AI SEO Statistics: Spa (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same spa questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 60% (ChatGPT) down to 40% (Claude), a 20-point gap on an identical question set.

Across the 15 spa answers it produced, ChatGPT recommended hiring a professional in 60% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 13.3% of answers (about 0.4 distinct providers per answer) and included price or cost information 6.7% of the time. ChatGPT asked a clarifying question before answering in 73.3% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 46.7%, averaging 586 words per answer. On the remaining cues it told the buyer to check reviews in 26.7%, pointed to case studies or a portfolio in 20%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 73.3% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 spa answers it produced, Claude 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 20% of answers (about 0.6 distinct providers per answer) and included price or cost information 13.3% of the time. Claude asked a clarifying question before answering in 80% of cases, warned about red flags or scams in 33.3%, and told the buyer to verify credentials in 26.7%, averaging 281 words per answer. On the remaining cues it told the buyer to check reviews in 13.3%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 13.3%; a selection-criteria checklist appeared in 86.7% of its answers and a recommendation to gather multiple quotes in 6.7%.

Across the 15 spa answers it produced, Gemini 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 13.3% of answers (about 0.3 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 26.7%, and told the buyer to verify credentials in 20%, averaging 254 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 13.3%; a selection-criteria checklist appeared in 66.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a spa buyer to a professional (60%) and Claude the least (40%). ChatGPT produced the longest answers, at 586 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 spa, where all three landed within a few points of each other:

• Suggests a DIY approach first: 6.7%–13.3% across all three (a 7-point spread).
• Warns about red flags or scams: 26.7%–33.3% across all three (a 7-point spread).
• Names a specific provider: 13.3%–20% across all three (a 7-point spread).
• Mentions local proximity: 13.3%–20% across all three (a 7-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "recommends multiple quotes" (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 spa buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 13.3% of answers on average. Verifying credentials or certifications appeared in 31.1%. Warning about red flags or scams appeared in 31.1%.

On structuring the decision, a selection-criteria checklist showed up in 75.6% of answers on average and a recommendation to gather multiple quotes in 2.2%. The single least-reproduced protective signal for spa is "recommends multiple quotes" at 2.2% 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 spa (fitness 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 spa 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.