AI SEO Statistics: Plastic Surgeon (2026-07 edition)

Reading the 24 answers model by model shows how differently the three assistants treat the same plastic surgeon questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 100% (ChatGPT) down to 50% (Gemini), a 50-point gap on an identical question set.

Across the 8 plastic surgeon answers it produced, ChatGPT recommended hiring a professional in 100% of them and suggested a DIY approach first 12.5% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 0% of the time. ChatGPT asked a clarifying question before answering in 25% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 62.5%, averaging 486 words per answer. On the remaining cues it told the buyer to check reviews in 25%, pointed to case studies or a portfolio in 37.5%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 62.5% of its answers and a recommendation to gather multiple quotes in 25%.

Across the 8 plastic surgeon answers it produced, Claude recommended hiring a professional in 87.5% of them and suggested a DIY approach first 0% of the time. It named a specific provider in 12.5% of answers (about 0.5 distinct providers per answer) and included price or cost information 12.5% of the time. Claude asked a clarifying question before answering in 50% of cases, warned about red flags or scams in 37.5%, and told the buyer to verify credentials in 62.5%, averaging 292 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 37.5%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 62.5% of its answers and a recommendation to gather multiple quotes in 37.5%.

Across the 8 plastic surgeon 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 0% of answers (about 0 distinct providers per answer) and included price or cost information 12.5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 37.5%, and told the buyer to verify credentials in 37.5%, averaging 277 words per answer. On the remaining cues it told the buyer to check reviews in 12.5%, pointed to case studies or a portfolio in 12.5%, and framed the choice around local proximity in 0%; 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 plastic surgeon buyer to a professional (100%) and Gemini the least (50%). ChatGPT produced the longest answers, at 486 words on average. Specific providers were named most often by Claude (12.5%) — even there, roughly one answer in 8 carried a name.

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

• Mentions local proximity: 0% across all three models.
• Suggests a DIY approach first: 0%–12.5% across all three (a 13-point spread).
• Names a specific provider: 0%–12.5% across all three (a 13-point spread).
• Gives price or cost information: 0%–12.5% across all three (a 13-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions local proximity" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (37.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the plastic surgeon buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 12.5% of answers on average. Verifying credentials or certifications appeared in 54.2%. Warning about red flags or scams appeared in 29.2%.

On structuring the decision, a selection-criteria checklist showed up in 54.2% of answers on average and a recommendation to gather multiple quotes in 20.8%. The single least-reproduced protective signal for plastic surgeon is "tells the buyer to check reviews" at 12.5% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 8 questions behind every percentage on this page were drawn from real plastic surgeon (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 plastic surgeon 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.