What the audit measures
AI visibility is not one metric. A brand can be mentioned but misrepresented, cited without being recommended, recommended without receiving a citation, or absent from an important part of the customer journey. The audit records these conditions separately so the findings remain interpretable.
The prompt sample is designed around real audience decisions. It can include discovery, comparison, validation, troubleshooting and purchase questions, with important variations documented rather than selected after the answers are seen.
A baseline with boundaries
AI outputs can vary by model, time, location, account state and phrasing. The audit records the environment, date, prompt and sampling method. It does not pretend that a limited observation is a permanent universal result.
- Share of tested prompts in which the brand appears
- Recommendation position and competitors mentioned alongside it
- Cited URLs, domains and recurring source types
- Accuracy and consistency of important brand claims
- Topic and journey gaps
- Owned-page technical eligibility and retrievability
- Signals from reviews, reference sources and earned coverage
From observation to action
Findings are grouped by the team able to act: technical, content, digital PR, product, brand or analytics. Recommendations explain the supporting evidence and expected mechanism rather than attaching certainty to an opaque model.
The repeat-measurement specification is part of the deliverable. It defines which prompts should stay stable, what can change, how results will be recorded and which changes are large enough to investigate.
A useful first engagement
The audit works well as a defined starting project. It can stand alone, feed a broader AI-search strategy or become the baseline for a programme delivered by an internal team or agency.
What you receive
- Prompt universe and sampling approach agreed before measurement
- Visibility, inclusion, citation and message analysis
- Competitor and source comparison
- Technical and content eligibility review
- Findings deck with evidence and limitations made explicit
- Prioritised improvement plan and repeat-measurement specification
What the work is designed to change
- A defensible starting point for an AI-search programme
- Evidence that leadership and delivery teams can interrogate
- A clear distinction between visibility, sentiment, citation and referral traffic
- A measurement process that can be repeated after changes
Common questions
What is an AI visibility audit?+
It is a documented assessment of how a brand, product or topic appears in relevant AI-assisted searches. A useful audit examines inclusion, recommendations, descriptions, citations, competitors and the sources that may be shaping the result.
Which AI platforms do you test?+
The platform set is agreed around the audience and market. It can include Google AI features and major conversational assistants, with versions, dates and test conditions recorded.
Can the audit be repeated later?+
Yes. Repeatability is designed into the baseline, including the prompt sample, collection method, measures and known limitations.