A little bird told us.
Methodology
How nestfinder scores postcodes and what feeds those scores.
What we score
For every Australian postcode in our index, we compute a per-feature score: commute time, school fees fit, bedroom/bathroom/carpark fit, crime rates, amenity density, school performance, and the rest. Each of those features is percent-ranked across all postcodes: a cycle-commute score of 0.85 means "closer to your target than 85% of postcodes within its own city". Percent-ranking keeps the numbers comparable within a city: a school-performance score of 0.7 means the same thing regardless of which postcode it's attached to.
The heatmap can also paint the map along a single dimension at a time — transport, schools, crime, affluence, or amenities — as a way to explore one measure visually. That view is for exploring; your personalised rank uses every feature at once, weighted the way you've set your preferences.
How your preferences shape the ranking
Every feature score above is combined into one ranking per postcode, and your preferences profile controls how much each feature counts. Turn a preference up and postcodes that are strong on that feature move up your list; turn it down and it matters less. We don't publish the exact combining formula or the full table of default weights — publishing both together would let anyone reconstruct the model from public data and defeat the point of a personalised rank. What we do publish is what a score represents (above) and what feeds it (below), so you can judge whether to trust it without being handed a spreadsheet you could paste our source data into.
In the wizard, features are grouped the way most buyers reason about a postcode: Housing, Transport, Crime + community, Amenities, Schools, and Character. Every feature inside a group has its own slider — nothing is locked to a group-level weight — and you can leave the defaults or tune any of it yourself in your preferences profile.
What goes in
Every score traces back to a named source, not a black box: the ABS Census, state and territory crime statistics, myschool.edu.au (ACARA) school data, the community-maintained NBN upgrade map, and aggregated market data for sale prices and advertised rents. The "Data currency" table below shows exactly when each one was last pulled.
Intent-aware affordability
The affordability signal depends on what you're trying to do: buying, renting, or investing.
- Buying a home (PPOR): median sold price (across sold listings in the postcode, trailing 12 months), scored against your budget.
- Renting: median advertised weekly rent.
- Investing: gross yield — a derived estimate, not a directly-observed figure. It combines the ABS Census median weekly rent (adjusted for inflation to the current quarter) with the median sold price across sold listings in the postcode, trailing 12 months. Gross means before rates, strata, management fees, vacancy or tax.
Sale-price and weekly-rent inputs come from aggregated market data, refreshed monthly. The gross-yield estimate's rent figure additionally draws on ABS Census data, inflation-adjusted using ABS CPI Rents.
Data currency
Numbers are only as good as the date they were pulled. Census figures (which feed the affluence score) are a fixed 2021 release. Schools data comes from a committed reference snapshot — we know how long that exact file has been in service (see the table below), but not the date ACARA actually published the underlying figures, so we say both honestly rather than presenting one as the other. Crime and NBN data are refreshed on an ongoing basis from their upstream sources, but we don't have a precise "as at" date for those two yet; we say so rather than guess.