AI SEO Statistics: Physio (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same physio questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 75% (ChatGPT) down to 50% (Gemini), a 25-point gap on an identical question set.

Across the 40 physio answers it produced, ChatGPT recommended hiring a professional in 75% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 5% of the time. ChatGPT asked a clarifying question before answering in 82.5% of cases, warned about red flags or scams in 35%, and told the buyer to verify credentials in 35%, averaging 421 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 25%; a selection-criteria checklist appeared in 42.5% of its answers and a recommendation to gather multiple quotes in 10%.

Across the 40 physio answers it produced, Claude recommended hiring a professional in 60% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 2.5% of answers (about 0 distinct providers per answer) and included price or cost information 5% of the time. Claude asked a clarifying question before answering in 75% of cases, warned about red flags or scams in 22.5%, and told the buyer to verify credentials in 12.5%, averaging 278 words per answer. On the remaining cues it told the buyer to check reviews in 7.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 12.5%; a selection-criteria checklist appeared in 32.5% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 physio answers it produced, Gemini recommended hiring a professional in 50% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 7.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 17.5%, and told the buyer to verify credentials in 5%, averaging 294 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 37.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a physio buyer to a professional (75%) and Gemini the least (50%). ChatGPT produced the longest answers, at 421 words on average. Specific providers were named most often by Claude (2.5%) — even there, roughly one answer in 40 carried a name.

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

• Names a specific provider: 0%–2.5% across all three (a 3-point spread).
• Gives price or cost information: 5%–7.5% across all three (a 3-point spread).
• Mentions case studies or portfolio: 0%–10% across all three (a 10-point spread).
• Gives selection criteria: 32.5%–42.5% across all three (a 10-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "gives price or cost information" (identical coding in 97.5% of questions) and least consistently on "asks a clarifying question" (2.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the physio buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 9.2% of answers on average. Verifying credentials or certifications appeared in 17.5%. Warning about red flags or scams appeared in 25%.

On structuring the decision, a selection-criteria checklist showed up in 37.5% of answers on average and a recommendation to gather multiple quotes in 3.3%. The single least-reproduced protective signal for physio 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 physio (healthcare 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 physio 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.