Original research · 2026-07 edition

AI SEO Statistics: SEO Optimized Smart Home Sites (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 seo optimized smart home sites.

Each model answered every question once, same wording, same day. These are the prompts behind every percentage on this page.

How do I get my home automation company to appear on the first page of Google?
Is it worth paying for a niche-specific SEO agency for a smart home installation business?
What features should a professional smart home service website include to convert visitors?
How much should I budget for a custom-built website for my home theater and automation company?
Can a generic web designer handle the technical SEO needed for a smart home tech niche?
What are the most important keywords for ranking a smart home integration business locally?
Should I build my smart home site on WordPress or a platform like Squarespace for better SEO?
How long does it usually take to see organic traffic growth for a new home services site?
Show all 40 questions
What are the red flags when hiring a marketing agency for an IoT installation company?
Do I need separate landing pages for every smart home brand I install to rank better?
How do I find a web developer who understands the smart home industry and technical specs?
Is a monthly SEO retainer necessary for a small local smart home business?
My current website looks good but doesn't get any leads, what am I doing wrong?
What's the average conversion rate for a well-optimized smart home service website?
How can I optimize my site to show up for 'smart lighting installers near me'?
Is it better to hire a local agency or a specialized national agency for my smart home SEO?
What kind of content should I be posting on my home automation blog to attract high-end clients?
How do I track the ROI of my website and SEO spend for my home services business?
What's the difference between basic SEO and high-intent SEO for smart home companies?
Can I rank for competitive terms like home automation without a huge marketing budget?
How do I make sure my smart home website is mobile-friendly and fast for local searches?
What should be in a contract for a smart home web design and SEO project?
Are there specific website templates designed for smart home integrators that actually rank well?
How do I optimize my Google Business Profile to work with my smart home website's SEO?
Why are my competitors outranking me for smart home security installation in my city?
Should I focus on video content or written case studies for my smart home site's SEO?
What are the common mistakes smart home companies make when hiring a web designer?
How much content do I need on my service pages to satisfy search engine requirements?
Is it possible to migrate my old home services site to a new SEO-optimized one without losing my current rankings?
What's a fair price for a website that includes local SEO and lead generation forms for home automation?
Do I need a dedicated person to manage my smart home website's SEO every month?
How can I tell if an SEO company is using black hat techniques on my smart home site?
What technical SEO elements are most important for a site that features high-res project galleries?
Should I use a multi-page site or a single-page scrolling site for my home tech business?
How do I get high-quality backlinks for a smart home installation website?
I have a 5000 dollar budget for a new site and SEO, is that enough for a competitive market?
How do I write service descriptions for smart home tech that appeal to both users and search engines?
What are the pros and cons of using a lead-gen service vs building my own SEO-optimized site?
How can I optimize my smart home website for voice search queries?
What questions should I ask during a discovery call with a smart home SEO specialist?

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 seo optimized smart home sites buyers.

Behavior rates across 40 seo optimized smart home sites buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional33%35%25%83%
Suggests DIY first45%28%23%68%
Names specific providers8%13%13%75%
Gives price or cost info18%8%5%85%
Tells to check reviews3%5%0%93%
Tells to verify credentials3%0%0%98%
Mentions case studies / portfolio15%28%8%63%
Mentions local proximity18%33%33%55%
Gives selection criteria18%23%30%60%
Warns about red flags10%8%10%78%
Asks a clarifying question33%38%0%45%
Recommends multiple quotes0%3%0%98%

By model

How each assistant handled SEO Optimized Smart Home Sites questions.

Reading the 120 answers model by model shows how differently the three assistants treat the same seo optimized smart home sites questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 35% (Claude) down to 25% (Gemini), a 10-point gap on an identical question set.

Across the 40 seo optimized smart home sites answers it produced, ChatGPT recommended hiring a professional in 32.5% of them and suggested a DIY approach first 45% of the time. It named a specific provider in 7.5% of answers (about 0.3 distinct providers per answer) and included price or cost information 17.5% of the time. ChatGPT asked a clarifying question before answering in 32.5% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 2.5%, averaging 733 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 15%, and framed the choice around local proximity in 17.5%; a selection-criteria checklist appeared in 17.5% of its answers and a recommendation to gather multiple quotes in 0%.

Across the 40 seo optimized smart home sites answers it produced, Claude recommended hiring a professional in 35% of them and suggested a DIY approach first 27.5% of the time. It named a specific provider in 12.5% of answers (about 0.3 distinct providers per answer) and included price or cost information 7.5% of the time. Claude asked a clarifying question before answering in 37.5% of cases, warned about red flags or scams in 7.5%, and told the buyer to verify credentials in 0%, averaging 330 words per answer. On the remaining cues it told the buyer to check reviews in 5%, pointed to case studies or a portfolio in 27.5%, and framed the choice around local proximity in 32.5%; a selection-criteria checklist appeared in 22.5% of its answers and a recommendation to gather multiple quotes in 2.5%.

