AI SEO Statistics: Boutique Shops (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same boutique shops questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 86.7% (ChatGPT) down to 73.3% (Claude), a 13-point gap on an identical question set.

Across the 15 boutique shops answers it produced, ChatGPT recommended hiring a professional in 86.7% of them and suggested a DIY approach first 13.3% 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 26.7% of the time. ChatGPT asked a clarifying question before answering in 20% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 6.7%, averaging 664 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 26.7%, and framed the choice around local proximity in 6.7%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 6.7%.

Across the 15 boutique shops answers it produced, Claude recommended hiring a professional in 73.3% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 20% of answers (about 0.5 distinct providers per answer) and included price or cost information 20% of the time. Claude asked a clarifying question before answering in 46.7% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 0%, averaging 311 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 26.7%, and framed the choice around local proximity in 6.7%; a selection-criteria checklist appeared in 33.3% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 boutique shops answers it produced, Gemini recommended hiring a professional in 80% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 40% of answers (about 1.2 distinct providers per answer) and included price or cost information 40% 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 0%, averaging 253 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 20%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a boutique shops buyer to a professional (86.7%) and Claude the least (73.3%). ChatGPT produced the longest answers, at 664 words on average. Specific providers were named most often by Gemini (40%) — even there, roughly one answer in 3 carried a name.

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

• Tells the buyer to check reviews: 6.7% across all three models.
• Suggests a DIY approach first: 13.3%–20% across all three (a 7-point spread).
• Tells the buyer to verify credentials: 0%–6.7% across all three (a 7-point spread).
• Mentions case studies or portfolio: 20%–26.7% across all three (a 7-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "tells the buyer to verify credentials" (identical coding in 93.3% of questions) and least consistently on "gives selection criteria" (40%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the boutique shops buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 6.7% of answers on average. Verifying credentials or certifications appeared in 2.2%. Warning about red flags or scams appeared in 17.8%.

On structuring the decision, a selection-criteria checklist showed up in 37.8% of answers on average and a recommendation to gather multiple quotes in 2.2%. The single least-reproduced protective signal for boutique shops is "tells the buyer to verify credentials" 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 boutique shops (ecommerce / online retail; 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 boutique shops 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.