You typed your own company name into ChatGPT and got nothing. Then you asked it for the best HVAC company in your city and it named three competitors, including one that has been in business four years to your twenty. That combination feels like a bug. It is not. It is almost always a diagnosis problem: ChatGPT answers HVAC questions through two separate retrieval systems, and nearly every article telling you how to fix this addresses only one of them.
The advice you have probably already found says to go claim your Foursquare listing, because Foursquare supplies 60 to 70% of ChatGPT's local results. That number is real research, badly aged. Below is where it came from, what replaced it, and the actual two-path diagnostic to run before you spend a dollar on this.
Two ChatGPTs, two reasons you are missing
Ask ChatGPT "who does mini split installation in Hamilton" and you often get a scannable list of businesses with names, ratings, hours and a map. Ask it "should I repair or replace a 16 year old furnace, and who in Hamilton does that work" and you tend to get prose with inline links to articles and company pages.
Those are two different machines.
The places path produces the business card. It is grounded in structured local data that OpenAI licenses: names, categories, addresses, hours, ratings, photos. You do not get into that output by writing better website copy. You get in by existing, completely and correctly, inside the datasets being licensed.
The web answer path produces the prose. It retrieves and cites live web pages, and its candidate pool is overwhelmingly shaped by Bing's index. Seer Interactive's analysis of 500 ChatGPT citations across 100 queries found 87% matched Bing's top organic results, against a 56% match for Google where the median rank of a cited page was 17. That is the path our guide to ranking on ChatGPT covers in depth.
Almost every "why isn't my business in ChatGPT" article collapses these into one story and hands you a single checklist. That is why the advice so often does not work: contractors apply a places-path fix to a web-path problem, see nothing change, and conclude the whole channel is nonsense.
Tip
Before fixing anything, write down the exact prompt that failed. If the answer you got contained business cards with ratings and hours, you have a places-path problem. If it was paragraphs with links to web pages, you have a web-path problem. The fixes barely overlap.
The Foursquare advice is fifteen months stale
This is the part worth reading carefully, because it is currently the single most repeated piece of HVAC AI-search advice online, and it is being sold to contractors as the fix.
The claim: 60 to 70% of ChatGPT's local results come from Foursquare's city guide listings. You will find it in the top two Google results for this exact question, stated flatly, with the recommendation to go claim your Foursquare listing first.
Steady Demand traced the provenance. On 5 May 2025, Spanish SEO consultant Natzir Turrado ran 50 prompts across five Spanish cities, inspecting ChatGPT's raw JSON rather than the rendered answer. His finding: 60 to 70% of the businesses ChatGPT displayed in first place came from Foursquare. That is a real measurement. It is also five Spanish cities, one country, and first position only.
Nine days later a marketing blog restated it as "between 60% and 70% of local results on ChatGPT come from Foursquare." No geography. No first-result-only. No sample size. Of the eight downstream repetitions Steady Demand traced between May 2025 and June 2026, exactly one kept any hedge, an 87.5% caveat-stripping rate. Along the way the number picked up a comparison to Google Business Profile and Yelp that appears nowhere in the original research.
Then they tested it. 2,880 prompts across 12 verticals and 12 US markets, deliberately weighted toward restaurants, bars, coffee shops and hotels where Foursquare's data is strongest, with plumbers and auto repair kept in as unfavourable controls. The result across 2,879 successful runs on ChatGPT's main product surface:
| Provider | Cited | Retrieved | Business-card grounding |
|---|---|---|---|
| Yelp | 1.04% | 2.08% | 95.83% |
| TripAdvisor | 13.55% | 20.70% | 28.90% |
| OpenTable | 1.70% | 3.58% | 16.88% |
| Apple Maps | 0.14% | 0.97% | 0.00% |
| Foursquare | 0.00% | 0.00% | 0.00% |
Foursquare was the only major local-data provider out of ten checked that measured exactly zero everywhere. An independent cross-check on a different API surface, 1,728 more prompts, found a single Foursquare citation, a 0.06% share whose 95% confidence interval tops out at 0.33%.
