AI SEO Statistics: Garden Center Websites (2026-07 edition)
39 questions · 117 AI responses · 3 models · measured 2026-07-06
The question bank
The questions we tested — sampled from real buyer journeys in garden center websites.
Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.
Show all 39 questions
Model by model
20-point average divergence: which AI you ask changes the answer.
The divergence index is the average gap between the most and least likely model per behavior. Higher = the models disagree more about garden center websites buyers.
| ChatGPT | Claude | Gemini | Consensus | |
|---|---|---|---|---|
| Recommends hiring a professional | 28% | 18% | 18% | 82% |
| Suggests DIY first | 28% | 10% | 13% | 72% |
| Names specific providers | 8% | 21% | 28% | 72% |
| Gives price or cost info | 21% | 28% | 31% | 67% |
| Tells to check reviews | 10% | 8% | 3% | 90% |
| Tells to verify credentials | 3% | 8% | 5% | 95% |
| Mentions case studies / portfolio | 3% | 5% | 0% | 92% |
| Mentions local proximity | 46% | 44% | 39% | 46% |
| Gives selection criteria | 62% | 56% | 44% | 49% |
| Warns about red flags | 23% | 21% | 13% | 85% |
| Asks a clarifying question | 67% | 62% | 0% | 18% |
| Recommends multiple quotes | 15% | 8% | 0% | 82% |
By model
How each assistant handled Garden Center Websites questions.
Reading the 117 answers model by model shows how differently the three assistants treat the same garden center websites questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 28.2% (ChatGPT) down to 17.9% (Claude), a 10-point gap on an identical question set.
Across the 39 garden center websites answers it produced, ChatGPT recommended hiring a professional in 28.2% of them and suggested a DIY approach first 28.2% of the time. It named a specific provider in 7.7% of answers (about 0.3 distinct providers per answer) and included price or cost information 20.5% of the time. ChatGPT asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 23.1%, and told the buyer to verify credentials in 2.6%, averaging 453 words per answer. On the remaining cues it told the buyer to check reviews in 10.3%, pointed to case studies or a portfolio in 2.6%, and framed the choice around local proximity in 46.2%; a selection-criteria checklist appeared in 61.5% of its answers and a recommendation to gather multiple quotes in 15.4%.
Across the 39 garden center websites answers it produced, Claude recommended hiring a professional in 17.9% of them and suggested a DIY approach first 10.3% of the time. It named a specific provider in 20.5% of answers (about 0.5 distinct providers per answer) and included price or cost information 28.2% of the time. Claude asked a clarifying question before answering in 61.5% of cases, warned about red flags or scams in 20.5%, and told the buyer to verify credentials in 7.7%, averaging 270 words per answer. On the remaining cues it told the buyer to check reviews in 7.7%, pointed to case studies or a portfolio in 5.1%, and framed the choice around local proximity in 43.6%; a selection-criteria checklist appeared in 56.4% of its answers and a recommendation to gather multiple quotes in 7.7%.
Across the 39 garden center websites answers it produced, Gemini recommended hiring a professional in 17.9% of them and suggested a DIY approach first 12.8% of the time. It named a specific provider in 28.2% of answers (about 1.2 distinct providers per answer) and included price or cost information 30.8% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 12.8%, and told the buyer to verify credentials in 5.1%, averaging 270 words per answer. On the remaining cues it told the buyer to check reviews in 2.6%, pointed to case studies or a portfolio in 0%, and framed the choice around local proximity in 38.5%; a selection-criteria checklist appeared in 43.6% of its answers and a recommendation to gather multiple quotes in 0%.
Taken together, ChatGPT is the assistant most likely to route a garden center websites buyer to a professional (28.2%) and Claude the least (17.9%). ChatGPT produced the longest answers, at 453 words on average. Specific providers were named most often by Gemini (28.2%) — even there, roughly one answer in 4 carried a name.
Where they disagree
The behaviors where the choice of model changes the answer.
The divergence index for this study is 19.5 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a garden center websites buyer happens to ask matters most:
- Asks a clarifying question: from 0% (Gemini) to 66.7% (ChatGPT) — a 67-point spread.
- Names a specific provider: from 7.7% (ChatGPT) to 28.2% (Gemini) — a 21-point spread.
- Suggests a DIY approach first: from 10.3% (Claude) to 28.2% (ChatGPT) — a 18-point spread.
- Gives selection criteria: from 43.6% (Gemini) to 61.5% (ChatGPT) — a 18-point spread.
- Recommends multiple quotes: from 0% (Gemini) to 15.4% (ChatGPT) — a 15-point spread.
The widest single gap — asks a clarifying question, 67 points — means a garden center websites buyer can receive materially different guidance on the same question depending only on which assistant they happen to open, so any visibility strategy built on a single model's behavior describes only part of the garden center websites market.
