The four components
A real audit mirrors the free-scan deliverable. Each component answers a different question, and together they explain not just whether AI recommends you but why.
| Component | What it reveals |
|---|---|
| Baseline probe panel | Your real buyer questions run across the frozen five-engine panel, each sampled k times and scored mention / recommendation / absent — a gap map of which queries name competitors instead of you. |
| Retrieval & rendering | Whether pages are server-rendered and retrievable, whether schema is present, missing, or wrong-vertical, plus robots, llms.txt, and canonical hygiene. A page an engine cannot read cannot be cited. |
| Internal-link topology | How your pages link to each other — the strongest on-page lever we measure. Orphaned pages rarely get cited; well-linked pages do. |
| Competitor context | How rivals score on the same queries, so each gap reads as a specific business someone recommends over you, not a blank. |
Why the probe panel is the core
The panel is the instrument. It is frozen so results are comparable run to run: the same five engines (ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews), the same buyer questions, each sampled k times because a single answer is noisy. Sampling several times turns a coin-flip into a rate.
Every query gets scored mention, recommendation, or absent. Roll those up and you get a per-engine visibility rate plus a gap map: the specific questions where an engine names a competitor and never you. That map is what the rest of the audit exists to explain and the fix list exists to close.
k = the number of times each query is sampled per engine. Rates, not single answers.
Why retrieval and links decide the outcome
An engine can only cite a page it can retrieve. The rendering check catches the silent failures: content that only exists after client-side JavaScript, missing or wrong-vertical schema, a robots or canonical setup that hides the page. These are cheap to fix and gate everything else.
Internal links are the strongest on-page lever we have measured. In a 91-post audit, pages with zero inbound internal links were self-cited about 4.5% of the time; pages with ten or more inbound links hit roughly 44%. Topology is why two pages with similar content get cited at wildly different rates.
Common questions
How is an audit different from the free scan?+
The free scan runs a slice of the probe panel on your domain so you can see the gap map on a live engine. A full audit adds the retrieval and rendering check, internal-link topology, competitor context on the same queries, and a prioritized fix list.
Which engines does the panel cover?+
A frozen five-engine panel: ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. It is frozen so scores are comparable from one run to the next.
Why sample each query more than once?+
A single AI answer is noisy — the same question can name a competitor one time and you the next. Sampling each query k times turns that into a stable rate you can track and improve.
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