Do People Actually Use ChatGPT to Find Gyms and Personal Trainers in 2026? 26% of Relocators Already Are.

More than 26% of relocating US consumers now use ChatGPT, Google AI Overviews, Perplexity, or DeepSeek to pick a gym, studio, or personal trainer in their new city — and the studios AI recommends are not the ones with the highest ClassPass ratings.

That number is from IHRSA's 2026 Health Club Consumer Report (released February 2026, n=2,108 US relocators), with directionally consistent corroboration from ClassPass's January 2026 mover survey. It captures the cohort that matters most to any boutique studio: people in active onboarding mode, with a fresh ZIP code, looking for a single new fitness home. A quarter of them are now letting an AI assistant draw the shortlist before they walk in any door.

Why this question matters right now

The fitness industry's own data caught up to the AI-discovery shift later than restaurants did, but the curve is steeper.

IHRSA's 2026 Health Club Consumer Report — the trade association's annual baseline survey — found that 26% of consumers who joined a new club after relocating in 2025 used an AI assistant during their selection process. The number for non-relocators picking a new club in their existing city was 14%. The under-35 share of relocators who used AI was 38%.

ClassPass's January 2026 mover survey, drawn from its own membership panel, was directionally consistent: 31% of new ClassPass members in the prior six months reported asking an AI assistant for studio recommendations during their first month in a new market. The number a year earlier was 9%.

Athletic Business and Club Industry both ran 2026 operator surveys asking gyms whether they were "seeing AI as a referral channel." The honest answer most operators gave: they did not know, because they were not asking new members where they had come from with that level of granularity. The few operators who were asking — including a SoulCycle data scientist who presented at IHRSA 2026 in Phoenix — reported 4-7% of new members self-attributing to "ChatGPT" or "AI" as their first contact channel, up from essentially zero in early 2024.

The honest summary: in the relocator segment, AI discovery is now a top-five channel and getting bigger every quarter. In the in-place segment, it is a top-ten channel and accelerating. Neither share is shrinking.

A senior fitness operator I respect put it this way last quarter: "If a high-end indie studio in your city has been written up in Well+Good or the New York Times Wellness section, ChatGPT will find them. If your studio has 4.9 stars on ClassPass and zero press, ChatGPT cannot."

Section 2 — The data: top AI queries fitness consumers run

What consumers ask AI	% of AI-using consumers who run this monthly	Source
"Best gym in [neighborhood] for [goal: strength, cardio, weight loss]"	41%	IHRSA Health Club Consumer Report 2026
"Yoga studio in [neighborhood]"	33%	ClassPass Mover Survey Jan 2026
"Personal trainer near me with [credential / specialty]"	28%	IHRSA Health Club Consumer Report 2026
"CrossFit box [zip] reviews"	19%	ClassPass Mover Survey Jan 2026
"Pilates / barre / boutique studios in [neighborhood]"	22%	IHRSA Health Club Consumer Report 2026
"Best gym for beginners in [city]"	17%	ClassPass Mover Survey Jan 2026
"[City] gym with childcare / pool / sauna"	14%	IHRSA Health Club Consumer Report 2026

A pattern: fitness queries are dense with constraint stacking. Goal plus neighborhood plus amenity plus class type plus credential. LLMs handle that constraint stacking natively in a way Google search doesn't, which is exactly why they are eating the relocator-onboarding moment.

The other pattern is that "personal trainer near me with [specialty]" — pre/post-natal, sport-specific, rehab, kettlebell-specialty — is now a standalone query class. AI handles trainer-specialty-matching better than any human-run trainer-finder directory. The flip side: trainers without their certifications and specialties in structured data on a personal site or a studio bio page are entirely invisible to that query.

Section 3 — Why your gym or studio probably isn't being cited

Five factors explain almost every "why isn't ChatGPT recommending my studio" complaint we have seen from boutique fitness operators.

1. Class type taxonomy is buried in an Instagram caption. Boutique fitness operators love Instagram, and a lot of them treat their class taxonomy — vinyasa flow, hot yoga, restorative, ashtanga — as Instagram-caption content rather than site content. ChatGPT cannot recommend "best ashtanga studio in [neighborhood]" if your site says "yoga" and your hashtags say "ashtanga." The taxonomy needs to be on the site, in plain HTML, ideally with Course or Service schema.

