Reddit just beat realestate.com.au in Australian property AI search

01 · The headline number

Real estate is the fifth-most AI-exposed industry in Australia

Real estate sits in the high-exposure quartile alongside Accounting, E-commerce, IT, and B2B services. 50.9% of property-related searches returned a Google AI Overview, putting the vertical roughly 13 percentage points above the national average and just behind the four most AI-exposed industries we measured.

The trigger rate alone isn't the interesting story for property. What stands out is which sources Google's AI reaches for when it writes those answers, and what happens to the AI the moment a buyer adds a suburb to their search. Both numbers reorder the conventional real estate playbook. Portals lose their citation monopoly. Suburb pages, paradoxically, become the safest surface on the internet.

02 · The intent breakdown

Informational intent is overwhelmingly AI-exposed

We split every property query into one of four intents (informational, commercial, transactional, navigational) and measured each separately. Real estate has the steepest intent split of any high-exposure vertical: information queries trigger AIO almost four times more often than navigational ones.

Informational intent at 77.6% is one of the highest reads in our entire dataset, exceeding both Accounting (74.0%) and IT (74.6%). "What is stamp duty", "how does the FHSS scheme work", "what is a building and pest inspection", "how long does settlement take", almost eight in ten of these explainer questions now meet a Google AI summary above the organic list. For property businesses whose blog strategy is built on the explainer post, this is the surface most at risk.

Commercial intent at 28.1% is dramatically lower than the comparable verticals: 14 points below B2B services and almost 20 below Accounting. When an Australian buyer searches "best buyer's agent Sydney" or "compare conveyancing fees", Google's AI defers to the organic results more than three-quarters of the time. This is consistent with the local-intent pattern below, the AI seems to recognise property comparisons as fundamentally local decisions, not summarisable ones.

Transactional intent at 40.0% with 558 queries is a reasonable middle ground. Navigational intent (18.5%) is the cleanest surface left, where brand and login queries still drop the user straight into your funnel.

03 · Mobile vs desktop

Mobile and desktop look almost identical

We split the dataset by device. Real estate is the narrowest mobile–desktop gap of any service vertical we measured, just 1.0 percentage points. Property buyers see almost the same AI exposure regardless of how they search.

The +1.0pp mobile gap is among the smallest in the entire study (compare Legal +7.2pp, Accounting +7.1pp, B2B +4.4pp). Property research seems to be a genuinely device-agnostic activity, buyers do the same kinds of queries on a laptop in the kitchen as they do on a phone on the train. That fits the lifecycle of an Australian property search, which spans weeks or months of cross-device research.

Practical implication: for property businesses, the convenient assumption that "mobile AIO is a different problem to desktop AIO" doesn't hold. Whatever citation strategy you build needs to perform across both devices. The flip side: a mobile-only AIO audit gives you a reasonable read on the whole vertical, which isn't true for accounting or legal firms.

04 · The citation leaderboard

Reddit is the #1 cited domain, ahead of realestate.com.au

This is the most striking finding in the property dataset. Of every AIO citation Google produces on an Australian real estate query, Reddit threads account for 5.9%, more than any other domain. That's ahead of realestate.com.au (4.1%), ahead of every individual agency and franchise, and ahead of every government source.

The single most cited source in Australian property AIOs is a user-generated forum. r/AusFinance, r/AusProperty, r/Sydney and similar subreddits are collectively cited more often than Australia's largest portal. Reddit's content is exactly the format Google's AI prefers: explicit Q&A structure, plain-English answers, personal stories, lived-experience credibility, and a high density of suburb names and price points.

realestate.com.au at #2 (4.1%) is doing fine given it competes with every Reddit thread ever written, but the gap is real and structural. The portal pays a content tax that Reddit doesn't: REA's pages are listing-oriented, and Google's AI struggles to summarise a transactional listing into an answer. Reddit's threads, on the other hand, read like ready-made AIO source material.

The rest of the leaderboard reorders expectations further. YouTube at #3 (2.1%) confirms that video explainers (mortgage walk-throughs, "how to buy your first home" guides, suburb tours) earn real estate citations. Entry Education at #4 is a real estate licensing course , their explainer content on becoming an agent gets cited on a wide range of property career and process questions. Aussie at #5 (a mortgage broker) and ANZ (#15) confirm that finance content sits inside the same citation pool as property content in Google's model.

Wider context: 69.2% of real estate AIO citations point to Australian domains, well above the dataset midpoint (54.9%) and a healthy signal that local ranking signals still carry weight here. The franchise sites in the top 20 (LJ Hooker at #13, plus REIQ, REAA and REBAA from the industry bodies) confirm that brand-name agencies do earn citations, just at a fraction of Reddit's volume.

05 · Local intent

Add a suburb name and the AI vanishes

Across our 18-industry dataset, local-intent queries trigger less AIO than general queries in 17 verticals. Real estate isn't just in that group, it's at the top of it. This is the largest insulation effect in our entire study.

