What should an AI visibility report include?

An effective AI visibility report should show where your brand appears in AI answers, how it is described, which sources influence that visibility, how you compare with competitors, and whether it affects business outcomes. For a marketing team, it should be more than a single “visibility score”: it must connect prompt-level evidence to prioritized actions.

Recommended report structure

1. Executive summary

Start with a one-page overview containing:

• Overall visibility or share-of-voice score.
• Change since the previous period.
• Most important gains and losses.
• Competitive position.
• Top three recommended actions.
• Business signal, such as AI-referred traffic, leads, or conversions, where reliable data exists.

Leadership should be able to understand the current situation in under two minutes. Strong reporting frameworks typically organize the summary around current state, trend, competition, and business impact.

2. Scope and methodology

Make the measurement reproducible. State:

• Reporting period and comparison period.
• AI platforms tested, such as ChatGPT, Google AI Overviews, Gemini, Perplexity, and Claude.
• Locations, languages, devices, and personalization settings.
• Prompt categories and funnel stages.
• Number of runs per prompt.
• Whether results were manually reviewed or collected through an API.
• Definition of each metric.
• Limitations, such as model variability or changing search results.

Without this section, month-over-month changes can be misleading because the prompt set or platform coverage may have changed.

3. Prompt inventory

Show the exact questions being monitored, grouped by:

• Brand and product queries.
• Category and solution queries.
• Problem-aware questions.
• “Best,” “top,” and comparison queries.
• Competitor queries.
• Local or regional queries.
• Awareness, consideration, and purchase-stage prompts.

For each prompt, record the platform, date tested, response, brand presence, competitor presence, cited sources, and recommended action. Segmenting by platform, topic, and funnel stage prevents an aggregate score from hiding important gaps.

4. Visibility and prominence

Do not treat every mention as equal. Report:

• Mention rate: percentage of responses that mention the brand.
• Recommendation rate: percentage that actively recommend the brand.
• Share of voice: your visibility relative to the tracked competitor set.
• Prominence: whether the brand appears first, in a shortlist, mid-answer, or only at the end.
• Prompt coverage: percentage of priority prompts where the brand appears.
• Platform breakdown: performance by AI engine.
• Topic breakdown: performance by category or product.
• Funnel breakdown: performance by buyer stage.

A brand named first in an answer has a different commercial value from one briefly mentioned at the bottom, so prominence should be reported separately from presence.

5. Accuracy, sentiment, and positioning

Analyze how the AI describes the brand:

• Factual accuracy.
• Positive, neutral, or negative sentiment.
• Key attributes associated with the brand.
• Product strengths and weaknesses mentioned.
• Incorrect claims or outdated information.
• Whether positioning matches your intended brand strategy.
• Whether the brand is framed as a leader, alternative, budget option, specialist, or irrelevant result.

Include representative answer excerpts, not just scores. For example:

“Frequently recommended for enterprise analytics, but rarely mentioned for small-business use.”

That tells the marketing team more than a generic sentiment score.

6. Citations and source influence

This is one of the most actionable sections. Track:

• Citation frequency.
• Citation share versus competitors.
• Pages and domains cited.
• Owned versus third-party sources.
• The pages cited for each prompt.
• Whether cited pages contain accurate, current information.
• Missing or weak sources where competitors are cited instead.
• Common source types: review sites, directories, publishers, forums, documentation, and social platforms.

Separate brand mentions from citations. A model may mention your company without relying on your website, while a citation shows that a source helped support the answer. This distinction is central to diagnosing whether the problem is brand awareness, content quality, authority, or discoverability.

7. Competitive benchmark

Use a fixed competitor set and the same prompt set for every reporting period. Include:

Dimension	Your brand	Competitor A	Competitor B
Mention rate	—	—	—
Recommendation rate	—	—	—
First-position rate	—	—	—
Citation share	—	—	—
Positive-accuracy rate	—	—	—
Priority-prompt coverage	—	—	—

Also identify:

• Prompts where competitors replace your brand.
• New competitors entering AI answers.
• Topics where you lead.
• Topics where you are absent.
• Sources that competitors receive citations from but you do not.

8. Trends and changes

Show at least three to six reporting periods where possible. Chart:

• Visibility and recommendation rates.
• Citation share.
• Sentiment and accuracy.
• Platform-specific performance.
• Prompt-cluster performance.
• Competitive rank.
• AI-referred traffic and conversions.

Explain why movement occurred. For example, a decline may result from a competitor gaining citations, a source being removed, a product page becoming outdated, or a change in the tracked prompt mix.

9. Business impact

Connect visibility to outcomes without overstating causation. Include:

• AI-assistant referral sessions.
• Visits to AI-cited pages.
• Branded search growth.
• Assisted conversions.
• Leads or sign-ups.
• Pipeline or revenue influenced by AI discovery.
• Conversion rate for AI-referred traffic.
• Performance of pages cited in AI answers.

Keep AI visibility metrics separate from ordinary organic traffic metrics, especially where AI Overviews or AI Mode are mixed into search reporting.

10. Evidence appendix

Include enough raw evidence for someone to audit the conclusions:

• Exact prompts.
• Platform and test date.
• Full or relevant answer excerpts.
• Mention and recommendation classification.
• Citation URLs.
• Competitor appearances.
• Screenshots where useful.
• Scoring rules.
• Any excluded or anomalous results.

This is particularly important because AI responses vary between runs and platforms.

Prioritized action plan

End with a short action table:

Priority	Finding	Recommended action	Owner	Expected signal	Deadline
High	Competitors are cited for category prompts	Improve comparison and category pages; pursue relevant third-party coverage	SEO/content	Higher citation share	Next period
High	Product description is inaccurate	Update structured product information and authoritative pages	Product/content	Higher accuracy rate	30 days
Medium	Strong ChatGPT visibility but weak Gemini visibility	Review platform-specific source gaps	SEO/PR	Improved platform coverage	60 days

Every recommendation should tie back to a measured finding. Avoid generic suggestions such as “publish more content.”

Best format for your team

For a recurring marketing report, I’d use:

1. One-page executive dashboard.
2. Three to five pages of analysis covering visibility, positioning, citations, and competition.
3. A prioritized action plan with owners and deadlines.
4. An evidence appendix containing prompt-level results.

The central principle is: report presence, prominence, accuracy, citations, competition, and business impact separately. A single blended score is useful for a headline, but not sufficient for deciding what your marketing team should do next.