Original research · 2026-07 edition

AI SEO Statistics: Crossfit Gym (2026-07 edition)

15 questions · 45 AI responses · 3 models · measured 2026-07-04

The question bank

The questions we tested — sampled from real buyer journeys in crossfit gym.

Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.

I'm bored with my standard treadmill routine and want more variety, how exactly does a CrossFit membership work differently than a regular gym?
Can I learn the Olympic lifts at home using YouTube, or is it worth paying for a coach at a local box?
What specific certifications should I ask about when vetting the head coach at a CrossFit affiliate?
Why does a CrossFit membership cost $150 to $200 a month compared to $20 at a big box gym?
CrossFit vs. functional HIIT studios: which one is better if my main goal is building strength rather than just burning calories?
How do I find a gym that focuses more on longevity and technique rather than just the competitive leaderboard stuff?
What are some red flags in a trial class that suggest the gym might have an unsafe culture or poor programming?
I have a beach vacation in 8 weeks and need to get in shape fast, is CrossFit too intense to start as a total beginner?
Show all 15 questions
I've heard people get rhabdo or bad back injuries from CrossFit, how do I know if a gym's programming is actually safe?
What does a typical 60-minute class look like from the warm-up to the actual workout of the day?
Do I need to invest in lifters, hand grips, and a jump rope before I even sign up for my first month?
Is it standard for gyms to require a multi-week foundations or 'on-ramp' course before letting me join regular classes?
I'm pretty introverted and just want to workout, is the 'community' aspect of these gyms mandatory or can I just do my own thing?
Am I too old to start CrossFit at 45 if I have some minor knee issues and haven't exercised in a decade?
How many days a week do I realistically need to attend to justify the high monthly cost and see actual physical changes?

Model by model

16-point average divergence: which AI you ask changes the answer.

The divergence index is the average gap between the most and least likely model per behavior. Higher = the models disagree more about crossfit gym buyers.

Behavior rates across 15 crossfit gym buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional47%33%20%73%
Suggests DIY first7%7%0%87%
Names specific providers7%20%33%60%
Gives price or cost info7%7%20%73%
Tells to check reviews7%0%0%93%
Tells to verify credentials13%27%7%73%
Mentions case studies / portfolio0%0%0%100%
Mentions local proximity7%0%0%93%
Gives selection criteria47%67%33%53%
Warns about red flags13%33%20%80%
Asks a clarifying question47%60%0%20%
Recommends multiple quotes0%0%0%100%

By model

How each assistant handled Crossfit Gym questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same crossfit gym questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 46.7% (ChatGPT) down to 20% (Gemini), a 27-point gap on an identical question set.

Across the 15 crossfit gym answers it produced, ChatGPT recommended hiring a professional in 46.7% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 6.7% of answers (about 0.3 distinct providers per answer) and included price or cost information 6.7% of the time. ChatGPT asked a clarifying question before answering in 46.7% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 13.3%, averaging 570 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 6.7%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 crossfit gym answers it produced, Claude recommended hiring a professional in 33.3% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 20% of answers (about 0.7 distinct providers per answer) and included price or cost information 6.7% of the time. Claude asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 26.7%, averaging 302 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 crossfit gym answers it produced, Gemini recommended hiring a professional in 20% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 33.3% of answers (about 0.9 distinct providers per answer) and included price or cost information 20% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 6.7%, averaging 239 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 33.3% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a crossfit gym buyer to a professional (46.7%) and Gemini the least (20%). ChatGPT produced the longest answers, at 570 words on average. Specific providers were named most often by Gemini (33.3%) — even there, roughly one answer in 3 carried a name.

Where they disagree

The behaviors where the choice of model changes the answer.

The divergence index for this study is 16.3 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a crossfit gym buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 60% (Claude) — a 60-point spread.
  • Gives selection criteria: from 33.3% (Gemini) to 66.7% (Claude) — a 33-point spread.
  • Recommends hiring a professional: from 20% (Gemini) to 46.7% (ChatGPT) — a 27-point spread.
  • Names a specific provider: from 6.7% (ChatGPT) to 33.3% (Gemini) — a 27-point spread.
  • Tells the buyer to verify credentials: from 6.7% (Gemini) to 26.7% (Claude) — a 20-point spread.

