Make your brand the clearest source about itself.
Build consistent entity signals, verifiable claims and citation-ready pages so answer engines can represent the brand accurately.
Focus the GEO program on decisions that matter.
Build consistent entity signals, verifiable claims and citation-ready pages so answer engines can represent the brand accurately.
Entity clarity
Make products, people, claims and category relationships explicit.
Claim evidence
Connect important claims to product documentation, methodology and credible sources.
Narrative monitoring
Detect inaccurate summaries and competitor-framed descriptions early.
A practical path from signal to action.
Keep measurement comparable while giving each finding supporting evidence and a next check.
What decides AI visibility for brand sites
A brand site has no catalogue to mark up and no marketplace listing to fall back on. Its whole GEO problem is entity resolution: whether a model is confident about who you are, what you do, and which of the names in circulation refer to you.
| Ambiguity produces confident wrong answers | The common failure for brand sites is not silence but a plausible wrong detail: an outdated price, a market you left, a feature that belongs to a competitor. It traces back to one stale source more often than to any weakness on your own site. |
|---|---|
| One name, everywhere, or you split your own share | Spelling variants, a product line described as a separate company, a legal entity that differs from the trading name: each of these can appear as a separate brand in a share-of-voice table. The measurement is not wrong; the entity is. |
| Third-party corroboration outweighs your own pages | A model needs the same fact from independent places before it will state it confidently. A claim that exists only on your own domain is the weakest form of evidence you can offer, however well marked up it is. |
| Machine-readable identity is cheap and underused | Organization markup with a logo, a founding date and links to your official profiles, plus a public knowledge-graph entry, lets you state your own identity in a form machines already trust. It is one of the few levers a brand can pull without waiting for coverage. |
Start with these three
- Ask each assistant what your company does, and read the answer for wrong details rather than for whether you were mentioned.
- Check your own share-of-voice table for two rows that are actually the same brand.
- Publish Organization markup with sameAs links to every official profile you control, and claim a public knowledge-graph entry.
See the question, answer status and evidence together.
Sample UI demonstrates the evidence depth of a formal project.
Visibility evidence
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Questions teams ask before they start
Does a snapshot replace onboarding?
No. A snapshot is a limited sample. A formal project still needs confirmed markets, competitors and monitored prompts before continuous measurement begins.
Will snapshot data be charged twice in the App?
Not by default. Claimable snapshot results can be inherited, while a new formal run starts only after onboarding is confirmed.
Can teams measure more than one market?
Yes. Markets and languages should be treated as separate measurement segments so results remain comparable.
How long before results are meaningful?
A single run gives a baseline. Trends need several runs, because one sample cannot separate a real change from model variance.
What is actually needed to get started?
One domain. The brand profile, traceable facts and buyer questions are generated from it and stay editable before any formal run.
Who on the team uses this day to day?
Usually whoever owns content and organic growth. The measurement side needs no engineering work, and publishing always stops at a human approval step.
Turn AI visibility into a repeatable growth system.
Create a project, confirm your market and start measuring the questions that matter.