Methodology and data transparency

Data sources

We combine public bond-rent statistics with OpenStreetMap extracts for local context. Listing fields you enter in tools stay in your browser unless a page explicitly says otherwise.

How processing works

1. Import benchmark tables from the Tenancy Services snapshot.
2. Match suburb names to the active benchmark period.
3. Run calculators in your browser: affordability, move-in cash pressure, and market context vs benchmarks.
4. When a benchmark is missing, the site shows that clearly instead of guessing.

What we measure

• Weekly affordability against household take-home income.
• Move-in cash load (bond, advance rent, and setup estimates).
• Market context relative to suburb/property benchmarks.

How scoring works (listing tools)

Each listing is turned into comparable pressure signals. Those can be combined into a 0–100 composite score for side-by-side comparison, with visible sub-metrics so you can see why one option ranks above another.

GoWisely Liveability Score

On Auckland suburb pages we show a single 0–100 score based on mapped points of interest inside that suburb’s boundary (from OpenStreetMap). It does not use bond statistics, rent benchmarks, or listing data.

The score is a rough signal for everyday services in our snapshot — for example shops and transport stops. It is not a rating of safety, schools, or whether a suburb is “better” — and it can read lower where the map has less detail.

We combine five factors — essentials, getting around, family and care, lifestyle, and day-to-day services — each built from mapped place types in that suburb. Together they feed the single 0–100 score on the suburb page.