Documented protocol · 2026-07 edition

How the AI SEO Statistics study is run.

Every percentage published in this research traces back to a stored, auditable AI response. This page documents the full protocol — sampling, collection, coding, QA, and limitations — so any figure can be evaluated on its method, not on trust.

Protocol

Five steps, frozen per edition.

1 · Question bank

Real buyer questions, frozen per industry

Each industry gets a bank of standardized buyer questions covering discovery, DIY-vs-hire, vetting, pricing, comparison, local availability, urgency and red-flag scenarios. Banks are frozen per edition so editions are comparable; the exact questions are published on each industry page.

2 · Collection

One response per model per question

Every question is asked once to each model (chatgpt: gpt-5-mini · claude: claude-sonnet-5 · gemini: gemini-3-flash-preview), with identical wording, in a fresh context, within the same collection window. No retries, no cherry-picking: the first response is the recorded response.

3 · Coding

A fixed 12-behavior rubric

Each stored response is coded against the same 12 binary behaviors (definitions below). Percentages are simple proportions over the industry’s question set — no weighting, no modeling.

4 · QA

Human review before publication

Coded results are checked for consistency (cross-model and cross-industry), and every published headline number is re-verified against the underlying responses before an edition goes live.

5 · Editions

Same URLs, quarterly refresh

The study is re-run on a set cadence with the same protocol. Pages update in place — URLs never change — and prior editions are retained so behavior deltas can be reported over time.

Audit trail

Raw responses are stored

The full text of every AI response is archived per question and per model. Any published statistic can be traced to the exact responses that produced it.

Rubric

The 12 coded behaviors.

BehaviorCoded as present when…
Recommends hiring a professionalThe answer advises engaging a professional rather than (or before) self-service.
Suggests DIY firstThe answer proposes trying a do-it-yourself route before hiring.
Names specific providersThe answer names at least one identifiable brand, company or practitioner.
Gives price or cost infoThe answer includes price points, ranges or cost frameworks.
Tells to check reviewsThe answer instructs the buyer to consult reviews or ratings.
Tells to verify credentialsThe answer instructs verification of licenses, certifications or affiliations.
Mentions case studies / portfolioThe answer suggests asking for past work or documented outcomes.
Mentions local proximityThe answer weighs geographic closeness in the choice.
Gives selection criteriaThe answer provides an explicit checklist for choosing a provider.
Warns about red flags / scamsThe answer warns about fraud patterns or warning signs.
Asks a clarifying questionThe answer asks the buyer for more context before advising.
Recommends multiple quotesThe answer advises comparing several providers or bids.

Limitations

What these numbers are — and are not.

AI outputs vary with model version, location, personalization, retrieval mode and time. Figures describe a defined sample within a defined collection window — a controlled snapshot, not an absolute or permanent ranking. Sample sizes are published with every statistic (current edition: 547 questions, 1,641 responses across 14 industries). Where we publish composite industry benchmarks, they are always labeled “Estimated” and kept visually separate from measured results.

Citation license

These statistics are free to cite with attribution and a link.Authority Specialist. “AI SEO Statistics (2026-07 edition).” AuthoritySpecialist.com. https://authorityspecialist.com/research/ai-seo-statistics/methodology