Across the 40 seo optimized smart home sites answers it produced, Gemini recommended hiring a professional in 25% of them and suggested a DIY approach first 22.5% 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 5% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 10%, and told the buyer to verify credentials in 0%, averaging 240 words per answer. On the remaining cues it told the buyer to check reviews in 0%, pointed to case studies or a portfolio in 7.5%, and framed the choice around local proximity in 32.5%; a selection-criteria checklist appeared in 30% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, Claude is the assistant most likely to route a seo optimized smart home sites buyer to a professional (35%) and Gemini the least (25%). ChatGPT produced the longest answers, at 733 words on average. Specific providers were named most often by Claude (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 16.8 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a seo optimized smart home sites buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 37.5% (Claude) — a 38-point spread.
  • Suggests a DIY approach first: from 22.5% (Gemini) to 45% (ChatGPT) — a 23-point spread.
  • Mentions case studies or portfolio: from 7.5% (Gemini) to 27.5% (Claude) — a 20-point spread.
  • Mentions local proximity: from 17.5% (ChatGPT) to 32.5% (Claude) — a 15-point spread.
  • Gives price or cost information: from 5% (Gemini) to 17.5% (ChatGPT) — a 13-point spread.

The widest single gap — asks a clarifying question, 38 points — means a seo optimized smart home sites 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 seo optimized smart home sites market.

Where they agree

The points of near-consensus in SEO Optimized Smart Home Sites.

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

  • Tells the buyer to verify credentials: 0%–2.5% across all three (a 3-point spread).
  • Warns about red flags or scams: 7.5%–10% across all three (a 3-point spread).
  • Recommends multiple quotes: 0%–2.5% across all three (a 3-point spread).
  • Names a specific provider: 7.5%–12.5% across all three (a 5-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 97.5% of questions) and least consistently on "asks a clarifying question" (45%).

Every behavior, measured

All twelve coded behaviors for SEO Optimized Smart Home Sites, averaged across the three models.

The behaviors AI models reproduce most often for seo optimized smart home sites are suggests a DIY approach first (31.7% on average), recommends hiring a professional (30.8%) and mentions local proximity (27.5%); the rarest are recommends multiple quotes (0.8%), tells the buyer to verify credentials (0.8%) and tells the buyer to check reviews (2.5%). 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: 31.7% on average (ChatGPT 45%, Claude 27.5%, Gemini 22.5%) — a 23-point spread.
  • Recommends hiring a professional: 30.8% on average (ChatGPT 32.5%, Claude 35%, Gemini 25%) — a 10-point spread.
  • Mentions local proximity: 27.5% on average (ChatGPT 17.5%, Claude 32.5%, Gemini 32.5%) — a 15-point spread.
  • Gives selection criteria: 23.3% on average (ChatGPT 17.5%, Claude 22.5%, Gemini 30%) — a 13-point spread.
  • Asks a clarifying question: 23.3% on average (ChatGPT 32.5%, Claude 37.5%, Gemini 0%) — a 38-point spread.
  • Mentions case studies or portfolio: 16.7% on average (ChatGPT 15%, Claude 27.5%, Gemini 7.5%) — a 20-point spread.
  • Names a specific provider: 10.8% on average (ChatGPT 7.5%, Claude 12.5%, Gemini 12.5%) — a 5-point spread.
  • Gives price or cost information: 10% on average (ChatGPT 17.5%, Claude 7.5%, Gemini 5%) — a 13-point spread.
  • Warns about red flags or scams: 9.2% on average (ChatGPT 10%, Claude 7.5%, Gemini 10%) — a 3-point spread.
  • Tells the buyer to check reviews: 2.5% on average (ChatGPT 2.5%, Claude 5%, Gemini 0%) — a 5-point spread.
  • Tells the buyer to verify credentials: 0.8% on average (ChatGPT 2.5%, Claude 0%, Gemini 0%) — a 3-point spread.
  • Recommends multiple quotes: 0.8% on average (ChatGPT 0%, Claude 2.5%, Gemini 0%) — a 3-point spread.

Trust signals

How well the models protect the seo optimized smart home sites buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the seo optimized smart home sites buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 2.5% of answers on average. Verifying credentials or certifications appeared in 0.8%. Warning about red flags or scams appeared in 9.2%.

On structuring the decision, a selection-criteria checklist showed up in 23.3% of answers on average and a recommendation to gather multiple quotes in 0.8%. The single least-reproduced protective signal for seo optimized smart home sites is "tells the buyer to verify credentials" at 0.8% 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 SEO Optimized Smart Home Sites providers?

For service providers the decisive question is whether these systems name anyone at all. Across 120 seo optimized smart home sites 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 seo optimized smart home sites: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 40 SEO Optimized Smart Home Sites questions cover.

The 40 questions behind every percentage on this page were drawn from real seo optimized smart home sites (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 seo optimized smart home sites 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 seo optimized smart home sites 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 →