AI Visibility Assessments

An AI Visibility Assessment is the recurring measurement layer beneath a GEO program. It tracks how often your brand is mentioned, cited, ranked, and described favourably in AI answers over time — per platform, per prompt cluster, and against a fixed competitive set — so visibility becomes a trend rather than an anecdote.

What we measure

Four metric families: mention rate (how often you appear at all), citation share (how often your own domain is the cited source), answer position (whether you are named first, in the middle, or as an afterthought), and sentiment and framing (whether the model describes you as the safe enterprise choice, a niche option, or something inaccurate). Each is broken down per platform, because Perplexity and ChatGPT do not weigh the same signals and rarely move in step.

How assessments run

We fix a prompt panel and a competitive set at the start so that results are comparable over time, then re-run the panel on a defined cadence — monthly for fast-moving categories, quarterly for stable ones. Responses are logged with their citations, so when a number moves we can point to the specific change: a new third-party article being cited, a competitor's fresh comparison page, a knowledge-graph correction taking effect. Additions to the prompt panel are versioned rather than silently swapped in.

How teams use the output

Marketing leaders use the assessment as the scoreboard for the GEO program and as an early-warning system: a sudden drop in citation share usually means a source that was carrying your brand has been displaced. It also settles internal arguments — instead of debating whether AI matters in your category, you have a measured share-of-voice figure and a competitor curve next to it.

Ready to see where ai visibility assessments would move the needle?

Start with a GEO Audit scoped to your category, prompts, and competitive set.