Original research · 2026-07 edition

AI SEO Statistics: Flooring Installer (2026-07 edition)

15 questions · 45 AI responses · 3 models · measured 2026-07-04

The question bank

The questions we tested — sampled from real buyer journeys in flooring installer.

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

My hardwood floors are starting to cup and show gaps, do I need a total replacement or can they just be refinished?
Is it worth the extra cost to hire a pro for LVP installation or is it easy enough to do on my own over a weekend?
What are the typical red flags I should look for when a flooring contractor gives me a quote that seems too low?
What is the average labor-only cost per square foot for installing large format porcelain tile in a bathroom?
We have three large dogs and need floors that won't scratch; should we go with luxury vinyl or a specific type of tile?
How long does a crew typically take to remove old glued-down carpet and install new laminate in a 1,500 square foot house?
I just had a major pipe burst and my floors are ruined; how quickly can a contractor usually start a replacement job?
I want a complex chevron pattern in my entryway, does that require a specialist or can any general flooring installer handle it?
Show all 15 questions
What specific details should be included in a flooring contract to make sure I don't get hit with hidden fees for subfloor prep?
Is it better for me to buy the flooring materials myself at a warehouse or let the installer source them for me?
Do I need to check if my flooring guy is licensed and insured if they are just doing a small 10x10 bedroom?
I have a $4,000 budget for a 500 square foot basement; what are my best options for materials and professional labor?
If my concrete subfloor is unlevel, will a flooring installer usually handle the self-leveling compound or do I need a different pro?
Does the quote for new flooring usually include moving heavy furniture and putting it back, or is that a separate service charge?
My installer says the wood needs to sit in my living room for 48 hours before they start; is that a standard practice or a delay tactic?

Model by model

23-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 flooring installer buyers.

Behavior rates across 15 flooring installer buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional80%80%27%40%
Suggests DIY first20%13%20%80%
Names specific providers0%0%13%87%
Gives price or cost info33%40%40%53%
Tells to check reviews7%7%0%93%
Tells to verify credentials27%7%0%73%
Mentions case studies / portfolio13%7%0%87%
Mentions local proximity33%20%0%60%
Gives selection criteria80%53%27%33%
Warns about red flags13%13%13%80%
Asks a clarifying question67%33%0%33%
Recommends multiple quotes27%33%0%60%

By model

How each assistant handled Flooring Installer questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same flooring installer questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 80% (ChatGPT) down to 26.7% (Gemini), a 53-point gap on an identical question set.

Across the 15 flooring installer answers it produced, ChatGPT recommended hiring a professional in 80% 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 33.3% of the time. ChatGPT asked a clarifying question before answering in 66.7% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 26.7%, averaging 541 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 13.3%, and framed the choice around local proximity in 33.3%; a selection-criteria checklist appeared in 80% of its answers and a recommendation to gather multiple quotes in 26.7%.

Across the 15 flooring installer answers it produced, Claude recommended hiring a professional in 80% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 0% of answers (about 0 distinct providers per answer) and included price or cost information 40% of the time. Claude asked a clarifying question before answering in 33.3% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 6.7%, averaging 300 words per answer. On the remaining cues it told the buyer to check reviews in 6.7%, pointed to case studies or a portfolio in 6.7%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 53.3% of its answers and a recommendation to gather multiple quotes in 33.3%.

Across the 15 flooring installer answers it produced, Gemini recommended hiring a professional in 26.7% of them and suggested a DIY approach first 20% of the time. It named a specific provider in 13.3% of answers (about 0.3 distinct providers per answer) and included price or cost information 40% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 13.3%, and told the buyer to verify credentials in 0%, averaging 283 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 26.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a flooring installer buyer to a professional (80%) and Gemini the least (26.7%). ChatGPT produced the longest answers, at 541 words on average. Specific providers were named most often by Gemini (13.3%) — 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 23.3 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a flooring installer buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 66.7% (ChatGPT) — a 67-point spread.
  • Recommends hiring a professional: from 26.7% (Gemini) to 80% (ChatGPT) — a 53-point spread.
  • Gives selection criteria: from 26.7% (Gemini) to 80% (ChatGPT) — a 53-point spread.
  • Mentions local proximity: from 0% (Gemini) to 33.3% (ChatGPT) — a 33-point spread.
  • Recommends multiple quotes: from 0% (Gemini) to 33.3% (Claude) — a 33-point spread.

