AI SEO Statistics: Fitness (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same fitness questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 55% (ChatGPT) down to 32.5% (Gemini), a 23-point gap on an identical question set.

Across the 40 fitness answers it produced, ChatGPT recommended hiring a professional in 55% of them and suggested a DIY approach first 17.5% of the time. It named a specific provider in 25% of answers (about 1.1 distinct providers per answer) and included price or cost information 17.5% of the time. ChatGPT asked a clarifying question before answering in 52.5% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 32.5%, averaging 472 words per answer. On the remaining cues it told the buyer to check reviews in 17.5%, pointed to case studies or a portfolio in 10%, and framed the choice around local proximity in 42.5%; a selection-criteria checklist appeared in 57.5% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 fitness answers it produced, Claude recommended hiring a professional in 42.5% of them and suggested a DIY approach first 17.5% of the time. It named a specific provider in 37.5% of answers (about 1.5 distinct providers per answer) and included price or cost information 27.5% of the time. Claude asked a clarifying question before answering in 82.5% of cases, warned about red flags or scams in 25%, and told the buyer to verify credentials in 27.5%, averaging 276 words per answer. On the remaining cues it told the buyer to check reviews in 30%, pointed to case studies or a portfolio in 7.5%, and framed the choice around local proximity in 52.5%; a selection-criteria checklist appeared in 70% of its answers and a recommendation to gather multiple quotes in 10%.

Across the 40 fitness answers it produced, Gemini recommended hiring a professional in 32.5% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 57.5% of answers (about 2.5 distinct providers per answer) and included price or cost information 35% of the time. Gemini asked a clarifying question before answering in 15% of cases, warned about red flags or scams in 22.5%, and told the buyer to verify credentials in 20%, averaging 250 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 42.5%; a selection-criteria checklist appeared in 47.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a fitness buyer to a professional (55%) and Gemini the least (32.5%). ChatGPT produced the longest answers, at 472 words on average. Specific providers were named most often by Gemini (57.5%) — even there, roughly one answer in 2 carried a name.

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

• Warns about red flags or scams: 20%–25% across all three (a 5-point spread).
• Mentions case studies or portfolio: 2.5%–10% across all three (a 8-point spread).
• Suggests a DIY approach first: 7.5%–17.5% across all three (a 10-point spread).
• Mentions local proximity: 42.5%–52.5% across all three (a 10-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "recommends multiple quotes" (identical coding in 90% of questions) and least consistently on "asks a clarifying question" (15%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the fitness buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 17.5% of answers on average. Verifying credentials or certifications appeared in 26.7%. Warning about red flags or scams appeared in 22.5%.

On structuring the decision, a selection-criteria checklist showed up in 58.3% of answers on average and a recommendation to gather multiple quotes in 3.3%. The single least-reproduced protective signal for fitness is "recommends multiple quotes" at 3.3% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real fitness services (gyms, personal trainers, studios, wellness) buyer journeys, expanded from 5 seed prompts. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact fitness 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.