AI SEO Statistics: Gardeners (2026-07 edition)

Reading the 15 answers model by model shows how differently the three assistants treat the same gardeners questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 60% (ChatGPT) down to 20% (Gemini), a 40-point gap on an identical question set.

Across the 5 gardeners answers it produced, ChatGPT recommended hiring a professional in 60% 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 0% of the time. ChatGPT asked a clarifying question before answering in 60% of cases, warned about red flags or scams in 0%, and told the buyer to verify credentials in 0%, averaging 522 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 0% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 5 gardeners 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 0% of answers (about 0 distinct providers per answer) and included price or cost information 20% of the time. Claude asked a clarifying question before answering in 100% of cases, warned about red flags or scams in 0%, and told the buyer to verify credentials in 0%, averaging 264 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 40% of its answers and a recommendation to gather multiple quotes in 20%.

Across the 5 gardeners answers it produced, Gemini recommended hiring a professional in 20% 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 20% of the time. Gemini asked a clarifying question before answering in 20% of cases, warned about red flags or scams in 0%, and told the buyer to verify credentials in 0%, averaging 292 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 0%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a gardeners buyer to a professional (60%) and Gemini the least (20%). ChatGPT produced the longest answers, at 522 words on average. No model named a specific provider in more than 0% of answers.

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

• Suggests a DIY approach first: 20% across all three models.
• Names a specific provider: 0% across all three models.
• Tells the buyer to check reviews: 0% across all three models.
• Tells the buyer to verify credentials: 0% across all three models.

Measured question by question, the three assistants coded a response the same way most consistently on "suggests a DIY approach first" (identical coding in 100% of questions) and least consistently on "asks a clarifying question" (0%).

Beyond whether to hire, the rubric codes how carefully each assistant protects the gardeners buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 0% of answers on average. Verifying credentials or certifications appeared in 0%. Warning about red flags or scams appeared in 0%.

On structuring the decision, a selection-criteria checklist showed up in 20% of answers on average and a recommendation to gather multiple quotes in 6.7%. The single least-reproduced protective signal for gardeners is "tells the buyer to check reviews" at 0% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.

The 5 questions behind every percentage on this page were drawn from real gardeners (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 gardeners 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.