Clear division of responsibility
BuyerLens is general-information research and education software. It is not a buyer’s agent, real estate agent, mortgage broker, financial adviser, conveyancer, solicitor, accountant, tax agent, valuer or building inspector. It does not act, inspect, negotiate, bid, apply, sign, transact or contact anyone on your behalf.
How suburb candidate discovery works
- The user chooses a deposit, borrowing-power estimate, states, property type, research preference, minimum yield and maximum vacancy rate.
- BuyerLens calculates a state-specific purchase ceiling using the disclosed maximum LVR, stamp duty, purchase-cost and cash-reserve assumptions.
- A budget-bounded, state-diversified sample is filtered for price, yield and vacancy.
- Remaining candidates are ranked using available long-term growth, rental growth, demand, supply and confidence evidence.
- The result shows sample coverage, evidence coverage and confidence so missing information is visible.
Discovery is not exhaustive. An absent suburb has not necessarily failed. Rank scores are relative to the fetched candidate set, are not forecasts, and must not be read as a direction to buy. See the public methodology overview for the evidence themes, scoring safeguards, validation status and known limitations.
Scorecard evidence rule
The scorecard requires several independent themes to align. Missing evidence receives no hidden positive assumption. Strong evidence classifications require broad signal and theme coverage; one high metric cannot qualify a suburb by itself.
Exact internal weights, calibration factors and ranking rules are not published. Users can still inspect the components, sources, dates, coverage and limitations attached to their own results.
Sources and update timing
| Source | Used for | Timing and limitation |
|---|---|---|
| HtAG Analytics | Prices, rents, yield, growth, vacancy, demand and supply signals | Provider observations can follow different release schedules and may be quarterly. BuyerLens may reuse a recent licensed result to manage cost. Retrieval time is not the market observation date. |
| Australian Bureau of Statistics | Demographics, dwellings and household context | The current demographic integration uses the 2021 Census and is historical context, not a live market signal. |
| State government sales and rental-bond data | Recorded sales and rental evidence where available | Coverage, release periods and property-type detail vary by state. The app displays the available source period or ingestion date. |
| Reserve Bank of Australia | Cash-rate and indicative investor-rate defaults | BuyerLens checks for updates daily and retains clearly identified fallbacks. The result is not a lender quote or serviceability assessment. |
| Government planning and hazard services | Available flood, bushfire and planning overlays | Coverage differs by jurisdiction and can be incomplete or unavailable. “Not assessed” never means “no risk”. |
| Property portals and Google | User-directed listing searches and professional-search links | BuyerLens links users to the original service. It does not certify listings or vet professionals returned by a search. |
Calculations and scenarios
Calculator and Scenario Lab outputs are deterministic estimates based on the values the user enters and the assumptions displayed with the result. Scenarios are counterfactual examples—not predictions. Stamp duty uses standard investor schedules and does not include every concession, surcharge or personal circumstance. Borrowing estimates do not reproduce a lender’s complete policy or expense benchmark.
Break-even figures identify the mathematical point at which the selected scenario changes sign. They do not establish affordability, suitability or an acceptable level of risk.
Research Coach and AI
The Research Coach is an AI data explainer powered by Anthropic. It can explain concepts, call BuyerLens research tools and summarise candidates matching filters selected by the user. It may make mistakes. Current numerical claims should be tied to retrieved tool data and displayed sources.
- It does not decide which property is suitable.
- It must not invent listings, prices or missing evidence.
- It does not recommend a particular loan, ownership structure, SMSF strategy, tax treatment or legal action.
- It does not contact agents or professionals, make offers, negotiate, bid or transact.
Chat text is sent to Anthropic to produce a response. Do not enter card, bank, identity, tax-file, Medicare, password or document information. See the Privacy Policy for processing and deletion details.
Methodology versions
| Component | Current version | Purpose |
|---|---|---|
| Suburb discovery | suburb-discovery/2.1.0 | Evidence-aware candidate comparison with relevant geographic context, coverage, confidence and freshness controls. |
| Suburb scorecard | suburb-scorecard/2.1.0 | Multi-theme evidence assessment with consistent classification, minimum-coverage and source-date safeguards. |
| Deal calculator | deal-calculator-io/1.0.0 | Upfront costs, yield, interest-only pre-tax cash flow and break-even estimates. |
| Scenario Lab | deal-scenario/2.0.0 | P&I or interest-only cash flow, break-even points and user-entered growth illustrations. |
| Research dossier | research-dossier/1.0.0 | User-prepared record of preferences, candidates, evidence, scenarios and open questions. |
| Due-diligence template | due-diligence/1.0.0 | Educational checklist and professional-handoff questions. |
Change log
July 2026 — v2.1: improved the relevance of peer context, strengthened treatment of undated evidence and expanded validation outputs to include return and downside measures.
July 2026 — v2: strengthened correlation control, geographic context, freshness and missing-evidence handling, and introduced rolling-origin validation. The model remains an evidence-ranking framework until its evidence gate is passed.
July 2026 — v1: introduced explicit evidence coverage, diversified discovery, methodology versioning, scenario ranges, persistent Research Cases and user-prepared dossiers.
Data budgets, history, conflicts and corrections
Some licensed data lookups have a monthly account allowance. When that allowance is exhausted, new paid lookups stop; a recent cached result may remain available without another provider request. The app identifies when a result was observed and retrieved so reuse is not presented as new market evidence.
Refreshing a saved candidate can preserve the previous evidence snapshot in its Research Case history. BuyerLens retains a bounded set of recent explicitly saved dossier versions; the current limit is shown inside the product.
Professional-search results are not vetted or ranked because of payment to BuyerLens. BuyerLens does not currently receive referral commissions for those search results. If a commercial relationship affects a result in future, it must be identified beside that result.
If a source, calculation or explanation appears wrong, do not rely on it. Use Send feedback and include the source label, observation date and result you are challenging. Material methodology corrections will be recorded on this page.
What to verify before acting
- Confirm borrowing capacity and any particular credit product with a licensed mortgage broker or lender.
- Have a conveyancer or solicitor review the contract, title, planning information and transaction dates.
- Confirm personal tax and ownership-structure questions with a qualified accountant or tax adviser.
- Arrange appropriate building, pest, strata and other inspections.
- Verify rent, insurance, management costs and local demand independently.
- Inspect the property and surrounding streets yourself or engage an appropriately qualified professional.
BuyerLens helps you prepare better research and better questions. Completion of a checklist does not mean a property is safe, suitable or ready to purchase.