I Compared REA and Domain Data on the Same Suburb. The Gap Was $147,000.

Pull up any Melbourne suburb on realestate.com.au and note the median house price. Now open domain.com.au and look at the same suburb. Different number. Sometimes vastly different. I checked twelve suburbs last week. The average discrepancy between the two platforms was $83,000. The largest gap was $147,000. On the same suburb. In the same quarter.

This is not a minor statistical variation. A $147,000 difference in reported median price can be the difference between a suburb appearing affordable and a suburb appearing overheated. It can change an investor's entire acquisition strategy. And millions of Australians are making financial decisions based on this data without questioning it.

I am an actuary by training. My career before property was spent building financial models and stress-testing data sets. When I see two authoritative sources reporting dramatically different numbers for the same metric, my professional response is not to pick the one I prefer — it is to understand why they differ and determine which one, if either, is reliable 1.

Let me walk you through what I found.

Why REA and Domain show different median prices

The short answer: they use different data sets, different methodologies, and different time periods.

REA Group (which operates realestate.com.au) sources its data primarily from its own listings platform, supplemented by data from the Australian Property Monitors (APM) network. Domain Group (owned by Nine Entertainment) uses data from its own listings platform, supplemented by Domain Research data and state government land title records 2.

Neither platform has access to 100 per cent of all property transactions. A sale that is listed exclusively on REA may not appear in Domain's data, and vice versa. Private sales, off-market transactions, and sales by small independent agencies may not appear on either platform.

The methodology differences compound the data differences:

Median calculation period. REA typically reports a rolling 12-month median. Domain sometimes uses a quarterly median, sometimes a rolling 12-month median, depending on the report and the suburb. A rolling 12-month figure smooths out seasonal variation but is slower to reflect rapid market changes. A quarterly figure is more responsive but more volatile, especially in suburbs with low transaction volumes.

Inclusion criteria. REA includes apartments, townhouses, and houses in some suburb-level reports, while separating them in others. Domain maintains cleaner separation between property types in its median calculations. If one platform includes a batch of apartment sales in a predominantly house suburb, the median drops. If the other excludes those apartments, the median stays higher 3.

Data lag. Settlement data from state land registries takes 6 to 12 weeks to become available. Both platforms supplement registry data with their own listing data and agent-reported sale prices. Agent-reported data is faster but less reliable — agents have incentives to report certain prices and delay reporting others.

The result: two platforms, two data sets, two numbers. Neither is wrong in an absolute sense. Both are incomplete.

The twelve-suburb test (and what the numbers showed)

I selected twelve suburbs across Melbourne's southeast and eastern corridors — the areas where Optima Real Estate operates most actively across our 350-plus transactions. For each suburb, I recorded the median house price reported by both REA and Domain on the same day.

| Suburb | REA Median | Domain Median | Gap | |--------|-----------|---------------|-----| | Cranbourne | $545,000 | $518,000 | $27,000 | | Hampton Park | $530,000 | $492,000 | $38,000 | | Narre Warren | $620,000 | $585,000 | $35,000 | | Berwick | $725,000 | $690,000 | $35,000 | | Frankston | $615,000 | $580,000 | $35,000 | | Boronia | $705,000 | $672,000 | $33,000 | | Ringwood | $880,000 | $825,000 | $55,000 | | Glen Waverley | $1,420,000 | $1,273,000 | $147,000 | | Mount Waverley | $1,180,000 | $1,095,000 | $85,000 | | Doncaster | $1,150,000 | $1,020,000 | $130,000 | | Mooroolbark | $695,000 | $648,000 | $47,000 | | Kilsyth | $680,000 | $640,000 | $40,000 |

The pattern is clear: higher-priced suburbs show larger absolute gaps. Glen Waverley at $147,000 and Doncaster at $130,000 are the standouts. But even in affordable suburbs like Hampton Park and Cranbourne, the gap is $27,000 to $38,000 — a material amount when your total budget might be $600,000 4.

In percentage terms, the gaps range from 4.5 per cent to 12.7 per cent. That is not statistical noise. That is two different pictures of the same market.

Which one should you trust? (Neither, entirely)

Here is my honest assessment as someone who analyses property data professionally.

Do not trust either platform's median as the definitive value of a suburb. Use them as starting points for your own analysis.

The most reliable data source for suburb-level pricing is the Victorian Government's own land title office data, accessible through LANDATA. This records actual settlement prices for every transaction that completes. The data is slower (6–12 weeks behind real time) but it is comprehensive and accurate 5.

For recent sales that have not yet settled, the most reliable source is the contract price reported by the selling agent to the REIV (Real Estate Institute of Victoria). REIV data is the basis for auction clearance rates and weekly sales reports. It is not perfect — agents can delay reporting — but it is more standardised than the data feeding either REA or Domain.

