What gets measured
| Layer | Method | Output |
|---|---|---|
| Answer presence | Systematic prompting across engines on your question set, tracked over a window - not one-off screenshots | Mention rate, share of voice, sentiment, position when named |
| Competitor citations | The same question set, scored for who gets cited instead | Who owns each question, and with which page formats |
| Crawler reality | Your server logs, analyzed for AI bot activity (GPTBot, PerplexityBot, ClaudeBot, Google-Extended and peers) | What the engines actually fetch - and what they are blocked from |
| Content liftability | Page-level review: is there a quotable answer, a verifiable claim, a clean structure? | Per-page citation-readiness scoring |
| AI-referred traffic | Analytics segmentation of AI referrers and dark-traffic patterns | The baseline for the only trend line leadership will ask about |
What the deliverable looks like
One document, evidence-first: every claim traces to a logged answer, a crawler log line, or an analytics segment. Findings rank by opportunity - the questions with buying intent where you are absent and a competitor is quotable - and every recommendation names its mechanism, so your team can execute without us if they choose.
House law applies here too: anything the audit could not measure is labeled an assumption, in the deliverable itself. An AI-visibility report full of unverifiable claims would be its own counterexample.
What usually surprises people
- How often AI crawlers were quietly blocked years ago by a blanket bot rule nobody revisited.
- How many of their category's questions carry zero search volume - invisible to every keyword tool they have ever bought.
- That a competitor's mediocre-but-well-structured guide outcites their excellent-but-unquotable one, consistently.