How is a suburb score worked out?
See what goes into each of the five dimensions, and what a score cannot tell you.
The working behind Suburb research. Its examples are made up, and are not any real suburb's figures.
1. What does a dimension read?
A suburb is scored against its peers, the other suburbs of the same state and home type. Under each dimension's bar, its words say where it ranks against other suburbs, and its trend since last month.
- 61 or more reads ahead of most, 40 to 60 in line with most, and under 40 behind most.
- A rise of 3 or more reads improving, a fall of 3 or more softening, and less steady. With no score last month, there is no trend.
Say Growth scores 68, up from 64. It reads ahead of most on how values and sales have moved, and improving. Risk, at 70, reads fewer warning signs than most.
2. What else does the analysis show?
Where it leads and Where it trails each name up to four inputs, from the top or bottom 30% of other suburbs. The analysis is four pages, listed under Suburb analysis in the sidebar: the score, prices and rent, the local area, and people and homes.
Download PDF saves it, and a Business account can send it to a client.
3. What does a suburb score compare?
Each input ranks a suburb against every other suburb in the same state with published homes of the same type that month. The least favourable scores 0, the most favourable 100, and the rest are spaced evenly between.
Say 41 suburbs have a vacancy rate. Lower is better, so the lowest scores 100 and the 21st scores 50. Suburbs with the same figure share a score.
An input is scored only where at least 20 other suburbs, and at least 10% of all of them, have evidence for it. Missing evidence stays unavailable, never zero.
4. How is a score built?
The suburb score is the weighted average of the five dimensions, so two suburbs can reach the same score from different parts.
For the card above, 68 × 25% + 50 × 25% + 60 × 20% + 40 × 15% + 70 × 15% is 17 + 12.5 + 12 + 6 + 10.5, which is 58.
A score of 70 or more reads as Strong, 60 to 69 as Positive, 50 to 59 as Balanced, 40 to 49 as Mixed and under 40 as Weaker, the same bands the map colours. The card above reads as Balanced.
A dimension needs evidence for half its weighting. With three or four dimensions carrying at least 60%, the score is partial. With less, there is none.
5. What goes into each dimension?
Growth and Rental market carry 25% each, Liquidity 20%, and Stability and Risk 15% each.
Each dimension is built from inputs, each with its weight and whether a higher or lower figure counts in the suburb's favour. Vacancy rate counts in Rental market and in Risk.
Growth, 25% of the suburb score
| Input | Weight | Better when |
|---|---|---|
| Modelled value change · 3 months | Weight 7.5% | Better when Higher |
| Modelled value change · 12 months | Weight 7.5% | Better when Higher |
| Modelled value change · 36 months | Weight 7.5% | Better when Higher |
| Modelled value change · 60 months | Weight 7.5% | Better when Higher |
| Sale-price change · 3 months | Weight 9% | Better when Higher |
| Sale-price change · 12 months | Weight 9% | Better when Higher |
| Sale-price change · 36 months | Weight 9% | Better when Higher |
| Sale-price change · 60 months | Weight 9% | Better when Higher |
| Sale-price annual growth · 5 years | Weight 6% | Better when Higher |
| Sale-price annual growth · 10 years | Weight 6% | Better when Higher |
| Sale-price annual growth · 20 years | Weight 6% | Better when Higher |
| Sales-volume change · 1 month | Weight 5.33% | Better when Higher |
| Sales-volume change · 3 months | Weight 5.33% | Better when Higher |
| Sales-volume change · 12 months | Weight 5.34% | Better when Higher |
Rental market, 25% of the suburb score
| Input | Weight | Better when |
|---|---|---|
| Modelled rental yield | Weight 50% | Better when Higher |
| Rental-listing count | Weight 7.5% | Better when Higher |
| Renter ratio | Weight 7.5% | Better when Higher |
| Indicative gross yield | Weight 10% | Better when Higher |
| Asking-rent change · 12 months | Weight 7.5% | Better when Higher |
| Asking-rent change · 60 months | Weight 7.5% | Better when Higher |
| Vacancy rate | Weight 10% | Better when Lower |
Liquidity, 20% of the suburb score
| Input | Weight | Better when |
|---|---|---|
| Median time on market | Weight 18.37% | Better when Lower |
| Sales count · 1 month | Weight 4.59% | Better when Higher |
| Sales count · 3 months | Weight 4.59% | Better when Higher |
| Sales count · 6 months | Weight 4.59% | Better when Higher |
| Sales count · 12 months | Weight 4.59% | Better when Higher |
| Sales turnover | Weight 10.2% | Better when Higher |
| Listing count · 12 months | Weight 16.33% | Better when Higher |
| Auction-listing count · 12 months | Weight 8.16% | Better when Higher |
| Stock on market | Weight 18.37% | Better when Lower |
| New-listing ratio | Weight 10.21% | Better when Lower |
Stability, 15% of the suburb score
| Input | Weight | Better when |
|---|---|---|
| Modelled value uncertainty | Weight 16% | Better when Lower |
| Dwellings with a modelled value | Weight 10% | Better when Higher |
| Repeat-sale price consistency | Weight 16% | Better when Lower |
| Owner-occupier ratio | Weight 9% | Better when Higher |
| Average hold period | Weight 9% | Better when Higher |
| Renter ratio | Weight 5% | Better when Higher |
| Government-owned ratio | Weight 5% | Better when Lower |
| Median equity ratio | Weight 20% | Better when Higher |
| Total properties | Weight 5% | Better when Higher |
| Repeat-sales count · 12 months | Weight 5% | Better when Higher |
Risk, 15% of the suburb score
| Input | Weight | Better when |
|---|---|---|
| New-property sale concentration | Weight 15% | Better when Lower |
| New-listing ratio | Weight 14% | Better when Lower |
| Listing-volume change · 1 month | Weight 5.33% | Better when Lower |
| Listing-volume change · 3 months | Weight 5.33% | Better when Lower |
| Listing-volume change · 12 months | Weight 5.34% | Better when Lower |
| Stock on market | Weight 12% | Better when Lower |
| Vacancy rate | Weight 12% | Better when Lower |
| Government-owned ratio | Weight 8% | Better when Lower |
| Sales-volume change · 1 month | Weight 4.33% | Better when Higher |
| Sales-volume change · 3 months | Weight 4.33% | Better when Higher |
| Sales-volume change · 12 months | Weight 4.34% | Better when Higher |
| Modelled value uncertainty | Weight 6% | Better when Lower |
| Dwellings with a modelled value | Weight 4% | Better when Higher |
6. What can a suburb score not tell you?
A score compares a suburb with other suburbs of its state and home type only. It says nothing about one property: its condition, comparable sales, contract, finance or tax.
It does not change a property's PropRetire value. What does market evidence add? says how market data is used elsewhere.