Suburb research

Type a name in Search suburbs and choose it from the list, or select a suburb on the map. The list shows the eight closest matches, each with its result for what the map is coloured by.

Across Australia each suburb is a dot. Zoom in and the dots give way to suburb outlines. The map's legend names each colour. For Overall score the bands are Under 40, 40 to 49, 50 to 59, 60 to 69 and 70 or more. A partial score takes its band's colour with hatching over it. The legend also shows Unavailable.

Filters opens the choices that change the map.

• Home type is Houses or Units.
• Colour by is Overall score, Five-year population change, Sale-price context in the state, Recorded sale activity, Recorded listing activity or Advertised weekly rent. Its help says what the choice measures and what it cannot tell you.
• State or territory keeps one state.
• Show on map adds markers for each Hospital, Government school, Station, Site reporting emissions and Infrastructure project as you zoom in.
• Scores, Market and People each keep the suburbs in the bands you choose. Score completeness keeps a Full score, a Partial score or Unavailable.

Say you want suburbs in Victoria scoring 70 or more. Set State or territory to Victoria and tick 70 or more under Scores. The button reads Filters: 2, and the panel counts the suburbs that match. Clear all removes every filter.

Select a suburb and its card opens. It names the home type and state, such as Units · Victoria. Then come its Overall score, its five dimension scores as bars, and up to three facts: Market gives the recorded sale-price range, People the change in five years, and Services the distance to the closest hospital and school. Open analysis opens the full page.

The analysis page has the suburb's name as its title, for one home type. Switch to houses or Switch to units opens the other. The first line gives the profile against the state's peers for that home type.

Current relative score gives the Overall score and its five dimensions. The overall score's help gives the date it compares on and names the strongest and weakest dimensions. Where the inputs with evidence carry under three quarters of the weighting, Data behind the score leads with Moderate, or with Limited under half.

These are the map's bands, so a score of 62 sits in the map's 60 to 69 band and reads Positive. A partial score reads Partial market profile, whatever its number.

Each dimension reads where it sits against its peers.

• Under each position is its trend between the latest two monthly scores. A rise of 3 or more reads Improving, a fall of 3 or more reads Softening, and anything less reads Steady.
• The highest dimension at 65 or more leads the profile, such as Growth leads. Below 65, none leads.
• Each dimension's help lists its inputs, whether each is better higher or lower, and the suburb's score out of 100 on each.

Say Growth scores 68 this month and 64 last month. It reads Above peers and Improving. If no other dimension reaches 68, the page reads Growth leads.

Opportunities and watch-outs come from inputs in the top or bottom 30% of peers, where at least half the peers have evidence for that input. Related inputs share one sentence, such as Homes sell faster than in most peers. Up to four of each show, led by those furthest from the middle once weighted. Where none stands out, the page says No input stands out from peers as an opportunity.

• PropRetire score history draws the overall and dimension scores month by month. Score movement then lists up to four dimensions that moved 3 or more points, largest first.
• Market evidence gives Market ranges. Each is a range, not one figure: Recorded sale-price range, Area model-value range, Asking-rent range, Indicative gross yield, Typical time to sell, Stock on market, Annual value growth, 5 years, and Vacancy, 12 months. Rent and supply and Published market movement follow.
• Area context maps the closest services and gives connectivity. People and homes gives the population history, housing tenure, home types, resident ages, household types and the unemployment rate.

Download PDF saves the analysis. A Business account can also send it to a client.

On a suburb's card, select Add to comparison. The suburb is outlined on the map and listed under the search. The button shows only when the suburb can join. A suburb can join when it has a result for the same period as the first suburb, for what the map is coloured by.

Compare suburbs at the top stays off until two are added. Then it reads Compare 2 suburbs. A comparison holds up to four suburbs of one home type, so changing Home type empties it.

Say you add two Victorian unit suburbs. Compare 2 suburbs opens Suburb comparison. Suburbs compared lists each, with Remove beside it, and Add another suburb takes you back to add a third or fourth.