Add "near me", a suburb name, or a city qualifier to a property query and the AIO trigger rate collapses from 58.9% to 21.4%. A 37.5 percentage-point drop , larger than IT Services (-36.0pp), larger than B2B (-33.6pp), more than double the gap in Accounting (-17.7pp).

Why this happens: when an Australian buyer searches "houses for sale Manly", "real estate agents Bondi", or "property prices Brunswick", Google's AI reads the query as a "find a property / find a provider" question. It backs out, hands the result to the local pack and the organic listings, and stays out of the way. The AI is trained to recognise that summarising a localised property search is the wrong service to offer.

Translation for your agency: the suburb-specific service pages every real estate brand has been building for a decade are now more valuable than they were a year ago. "Property management [suburb]", "buyer's agent [suburb]", "real estate agents [suburb]" pages trigger AIO at well under half the rate of your explainer content. They are the cleanest organic surface in the vertical. Build more of them. Make them deeper. Compete for the long tail of every postcode you service.

06 · Page-type safety map

Homepages are safe. Blog content is almost completely overwritten.

We measured AIO trigger rate by what kind of page ranks #1 in the property SERP. The pattern is the most extreme page-type spread of any vertical we looked at: a 66-point gap between the most exposed and least exposed page types.

When a property blog post or "guide to" article ranks #1 for a query, AIO appears 90.3% of the time , among the highest blog-trigger rates we measured anywhere. The explainer-style content most agencies and buyer's agents have been producing for the last decade is, for practical purposes, AI summary fodder. Nine out of ten of those rankings now sit beneath a Google answer that satisfies the query before the click happens.

Homepages at 23.9% are the safest surface in the vertical, meaningfully cleaner than Accounting homepages (18.6% is even cleaner, but Accounting homepages are pure-brand pages; property homepages typically include search functionality and listings). Property homepages usually load with a listings search widget, geographic scope, and an explicit transactional purpose, exactly the "I'm not summarisable" signals the AI respects.

Location pages at 37.2% are the second-safest surface, consistent with the local-intent pattern in the previous section. Suburb landing pages, "property management [city]" pages, and area-targeted service pages run at less than half the trigger rate of your blog content. The blog/homepage gap of 66 percentage points is the largest in our entire study.

Our view: the page-type spread for real estate is the most extreme we've measured. Your content stack is bifurcated. The half that ranks for explainer queries is being replaced by AI; the half that ranks for search-and-transact queries is mostly being left alone. Re-prioritise accordingly.

07 · What to do about it

Five actions we'd take if we ran an Australian real estate business

1. Write content that reads like a Reddit answer, not a brochure. Reddit (5.9% citation share) outranks every portal and every agency for a reason. Its threads are explicit Q&A, plain-English, dated, suburb-tagged, and answer the asker's exact question in the first paragraph. Restructure your "guides" the same way: lead with the answer, then the context. Add real prices, real years, real suburbs. Strip out the SEO-padding paragraphs. Generic "guide to buying your first home" content is now AI training data, not click bait.
2. Build a suburb-specific landing page for every postcode you service, and make them deep. Location-qualified queries trigger AIO at 21.4% vs 58.9% for general queries. A 37.5-point safety margin, the largest of any vertical in our study. "Property management [suburb]", "buyer's agent [suburb]", "real estate agents [suburb]" pages are now your most defensible SEO surface. Most agency sites have one or two suburb pages with a paragraph of generic copy. The opportunity is to build twenty, with real recent sales data, local market commentary, and a clear call to action, for every postcode you actually work in.
3. Treat YouTube as your second content channel, not an afterthought. YouTube is the #3 cited domain in property AIOs (2.1%, 615 citations). Walk-through videos of suburbs, "how settlement works in Australia" explainers, mortgage broker interviews, and buyer's-agent breakdowns earn AIO citations in a way text content increasingly can't. The production cost is real, but the marginal click value of a YouTube citation is higher than a Reddit one because you control the channel and the call to action.
4. Reconsider portal listing spend in light of the citation data. realestate.com.au is the #2 cited domain (4.1%) and remains a transactional must-have for listings. But its share of the AI citation pool is significantly smaller than its share of agency marketing budgets. If you're spending more on listing portal fees than on suburb-specific content and direct organic presence, the AIO data suggests rebalancing. The portals own listings; the AI answers everything else.
5. Build out career, training, and education content for the citation gap nobody is fighting for. Entry Education's licensing course pages are the #4 cited domain in our dataset (1.9%). Search platforms (Seek combined at 2.6%, Indeed at 1.1%) and industry bodies (REIQ, REAA, REBAA) appear repeatedly in the top 20. The Australian property industry's recruitment and education content is being cited alongside its consumer content because Google's model doesn't separate the two cleanly. Strong career pages, "how to become an agent" content, and industry certification explainers earn citations agencies currently leave on the table.