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Research

AI visibility research

The public methods and owned scan evidence below show how VisiScan records buyer-intent answers, mentions, competitors and cited domains. Every page states its measurement basis and limitations.

Quick answer: what the research shows

The current public evidence includes one owned-domain scan, 30 raw answer observations, 15 matched sample pairs and a 40-case entity-matching benchmark. No qualified industry source map is presented until its consent and sample requirements are met.

Measurement methods

Public sample report

A real owned-domain scan with exact prompts, engine coverage, raw answers and limitations.

Branded-prompt bias

A calculation showing why recognition and discovery need separate denominators.

AI Visibility Index

Dated, consented measurements grouped only when their questions, markets, models and sampling settings are compatible. A group needs at least ten businesses before it is shown.

View the Visibility Index →

First-party benchmark: VisiScan's day-one score

We pointed our own AI visibility audit at visiscan.app on the day the product started measuring real scans. The September 9 result contains 30 live answer observations across five questions and three available engines; Gemini was unavailable and excluded. The raw observations, data card, and score explanation are public.

How to use this data

The Visibility Index and citation source maps are free to browse. For most businesses, the most actionable path is:

  1. Check where you rank in the Visibility Index for your industry and country.
  2. Look at your industry's citation source map to see which domains AI engines trust — then make sure your business is listed and accurate on those sources.
  3. Run a free VisiScan on your own site to get your individual visibility and readiness scores, your top competitor, and your highest-impact fix.
  4. Subscribe to Monitor for weekly re-scans and trend tracking to catch changes before they cost you customers.
Run a free scan →