AI visibility reporting template for GEO and AEO

Use this structure for a client update, a marketing review, or a product discussion. Keep the opening to the findings that need a decision.

The report should make it possible to trace a percentage back to its sample and an interpretation back to the actual answer. Put remaining uncertainty beside the conclusion it affects.

Worked example

Start with

Use the outline below for a monthly review or client update. Replace every bracketed field. Keep the conclusion short enough to read before opening the detailed evidence.

Read the evidence

The completed example uses 64 mentions from 140 answers, compared with 52 from 140. Both periods contain the same number of answers. The highlighted answer supports the proposed topic to investigate; it does not prove why the aggregate number changed.

Make the decision

Separate the observed change, your interpretation, and the action requiring agreement. Give each action an owner and a review date. If the prompt set or platform mix changed, say so before comparing percentages.

Take this away

Copy the outline into your own document. Keep answer references and cited URLs with each finding so a colleague can reproduce the reasoning. Remove a proposed action if you cannot explain which evidence made it relevant.

Reusable outline

Download text

AI VISIBILITY REPORT
Brand / workspace: [name]
Period and comparison: [dates]
Question set, platforms, language, market: [scope]
Collection coverage: [planned / completed / failed]
Result: [answers mentioning brand] / [total answers] = [rate]
Change: [percentage points, comparable periods only]
Finding: [one observed change]
Evidence: [question, answer reference, exact passage, cited URL]
Interpretation: [what the evidence suggests; remaining uncertainty]
Action: [specific work]
Owner and review date: [name, date]
Sample changes and limitations: [what affects comparison]

Completed report

Download text

AI VISIBILITY REPORT
Brand: Klaviyo
Period: August vs July 2026
Scope: Same ten ecommerce questions, two platforms, seven collection days in each period
Coverage: 140 collected answers per period
Result: 64 / 140 = 45.7%; previously 52 / 140 = 37.1%
Change: +8.6 percentage points
Finding: The example recommends ecommerce automation and flags Mailchimp pricing.
Evidence: The example email-platform question; Klaviyo recommendation and Mailchimp warning.
Interpretation: Pricing deserves investigation. This does not establish the cause of the aggregate rise.
Action: Draft a transparent contact-list cost comparison.
Owner: Content lead (to assign)
Review: Next monthly review; retain the original prompt set.

What to put in the report

Open with the headline visibility score and why it changed.
Show 2-3 prompt examples with source evidence.
Explain competitor movement in the same review window.
End with a short action plan and owner.

Before you share

Reuse one format every week or month.
Keep screenshots secondary to prompt and citation evidence.
Send the report fast enough that teams can still act on it.

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