GEO for Real Estate & Proptech: AI-Powered Property Discovery
When a buyer asks AI where to live, who gets named?
The model names the sites that gave it clean, quotable data — and our check of six proptech homepages on August 15, 2026 found most of them didn't. Compass and Opendoor publish an llms.txt file. Yardi wrote a careful AI crawler policy that blocks scraper bots, then pointed those blocked bots at an llms.txt file that doesn't exist. Roofstock and Matterport shipped zero structured data on their homepages at all.
What we found on six proptech homepages
We fetched each homepage the way our AI crawler check does — raw HTML, robots.txt, and the llms.txt path — then compared what a language model would actually see:
| Site | llms.txt | AI crawler rules in robots.txt | Structured data on homepage |
| Compass | published (v1.0.0, updated 2026-07-06) | none | Organization, WebSite, ContactPoint |
| Opendoor | published (v1.0.0, released 2026-04-19) | none | Organization, WebSite, WebPage |
| Yardi | missing (404) | blocks cohere-ai, Diffbot, Bytespider; allows /llms.txt | WebSite, WebPage, SearchAction, Brand |
| Buildium | missing (404) | none | Organization, WebSite, SoftwareApplication, 25 FAQ Q&A |
| Roofstock | missing (404) | none | none |
| Matterport | missing (404) | none | none |
The quiet gap is Yardi. Its robots.txt, updated July 2026, says it blocks "bad AI training crawlers only" — cohere-ai, Diffbot, and Bytespider get Disallow: / — and then grants each of them Allow: /llms.txt. Somebody read the playbook, then stopped halfway. The permission is there. The file is a 404.
The llms.txt split: consumer platforms get it, enterprise doesn't
The pattern is too clean to be luck. Compass and Opendoor are consumer-first — they answer "how much is my house worth" and "can I get a cash offer" for people who increasingly ask those questions inside ChatGPT and Perplexity. Roofstock, Buildium, and Yardi sell to investors and property managers; Matterport sells 3D capture to real estate pros. The consumer brands treat AI answers as lead generation. The B2B brands treat them as someone else's problem.
That's a miscalculation, because AI search already answers the questions these companies care about: "best property management software for small landlords," "how does Matterport compare to Zillow 3D Home," "is Roofstock a safe way to invest in rental properties." Our GEO statistics across 200+ audited domains shows the average site scores 45/100, and citation goes to whoever ships self-contained answers — not whoever has the biggest brand.
Buildium proves the point from the other side. It has no llms.txt, yet its homepage ships 25 FAQ questions with answers — the exact pattern that gets cited. It's one llms.txt file away from being the cleanest proptech site we tested.
The fix: ship the file, then make listings quotable
- Publish llms.txt this week. It's a text file; there's no build step. List your top 30 pages — home search, rent, sell, calculator, and one page per product line. The llms.txt checker validates the format in seconds. This single step takes you from the Roofstock/Buildium/Matterport tier to the Compass tier.
- Point blocked crawlers somewhere real. If you already maintain AI crawler rules like Yardi does, verify the file you're granting access to exists. A crawler that reads Allow: /llms.txt and hits a 404 won't retry nicely.
- Add RealEstateListing schema to listing pages, not just ItemList. Opendoor's /homes page ships 140 ItemList entries but zero RealEstateListing markup — a search engine reading that page sees a list of links, not a set of properties with price, beds, and baths. The schema checker catches syntax errors before deploy.
- Answer the investor/agent questions in plain text on the page. Overhead, fees, and time-to-close are the facts AI quotes. If they live in a PDF or a JS-rendered tab, the model quotes your competitor's blog instead.
- Keep the FAQ momentum. Buildium's 25-question FAQ block is the strongest citation signal we found in this audit. Extend it to the questions your sales team hears weekly.
The listing page is the citation magnet
Proptech runs on structured data already — listings, prices, square footage, availability. That's exactly what language models quote, and most of it is trapped in formats they can't read. The companies that win AI search in real estate will be the ones that hand the model the facts instead of making it dig. Compass and Opendoor started. Yardi built the gate. The rest haven't started yet.
Run the free GEO audit on your homepage and one listing page today — you'll get the six-dimension score and a fix list ordered by impact. For the mechanics behind how citations actually work, how to get cited by ChatGPT covers the full playbook.