They also tested the obvious rebuttal, that Foursquare might ground answers invisibly without being cited. Across 137 market-and-category combinations, the businesses ChatGPT actually named resembled Google's result set more than Foursquare's (7.5% versus 5.7% mean overlap, p = 0.008). The hidden-influence story, if anything, points at Google.
Watch out
If an agency's HVAC AI-search pitch leads with the Foursquare number, ask them for the sample size, the country, and the collection date. The honest answer is 50 prompts, Spain, May 2025, first position only. That is the entire evidentiary base for advice being sold to North American contractors in 2026.
None of this means Foursquare is worthless. Claiming the listing takes twenty minutes and its data still flows into parts of the mapping ecosystem. It means you should stop treating it as the lever.
What actually holds the places slot now
On 23 July 2026, Yelp licensed its reviews, photos and business data to OpenAI. Reported first by Axios and covered by MarTech and Search Engine Land, the deal put roughly 330 million reviews and more than 8 million business listings behind ChatGPT's local answers. It is non-exclusive, so Yelp continues licensing the same data to Apple Maps, Bing and Alexa.
That timing explains the measurement. The Yelp deal landed four weeks before the August 2026 data collection, and Yelp turned up attached to 95.83% of ChatGPT's structured business cards. The number barely moves by category: 93.75% for hair salons, and 97.92% for plumbers, the closest analogue to HVAC in that sample and one that was deliberately included as an unfavourable control.
For an HVAC owner, the practical translation is blunt. A thin, unclaimed or category-vague Yelp profile is now a hole in ChatGPT's business card for your company, not merely a neglected directory entry.
The deal carries a second detail most coverage skipped past. Yelp's Request a Quote is being brought into ChatGPT for local service searches, which means a homeowner can ask for an HVAC company and submit a quote request without ever leaving the chat. That is a lead that never touches your website, never fires your analytics, and never shows up in any attribution report you own. It arrives as a Yelp quote request, and if your team treats Yelp quote requests as low-priority spam, you will lose these while insisting AI sends you nothing. The same blind spot we mapped in how to track where your leads come from applies here with a new source attached.
Stop checking once
Nearly every audit method you will find online says: ask ChatGPT for the best HVAC company in your city and see if you appear. That method is close to worthless, and one practitioner in r/GrowthHacking put the reason more precisely than any vendor blog has:
"Worth pinning down given the non-determinism: ChatGPT can hand back a different list each run, so one query per business is basically a coin-flip sample. If you re-ran each city 15-20 times and reported a hit rate, that 72% gets really hard to argue with. Same logic as polling."
He was critiquing a study of 500 local businesses across plumbing, HVAC, dentistry, electrical and landscaping that found 72% did not appear in AI search at all, and reported that Google Maps ranking had almost nothing to do with which ones did. A companion run on 200 businesses across six cities found only 28% appeared in at least one AI result.
The correction matters more than the headline numbers. Run your prompt 10 to 20 times, each in a fresh chat, and record the fraction of runs that name you. Appearing in 4 of 20 runs is not the same condition as appearing in 0 of 20. The first is a ranking problem you can improve. The second is an absence problem, and absence is usually a data problem on the places path.
Do the same per engine rather than blending into one score. As one operator building local AI tracking noted after scanning a single category across six engines, a business at 13% overall inclusion can be strong specifically in ChatGPT while another at 30% overall is concentrated almost entirely in Perplexity. A blended "AI visibility percentage" hides exactly the thing you need to act on.
We run this as a measured hit rate across ChatGPT, Perplexity and Google AI, not a single screenshot, and we tell you which of the two paths is actually failing for your company before recommending a single fix.
The 2 AM furnace story is the wrong thing to panic about
Every article on this topic opens the same way. It is 2 AM, the furnace is dead, the house is 52 degrees, and the homeowner opens ChatGPT instead of Google. It is a vivid scene and it is mostly not what the data shows.
Leadhub studied 319 HVAC keywords and found 9.7% triggered AI Overviews overall, but the split is the story: only 0.4% of short-tail keywords against 62% of long-tail keywords. Pew Research Center, watching the actual browsing behaviour of 900 US adults, found the identical shape in Google, with 8% of one and two word searches producing an AI summary versus 53% of searches of ten words or more.
