Definition
AI visibility is to answer engines what search rankings are to Google - the observable, trackable presence of your brand inside the outputs a buyer sees. It answers a simple question: when the market asks AI about your category, are you in the answer, and how favorably?
The four core metrics
Serious AI visibility programs standardize on four metrics. Together they describe both the breadth and quality of your presence across engines.
- Prompt coverage - % of tracked prompts where your brand appears
- Mention share - your brand's share of all brand mentions across the prompt set
- Citation share - % of AI citations pointing to your domains
- Sentiment - how favorably your brand is described in AI answers
Building a prompt set
The prompt set is the foundation. A weak or unrepresentative set produces vanity metrics. Build it from real buyer language: sales call transcripts, support tickets, community threads, and competitor keywords.
- 30-100 prompts covering the full buyer journey
- Mix category, comparison, alternative, and use-case prompts
- Include long-tail phrasing, not just head terms
- Refresh quarterly as buyer language evolves
Cross-engine measurement
Each engine has different retrieval behavior. ChatGPT weights authoritative sources and its own training data. Perplexity leans on freshly indexed, well-cited pages. Gemini blends Google's index with generative synthesis. Measuring only one engine gives a partial view.
From measurement to action
Metrics without a workstream are noise. Pair each metric with an owner and a lever: coverage gaps -> content and prompt-targeted pages; low citation share -> PR and Reddit/YouTube seeding; negative sentiment -> messaging and review response.