Loading...
A good AI Visibility report shows period, data basis, visible signals, open limits, actions and rechecks. It does not replace proof with invented testimonials and it does not guarantee AI recommendations.
Report content
Customers and agencies need to see which data went into the report and what was not measured.
The report stores a state instead of being reconstructed differently from live tables later.
Scanner, feeds, crawler signals, visibility runs, actions and rechecks are kept as separate sources.
The report states which providers, regions, prompts or data were not included.
Evidence
Evidence means observable technical or measurable signals. It does not create a guarantee, but it makes the current state traceable.
Status, validation, hashes, last build and reachable endpoints explain delivery.
Server-side access, bot name, feed type, IP state and hash state show observable access.
Answers, sources, mentions, competitors and share of voice are documented as measurement data.
Workflow
The report is the result of data, measurement and actions, not just a nice export.
Define data sources and period.
Collect scan, feed, crawler and visibility signals.
Add actions, rechecks and open limits.
Store snapshot.
Output report with data basis, results and next steps.
Informationsgrenze
The page must build trust without overstating the product legally or technically.
No. Reports document account or audit data. Case studies would be customer success stories and are not invented.
Because live data changes. A snapshot makes clear which state was exported.
No. It can document technical delivery, measurements, findings and tasks. External AI providers decide on usage and presentation.
The report should explain what is measurable, what is open and which task makes sense next.
View pricing