Someone typing "ac repair near me" at 2 AM is very likely not seeing an AI answer at all. They are seeing the map pack, which is why ranking in the Google map pack remains the higher-value work for emergency demand.
The searches genuinely exposed to AI are the long, considered ones. Whether to repair or replace a 16 year old furnace. Whether a heat pump makes sense in a cold climate. What a mini split retrofit costs on a two storey house with no ductwork. Those are the queries where an AI answer names two or three companies, and they map to your highest-ticket replacement work rather than your $180 emergency diagnostic.
That reframing changes what you fix. Optimizing your Yelp hours field for 24/7 emergency coverage is reasonable housekeeping. It is not where the AI-exposed revenue is.
By the numbers
BrightLocal's 2026 survey of 1,002 US consumers found generative AI jumped from 6% to 45% as a source people use to find and evaluate local businesses in a single year. The channel is real and moving fast. What it is not is a replacement for emergency-intent local search.
A diagnostic you can run this week
Work the paths in order. Do not skip to tactics.
1. Classify the failure. Run your three most valuable prompts 15 times each in fresh chats. Note for each run whether you got business cards or prose, and whether you were named. You now have a hit rate and a path.
2. If the failure is on the places path, audit your presence in the licensed data:
- Claim and complete your Yelp profile. Correct category, every service listed separately, real hours, photos, and enough recent reviews to be a legible entity rather than a stub.
- Complete your Google Business Profile and Bing Places listings. Bing Places matters twice, once as local data and once because Bing's index feeds the other path.
- Fix NAP consistency. One business name, one address format, one phone number, everywhere. Conflicting records are the most common reason a real company reads as unverifiable.
- List services discretely, not as a blob. "HVAC contractor" cannot match "mini split installation in Hamilton." AC repair, AC installation, furnace repair, furnace installation, heat pump service, duct cleaning, thermostat installation and mini split installation are eight separate matchable entries.
3. If the failure is on the web answer path, audit retrievability:
- Confirm you are indexed in Bing, not just Google. Bing Webmaster Tools is free and this takes ten minutes. A surprising number of contractor sites are fully indexed in Google and thinly indexed in Bing.
- Confirm you are not blocking AI crawlers at the CDN or in robots.txt. OpenAI runs separate bots for training, search indexing and live user-triggered fetches. Blanket bot blocking at the edge is a common accidental self-own.
- Add LocalBusiness schema, or the
HVACBusinesssubtype, with each service as its own entity including area served and availability. - Write answer-first pages on the researchy questions above, with specific numbers, because those are the queries that actually trigger AI answers.
4. Fix reviews for extraction, not just for stars. A review saying "great service, fixed our AC" gives a model nothing to work with. One saying the tech arrived within an hour of a 10 PM furnace failure, had heat restored by midnight, and quoted a replacement on an 18 year old unit gives it four separate extractable facts: emergency availability, response time, furnace capability, replacement consultation. Ask customers for the service, the timing and the outcome.
5. Re-measure the same way in 30 days. Same prompts, same 15 runs, same engines. Anything less rigorous cannot distinguish a real improvement from ChatGPT's run-to-run variance.
What nobody can promise you
There is no paid placement in ChatGPT's organic local recommendations, and there is no submission form that guarantees inclusion. Both retrieval paths depend on third-party data and indexes that change without notice, which is exactly what happened here: a genuine May 2025 finding about Foursquare was overtaken by a July 2026 licensing deal, and every page still repeating the old number is now confidently wrong.
Expect weeks rather than days. Licensed local data refreshes on the provider's schedule, and the web path moves when Bing recrawls. Any agency guaranteeing a ChatGPT citation by a date is selling certainty over a system they do not control.
The honest summary for an HVAC owner: find out which path is failing, fix your Yelp and Bing presence before your Foursquare listing, write for the long repair-versus-replace questions rather than the emergency ones, and measure as a hit rate across repeated runs. That sequence is unglamorous, and it is currently the opposite of what the top-ranking advice tells you to do. It is also the sequence our generative search optimization work runs for HVAC clients.