AI SEO Statistics: Education (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same education questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 37.5% (Claude) down to 32.5% (ChatGPT), a 5-point gap on an identical question set.

Across the 40 education answers it produced, ChatGPT recommended hiring a professional in 32.5% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 37.5% of answers (about 1.7 distinct providers per answer) and included price or cost information 22.5% of the time. ChatGPT asked a clarifying question before answering in 40% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 27.5%, averaging 603 words per answer. On the remaining cues it told the buyer to check reviews in 20%, pointed to case studies or a portfolio in 10%, and framed the choice around local proximity in 12.5%; a selection-criteria checklist appeared in 52.5% of its answers and a recommendation to gather multiple quotes in 7.5%.

Across the 40 education answers it produced, Claude recommended hiring a professional in 37.5% of them and suggested a DIY approach first 22.5% of the time. It named a specific provider in 52.5% of answers (about 2.8 distinct providers per answer) and included price or cost information 35% of the time. Claude asked a clarifying question before answering in 65% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 20%, averaging 302 words per answer. On the remaining cues it told the buyer to check reviews in 15%, pointed to case studies or a portfolio in 15%, and framed the choice around local proximity in 25%; a selection-criteria checklist appeared in 50% of its answers and a recommendation to gather multiple quotes in 5%.

Across the 40 education answers it produced, Gemini recommended hiring a professional in 32.5% of them and suggested a DIY approach first 7.5% of the time. It named a specific provider in 57.5% of answers (about 1.7 distinct providers per answer) and included price or cost information 32.5% 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 12.5%, averaging 222 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 7.5%; a selection-criteria checklist appeared in 45% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, Claude is the assistant most likely to route an education buyer to a professional (37.5%) and ChatGPT the least (32.5%). ChatGPT produced the longest answers, at 603 words on average. Specific providers were named most often by Gemini (57.5%) — even there, roughly one answer in 2 carried a name.

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

• Recommends hiring a professional: 32.5%–37.5% across all three (a 5-point spread).
• Warns about red flags or scams: 7.5%–12.5% across all three (a 5-point spread).
• Gives selection criteria: 45%–52.5% across all three (a 8-point spread).
• Recommends multiple quotes: 0%–7.5% across all three (a 8-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "warns about red flags or scams" (identical coding in 90% of questions) and least consistently on "asks a clarifying question" (27.5%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the education buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 11.7% of answers on average. Verifying credentials or certifications appeared in 20%. Warning about red flags or scams appeared in 10%.

On structuring the decision, a selection-criteria checklist showed up in 49.2% of answers on average and a recommendation to gather multiple quotes in 4.2%. The single least-reproduced protective signal for education is "recommends multiple quotes" at 4.2% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 40 questions behind every percentage on this page were drawn from real education services (schools, tutoring, courses, edtech) 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 education 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.