The value of AI visibility work only becomes visible when it’s reported properly. A good report shows clearly on which question, on which platform and how much you’ve progressed — instead of vague phrases like “things are going well”.
Core metrics to track
- Mention rate: What share of the questions in your panel mention your brand.
- Citation rate: How often your site is shown as the source of the answer.
- Share of answer: Your total share in answers compared to competitors.
- Accuracy and tone: Whether your brand is conveyed accurately and positively.
- AI traffic: Visits and conversions coming from answer engines.
- Lead impact: How visibility shows up in forms, calls and sales.
What does a good report look like?
- Comparative. It compares this month with last month and with competitors; it shows the trend.
- Concrete. It speaks through specific questions and platforms rather than general statements.
- Honest. It shows losses and variability alongside gains.
- Actionable. It answers “what’s next”; it offers a priority list.
Dashboard + executive summary
The most effective approach combines the two: a live dashboard shows what changed in real time, while a monthly executive summary answers “what did we do this month, what did we gain, what’s next”. The dashboard gives the data, the summary gives the context.
What to avoid
- Building the dashboard with bias to make metrics look good.
- Reporting only won questions and hiding losses.
- Not stating the limits of traffic data (zero-click).
Honest reporting is a core principle of our visibility measurement service.
Summary
AI visibility should be reported with mention, citation, share-of-answer, traffic and lead metrics, through a comparative and honest dashboard + executive summary. To see what a sample report looks like, you can start with the analysis.