Attribution / 10 September 2026 / 4 min read
You cannot prove AI visibility drove revenue, and you should stop trying
The honest version of attribution is weaker than what vendors promise and considerably more useful.
Every practitioner working on AI visibility eventually gets the same question from a CFO or client: what did this produce? It is a fair question and the usual answers are dishonest.
Why the attribution genuinely breaks
Someone asks an assistant which tool to buy. It names three, including you. They do not click a link because there often is not one. Days later they type your name into a browser or go straight to your site.
Your analytics records direct traffic or branded search. The AI answer that created the demand is invisible, and no amount of modelling recovers a touchpoint that was never instrumented.
What vendors claim anyway
Some tools show revenue attributed to AI visibility. Ask how it is calculated and the answer is usually a correlation between a visibility score and a revenue line during a period when many other things changed.
That is not attribution. It is two charts on the same axis.
The honest claim, which is still worth having
You can establish, with sample sizes stated:
- Whether visibility moved, on which engines, and in which specific questions.
- What you changed and when.
- Whether connected questions and sources moved differently from those that were not connected.
That is co-occurrence, not causation, and it should be labelled as such. It is also enough to decide what to do next.
A better question than “what did it produce?”
Ask instead: are we named in the answers our buyers get, more often than last month, in the questions that matter most?
That is measurable, honestly. Revenue attribution for this channel is not, yet. Pretending otherwise costs credibility the first time someone checks the working.