Public audit template

AI Visibility Audit Template

Use a public AI visibility audit template to document commercial questions, models, recommendations, citations, competitors, evidence gaps, actions, and retests.

How to use it

Complete one record per question, provider, model, date, and repetition.

Keep the raw answer and citation evidence beside this record in your working system. Separate what the answer did from why you think it did it. That distinction makes a review possible and prevents a proposed action from being mistaken for a measured fact. If you have not defined the question set yet, follow the guide to run an AI visibility audit for your brand before completing the worksheet.

Copyable worksheet

Start with the complete record.

AI VISIBILITY AUDIT RECORD

Company:
Market/category:
Buyer persona:
Commercial intent:
Question/prompt:
Provider/model:
Test date (UTC):

Mention (yes/no):
Recommended (yes/no):
Answer position:
Citations:
Owned citation (yes/no + URL):
Competitors considered:
Accuracy notes:

Evidence gap:
Confidence (low/medium/high + rationale):
Proposed action:
Owner:
Acceptance criteria:
Retest date:
Field guide

What to record and why.

Scope the decision

Company
The exact brand or product being measured.
Market
The category and boundaries used to decide which alternatives are relevant.
Buyer persona
The role, company context, and problem represented by the question.
Commercial intent
Discovery, comparison, validation, pricing, migration, or another stated decision.
Question / prompt
The exact tested wording. Do not silently rewrite it after seeing the answer.

Record the run

Provider / model
The named system and model identifier when available.
Test date
The measurement date and timezone, preferably UTC.
Mention
Whether the answer names the measured brand.
Recommended
Whether it presents the brand as a plausible option for the stated need.
Position
The answer order only when the format makes position meaningful.

Retain the evidence

Citations
Every source URL or source label surfaced with the answer.
Owned citation
Whether a citation belongs to the measured company, with the exact URL.
Competitors
Vendors considered for the same question—not every organization mentioned.
Accuracy
Claims that match, conflict with, or cannot be verified against current evidence.
Evidence gap
The smallest supported explanation for the observed recommendation difference.

Turn evidence into work

Confidence
Low, medium, or high, plus the evidence and repetitions supporting that judgment.
Proposed action
A bounded change tied directly to the gap; “publish more content” is not specific enough.
Owner
The person or team accountable for the action.
Acceptance criteria
The observable site, evidence, or answer condition that defines completion.
Retest date
When the same decision and recorded conditions should be measured again.
Review rule

Do not upgrade confidence without new evidence.

A clear-looking answer can still be unstable. Increase confidence only when repetitions, source evidence, and comparable provider runs support the same interpretation. Keep disagreements visible.

Automation boundary

Automate collection; review consequential interpretation.

RecoProof can automate the bounded crawl, question preparation, benchmark, extraction, and report assembly. Human review still matters when evidence is incomplete, category fit is ambiguous, or a proposed action could change positioning, pricing, or product claims.

Run this automatically with RecoProof