AI SEO Statistics: Home Inspector SEO Marketing (2026-07 edition)
40 questions · 120 AI responses · 3 models · measured 2026-07-06
The question bank
The questions we tested — sampled from real buyer journeys in home inspector seo marketing.
Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.
Show all 40 questions
Model by model
17-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 home inspector seo marketing buyers.
| ChatGPT | Claude | Gemini | Consensus | |
|---|---|---|---|---|
| Recommends hiring a professional | 28% | 13% | 18% | 80% |
| Suggests DIY first | 60% | 35% | 28% | 45% |
| Names specific providers | 10% | 10% | 13% | 78% |
| Gives price or cost info | 10% | 10% | 10% | 93% |
| Tells to check reviews | 0% | 5% | 0% | 95% |
| Tells to verify credentials | 0% | 0% | 0% | 100% |
| Mentions case studies / portfolio | 15% | 10% | 0% | 80% |
| Mentions local proximity | 25% | 40% | 45% | 50% |
| Gives selection criteria | 20% | 25% | 10% | 68% |
| Warns about red flags | 23% | 10% | 5% | 73% |
| Asks a clarifying question | 38% | 55% | 0% | 28% |
| Recommends multiple quotes | 0% | 0% | 0% | 100% |
By model
How each assistant handled Home Inspector SEO Marketing questions.
Reading the 120 answers model by model shows how differently the three assistants treat the same home inspector seo marketing questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 27.5% (ChatGPT) down to 12.5% (Claude), a 15-point gap on an identical question set.
Across the 40 home inspector seo marketing answers it produced, ChatGPT recommended hiring a professional in 27.5% of them and suggested a DIY approach first 60% of the time. It named a specific provider in 10% of answers (about 0.3 distinct providers per answer) and included price or cost information 10% of the time. ChatGPT asked a clarifying question before answering in 37.5% of cases, warned about red flags or scams in 22.5%, and told the buyer to verify credentials in 0%, averaging 630 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 15%, and framed the choice around local proximity in 25%; a selection-criteria checklist appeared in 20% of its answers and a recommendation to gather multiple quotes in 0%.
Across the 40 home inspector seo marketing answers it produced, Claude recommended hiring a professional in 12.5% of them and suggested a DIY approach first 35% of the time. It named a specific provider in 10% of answers (about 0.3 distinct providers per answer) and included price or cost information 10% of the time. Claude asked a clarifying question before answering in 55% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 0%, averaging 309 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 10%, and framed the choice around local proximity in 40%; a selection-criteria checklist appeared in 25% of its answers and a recommendation to gather multiple quotes in 0%.
Across the 40 home inspector seo marketing answers it produced, Gemini recommended hiring a professional in 17.5% of them and suggested a DIY approach first 27.5% of the time. It named a specific provider in 12.5% of answers (about 0.2 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 5%, and told the buyer to verify credentials in 0%, averaging 262 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 45%; a selection-criteria checklist appeared in 10% of its answers and a recommendation to gather multiple quotes in 0%.
Taken together, ChatGPT is the assistant most likely to route a home inspector seo marketing buyer to a professional (27.5%) and Claude the least (12.5%). ChatGPT produced the longest answers, at 630 words on average. Specific providers were named most often by Gemini (12.5%) — even there, roughly one answer in 8 carried a name.
Where they disagree
The behaviors where the choice of model changes the answer.
The divergence index for this study is 17.4 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a home inspector seo marketing buyer happens to ask matters most:
- Asks a clarifying question: from 0% (Gemini) to 55% (Claude) — a 55-point spread.
- Suggests a DIY approach first: from 27.5% (Gemini) to 60% (ChatGPT) — a 33-point spread.
- Mentions local proximity: from 25% (ChatGPT) to 45% (Gemini) — a 20-point spread.
- Warns about red flags or scams: from 5% (Gemini) to 22.5% (ChatGPT) — a 18-point spread.
- Recommends hiring a professional: from 12.5% (Claude) to 27.5% (ChatGPT) — a 15-point spread.
The widest single gap — asks a clarifying question, 55 points — means a home inspector seo marketing 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 home inspector seo marketing market.
Where they agree
The points of near-consensus in Home Inspector SEO Marketing.
On other behaviors the three models move almost in lockstep — the points of near-consensus for home inspector seo marketing, where all three landed within a few points of each other:
- Gives price or cost information: 10% across all three models.
- Tells the buyer to verify credentials: 0% across all three models.
- Recommends multiple quotes: 0% across all three models.
- Names a specific provider: 10%–12.5% across all three (a 3-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 100% of questions) and least consistently on "asks a clarifying question" (27.5%).
Every behavior, measured
All twelve coded behaviors for Home Inspector SEO Marketing, averaged across the three models.
The behaviors AI models reproduce most often for home inspector seo marketing are suggests a DIY approach first (40.8% on average), mentions local proximity (36.7%) and asks a clarifying question (30.8%); the rarest are recommends multiple quotes (0%), tells the buyer to verify credentials (0%) and tells the buyer to check reviews (1.7%). Each figure below is the share of a model's 40 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:
- Suggests a DIY approach first: 40.8% on average (ChatGPT 60%, Claude 35%, Gemini 27.5%) — a 33-point spread.
- Mentions local proximity: 36.7% on average (ChatGPT 25%, Claude 40%, Gemini 45%) — a 20-point spread.
- Asks a clarifying question: 30.8% on average (ChatGPT 37.5%, Claude 55%, Gemini 0%) — a 55-point spread.
- Recommends hiring a professional: 19.2% on average (ChatGPT 27.5%, Claude 12.5%, Gemini 17.5%) — a 15-point spread.
- Gives selection criteria: 18.3% on average (ChatGPT 20%, Claude 25%, Gemini 10%) — a 15-point spread.
- Warns about red flags or scams: 12.5% on average (ChatGPT 22.5%, Claude 10%, Gemini 5%) — a 18-point spread.
- Names a specific provider: 10.8% on average (ChatGPT 10%, Claude 10%, Gemini 12.5%) — a 3-point spread.
- Gives price or cost information: 10% on average (ChatGPT 10%, Claude 10%, Gemini 10%).
- Mentions case studies or portfolio: 8.3% on average (ChatGPT 15%, Claude 10%, Gemini 0%) — a 15-point spread.
- Tells the buyer to check reviews: 1.7% on average (ChatGPT 0%, Claude 5%, Gemini 0%) — a 5-point spread.
- Tells the buyer to verify credentials: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
- Recommends multiple quotes: 0% on average (ChatGPT 0%, Claude 0%, Gemini 0%).
Trust signals
How well the models protect the home inspector seo marketing buyer.
Beyond whether to hire, the rubric codes how carefully each assistant protects the home inspector seo marketing buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 1.7% of answers on average. Verifying credentials or certifications appeared in 0%. Warning about red flags or scams appeared in 12.5%.
On structuring the decision, a selection-criteria checklist showed up in 18.3% of answers on average and a recommendation to gather multiple quotes in 0%. The single least-reproduced protective signal for home inspector seo marketing is "tells the buyer to verify credentials" 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.
Referral behavior
Do AI models name Home Inspector SEO Marketing providers?
For service providers the decisive question is whether these systems name anyone at all. Across 120 home inspector seo marketing answers, a specific provider was named in 10.8% of responses on average — roughly 0.3 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for home inspector seo marketing: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.
The question set
What these 40 Home Inspector SEO Marketing questions cover.
The 40 questions behind every percentage on this page were drawn from real home inspector seo marketing (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 home inspector seo marketing 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 40 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 home inspector seo marketing 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.
40 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 →