How to Get Recommended by ChatGPT

What "getting recommended by ChatGPT" actually means

It means the model names your business inside its answer when a buyer asks something like "who's the best roofer in Fort Lauderdale" — not that you rank on a results page. ChatGPT does not browse a ranked list; it assembles an answer from sources it trusts and can quote. So "getting recommended" is the work of making your business the easiest, most quotable, most verifiable entity for the model to cite. That is a different gate than Google ranking, and most local pages fail it even when their SEO looks fine.

We know that because we measured it. FAME runs a 46-check Herald scan plus an information-gain gate on every page before we ship it. On a recent fleet scan of 9 live local-contractor pages, 5 of 9 passed technical SEO but failed the AI-citation gate — two of them scored 85/100 on technical SEO and only 12/100 on information gain. They were clean, fast, and crawlable, and the model still had no unique fact to lift. That gap is the whole game.

The signals that get a business named

Direct answer: ChatGPT recommends businesses that are defined as clear entities, backed by consistent third-party proof, and saying something specific enough to quote. Concretely, the levers we pull are:

• Entity schema (JSON-LD). LocalBusiness, Service, and FAQ schema tell the model exactly what you are, what you do, and where — name, address, phone, service area, hours, services. Ambiguity is the enemy; schema removes it.
• Fact density / information gain. Real prices, response windows, license numbers, warranty terms, named neighborhoods served. This is what passes our information-gain gate and what the model actually quotes.
  Fact: JSON-LD schema and fact-dense content can lift a business's visibility in AI answers by up to ~40%.
• Consistent citations and reviews. Matching NAP across Google Business Profile, Yelp, BBB, and trade directories, with a steady stream of recent reviews. Inconsistency makes the model distrust the entity and stay vague.
• AI-bot crawlability. robots.txt must allow OAI-SearchBot, GPTBot, and SearchGPT, and an llms.txt file should map your key pages so the crawler finds the quotable facts fast.
• Bing index coverage. ChatGPT browsing leans on Bing's index, so submit your sitemap to Bing Webmaster Tools — not just Google Search Console.
• Answer-first structure. Lead every page with the direct answer, then the detail. Models extract the lead sentence; bury the answer and you don't get cited.

The exact checklist we run

This is the order FAME works a page so ChatGPT will name the business:

1. Add LocalBusiness + Service + FAQ JSON-LD with full NAP, geo coordinates, and service area.
2. Run the information-gain gate: strip generic copy, inject first-hand facts (price ranges, response times, license #, areas served) until the page clears the bar — the step the two 85/100-technical pages skipped.
3. Rewrite answer-first: the buyer's question answered in the first sentence of every section.
4. Verify NAP is identical across Google Business Profile, Bing Places, Yelp, BBB, and the site footer.
5. Build and maintain real reviews; reply to them so the proof reads as current.
6. Open robots.txt to OAI-SearchBot / GPTBot / SearchGPT and publish an llms.txt pointing at the fact-dense pages.
7. Submit the sitemap to Bing Webmaster Tools and confirm indexation.
8. Re-run the 46-check Herald scan and only ship when both the technical and AI-citation gates pass.

How to verify you're actually being cited

Direct answer: test the buyer question in ChatGPT itself and watch your crawl logs. Open ChatGPT logged in with browsing on and ask the real buyer question — "best [your trade] near [your FL city]" — across several phrasings and a couple of nearby cities, because recommendations vary by query and location. Note whether you're named, and whether the model links your site as a source. Then check your server logs for hits from OAI-SearchBot and GPTBot: if those bots aren't crawling you, ChatGPT has nothing of yours to quote, and that's your first fix. Track the named-vs-not result over time as you ship the checklist — that's the only honest scoreboard.

The Florida-local angle

Direct answer: local intent is exactly where getting recommended by ChatGPT pays off, because the buyer asking AI "who should I call in [FL city]" is in-market and the field is thin. Most Florida contractors have decent Google rankings and zero AI-citation readiness — the same pattern as our 5-of-9 fleet scan. That's the opening: a Florida service business that ships entity schema, fact-dense pages, consistent citations, and AI-bot access can be the one ChatGPT names while competitors stay invisible inside the answer.

And the clicks that come back are better —

OpenAI states ads do not influence ChatGPT's answers — paid placement runs on a separate system. To get recommended by ChatGPT, the recommendation is earned through the signals above, which is exactly the checklist FAME runs on every page so the model names you when a Florida buyer asks.