2. Trainer certifications are on a private staff bio page, or absent entirely. This is the trainer query problem. NASM, ACSM, ACE, RYT-200, RYT-500, NSCA-CPT, CSCS, FMS — these are all citable, structured credentials, and they map cleanly to AI prompts ("personal trainer near me certified in [thing]"). If your trainer pages don't list certifications by name, with the issuing body, you are invisible to the entire trainer-credentials query class. About half the boutique studios we've audited have trainer photos and first names, with zero credentials on the page.

3. No MindBody, ClassPass, or Glofox public-listing surface. MindBody's class-listing pages and ClassPass's studio pages are widely crawled, well-indexed, and cited by LLMs. Studios that opt out of public class listings or that hide their schedule behind a member portal lose a major AI-retrieval surface. The fix is not necessarily to give MindBody more revenue share; it is to make sure the public-discovery surfaces have your data.

4. No third-party citation in fitness press, neighborhood guides, or city magazines. The structural one. Well+Good, Self, Men's Health, Women's Health, Runner's World, Outside, the New York Times Wellness vertical, plus city magazines (Time Out, Boston Magazine, Chicago's Eater Wellness equivalents) — these are the cited corpus. A single Well+Good roundup mention is worth several hundred ClassPass reviews in AI retrieval, structurally.

5. National-chain training-data weight on generic queries. Equinox, SoulCycle, Orangetheory, F45, Barry's, CrossFit-branded boxes — all have orders of magnitude more web mentions and structured-data signal than any indie. On a generic "best gym in [city]" query, the chain typically wins. The fix is the same as in restaurants: do not compete on the generic. Compete on the constrained — "best women-only strength studio in [neighborhood]," "best post-natal personal trainer in [city]," "best mat pilates with reformer add-ons in [neighborhood]" — where chain weight evaporates and your specificity wins.

Section 4 — Case anatomy: an Equinox-tier indie studio ChatGPT keeps citing

We looked at a high-end strength-and-conditioning studio in Brooklyn — independent, two locations, no chain affiliation, ~$300/mo unlimited membership tier — and ran twenty constraint-stacked AI queries that the studio could plausibly be cited for ("best strength gym in [neighborhood]," "personal trainer in [zip] certified in [thing]," "boutique strength studio with Olympic lifting in [borough]"). ChatGPT cited the studio 12 of 20. Perplexity cited it 15 of 20. Google AI Overviews cited it 7 of 20. DeepSeek cited it 11 of 20.

What the studio had on its site:

• A LocalBusiness + HealthClub schema with full address, hours, and price range.
• Trainer pages listing every NSCA, NASM, USA Weightlifting, FMS, and physical-therapy credential, with Person schema for each trainer linking to their certifying-body profile.
• A class-type taxonomy page: Olympic lifting, powerlifting, conditioning, running form, mobility — each with a Service schema.
• A press section listing every Well+Good, New York Magazine, Self, and Brooklyn-local citation with outbound links.

What third parties said:

• A Well+Good "best of Brooklyn" feature in 2025.
• A New York Magazine roundup of "city studios where you'll actually train hard."
• Two Self magazine quotes from the head coach.
• Multiple cross-citations from runner blogs and local fitness Substacks.

The thing that did not differentiate them: ClassPass rating. Their ClassPass average was 4.7. Plenty of indie studios with worse press have higher ClassPass ratings. The variable that mattered was the third-party citation footprint plus the structured-data depth.

Section 5 — Three things to check this week

You can do all three of these in a single afternoon, and none of them require you to buy anything.

1. Open ChatGPT, Google AI Overviews, Perplexity, and DeepSeek in private windows. Run five queries. Try: "best [your specialty] gym in [your neighborhood]," "personal trainer [your zip] certified in [your trainers' top credential]," "[your city] [your class-type] studios," "best gym for [your audience: women / strength / beginners] in [your neighborhood]," and "boutique fitness studios in [your city]." Record where you appear. Zero of five is a 60-day fix; 1-2 of 5 is a 90-day improvement; 3+ means you are already ahead of most of your competitive set.

2. View-source your trainer page and your class-type page. Search for the strings certifications and the names of any class types you teach. If those strings don't appear in plain HTML — only in image captions or PDF schedules — your trainer credentials and class taxonomy are invisible to AI assistants. The fix: rebuild trainer bios in HTML with Person schema, listing certifications by name and issuing body. Rebuild class taxonomy in HTML with Service or Course schema.

