
Median household income $96,000 (ABS 2021 Census, SA2) — 21% above Perth metro. Strong disposable income for daily specialty coffee.
Population density
Moderate14,200 in trade area
25–44 dominant (48%)
Demographic profile
Moderate25–44 dominant (48%)
Leederville trades on a young professional and student mix with above-metro income — ideal for $6.50+ specialty coffee a…
WHAT WOULD CHANGE THIS
A material rise in competition density or rent moving above the workable band would weaken the fit assessment.
Street context, who lives in the catchment, and whether that population matches your concept.
Suburb intelligence
Leederville trades on a young professional and student mix with above-metro income — ideal for $6.50+ specialty coffee and all-day food. Street activity (qualitative) — High.
Transit
Leederville station · bus corridor
Street type
Main street retail strip
Area median rent
A$12,500/mo
You submitted A$12,500/mo
Nearby anchors (500m)
Street activity
Proxy-basedFoot-traffic signal — see Data confidence for the full gap detail.
See data confidence for foot-traffic gaps.
Not measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday.
Estimated daypart curve (transit + POI)
Not pedestrian counts — validate peak hours on site.
6am · 9am · 12pm · 3pm · 6pm · 9pm
Area demographics
Leederville trades on a young professional and student mix with above-metro income — ideal for $6.50+ specialty coffee and all-day food.
POPULATION
14,200
Growth: +1.8% (2016–2021)
INCOME BAND
High
Median A$96,000/yr (ABS-adjacent)
AGE COHORT
25–44 dominant (48%)
25–44
HOUSEHOLD SIZE
2.1 avg
EMPLOYMENT
68%
EDUCATION
Bachelor+ 42%
TOP INDUSTRIES
Health · Professional services · Retail
Customer demographic match
Income
Age group
Density
Employment
Education
This area is a strong demographic match for a specialty café on the dimensions we could measure. The local population aligns with the typical customer profile in income, age, and lifestyle.
Cafes thrive in areas with a mix of professionals, students, and young families who value convenience and social dining.
Operator lens
Three plain-English reads of the same numbers, framed the way operators in this category actually think about a deal.
Rent of 15.9% sits in the stretched band for this category. Net margin wasn't measurable; treat the headline figure with caution.
Projected 150 customers/day clears break-even (132) by 18 (+14%). Thin cushion — operators normally treat anything under 15% as a single-bad-week-from-trouble.
4 café competitors within 600 m — mid-density — plan for +2 net new competitors within 12 months as the watch trigger.
Who signs this lease?
The same site reads differently for different operator profiles. Below: how a first-time owner, experienced category operator, franchise system, and high-volume takeaway concept would each weigh this lease.
Evidence & methodology
Submitted vs observed vs modelled inputs, confidence by topic, where each figure comes from, and how Locatalyze decides PROCEED / VERIFY / AVOID.
Evidence & confidence
Indicative only overall — buckets below show submitted vs modelled inputs; the topic table shows strength by lease factor. Gaps are listed once (not repeated in each section).
This report analysed 4 competitors, and 5 of 5 data checks for 214 Oxford Street, Leederville WA 6007.
Evidence quality
1 submitted · 2 observed · 4 modelled · 2 missing — submitted figures come from you; modelled figures remain assumptions until confirmed.
Submitted
Observed
Modelled
Missing
By topic
Gaps to close before signing
88% data signal · Gaps: street-activity proxy only Sections with thin inputs are hidden rather than fabricated.
Average source confidence (0%) reflects per-metric reliability. Data signal (88%) is the share of inputs from measured sources vs category benchmarks — that drives the headline confidence tier above.
Appendix A1
Each report is assembled from eight independent research stages that run in parallel against current data sources — Google Maps for competitors, ABS Census 2021 for demographics, and category- specific financial benchmarks. Rent benchmarks and demand scores are AI-estimated from suburb context and category patterns. Stages that fail or time out fall back to category-level benchmarks; the confidence label reflects the proportion of measured vs estimated data.
Composite score weighting
| Rent burden | 20% |
| Competition | 25% |
| Demand | 20% |
| Profitability | 25% |
| Location | 10% |
Verdict ladder
Rent is compared against a workable band of 8–18% of monthly revenue for the category — the industry-standard hospitality viability threshold, consistent with CBRE Australian Retail Benchmarks and Retail Doctor Group occupancy-cost guidelines. Inside the band means rent burden sits within the model range; above the band signals margin risk unless pricing is premium.
Appendix A2
Locatalyze blends measured and benchmark data. The table below lists the source for each major section. The Data Quality section in the main report shows which data checks resolved for this specific report.
| Section | Primary source | Fallback |
|---|---|---|
| Competition | Google Maps Places API | Category density benchmarks |
| Demographics | ABS Census 2021 | Suburb-level inference |
| Foot traffic | Pedestrian count register (when available) | Not measured at this premises. Category street-activity is a proxy — count pedestrians at this door on two weekdays and one Saturday. |
| Rent benchmark | Commercial listing register | Category band for suburb |
| Demand | Location demand signals | Category demand index |
| Revenue model | Operator inputs + revenue model | Category cost stack |
| Trajectory | ABS + listings velocity | State trend benchmark |
Appendix A3
Every Locatalyze report carries a confidence label. The label is informational — content is never hidden based on confidence. A low-confidence report displays every section with the verdict dimmed and qualifiers applied. This appendix explains what each label means so a recipient can read the memo with appropriate weight.
Most data checks resolved against measured inputs. The evidence strength supports the stated recommendation without changing its direction.
One or two key inputs are estimated. Treat the verdict as a working estimate; the items listed under Top Risks need verification before signing.
Inputs are thin. The score is benchmark-derived — read the memo as direction-of-travel, not a precise site measurement.
Appendix A4
Appendix A5
This memo is decision support, not financial, legal, or tax advice. Locatalyze synthesises public, licensed, and modelled data into a structured read; figures are model outputs subject to the assumptions and data quality described above. Recipients must conduct their own diligence before committing capital, signing a lease, or making any other binding decision.
Reference
SAMPLE-L
Subject site
214 Oxford Street, Leederville WA 6007
Business type
Specialty Café
Generated
12 May 2026
Analysis model
Locatalyze v7.4
Document type
Location Intelligence Memo
Classification
Confidential
Issued by
Locatalyze · www.locatalyze.com
Unlocked report preview
Locatalyze should feel like a consultant: clear recommendation, visible assumptions, and a plain policy if generation fails.
Location recommendation
PROCEED / VERIFY / AVOID, confidence level, entry conditions, and the specific assumptions behind the recommendation.
Commercial pressure
Competitor concentration, nearby winners, rent pressure, and where a new operator would need to differentiate.
Financial model (paid unlock)
Revenue range, break-even pressure, rent-to-sales test, scenario assumptions, and the inputs you can replace.
Failure modes
The visible reasons a location could fail even when the suburb looks attractive.
Buyer protection and regeneration policy
Practical protection for technical failures, with honest limits around commercial outcomes.
In this sample (unlocked)
Live assessments from onboarding use the Location Decision Report format. This sample keeps the legacy memo shell for conversion QA — same decision words, not a guarantee of identical section layout.
On your address
Your live Location Decision Report exports via browser print/PDF from the assessment page. How scoring works →
Ready to run your lease?
Generate your own report →Address-level analysis on your Mapbox pin — not a generic suburb summary.
The old way
The Locatalyze way
Next step
Stop guessing on rent. Run your address.
Live competitors, suburb rent bands, and location score, data confidence, and proceed / verify / avoid screening recommendation — built from your Mapbox pin and lease inputs.