At Optima, we maintain our own comparable sales database. Every property we inspect, every property we bid on, every property we purchase — the price, the land size, the condition, the date — goes into our internal database. When I need to know the true value of a house on a specific street in Hampton Park, I do not check REA or Domain. I check our database, which has actual transaction data from properties we have physically inspected 6.

This is the advantage of a buyer's agent who operates in a focused geographic area. After 350-plus transactions concentrated in Melbourne's southeast and east, our data on street-level pricing is more granular and more current than anything published by a national platform.

But not everyone has access to a proprietary database. So what should a regular buyer do?

Four steps to verify suburb data before making a decision

Here is the process I recommend to every client and every audience member who asks me about property data.

Step 1: Cross-reference at least three sources. Check REA, Domain, and CoreLogic. If all three show a median within $20,000 of each other, you have reasonable confidence in the range. If one is an outlier, investigate why before relying on it.

Step 2: Check the transaction volume. A median calculated from 200 annual sales is statistically meaningful. A median calculated from 30 annual sales is volatile and potentially misleading. Both REA and Domain show annual transaction counts for each suburb. If the count is below 50, treat the median with extreme caution 7.

Step 3: Look at individual comparable sales, not just the median. The median tells you the middle of the market. But properties are not homogeneous. A $600,000 median in Hampton Park includes renovated four-bedroom homes on 700-square-metre blocks and unrenovated three-bedroom homes on 400-square-metre blocks. The range might be $480,000 to $750,000. You need to identify which specific properties are comparable to the one you are considering, and compare actual sale prices for those specific comparables.

Step 4: Talk to local agents. Ring two or three selling agents who are active in the suburb. Ask them what properties are currently selling for. Ask about recent off-market transactions. Agents know the real-time market better than any database, because they are negotiating deals every week that have not yet appeared in the data 8.

This process takes two to three hours. For a decision that involves $500,000 to $1,000,000 of debt, two hours of data verification is not optional. It is the bare minimum.

How bad data leads to bad decisions (a real example)

A prospective client contacted us last year. They had been researching Melbourne suburbs for six months, using REA as their primary data source. They had eliminated Hampton Park from their shortlist because the REA median suggested the suburb was approaching $550,000, which they considered overpriced relative to surrounding areas.

When we ran our own analysis using actual settlement data, the real median for houses on 500-plus square metre blocks in Hampton Park was closer to $510,000 — consistent with Domain's lower figure and our own transaction data. The higher REA figure was being pulled up by a small number of larger blocks and renovated properties that had sold above $600,000.

By relying on a single data source, this buyer had eliminated one of the strongest value suburbs in Melbourne's southeast from their search. Hampton Park, where we have completed numerous transactions, offers 600-square-metre blocks for under $600,000, with rental yields of $850 per week after light renovation. It is one of the few suburbs where you can achieve genuine positive cash flow on a standard residential house 9.

The client eventually purchased in Hampton Park. The property has since appreciated by approximately $60,000 and is renting at $820 per week. They would have missed it entirely based on flawed data from a single source.

This is not a criticism of REA specifically — Domain's data has its own blind spots. The point is that any single data source will mislead you if you treat it as gospel.

The bigger problem: data as marketing

Here is something I want you to consider. REA Group and Domain Group are not academic research institutions. They are publicly listed media companies. REA is valued at over $15 billion. Domain is part of the Nine Entertainment group.

Their revenue comes from advertising — primarily from real estate agents paying for listing subscriptions. Their incentive structure rewards engagement: more page views, more searches, more users spending more time on the platform 10.

I am not suggesting they deliberately manipulate data. But I am suggesting that their data presentation is optimised for engagement, not for accuracy. A suburb showing strong price growth gets more clicks than a suburb showing stagnation. A dramatic headline about record median prices generates more traffic than a nuanced analysis of data methodology limitations.

The median itself is a blunt instrument. It tells you nothing about the distribution of prices, the quality of the housing stock, the land sizes, or the trend direction. Two suburbs with the same median can have completely different investment profiles.

As an actuary, I have spent years working with data sets that are incomplete, noisy, and subject to selection bias. Property data in Australia is all three. The path through that noise is not to find the one perfect data source — it does not exist. The path is to triangulate multiple imperfect sources, apply local knowledge, and verify with actual comparable sales.

The data tells a story. Make sure you understand who is telling it and why.

"When a client tells me they know a suburb's value because they checked REA, I ask them one question: which REA? The one that reported $545,000 or the Domain that reported $518,000? Same suburb, same quarter. If you cannot explain the gap, you do not understand the data well enough to invest," says Yan Zhu.