AI SEO for real estate agencies.
When your customers ask ChatGPT, Gemini or Perplexity who to go to, the answer names a handful of businesses. This page is how your agency becomes one of them — the exact queries, signals and pages that decide it.
That’s the whole game: being the name inside the answer.
What your customers are asking AI right now
Real query patterns for real estate agencies. Every one of these ends with an AI naming businesses — the only question is whose.
- “best real estate agent [suburb]”
- “real estate commission [state]”
- “property appraisal near me”
- “how to choose a selling agent”
- “property manager fees [city]”
Why real estate agencies win or lose in AI answers
Commission is a question many agencies avoid
"What do agents charge" is a common vendor question that many agencies answer vaguely. Publishing the structure and inclusions plainly creates useful source material for an often-avoided topic.
Suburb data pages are citable authority
Median prices, days on market and sold results by suburb can make strong data pages. An agency that maintains accurate suburb pages may earn repeat citations as a local source.
Vendors choose agents, not agencies
"Best agent in [suburb]" is a person query. Agent profiles with track records — sales, suburbs, tenure — make each agent a verifiable entity engines can actually recommend.
The exact signals that get a agent named
- 1RealEstateAgent schema (the real schema.org type) with office and agent details
- 2Commission and fees explained in plain text — useful differentiation in an often-avoided topic
- 3Suburb market pages with real data, updated and dated
- 4Agent profile pages: sales history, suburbs, years — person-entity verification
- 5Google Business Profile AND Bing Places per office; reviews naming agent and outcome
The generic version of this list, with difficulty ratings, is in our 20-step guide — the list above is what it looks like for your trade specifically.
Question pages that win for real estate agencies
LLMs quote pages that answer one question plainly. These are the ones worth owning in your area:
- "Commission and fees, plainly" — the forbidden-topic page
- Suburb market pages — median, days-on-market, recent solds, updated monthly
- Agent profiles with real track records
PHK Real Estate
Full AEO treatment on a property business: structured data, consistent listings, question-shaped content and citation building across its rental portfolio.
Before
An Airbnb calendar with gaps; the business reported being absent from the AI queries it tested at baseline.
After
"After 4 weeks my whole calendar was full." — customer-reported individual experience from a review; not a typical or guaranteed result.
Client-reported results — read the full reviews from these businesses here.
Real estate agencies ask us
How do agents show up in ChatGPT shortlists?
Person-level verification: agent profiles with track records, RealEstateAgent schema, suburb data pages and reviews naming agents. "Best agent in [suburb]" is answered from evidence about people, not agency slogans.
Should we really publish commission?
An agency that publishes useful guidance early can build relevance, but no one owns a query forever. Ranges with inclusions ("typically X–Y% including marketing") answer honestly while preserving room for scope differences.
Suburb pages vs one big area page?
Create separate pages for meaningful suburbs you genuinely serve and can maintain. "[Suburb] median price" and "agents in [suburb]" are suburb-shaped queries, so accurate local pages can build citable authority more effectively than one broad area page.
We do this for other industries too
Ready to strengthen suburb-level visibility?
The $200 audit tests your real customer queries across ChatGPT, Gemini and Perplexity, and hands you the fix list — use it with us or run it yourself.