Help for the AI Visibility Audit

Enter the name your entity is known by — brand, person, product, event, or simply a domain. The clearer the term, the more reliably the audit identifies the intended entity.

For ambiguous names, the scout first asks which entity is meant. Use the optional context field to clarify market, role, or region so the analysis starts in the right meaning space.

The report separates what the model already "knows" without sources from what only becomes stable through current sources (grounding). This shows whether your visibility rests on learned knowledge or on current web sources.

High grounding need is not a bad sign but a signal: for new or fast-changing topics, consistent, current sources are the decisive lever.

In the tracking section you'll find real segment names. Enter one in the "Segment" field in Rankscale Prompt Research — it produces matching intents, prompts, and topics.

This turns the one-time snapshot into an ongoing tracking setup for observing visibility, citations, sentiment, and competitors over time.

Logged-in users: every analysis is saved to your archive automatically and can be reopened later under "Archive". You never lose an analysis.

Guests: save the analysis while it is visible by creating an account. Every saved audit is a stable snapshot, even if AI answers change later.

Grounding pages provide entities, roles, and key facts in a machine-readable way. They are a controllable source you can use to prove the intended role consistently and repeatedly.

They are especially effective for new, weakly anchored, or frequently confused entities. They do not replace brand building or tracking, but they create a stable factual basis for AI interpretation.