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In-app Reports

Review GEO progress inside the workspace.

Generate and review in-app reports covering visibility, citations, competitor context and knowledge gaps.

Delivery Inside the App
Visibility Cross-engine summary
Evidence Citations and answers
Context Competitors + knowledge
Core capability

What In-app Reports helps the team understand.

Generate and review in-app reports covering visibility, citations, competitor context and knowledge gaps.

01

Visibility review

Summarize the measured sample and per-model results.

02

Citation analysis

Review source domains, cited pages and question-level evidence.

03

Knowledge gaps

Connect weak answer coverage to missing brand facts.

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
Reuse existing measurementsGenerating a report does not need to rerun every AI question.
02
Show sample limitsReport conclusions remain tied to the measured question set.
03
Keep delivery in-appThe current product supports in-app reports only.
Illustrative product evidence

Move from summary metrics into the underlying question.

Sample data demonstrates the evidence depth of a formal project.

InsightWonder / In-app Reports 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 In-app Reports

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 In-app Reports into a complete GEO workflow.

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