Measuring Visibility When There Is No Ranking

The results list had a position, and position 3 beat position 8. An AI answer has none: you either appear or you do not, and if you appear it is as one source among several. Since June 2026 Search Console shows impressions, but no clicks and no queries. Anyone who wants to know whether their brand turns up in answers has to survey it themselves – and there the method matters more than the result.

The survey you can repeat

The only value of such a measurement lies in comparison with yourself. For that, four things must be fixed and must not change:

• The question list. Ten to twenty questions phrased the way a customer would ask – not the way an SEO would. Exactly this list, every time.
• The models. Two or three, noted with their version. Swapping a model between two measurements makes the series worthless.
• The cadence. Monthly is enough. More often mostly measures noise.
• What gets counted. Brand mentioned, domain linked, position within the source list. Three numbers, not a feeling.

For the standardised part our LLM Brand Check does the job: same question, same model, same output – exactly the reproducibility a manual check in a chat window does not have.

Variance is the normal case

The same question asked three times yields three answers. That is not a defect, it is the design. Two consequences:

Repeat instead of asking once. Three runs per question, then note the hit rate – “mentioned in 2 of 3 runs” is a statement, “mentioned” is not.

Report a range, not a decimal. Turning 17 queries into “34.7 percent visibility” invents a precision the data does not support. “In roughly a third of cases, with clear variance between models” is more honest and just as usable for decisions.

What this measurement does not say

It does not say whether it produces revenue. It does not say how many people saw the answer. It does not say whether your text was the reason for the mention. Turning it into a channel report sells a guess as a number.

What it gives you is an early-warning value: if mentions fall across three measurements, something changed – in you, in the models, or in the competition. That is a reason to look closer, not a result.

The effort, honestly calculated

Twenty questions times three runs times three models is 180 queries a month. That is an hour of work or a small script – and it is more substance than any external study on “AI visibility”, because it is imprecise about your brand rather than about the market.