The widest single gap — asks a clarifying question, 60 points — means a crossfit gym buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the crossfit gym market.

Where they agree

The points of near-consensus in Crossfit Gym.

On other behaviors the three models move almost in lockstep — the points of near-consensus for crossfit gym, where all three landed within a few points of each other:

  • Mentions case studies or portfolio: 0% across all three models.
  • Recommends multiple quotes: 0% across all three models.
  • Suggests a DIY approach first: 0%–6.7% across all three (a 7-point spread).
  • Tells the buyer to check reviews: 0%–6.7% across all three (a 7-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions case studies or portfolio" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (20%).

Every behavior, measured

All twelve coded behaviors for Crossfit Gym, averaged across the three models.

The behaviors AI models reproduce most often for crossfit gym are gives selection criteria (48.9% on average), asks a clarifying question (35.6%) and recommends hiring a professional (33.3%); the rarest are recommends multiple quotes (0%), mentions case studies or portfolio (0%) and mentions local proximity (2.2%). Each figure below is the share of a model's 15 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:

  • Gives selection criteria: 48.9% on average (ChatGPT 46.7%, Claude 66.7%, Gemini 33.3%) — a 33-point spread.
  • Asks a clarifying question: 35.6% on average (ChatGPT 46.7%, Claude 60%, Gemini 0%) — a 60-point spread.
  • Recommends hiring a professional: 33.3% on average (ChatGPT 46.7%, Claude 33.3%, Gemini 20%) — a 27-point spread.
  • Warns about red flags or scams: 22.2% on average (ChatGPT 13.3%, Claude 33.3%, Gemini 20%) — a 20-point spread.
  • Names a specific provider: 20% on average (ChatGPT 6.7%, Claude 20%, Gemini 33.3%) — a 27-point spread.
  • Tells the buyer to verify credentials: 15.6% on average (ChatGPT 13.3%, Claude 26.7%, Gemini 6.7%) — a 20-point spread.
  • Gives price or cost information: 11.1% on average (ChatGPT 6.7%, Claude 6.7%, Gemini 20%) — a 13-point spread.
  • Suggests a DIY approach first: 4.5% on average (ChatGPT 6.7%, Claude 6.7%, Gemini 0%) — a 7-point spread.
  • Tells the buyer to check reviews: 2.2% on average (ChatGPT 6.7%, Claude 0%, Gemini 0%) — a 7-point spread.
  • Mentions local proximity: 2.2% on average (ChatGPT 6.7%, Claude 0%, Gemini 0%) — a 7-point spread.
  • Mentions case studies or portfolio: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
  • Recommends multiple quotes: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).

Trust signals

How well the models protect the crossfit gym buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the crossfit gym buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 2.2% of answers on average. Verifying credentials or certifications appeared in 15.6%. Warning about red flags or scams appeared in 22.2%.

On structuring the decision, a selection-criteria checklist showed up in 48.9% of answers on average and a recommendation to gather multiple quotes in 0%. The single least-reproduced protective signal for crossfit gym is "recommends multiple quotes" at 0% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

Referral behavior

Do AI models name Crossfit Gym providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 crossfit gym answers, a specific provider was named in 20% of responses on average — roughly 0.6 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for crossfit gym: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Crossfit Gym questions cover.

The 15 questions behind every percentage on this page were drawn from real crossfit gym (fitness services; buyer hiring decisions for this specific service) buyer journeys. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact crossfit gym question set — not a general prior or a hand-picked subset. The full list is shown earlier on this page; the coded percentages are what those specific questions produced.

How to read this

A note on the numbers.

A percentage here is the share of a model's 15 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-04, the figures describe this specific crossfit gym question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.

Methodology

A controlled snapshot, documented end to end.

15 standardized buyer questions per industry, one response per model per question (ChatGPT (gpt-5-mini), Claude (claude-sonnet-5), Gemini (gemini-3-flash-preview)), collected 2026-07-04, coded against a fixed 12-behavior rubric with human QA. AI outputs vary with model version, location and time — figures describe this sample and window, and are refreshed each edition. Read the full methodology →