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AI Visibility

See whether AI names your brand when buyers ask.

Compare mention rates, original answers and competitor share of voice across the AI engines currently supported by InsightWonder.

Models Current engine set
Primary metric Mention rate
Evidence Original answers
Comparison Share of voice
Core capability

What AI Visibility helps the team understand.

Compare mention rates, original answers and competitor share of voice across the AI engines currently supported by InsightWonder.

01

Cross-engine view

Compare mention rates for the same questions across every supported model.

02

Question-by-model matrix

See exactly where your brand is absent, mentioned or recommended.

03

Original answer drilldown

Open the answer behind every result instead of trusting a score alone.

Operating model

Keep every result connected to evidence and action.

The product explains the result, preserves its source context and makes the next review explicit.

01
Confirm the formal question setOnboarding confirms market, language, competitors and usable questions.
02
Stream results as they finishA real multi-model run takes minutes and reports completed answers progressively.
03
Keep citations separateA cited page does not automatically count as a brand mention.
Illustrative product evidence

Move from summary metrics into the underlying question.

Sample data demonstrates the evidence depth of a formal project.

InsightWonder / AI Visibility Sample data

Visibility evidence

Last 30 days
AI visibility 34% +4%
Mentioned questions 10/29 +2
Share of voice 31% +4%
Cited pages 27 +9
Buyer question Brand status Evidence
Best modular sofa for a small apartment Gap Competitor cited
Most durable washable sofa under $2,000 Mentioned Product page
Low-VOC sofa for families Recommended Guide + review
FAQ

Questions about AI Visibility

Does this feature run from the public website?

No. Marketing pages explain the capability. Formal data collection begins only after a user enters the App and confirms the project scope.

Can snapshot results become part of this workflow?

Yes. A valid snapshot can be claimed as an initial sample, while onboarding still confirms markets, competitors and the formal monitored question set.

Are all metrics comparable across AI engines?

Core answer states can be normalized, but citations, search assistance and answer formats still need engine-specific evidence.

How often is the data refreshed?

Measurement runs on the schedule your plan allows, and monitoring quota is shared at the account level. Alerts require two consecutive runs to confirm, so model sampling noise does not become a false alarm.

Can the original AI answer be inspected?

Yes. Every result drills down to the answer that produced it, question by question and model by model, together with the citations found in that answer.

What happens when a model is unavailable?

That run is marked partial rather than being silently filled in. The remaining engines still complete, and the gap stays visible in the result.

From signal to action

Put AI Visibility into a complete GEO workflow.

Create a project, confirm your market and start measuring the questions that matter.