How to measure AI visibility (and not fool yourself)

You fixed your data and you want to know if it worked. AI visibility is measurable, but one reading tells you little. Track it over time and per assistant. The steps below show how to do it without fooling yourself.

What "AI visibility" means

It is how often AI assistants mention, cite or recommend you when someone asks a question in your category. People shorthand it as AI share of voice: the percentage of answers in your category that name your brand, relative to everyone named.

Three words that get muddled:

• Mentioned: the assistant names you in its answer.
• Recommended: it puts you forward as a good option, not just a name in a list.
• Cited: it uses your page as a source, usually with a link.

You can be recommended without being cited, or cited without being recommended. They are different wins, so track them separately.

The method

You do not need a lab. You need a repeatable panel of questions:

1. Write buyer-intent prompts. Ten to twenty to start, the real questions your customers ask: "best waterproof hiking boots under 150", "which running shoe for flat feet". More prompts give a steadier reading.
2. Ask each assistant. ChatGPT, Perplexity and Gemini retrieve and evaluate sources differently, so run the same prompts on each and record per assistant. The overlap between what ChatGPT and Perplexity cite is small, so an average across them hides more than it shows.
3. Record what you see. For each answer: were you absent, mentioned, recommended or cited? If cited, which page? Where in the answer did you appear? Being named first carries far more weight than fifth.
4. Repeat and watch the trend. Run the same panel on a schedule. One run is a snapshot, not a verdict, and the sources assistants pull from shift a lot month to month.

The trap: conclusions from one measurement

Answers vary between runs of the same prompt, so a single good or bad result is noise. Watch consistency: how reliably you show up across repeated tests of the same question. Low consistency means the assistant has a weak link between your brand and the topic, which is a data and content problem, not luck.

From measuring to fixing

The visibility number shows the result. Structured data, identifiers and feeds are what move it. If the number is low, the fix is usually upstream: missing schema, weak identifiers, or a retrieval crawler that cannot read you. Start by finding those gaps with a free store check, then track the trend as they close.

This is what our AI answer monitoring does: it runs a panel of questions about your products and category across assistants and tracks whether you are mentioned and recommended over time, so you are not copy-pasting prompts by hand. Product monitoring comes with every paid plan and brand monitoring with the Agency plan. See the plans, and for the fundamentals, what AEO is.