Methodology · Updated May 2026
Show the working.
propautopilot is an editorial research desk for Australian property. Seven specialists work from maintained source data, every claim is cited where a public citation exists, and each ranked suburb carries the profile, score inputs, evidence state, and reasoning lens that explain why it appears. Public surfaces use the platform freshness label — Updated May 2026 — and refresh on a monthly operating rhythm.
The seven specialists.
Each specialist consults the same primary data foundation but applies a different decision lens. Suburb-level conclusions are cross-checked across multiple specialists before a verdict is published.
- CoachDiscover
- Buyer profiling, brief shaping, capacity capture
- Suburb ScoutResearch
- Area-level reads, verdict calls (Buy / Watch / Avoid)
- HunterResearch
- Shortlist discipline and due-diligence prompts
- ValuerEvaluate
- Fair-value triangulation across comparable ladder + statutory inputs
- NegotiatorOffer
- Offer position, draft email, walk-away discipline
- StewardHold
- Long-hold portfolio, tax position, refinance windows
- AdvocateSettle
- Buyer's-side process, settlement, escalation
Primary sources we read.
Every claim on a public suburb report or in a Compass answer is grounded in the maintained source register. Investor accounts use the same register inside reports, shortlist comparisons, and Compass.
| Source | What we use it for | Cadence |
|---|---|---|
| ATO postcode tax statistics | Income distribution, rental income, CGT realised at exit | Annual (financial year) |
| ABS Census 2021 | Population mix, household types, dwelling stock, demographic flow | 5-yearly |
| NSW Fair Trading tenancy bond lodgements | Actual paid rents (not asking rents) | Quarterly publication |
| State land-record transactions | Settled property prices, the foundation of yield + growth math | Weekly to monthly per state |
| Public planning records | Supply pipeline + planned dwellings, an early signal of dilution | Continuous |
| ASIC company registers | Corporate holdings, trustees, beneficial-ownership traces | Continuous |
| News RSS feeds (council + market commentary) | Suburb-specific commentary tagged + cited | Daily |
| Additional maintained sources | Hazards, transit, schools, demographics, infrastructure pipelines, crime, environmental risk | Internal SLA; public copy uses the platform freshness month |
Citation chips.
Every cited claim renders an inline rust-accent chip. Tap the chip to open the citation drawer. The drawer shows the primary source name (statute-OK references only, no commercial vendor names), the field path, the last-fetched date, and any cross-source agreement metadata. The chip prefix is §, the trailing ↗ indicates an outbound primary-source link is available where the source publishes one.
Five confidence states.
Every metric on a suburb report carries a confidence state. The state determines whether a number is rendered, suppressed, or shown with explicit hedging. Never softened or fabricated.
- Primary
- Direct read from a primary source. Highest confidence.
- UI: Solid chip, full cite drawer
- Derived
- Computed from primary inputs (e.g. yield = annual rent ÷ purchase price). Confidence inherits the weakest input.
- UI: Solid chip, derivation expanded in drawer
- Provisional
- Pending. Input data exists but hasn't been recomputed yet (data lag, refresh window, model recompute). Renders 'Pending' rather than a stale figure.
- UI: Dashed chip, eta in drawer
- Conflict
- Two or more primary sources disagree by more than 5%. Renders the conservative read with the divergence flagged.
- UI: Amber chip, both readings shown in drawer
- Stale
- Primary source hasn't published in its expected window (e.g. quarterly source 5 months silent). Last-known value rendered with last-reviewed date prominent.
- UI: Greyed chip, age + 'last reviewed' in drawer
The score trace.
A ranked suburb should never be a black box. The shortlist engine records the buyer profile, matching filters, score inputs, visible lens, and evidence state that produced the ranking.
Compass reads the same trace. If a user asks why a suburb is ranked above another, the answer should refer to the same yield, vacancy, growth, affordability, and coverage signals that appear on the report.
Where source coverage is sparse or not comparable, the score uses a defined null-policy and confidence dampening instead of filling a misleading value. This keeps the recommendation coherent without pretending every suburb has the same evidence depth.
Quarterly refresh cadence.
Tax brackets, HGS caps, LMI schedules, state Duties Act rates, and source register reviews land every quarter. When a rate or rule changes, the update lands within two weeks and a last-reviewed date is surfaced on the affected calculator + the affected suburb fields.
This document is reviewed at the same cadence. Last reviewed: 2026-05-09.
Score methodology summary.
Scores combine maintained suburb-level evidence across demand, affordability, safety, lifestyle fit, hazards, and market conditions. Where evidence is incomplete, non-comparable, sparse, stale, or under review, propautopilot marks the field as unavailable or labels the evidence class rather than filling a misleading number.
Price fields distinguish sold-registry medians from asking/listing indices where applicable. If a surface cannot carry that distinction, it should show the value as unavailable. Public freshness uses the platform month label — Updated May 2026 — rather than exact source dates.
The score methodology paper includes the current recipe families, null-policy rules, worked examples, and monthly manual refresh prompts so evidence does not drift ahead of the public freshness label.
What we never do.
- Round to look agreeable. If the median is $1,182,500, we render $1,182,500, not "around $1.18M". Buyers see the exact figure, not a softened one.
- Pay-to-play. No suburb appears higher because someone paid. No vendor name appears in any verdict prose.
- Fear-first framing. Calculators state current rules and model what changes if they do. They don't amplify panic about negative gearing reform or rate moves.
- Backfill evidence. We do not invent missing source fields. The scoring layer uses the maintained evidence state and null-policy rules.
- Change the story per surface. The dashboard, report, and Compass answer must explain the same score with the same reasoning lens.
Read further.
- The Buyer's Playbook This methodology applied to the end-to-end buying journey, narrated by the seven specialists.
- Data catalogue Public data surfaces, source semantics, and maintenance cadence.
- About propautopilot What it is and what it isn't.
- How to find investment properties: analyst's framework 10-step worked example using this methodology.
- mitsi@propautopilot.ai Questions about the methodology, or report a citation that doesn't resolve.