AI SEO Statistics: Roofer (2026-07 edition)

Reading the 45 answers model by model shows how differently the three assistants treat the same roofer 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 40% (Gemini), a 47-point gap on an identical question set.

Across the 15 roofer answers it produced, ChatGPT recommended hiring a professional in 86.7% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 26.7% of the time. ChatGPT asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 26.7%, averaging 521 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 40%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 33.3%.

Across the 15 roofer answers it produced, Claude recommended hiring a professional in 73.3% of them and suggested a DIY approach first 26.7% of the time. It named a specific provider in 13.3% of answers (about 0.2 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 26.7%, and told the buyer to verify credentials in 26.7%, averaging 308 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 13.3%, and framed the choice around local proximity in 40%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 33.3%.

Across the 15 roofer answers it produced, Gemini recommended hiring a professional in 40% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 13.3% of answers (about 0.3 distinct providers per answer) and included price or cost information 26.7% 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 13.3%, averaging 287 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 26.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a roofer buyer to a professional (86.7%) and Gemini the least (40%). ChatGPT produced the longest answers, at 521 words on average. Specific providers were named most often by Claude (13.3%) — even there, roughly one answer in 8 carried a name.

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

• Gives price or cost information: 20%–26.7% across all three (a 7-point spread).
• Names a specific provider: 0%–13.3% across all three (a 13-point spread).
• Mentions case studies or portfolio: 6.7%–20% across all three (a 13-point spread).
• Suggests a DIY approach first: 13.3%–26.7% across all three (a 13-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "suggests a DIY approach first" (identical coding in 86.7% of questions) and least consistently on "asks a clarifying question" (20%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the roofer 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 22.2%. 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 22.2%. The single least-reproduced protective signal for roofer is "tells the buyer to check reviews" at 13.3% 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 roofer (home 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 roofer 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.