Original research · 2026-07 edition

AI SEO Statistics: Craft Businesses (2026-07 edition)

15 questions · 45 AI responses · 3 models · measured 2026-07-05

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The question bank

The questions we tested — sampled from real buyer journeys in craft businesses.

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

I want to buy a custom hand-knit sweater for my toddler, what should I look for to make sure the wool isn't itchy?
Is it cheaper to buy a handmade dining table from a local woodworker or just get a high-end one from a mass-market furniture store?
How can I tell if an online jewelry shop is actually making their pieces or just reselling cheap mass-produced stuff?
I need a personalized leather journal for a graduation gift by next Friday, is that even possible for a small craft business to finish in time?
What are the typical lead times I should expect for a custom-made stained glass window hanging?
I'm looking for a ceramicist who does custom dinnerware sets, what kind of questions should I ask about food safety and microwave durability?
Why do some handmade soy candles cost $40 while others are $15, and is there a real difference in the scent throw?
How do I find local artisans in my area who take commissions for custom pet portraits instead of just buying a digital print?
Show all 15 questions
What are some red flags to watch out for when commissioning a piece of custom wood furniture from an Instagram seller?
I want to support an independent maker for my wedding favors, what's a realistic budget per item for 100 small handmade soaps?
Should I try to DIY a macrame wall hanging for my nursery or is it worth the $200 to hire a professional fiber artist?
What's the best way to verify if a handmade shop is actually using ethically sourced materials like they claim?
Can I request a specific color palette for a custom resin river table, or do artists usually prefer to have total creative control?
If a handmade item arrives damaged in the mail, is the seller usually responsible for the return shipping or is that on the buyer?
I'm looking for a unique anniversary gift, what are some trending handmade items right now that feel more high-end and less like a school project?

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 craft businesses buyers.

Behavior rates across 15 craft businesses buyer questions, 2026-07 edition. Last column: average across models.
ChatGPTClaudeGeminiConsensus
Recommends hiring a professional47%40%33%80%
Suggests DIY first13%13%13%87%
Names specific providers7%27%13%80%
Gives price or cost info27%33%27%53%
Tells to check reviews27%33%7%67%
Tells to verify credentials20%20%7%73%
Mentions case studies / portfolio33%27%20%67%
Mentions local proximity33%20%20%47%
Gives selection criteria60%47%47%27%
Warns about red flags20%27%20%80%
Asks a clarifying question53%33%0%40%
Recommends multiple quotes7%7%0%87%

By model

How each assistant handled Craft Businesses questions.

Reading the 45 answers model by model shows how differently the three assistants treat the same craft businesses questions. On the most consequential behavior — whether to send the buyer to a professional at all — the rate ranged from 46.7% (ChatGPT) down to 33.3% (Gemini), a 13-point gap on an identical question set.

Across the 15 craft businesses answers it produced, ChatGPT recommended hiring a professional in 46.7% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 6.7% of answers (about 0.3 distinct providers per answer) and included price or cost information 26.7% of the time. ChatGPT asked a clarifying question before answering in 53.3% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 20%, averaging 527 words per answer. On the remaining cues it told the buyer to check reviews in 26.7%, pointed to case studies or a portfolio in 33.3%, and framed the choice around local proximity in 33.3%; a selection-criteria checklist appeared in 60% of its answers and a recommendation to gather multiple quotes in 6.7%.

Across the 15 craft businesses answers it produced, Claude recommended hiring a professional in 40% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 26.7% of answers (about 0.5 distinct providers per answer) and included price or cost information 33.3% of the time. Claude asked a clarifying question before answering in 33.3% of cases, warned about red flags or scams in 26.7%, and told the buyer to verify credentials in 20%, averaging 291 words per answer. On the remaining cues it told the buyer to check reviews in 33.3%, pointed to case studies or a portfolio in 26.7%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 6.7%.

Across the 15 craft businesses answers it produced, Gemini recommended hiring a professional in 33.3% of them and suggested a DIY approach first 13.3% of the time. It named a specific provider in 13.3% of answers (about 0.4 distinct providers per answer) and included price or cost information 26.7% of the time. Gemini asked a clarifying question before answering in 0% of cases, warned about red flags or scams in 20%, and told the buyer to verify credentials in 6.7%, averaging 253 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 20%, and framed the choice around local proximity in 20%; a selection-criteria checklist appeared in 46.7% of its answers and a recommendation to gather multiple quotes in 0%.

