AI SEO Statistics: Plasterers (2026-07 edition)

Reading the 120 answers model by model shows how differently the three assistants treat the same plasterers questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 82.5% (ChatGPT) down to 35% (Gemini), a 48-point gap on an identical question set.

Across the 40 plasterers answers it produced, ChatGPT recommended hiring a professional in 82.5% of them and suggested a DIY approach first 35% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 7.5% of the time. ChatGPT asked a clarifying question before answering in 75% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 15%, averaging 462 words per answer. On the remaining cues it told the buyer to check reviews in 12.5%, pointed to case studies or a portfolio in 10%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 35% of its answers and a recommendation to gather multiple quotes in 17.5%.

Across the 40 plasterers answers it produced, Claude recommended hiring a professional in 47.5% of them and suggested a DIY approach first 27.5% of the time. It named a specific provider in 2.5% of answers (about 0.1 distinct providers per answer) and included price or cost information 12.5% of the time. Claude asked a clarifying question before answering in 62.5% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 0%, averaging 286 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 15%; a selection-criteria checklist appeared in 15% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 40 plasterers answers it produced, Gemini recommended hiring a professional in 35% of them and suggested a DIY approach first 25% of the time. It named a specific provider in 2.5% of answers (about 0 distinct providers per answer) and included price or cost information 10% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 12.5%, and told the buyer to verify credentials in 0%, averaging 282 words per answer. On the remaining cues it told the buyer to check reviews in 2.5%, pointed to case studies or a portfolio in 2.5%, and framed the choice around local proximity in 10%; a selection-criteria checklist appeared in 7.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Taken together, ChatGPT is the assistant most likely to route a plasterers buyer to a professional (82.5%) and Gemini the least (35%). ChatGPT produced the longest answers, at 462 words on average. Specific providers were named most often by Claude (2.5%) — even there, roughly one answer in 40 carried a name.

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

• Names a specific provider: 0%–2.5% across all three (a 3-point spread).
• Warns about red flags or scams: 10%–12.5% across all three (a 3-point spread).
• Gives price or cost information: 7.5%–12.5% across all three (a 5-point spread).
• Mentions local proximity: 10%–15% across all three (a 5-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "names a specific provider" (identical coding in 95% of questions) and least consistently on "asks a clarifying question" (15%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the plasterers buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 5.8% of answers on average. Verifying credentials or certifications appeared in 5%. Warning about red flags or scams appeared in 10.8%.

On structuring the decision, a selection-criteria checklist showed up in 19.2% of answers on average and a recommendation to gather multiple quotes in 13.3%. The single least-reproduced protective signal for plasterers is "tells the buyer to verify credentials" at 5% 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 plasterers (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 plasterers 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.