Data Accuracy & Limitations

How Accurate Is Our Data?

Every metric on PropertyMetrics NZ is sourced from official, publicly available NZ government datasets — the same data used by banks, local councils, and professional investors. We do not use third-party aggregators, private data vendors, or AI-generated estimates for any core metric.

That said, no dataset is perfect. The accuracy of any figure depends on the source it comes from, how recently it was collected, and how closely the aggregated data matches any specific property or suburb. The table below summarises reliability by source.

Rental Yield Estimates — What You Need to Know

Rental yield is the metric most people use PropertyMetrics NZ for, and it also has the most important caveat to understand. Our rent figures come from MBIE tenancy bond data — a register of bonds lodged with Tenancy Services each time a new rental agreement starts.

• New tenancies only. Bond data captures the rent agreed when a new lease starts. Long-term tenants whose rent hasn't changed in years are not included. In stable suburbs this means our figures reflect current market rates — which may be higher than average rents actually being paid across the suburb.
• Aggregated by suburb and bedroom count. We aggregate bond data by suburb and bedroom count to produce median rent estimates. Thin suburbs (few new tenancies per quarter) have wider uncertainty and less representative medians.
• Property type is not always distinguished. Bond data does not always separate houses from apartments within a bedroom count. A 2-bedroom unit and a 2-bedroom townhouse in the same suburb may be averaged together.
• Purchase prices use user input. The yield calculator uses the purchase price you enter, not a government-issued valuation. Yield is highly sensitive to price — a $50,000 difference in purchase price on a $700,000 property changes the gross yield by roughly 0.4 percentage points.

What the Data Can and Can't Tell You

Our tools are designed for research, comparison, and shortlisting. They are not a substitute for property-specific due diligence, a registered valuation, or professional financial advice.

Calculated Scores vs Raw Data

Two metrics on PropertyMetrics NZ are calculated scores rather than direct government figures. It is important to understand how they are derived.

• Seismic risk score. We query the GeoNet earthquake catalogue for all significant events within 300 km of a property over the past 10 years, and compute a score weighted by magnitude and proximity. This is a PropertyMetrics NZ calculation — it is not an official GNS Science risk rating, an EQC assessment, or a structural engineering report. For formal seismic risk assessment of a specific building, engage a licensed structural engineer.
• Walkability score. We count cafes, supermarkets, parks, schools and transport nodes from OpenStreetMap within a 750 m and 1.5 km radius, weighted by category. OSM is community-maintained and coverage is thinner in smaller towns and rural suburbs. A low walkability score in a regional centre may reflect incomplete OSM data rather than a genuinely poor walking environment.

How We Handle Missing or Thin Data

Not every suburb has enough bond activity or property transactions to produce statistically reliable figures. When data is thin, we handle gaps in the following ways:

• Thin rental bond data. When a suburb has fewer than 10 bonds lodged for a bedroom count in a quarter, we widen the yield range displayed or combine it with the nearest meaningful aggregation. We do not interpolate or estimate missing values.
• Missing school zone data. If a property address cannot be matched to a school zone, the school zone field displays "Not matched" rather than an incorrect zone. You should confirm zone eligibility directly with the school.
• OSM amenity gaps. In suburbs with limited OpenStreetMap coverage, the walkability score may understate true amenity access. We flag this in the interface where coverage is known to be sparse.

How Often We Update

Each data source has a different update cycle. Here is when to expect our numbers to reflect the latest available data from each source.

How to Report an Error or Data Issue

If you find a figure that looks wrong, a suburb with missing data, or a school zone that doesn't match what the school has told you, we want to know. Our data pipeline depends on official sources and the occasional error does slip through.

• Use the Contact page to report the issue. Include the specific suburb, metric, and what you believe the correct figure to be.
• If you believe a source dataset is wrong, we will trace it back to the raw government data before making any correction. We cannot override official source data without evidence of a genuine error.
• For time-sensitive issues affecting a property transaction, always verify directly with the relevant authority (LINZ, the school, or your bank) rather than relying solely on our platform.