AI SEO Statistics: Botox and Fillers (2026-07 edition)

Reading the 15 answers model by model shows how differently the three assistants treat the same botox and fillers questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 100% (ChatGPT) down to 40% (Gemini), a 60-point gap on an identical question set.

Across the 5 botox and fillers answers it produced, ChatGPT recommended hiring a professional in 100% 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 20% of the time. ChatGPT asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 80%, averaging 380 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 20%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 5 botox and fillers answers it produced, Claude recommended hiring a professional in 80% 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 20% of the time. Claude asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 60%, averaging 270 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 20%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 5 botox and fillers answers it produced, Gemini recommended hiring a professional in 40% 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 20% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 20%, averaging 332 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 20%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a botox and fillers buyer to a professional (100%) and Gemini the least (40%). ChatGPT produced the longest answers, at 380 words on average. No model named a specific provider in more than 0% of answers.

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

• Names a specific provider: 0% across all three models.
• Gives price or cost information: 20% across all three models.
• Tells the buyer to check reviews: 0% across all three models.
• Mentions local proximity: 20% across all three models.

Measured question by question, the three assistants coded a response the same way most consistently on "names a specific provider" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (20%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the botox and fillers buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 0% of answers on average. Verifying credentials or certifications appeared in 53.3%. Warning about red flags or scams appeared in 20%.

On structuring the decision, a selection-criteria checklist showed up in 26.7% of answers on average and a recommendation to gather multiple quotes in 6.7%. The single least-reproduced protective signal for botox and fillers is "tells the buyer to check reviews" at 0% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 5 questions behind every percentage on this page were drawn from real botox and fillers (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 botox and fillers 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.