The widest single gap — asks a clarifying question, 67 points — means a flooring installer 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 flooring installer market.

Where they agree

The points of near-consensus in Flooring Installer.

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

  • Warns about red flags or scams: 13.3% across all three models.
  • Suggests a DIY approach first: 13.3%–20% across all three (a 7-point spread).
  • Gives price or cost information: 33.3%–40% across all three (a 7-point spread).
  • Tells the buyer to check reviews: 0%–6.7% across all three (a 7-point spread).

Measured question by question, the three assistants coded a response the same way most consistently on "tells the buyer to check reviews" (identical coding in 93.3% of questions) and least consistently on "asks a clarifying question" (33.3%).

Every behavior, measured

All twelve coded behaviors for Flooring Installer, averaged across the three models.

The behaviors AI models reproduce most often for flooring installer are recommends hiring a professional (62.2% on average), gives selection criteria (53.3%) and gives price or cost information (37.8%); the rarest are names a specific provider (4.4%), tells the buyer to check reviews (4.5%) and mentions case studies or portfolio (6.7%). Each figure below is the share of a model's 15 answers in which the behavior appeared at least once, averaged across the 3 models with the full per-model range in parentheses:

  • Recommends hiring a professional: 62.2% on average (ChatGPT 80%, Claude 80%, Gemini 26.7%) — a 53-point spread.
  • Gives selection criteria: 53.3% on average (ChatGPT 80%, Claude 53.3%, Gemini 26.7%) — a 53-point spread.
  • Gives price or cost information: 37.8% on average (ChatGPT 33.3%, Claude 40%, Gemini 40%) — a 7-point spread.
  • Asks a clarifying question: 33.3% on average (ChatGPT 66.7%, Claude 33.3%, Gemini 0%) — a 67-point spread.
  • Recommends multiple quotes: 20% on average (ChatGPT 26.7%, Claude 33.3%, Gemini 0%) — a 33-point spread.
  • Suggests a DIY approach first: 17.8% on average (ChatGPT 20%, Claude 13.3%, Gemini 20%) — a 7-point spread.
  • Mentions local proximity: 17.8% on average (ChatGPT 33.3%, Claude 20%, Gemini 0%) — a 33-point spread.
  • Warns about red flags or scams: 13.3% on average (ChatGPT 13.3%, Claude 13.3%, Gemini 13.3%).
  • Tells the buyer to verify credentials: 11.1% on average (ChatGPT 26.7%, Claude 6.7%, Gemini 0%) — a 27-point spread.
  • Mentions case studies or portfolio: 6.7% on average (ChatGPT 13.3%, Claude 6.7%, Gemini 0%) — a 13-point spread.
  • Tells the buyer to check reviews: 4.5% on average (ChatGPT 6.7%, Claude 6.7%, Gemini 0%) — a 7-point spread.
  • Names a specific provider: 4.4% on average (ChatGPT 0%, Claude 0%, Gemini 13.3%) — a 13-point spread.

Trust signals

How well the models protect the flooring installer buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the flooring installer buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 4.5% of answers on average. Verifying credentials or certifications appeared in 11.1%. Warning about red flags or scams appeared in 13.3%.

On structuring the decision, a selection-criteria checklist showed up in 53.3% of answers on average and a recommendation to gather multiple quotes in 20%. The single least-reproduced protective signal for flooring installer is "tells the buyer to check reviews" at 4.5% 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 Flooring Installer providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 flooring installer answers, a specific provider was named in 4.4% of responses on average — roughly 0.1 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for flooring installer: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Flooring Installer questions cover.

The 15 questions behind every percentage on this page were drawn from real flooring installer (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 flooring installer 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 15 answers in which the behavior appeared at least once — not a confidence score. Because each model answered every question exactly once on 2026-07-04, the figures describe this specific flooring installer 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.

15 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 2026-07-04, 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 →