Where they agree
The points of near-consensus in Garden Center Websites.
On other behaviors the three models move almost in lockstep — the points of near-consensus for garden center websites, where all three landed within a few points of each other:
- Tells the buyer to verify credentials: 2.6%–7.7% across all three (a 5-point spread).
- Mentions case studies or portfolio: 0%–5.1% across all three (a 5-point spread).
- Tells the buyer to check reviews: 2.6%–10.3% across all three (a 8-point spread).
- Mentions local proximity: 38.5%–46.2% across all three (a 8-point spread).
Measured question by question, the three assistants coded a response the same way most consistently on "tells the buyer to verify credentials" (identical coding in 94.9% of questions) and least consistently on "asks a clarifying question" (17.9%).
Every behavior, measured
All twelve coded behaviors for Garden Center Websites, averaged across the three models.
The behaviors AI models reproduce most often for garden center websites are gives selection criteria (53.8% on average), mentions local proximity (42.8%) and asks a clarifying question (42.7%); the rarest are mentions case studies or portfolio (2.6%), tells the buyer to verify credentials (5.1%) and tells the buyer to check reviews (6.9%). Each figure below is the share of a model's 39 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:
- Gives selection criteria: 53.8% on average (ChatGPT 61.5%, Claude 56.4%, Gemini 43.6%) — a 18-point spread.
- Mentions local proximity: 42.8% on average (ChatGPT 46.2%, Claude 43.6%, Gemini 38.5%) — a 8-point spread.
- Asks a clarifying question: 42.7% on average (ChatGPT 66.7%, Claude 61.5%, Gemini 0%) — a 67-point spread.
- Gives price or cost information: 26.5% on average (ChatGPT 20.5%, Claude 28.2%, Gemini 30.8%) — a 10-point spread.
- Recommends hiring a professional: 21.3% on average (ChatGPT 28.2%, Claude 17.9%, Gemini 17.9%) — a 10-point spread.
- Names a specific provider: 18.8% on average (ChatGPT 7.7%, Claude 20.5%, Gemini 28.2%) — a 21-point spread.
- Warns about red flags or scams: 18.8% on average (ChatGPT 23.1%, Claude 20.5%, Gemini 12.8%) — a 10-point spread.
- Suggests a DIY approach first: 17.1% on average (ChatGPT 28.2%, Claude 10.3%, Gemini 12.8%) — a 18-point spread.
- Recommends multiple quotes: 7.7% on average (ChatGPT 15.4%, Claude 7.7%, Gemini 0%) — a 15-point spread.
- Tells the buyer to check reviews: 6.9% on average (ChatGPT 10.3%, Claude 7.7%, Gemini 2.6%) — a 8-point spread.
- Tells the buyer to verify credentials: 5.1% on average (ChatGPT 2.6%, Claude 7.7%, Gemini 5.1%) — a 5-point spread.
- Mentions case studies or portfolio: 2.6% on average (ChatGPT 2.6%, Claude 5.1%, Gemini 0%) — a 5-point spread.
Trust signals
How well the models protect the garden center websites buyer.
Beyond whether to hire, the rubric codes how carefully each assistant protects the garden center websites buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 6.9% of answers on average. Verifying credentials or certifications appeared in 5.1%. Warning about red flags or scams appeared in 18.8%.
On structuring the decision, a selection-criteria checklist showed up in 53.8% of answers on average and a recommendation to gather multiple quotes in 7.7%. The single least-reproduced protective signal for garden center websites is "tells the buyer to verify credentials" at 5.1% on average — the clearest opening for content that supplies it, since the models are not yet reliably surfacing that guidance on their own.
Referral behavior
Do AI models name Garden Center Websites providers?
For service providers the decisive question is whether these systems name anyone at all. Across 117 garden center websites answers, a specific provider was named in 18.8% of responses on average — roughly 0.7 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for garden center websites: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 39 Garden Center Websites questions cover.
The 39 questions behind every percentage on this page were drawn from real garden center websites (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 garden center websites 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.
How to read this
A note on the numbers.
A percentage here is the share of a model's 39 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-06, the figures describe this specific garden center websites question set and snapshot rather than a general prior. The full protocol and coding rubric are documented in the study methodology.
Methodology
A controlled snapshot, documented end to end.
39 standardized buyer questions per industry, one response per model per question (ChatGPT (gpt-5-mini), Claude (claude-sonnet-5), Gemini (gemini-3-flash-preview)), collected 2026-07-06, coded against a fixed 12-behavior rubric with human QA. AI outputs vary with model version, location and time — figures describe this sample and window, and are refreshed each edition. Read the full methodology →