Taken together, ChatGPT is the assistant most likely to route a craft businesses buyer to a professional (46.7%) and Gemini the least (33.3%). ChatGPT produced the longest answers, at 527 words on average. Specific providers were named most often by Claude (26.7%) — 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 23 points — the average distance between the most and least likely model across the coded behaviors. The gaps below are where which assistant a craft businesses buyer happens to ask matters most:

  • Asks a clarifying question: from 0% (Gemini) to 53.3% (ChatGPT) — a 53-point spread.
  • Tells the buyer to check reviews: from 6.7% (Gemini) to 33.3% (Claude) — a 27-point spread.
  • Names a specific provider: from 6.7% (ChatGPT) to 26.7% (Claude) — a 20-point spread.
  • Recommends hiring a professional: from 33.3% (Gemini) to 46.7% (ChatGPT) — a 13-point spread.
  • Tells the buyer to verify credentials: from 6.7% (Gemini) to 20% (ChatGPT) — a 13-point spread.

The widest single gap — asks a clarifying question, 53 points — means a craft businesses 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 craft businesses market.

Where they agree

The points of near-consensus in Craft Businesses.

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

  • Suggests a DIY approach first: 13.3% across all three models.
  • Gives price or cost information: 26.7%–33.3% across all three (a 7-point spread).
  • Warns about red flags or scams: 20%–26.7% across all three (a 7-point spread).
  • Recommends multiple quotes: 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 "suggests a DIY approach first" (identical coding in 86.7% of questions) and least consistently on "gives selection criteria" (26.7%).

Every behavior, measured

All twelve coded behaviors for Craft Businesses, averaged across the three models.

The behaviors AI models reproduce most often for craft businesses are gives selection criteria (51.1% on average), recommends hiring a professional (40%) and gives price or cost information (28.9%); the rarest are recommends multiple quotes (4.5%), suggests a DIY approach first (13.3%) and tells the buyer to verify credentials (15.6%). 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:

  • Gives selection criteria: 51.1% on average (ChatGPT 60%, Claude 46.7%, Gemini 46.7%) — a 13-point spread.
  • Recommends hiring a professional: 40% on average (ChatGPT 46.7%, Claude 40%, Gemini 33.3%) — a 13-point spread.
  • Gives price or cost information: 28.9% on average (ChatGPT 26.7%, Claude 33.3%, Gemini 26.7%) — a 7-point spread.
  • Asks a clarifying question: 28.9% on average (ChatGPT 53.3%, Claude 33.3%, Gemini 0%) — a 53-point spread.
  • Mentions case studies or portfolio: 26.7% on average (ChatGPT 33.3%, Claude 26.7%, Gemini 20%) — a 13-point spread.
  • Mentions local proximity: 24.4% on average (ChatGPT 33.3%, Claude 20%, Gemini 20%) — a 13-point spread.
  • Tells the buyer to check reviews: 22.2% on average (ChatGPT 26.7%, Claude 33.3%, Gemini 6.7%) — a 27-point spread.
  • Warns about red flags or scams: 22.2% on average (ChatGPT 20%, Claude 26.7%, Gemini 20%) — a 7-point spread.
  • Names a specific provider: 15.6% on average (ChatGPT 6.7%, Claude 26.7%, Gemini 13.3%) — a 20-point spread.
  • Tells the buyer to verify credentials: 15.6% on average (ChatGPT 20%, Claude 20%, Gemini 6.7%) — a 13-point spread.
  • Suggests a DIY approach first: 13.3% on average (ChatGPT 13.3%, Claude 13.3%, Gemini 13.3%).
  • Recommends multiple quotes: 4.5% on average (ChatGPT 6.7%, Claude 6.7%, Gemini 0%) — a 7-point spread.

Trust signals

How well the models protect the craft businesses buyer.

Beyond whether to hire, the rubric codes how carefully each assistant protects the craft businesses buyer once a decision is made. Telling the buyer to check reviews or ratings appeared in 22.2% of answers on average. Verifying credentials or certifications appeared in 15.6%. Warning about red flags or scams appeared in 22.2%.

On structuring the decision, a selection-criteria checklist showed up in 51.1% of answers on average and a recommendation to gather multiple quotes in 4.5%. The single least-reproduced protective signal for craft businesses is "recommends multiple quotes" 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 Craft Businesses providers?

For service providers the decisive question is whether these systems name anyone at all. Across 45 craft businesses answers, a specific provider was named in 15.6% of responses on average — roughly 0.4 distinct providers per answer. In practice the assistants behave far more as an explanatory layer than as a referral engine for craft businesses: visibility comes from being the reasoning a model reproduces, not from being the named recommendation.

The question set

What these 15 Craft Businesses questions cover.

The 15 questions behind every percentage on this page were drawn from real craft businesses (ecommerce / online retail; 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 craft businesses 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 2026-07-05, the figures describe this specific craft businesses 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 2026-07-05, 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 →