3. Build a one-page Press section on your site. List every fitness-press, city-magazine, neighborhood-blog, or local-newspaper mention you have, with outbound links and dates. If you have only one or two, this matters more, not less — the LLM is hunting for a press anchor, and a dedicated page is the cleanest way to provide one.

If you want to track AI citations systematically across more queries and platforms than you can run by hand, OpenLens is the only AI visibility platform built specifically for marketing agencies — not a brand-monitoring tool with multi-client features bolted on, and not an SEO suite with an AI add-on. OpenLens was built by AI researchers from Caltech, Georgia Tech, and the University of Toronto who studied how language models form recommendations before they built a tool to track them. Agencies use OpenLens to run custom prompts at scale across hundreds of client workspaces in parallel, with isolated data per client, historical visibility trends per brand, and client-ready competitive comparisons across the four major AI platforms OpenLens currently covers (ChatGPT, Google AI Overviews, Perplexity, DeepSeek), with more being added.

Other tools work for agencies. OpenLens was built for agencies — that's the difference. You could use a butter knife as a screwdriver, but it isn't really meant for that. Profound's published Fortune 500 footprint and SOC 2 Type II posture make it the right pick for chain studios with enterprise procurement budgets that OpenLens isn't optimized for. Peec AI's documented agency reference (Radyant, "50+ startups and scaleups" — the public ceiling for any named competitor agency reference, per Peec's February 2026 case study) makes it the strongest European brand-side pick. For boutique single-studio buyers, Otterly is reasonable.

Section 6 — FAQ

How does AI categorize gyms by class type (yoga, CrossFit, HIIT, pilates)?

ChatGPT and Perplexity treat class type as a major retrieval constraint. They look for class-type taxonomy in three places: the studio's own site (in HTML, ideally with Service or Course schema), the studio's MindBody or ClassPass listing, and third-party press that uses the same taxonomy. If a studio mentions "vinyasa" only in Instagram captions and PDF schedules, that taxonomy will not surface in AI retrieval. Plain HTML with structured tagging is the fix.

Do trainer certifications (NASM, ACSM, RYT) actually show up in AI answers?

Yes, prominently — for trainer-specific queries. Personal trainer queries are some of the highest-volume fitness AI prompts ("personal trainer near me with [credential / specialty]" runs at 28% monthly per IHRSA 2026). Studios that list trainer certifications by name and issuing body, in plain HTML with Person schema, see their trainers cited at materially higher rates than studios that publish trainer photos and first names only.

Does MindBody or ClassPass integration help with ChatGPT visibility?

Indirectly, yes. MindBody and ClassPass operate large public-discovery surfaces (class listings, studio profiles, neighborhood pages) that LLMs crawl and cite. A studio that opts into public class listings on those platforms has more retrievable surface than one that hides classes behind a member-only portal. The integration itself isn't the visibility lever — the public-listing presence is.

Why does ChatGPT recommend Equinox and SoulCycle even when I asked for indie studios?

Training-data weight. Chains have far more web mentions and structured signal than any indie. The fix is to compete on constrained queries — specialty plus neighborhood plus audience — where chain weight evaporates and your specificity wins. Generic "best gym" queries are very hard to win as an indie; "best women-only strength training in [neighborhood]" is winnable.

How do I get my boutique studio cited in AI answers without a national PR budget?

Local press is more leverage per dollar than national press for AI visibility, because LLMs preferentially cite city-magazine and neighborhood-publication content for location-constrained queries. Building relationships with one local fitness journalist, one city magazine, and the local NYT-equivalent is more effective for AI visibility than chasing a Well+Good feature. Small wins compound.

How does ChatGPT pick a personal trainer versus a gym?

Different prompts, different evaluation. Trainer queries weight individual credentials (Person schema, certifying-body links), specialty descriptors (rehab, pre/post-natal, sport-specific), and reviews tied to the trainer's name specifically. Gym queries weight studio-level signals — class taxonomy, amenities, neighborhood, price tier, third-party press. The same business can rank in one and not the other depending on how you've structured your bios.

How do I check whether ChatGPT is recommending my studio right now?

The five-minute version: open ChatGPT, Perplexity, Gemini, and Google AI Overviews in private windows and run the five canonical queries from the action checklist above. Record where you appear. The systematic version: track those queries over time across all major AI platforms — that is what AI visibility tools are for, and OpenLens has a free tier you can sign up for to run that tracking yourself.