AI SEO Statistics: Outpatient Rehab Center (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same outpatient rehab center questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 66.7% (ChatGPT) down to 40% (Gemini), a 27-point gap on an identical question set.

Across the 15 outpatient rehab center answers it produced, ChatGPT recommended hiring a professional in 66.7% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 6.7% of answers (about 0.2 distinct providers per answer) and included price or cost information 6.7% of the time. ChatGPT asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 13.3%, averaging 435 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 6.7%, and framed the choice around local proximity in 40%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 13.3%.

Across the 15 outpatient rehab center answers it produced, Claude recommended hiring a professional in 60% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 20% of answers (about 0.2 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 13.3%, and told the buyer to verify credentials in 26.7%, averaging 291 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 26.7%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 outpatient rehab center answers it produced, Gemini recommended hiring a professional in 40% of them and suggested a DIY approach first 6.7% of the time. It named a specific provider in 13.3% of answers (about 0.3 distinct providers per answer) and included price or cost information 13.3% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 20%, averaging 276 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 6.7%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route an outpatient rehab center buyer to a professional (66.7%) and Gemini the least (40%). ChatGPT produced the longest answers, at 435 words on average. Specific providers were named most often by Claude (20%) — even there, roughly one answer in 5 carried a name.

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

• Suggests a DIY approach first: 6.7% across all three models.
• Gives price or cost information: 6.7%–13.3% across all three (a 7-point spread).
• Warns about red flags or scams: 6.7%–13.3% 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 93.3% of questions) and least consistently on "asks a clarifying question" (13.3%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the outpatient rehab center buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 4.5% of answers on average. Verifying credentials or certifications appeared in 20%. Warning about red flags or scams appeared in 11.1%.

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 4.4%. The single least-reproduced protective signal for outpatient rehab center is "recommends multiple quotes" at 4.4% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 15 questions behind every percentage on this page were drawn from real outpatient rehab center (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 outpatient rehab center 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.