AI Visibility Audit

An AI visibility audit reads how much and in what way a brand appears in AI answers, using five measures: brand mentions, citations, sentiment, competitor share and the accuracy of information in the answer.

A brand mention tells you whether your name appears, and a citation tells you whether your page is shown as a source. The two are not the same. A brand can be mentioned without being cited, and a page can be quoted without the brand standing out.

That is why AI visibility cannot be expressed as a single position the way classic rankings are. Answer text is long and variable, so your place in a list says little on its own. The results become meaningful when read by question group and by platform.

A prompt set is a fixed list of questions users might actually ask, and it forms the basis of the measurement. Preparation starts with the brand's spelling variants, priority services and the competitors to compare against. Questions are grouped by informational, comparison and purchase intent.

Questions that include the brand name should be kept separate from category queries. The first shows only what the answer says, while the second shows whether the brand is remembered at all. Search data and the questions customer-facing teams hear bring the list closer to reality.

Digitruva submits the set for your approval before measurement and uses it unchanged in later rounds. Any new question is flagged separately, because changing the set breaks period-over-period comparison.

Because the results are a sample, not a count of the answers every user sees. They speak only for the selected questions and the repetitions run. Answers can vary by session, location and time, and models get updated too.

In chat, the same question also gets asked in different words, and earlier messages can shape the answer, so the set is only an approximation of real usage. That is why you should read ranges and trends instead of a single percentage.

Small differences may be noise, while change that repeats in the same direction means more. No direct cause-and-effect link can be drawn between visibility and sales either. The audit does not guarantee growth. It shows what is missing and where to start.

They show only part of it. According to Google's AI features documentation, Search Console counts AI Overviews and AI Mode data in the Performance report under the Web search type.

The Search Console generative AI report separates impressions on these two surfaces, but it only appears for sites with enough impressions and does not report clicks. Under Search Console's definition of position, all links in an AI Overview get the same position, so the position value should not be read like a ranking.

GA4 sees only visits from people who click through. If referral data is passed, the referring site shows up in the GA4 traffic source dimensions. If it is not, the visit can land in direct traffic. Unlinked brand mentions show up in neither tool. The prompt set fills that gap, while the measurement setup tracks visits and conversions.

Because the impact of work labeled AI SEO or ChatGPT SEO cannot be tracked without a baseline. Measurement also tells you what kind of problem you have. If the brand is never mentioned for category questions, the issue is usually content and off-site visibility.

If the brand is mentioned but misrepresented, outdated sources and inconsistent company information are reviewed. Pages where a competitor gets quoted reveal the missing content type. If the brand does not appear on Google surfaces, page indexing, snippet settings and the generative AI data in Search Console are reviewed as well.

Digitruva writes this distinction into the priority list and delivers the findings as input for the GEO optimization plan. That way the direction of the work is not left to guesswork.

Competitor share is the proportion of mentions and citations your brand and selected competitors receive within the same question group. The ratio holds only within the selected competitors and prompt set, and it does not mean market share.

That is why the topics a competitor leads on matter more than the overall count. Sentiment codes whether the brand is mentioned in a positive, neutral or negative context. Even when coding follows the same criteria, it involves interpretation, and borderline answers should be noted separately.

A recurring objection is a more valuable finding than a single negative sentence. Digitruva ties this reading to business decisions in the report. The findings feed marketing decisions alongside data from other channels.