AI SEO Statistics: Plastic Surgeon (2026-07 edition)
8 questions · 24/24 expected AI responses · 3 models · measured 2026-07-04
Apply these findings to your plastic surgeon SEO strategy.
This benchmark explains how AI assistants advise buyers. The related service page turns those findings into the technical, content, authority, and conversion priorities for this market.
The question bank
The questions we tested: a frozen buyer-intent benchmark for plastic surgeon.
The question set was curated from a predefined buyer-intent taxonomy and held constant for this edition. Each model received the same wording. These are the prompts behind every percentage on this page.
Model by model
24.3% question-level model disagreement.
This rate is the average pairwise disagreement between binary behavior codes across questions and behaviors. It is not the gap between the highest and lowest aggregated model percentages.
Behavior prevalence across 8 plastic surgeon benchmark questions, 2026-07 edition. Last column: equal-model mean.
| Behavior | ChatGPT | Claude | Gemini | Equal-model mean |
|---|---|---|---|---|
| Recommends hiring a professional | 100% | 87.5% | 50% | 79.2% |
| Suggests DIY first | 12.5% | 0% | 0% | 4.2% |
| Names specific providers | 0% | 12.5% | 0% | 4.2% |
| Gives price or cost info | 0% | 12.5% | 12.5% | 8.3% |
| Tells to check reviews | 25% | 0% | 12.5% | 12.5% |
| Tells to verify credentials | 62.5% | 62.5% | 37.5% | 54.2% |
| Mentions case studies / portfolio | 37.5% | 37.5% | 12.5% | 29.2% |
| Mentions local proximity | 0% | 0% | 0% | 0% |
| Gives selection criteria | 62.5% | 62.5% | 37.5% | 54.2% |
| Warns about red flags | 12.5% | 37.5% | 37.5% | 29.2% |
| Asks a clarifying question | 25% | 50% | 0% | 25% |
| Recommends multiple quotes | 25% | 37.5% | 0% | 20.8% |
Question-level agreement
How often all measured models received the same binary code.
Agreement is calculated question by question for each behavior. A high value can coexist with a low behavior prevalence; it means the models usually agreed on whether the behavior appeared.
All-model binary agreement by behavior across 8 benchmark questions.
| Behavior | All-model agreement |
|---|---|
| Recommends hiring a professional | 37.5% |
| Suggests DIY first | 87.5% |
| Names specific providers | 87.5% |
| Gives price or cost info | 87.5% |
| Tells to check reviews | 62.5% |
| Tells to verify credentials | 37.5% |
| Mentions case studies / portfolio | 37.5% |
| Mentions local proximity | 100% |
| Gives selection criteria | 50% |
| Warns about red flags | 75% |
| Asks a clarifying question | 37.5% |
| Recommends multiple quotes | 62.5% |
By model
How each assistant handled Plastic Surgeon questions.
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.
Where they disagree
The behaviors where the choice of model changes the answer.
Question-level model disagreement is 24.3%. This is the average pairwise rate at which models received different binary codes across questions and behaviors. The observed rate spreads below are a separate measure showing where which assistant a plastic surgeon buyer happens to ask matters most:
- Recommends hiring a professional: from 50% (Gemini) to 100% (ChatGPT). The spread is 50 points.
- Asks a clarifying question: from 0% (Gemini) to 50% (Claude). The spread is 50 points.
- Recommends multiple quotes: from 0% (Gemini) to 37.5% (Claude). The spread is 38 points.
- Tells the buyer to check reviews: from 0% (Claude) to 25% (ChatGPT). The spread is 25 points.
- Tells the buyer to verify credentials: from 37.5% (Gemini) to 62.5% (ChatGPT). The spread is 25 points.
The widest single gap concerns recommends hiring a professional at 50 points. This means a plastic surgeon 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 plastic surgeon market.
Where they agree
The points of near-consensus in Plastic Surgeon.
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%).
Every behavior, measured
All twelve coded behaviors for Plastic Surgeon, averaged across the three models.
The behaviors AI models reproduce most often for plastic surgeon are recommends hiring a professional (79.2% on average), tells the buyer to verify credentials (54.2%) and gives selection criteria (54.2%); the rarest are mentions local proximity (0%), names a specific provider (4.2%) and suggests a DIY approach first (4.2%). Each figure below is the share of a model's 8 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:
- Recommends hiring a professional: 79.2% on average (ChatGPT 100%, Claude 87.5%, Gemini 50%). The spread is 50 points.
- Tells the buyer to verify credentials: 54.2% on average (ChatGPT 62.5%, Claude 62.5%, Gemini 37.5%). The spread is 25 points.
- Gives selection criteria: 54.2% on average (ChatGPT 62.5%, Claude 62.5%, Gemini 37.5%). The spread is 25 points.
- Mentions case studies or portfolio: 29.2% on average (ChatGPT 37.5%, Claude 37.5%, Gemini 12.5%). The spread is 25 points.
- Warns about red flags or scams: 29.2% on average (ChatGPT 12.5%, Claude 37.5%, Gemini 37.5%). The spread is 25 points.
- Asks a clarifying question: 25% on average (ChatGPT 25%, Claude 50%, Gemini 0%). The spread is 50 points.
- Recommends multiple quotes: 20.8% on average (ChatGPT 25%, Claude 37.5%, Gemini 0%). The spread is 38 points.
- Tells the buyer to check reviews: 12.5% on average (ChatGPT 25%, Claude 0%, Gemini 12.5%). The spread is 25 points.
- Gives price or cost information: 8.3% on average (ChatGPT 0%, Claude 12.5%, Gemini 12.5%). The spread is 13 points.
- Suggests a DIY approach first: 4.2% on average (ChatGPT 12.5%, Claude 0%, Gemini 0%). The spread is 13 points.
- Names a specific provider: 4.2% on average (ChatGPT 0%, Claude 12.5%, Gemini 0%). The spread is 13 points.
- Mentions local proximity: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
Trust signals
How well the models protect the plastic surgeon buyer.
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. This is 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 Plastic Surgeon providers?
For service providers the decisive question is whether these systems name anyone at all. Across 24 plastic surgeon answers, a specific provider was named in 4.2% of responses on average, or roughly 0.2 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for plastic surgeon: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 8 Plastic Surgeon questions cover.
The 8 questions behind every percentage on this page form a frozen plastic surgeon (healthcare services; buyer hiring decisions for this specific service) buyer-intent benchmark. 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 rather than 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 8 answers in which the behavior appeared at least once. It is not a confidence score. Because each model answered every question exactly once on 2026-07-04, the figures describe this specific plastic surgeon 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.
8 frozen benchmark questions, one expected response per model per question (ChatGPT API (gpt-5-mini), Claude API (claude-sonnet-5), Gemini API (gemini-3-flash-preview)), collected 2026-07-04 and coded against a fixed 12-behavior rubric. The pipeline validates the schema, recomputes aggregates and reports consistency issues. AI outputs vary with model version, location and time, so the figures describe this edition's exact sample and measurement window. Read the full methodology →
Citation
Cite this edition.
Authority Specialist. “AI SEO Statistics: Plastic Surgeon (2026-07 edition).” AuthoritySpecialist.com. https://authorityspecialist.com/research/ai-seo-statistics/services/health/plastic-surgeon