AI SEO Statistics: Bookstore (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same bookstore questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 40% (ChatGPT) down to 40% (ChatGPT), a 0-point gap on an identical question set.

Across the 15 bookstore answers it produced, ChatGPT recommended hiring a professional in 40% of them and suggested a DIY approach first 26.7% of the time. It named a specific provider in 60% of answers (about 3.9 distinct providers per answer) and included price or cost information 13.3% of the time. ChatGPT asked a clarifying question before answering in 26.7% of cases, warned about red flags or scams in 6.7%, and told the buyer to verify credentials in 0%, averaging 466 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 26.7%; a selection-criteria checklist appeared in 26.7% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 15 bookstore answers it produced, Claude recommended hiring a professional in 40% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 86.7% of answers (about 4.9 distinct providers per answer) and included price or cost information 13.3% of the time. Claude asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 26.7%, and told the buyer to verify credentials in 13.3%, averaging 275 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 0%, and framed the choice around local proximity in 53.3%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 15 bookstore answers it produced, Gemini 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 86.7% of answers (about 3.4 distinct providers per answer) and included price or cost information 33.3% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 6.7%, averaging 225 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 6.7%, and framed the choice around local proximity in 33.3%; a selection-criteria checklist appeared in 33.3% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a bookstore buyer to a professional (40%) and ChatGPT the least (40%). ChatGPT produced the longest answers, at 466 words on average. Specific providers were named most often by Claude (86.7%) — even there, roughly one answer in 1 carried a name.

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

• Recommends hiring a professional: 40% across all three models.
• Mentions case studies or portfolio: 0%–6.7% across all three (a 7-point spread).
• Tells the buyer to verify credentials: 0%–13.3% across all three (a 13-point spread).
• Suggests a DIY approach first: 6.7%–26.7% across all three (a 20-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "mentions case studies or portfolio" (identical coding in 93.3% of questions) and least consistently on "asks a clarifying question" (20%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the bookstore buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 17.8% of answers on average. Verifying credentials or certifications appeared in 6.7%. Warning about red flags or scams appeared in 15.6%.

On structuring the decision, a selection-criteria checklist showed up in 35.6% of answers on average and a recommendation to gather multiple quotes in 6.7%. The single least-reproduced protective signal for bookstore is "tells the buyer to verify credentials" at 6.7% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 15 questions behind every percentage on this page were drawn from real bookstore (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 bookstore 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.