AI SEO Statistics: Beauty (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same beauty questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 75% (ChatGPT) down to 45% (Gemini), a 30-point gap on an identical question set.

Across the 40 beauty answers it produced, ChatGPT recommended hiring a professional in 75% 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 10% of the time. ChatGPT asked a clarifying question before answering in 75% of cases, warned about red flags or scams in 15%, and told the buyer to verify credentials in 25%, averaging 426 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 15%, and framed the choice around local proximity in 5%; a selection-criteria checklist appeared in 30% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 beauty answers it produced, Claude recommended hiring a professional in 62.5% of them and suggested a DIY approach first 15% of the time. It named a specific provider in 2.5% of answers (about 0.2 distinct providers per answer) and included price or cost information 15% of the time. Claude asked a clarifying question before answering in 55% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 12.5%, averaging 271 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 10%, and framed the choice around local proximity in 5%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 beauty answers it produced, Gemini recommended hiring a professional in 45% 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 15% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 2.5%, averaging 281 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 2.5%; a selection-criteria checklist appeared in 22.5% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a beauty buyer to a professional (75%) and Gemini the least (45%). ChatGPT produced the longest answers, at 426 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 beauty, 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).
• Mentions local proximity: 2.5%–5% across all three (a 3-point spread).
• Recommends multiple quotes: 0%–2.5% across all three (a 3-point spread).
• Gives price or cost information: 10%–15% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "names a specific provider" (identical coding in 97.5% of questions) and least consistently on "asks a clarifying question" (12.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the beauty buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 5% of answers on average. Verifying credentials or certifications appeared in 13.3%. Warning about red flags or scams appeared in 15%.

On structuring the decision, a selection-criteria checklist showed up in 30.8% of answers on average and a recommendation to gather multiple quotes in 1.7%. The single least-reproduced protective signal for beauty is "recommends multiple quotes" at 1.7% 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 beauty services (salons, spas, med spas, aesthetics) buyer journeys, expanded from 5 seed prompts. Each was put to all 3 models once, with identical wording, so the rates above describe how the assistants handled this exact beauty 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.