AI visibility
If the decision happens inside an AI answer, then citations are the new rankings and your analytics are half-blind. AI visibility is the scoreboard that tells you whether AI actually recommends you, for the questions that matter.
Why it exists
You cannot manage what you cannot see
The hardest part of AI search is that the most important moment is invisible to your old tools. A buyer asks an assistant, it names two or three brands, the buyer acts. No ranking changed that you can see. No session hit your analytics. If you only watch traffic, you are flying blind through the exact place your customers now decide.
AI visibility fixes that by measuring presence in the answer itself. It is the measure layer of agent legibility, and the only honest way to know whether your AI search optimization is working.
The metrics
What to measure instead of sessions
| Metric | The question it answers |
|---|---|
| Citation rate | How often do AI answers reference us at all? |
| Share of voice | Across our buyers' prompts, how present are we versus competitors? |
| Sentiment | When we are named, how are we described? |
| Agentic referrals | What traffic and revenue can we trace back to AI sources? |
Share of voice is the one to anchor on, because it is comparative and prompt-specific. Being cited a lot for questions nobody asks is vanity. Being the recommended option for the questions that precede a purchase is the whole game.
How to track it
From a prompt set to a dashboard
Start by writing down the prompts your buyers actually use, the questions that lead to choosing someone like you. Run them across the major assistants on a regular cadence and record whether you appear, how, and next to whom. For a focused set you can do this by hand with our free AI visibility tracker. To monitor it continuously and at scale, a dedicated platform is worth it: see our breakdown of AI visibility tools. For the mechanics of attributing citations, read how to track AI citations.