• Score comparison sets the scores side by side, then each suburb's opportunities and watch-outs.
• Market ranges sets each suburb's ranges side by side.
• Published movement gives how each suburb's market ranges moved.
• Local context gives census and area figures, such as unemployment and the socio-economic decile. It does not count towards the score.

Each suburb is scored against its own state's peers. The comparison names no winner. Download PDF saves it.

Each input ranks a suburb against its peers: every suburb in the same state with published homes of the same type in the same month. Suburbs follow the Australian Bureau of Statistics' 2021 suburbs and localities.

An input scores from 0 to 100, and a higher score is always better. The peers with that input are put in order. The one in the least favourable place scores 0, the one in the most favourable place scores 100, and the rest are spaced evenly between. Suburbs with the same figure share the middle of their places.

Say 41 peers have a vacancy rate. Lower vacancy is better, so the suburb with the lowest scores 100 and the one with the highest scores 0. The 21st scores 50. Each place moves the score 2.5 points, rounded to a whole number.

Missing evidence stays unavailable. It never counts as zero.

Evidence builds up from inputs to dimensions to the overall score.

1. An input has enough evidence when at least 20 peers have it, and at least a tenth of all the peers. Say a state has 300 suburbs with published units. An input then needs 30 of them.
2. A dimension scores when its inputs with enough evidence carry at least half its weighting. Its score is the weighted average of those inputs.
3. The overall score is the weighted average of the dimensions that score. It is full when all five score. It is partial when at least three score and together carry 60% of the weighting. Otherwise it is unavailable.

The dimensions carry Growth 25%, Rental market 25%, Liquidity 20%, Stability 15% and Risk signals 15% of the overall score.

Say Growth scores 68, Rental market 50, Liquidity 60, Stability 40 and Risk signals 70. The overall score is 68 × 25% + 50 × 25% + 60 × 20% + 40 × 15% + 70 × 15%. That is 17 + 12.5 + 12 + 6 + 10.5, which is 58.

Now say Stability and Risk signals have too little evidence. The other three carry 70%, so the score is partial. It is (68 × 25 + 50 × 25 + 60 × 20) ÷ 70, which is 4,150 ÷ 70 and rounds to 59. If Growth and Rental market had too little instead, the other three would carry 50%, and there would be no overall score.

Inside a dimension it works the same way. Modelled rental yield is half of Rental market. A suburb with no evidence for it keeps a Rental market score, as the other inputs carry the other half.

A partial score reads with Partial score after it, and its help says Some dimensions have too little evidence to score, so the overall score rests on the others. A dimension without a score reads Unavailable, and the page says it is excluded from the profile.

Each input's weight is its share of its dimension. Better when says whether a higher or lower figure counts in the suburb's favour. Some inputs count in two dimensions.

Growth is 25% of the overall score.

Rental market is 25% of the overall score.

Liquidity is 20% of the overall score.

Stability is 15% of the overall score.

Risk signals is 15% of the overall score. It scores higher when fewer warning signs show.

Vacancy rate is 10% of Rental market and 12% of Risk signals. A suburb with low vacancy scores well on it in both.

A score compares a suburb with its state peers only. It does not rank suburbs across Australia, and it does not forecast returns or recommend a suburb.

It does not change a property's PropRetire value or its Property outlook. It says nothing about one property: its condition, comparable sales, contract terms, planning controls, finance, insurance, ownership, cashflow or tax. What does market evidence add? says how market data is used elsewhere in PropRetire.

• Before the research is published, the page reads Suburb research is not published yet. Your records are unaffected.
• A link to a suburb with no research reads No published research for this suburb, with Suburb research to choose another.
• A card reads Scores for this suburb are not published yet, or This suburb could not be shown. Try again, with Try again.
• No market evidence for the home type in the suburb reads No market evidence is published for this home type in this suburb, so it has no score.
• Too few dimensions reads Too few dimensions have enough evidence for an overall score, which needs at least three that together carry 60% of the weighting.
• Old evidence reads The market evidence is out of date, so no score shows until the next release.
• On the analysis, a panel such as Score unavailable or Market ranges unavailable takes the place of a part that has nothing to show.
• A comparison with one suburb or none reads Add another suburb or No suburbs selected, with Research suburbs.