Guide
Reporting AI visibility upward
A credible AI visibility report shows share of voice against named competitors on a fixed question set, the change since the last period, and the specific work behind that change. Every figure should be openable — a number nobody can interrogate does not survive its first challenge.
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Lead with share, not with visibility
Visibility alone invites the obvious question: compared with what? Share of voice carries its own denominator, so it answers that before it is asked.
Show it against named competitors on the same questions. The comparison is the story; the absolute number rarely is.
Make every figure traceable
Keep the answers behind the numbers. When someone disputes a claim — and they will — opening the actual response an engine wrote ends the discussion in seconds.
This is also the honest constraint on how you report. If a figure cannot be traced back to stored answers, it should not be in the pack.
Report the trend, and name the variance
Answers are generated fresh and are not deterministic, so a single scan moves for reasons that have nothing to do with your work. Say so, and show the line rather than the point.
Naming that limitation early buys credibility for everything else. A report that admits what it cannot prove is far harder to dismiss than one that overclaims.
Questions
What cadence works for leadership?
Monthly for the report, weekly for the measurement underneath it. Reporting as often as you measure turns normal variance into a discussion every week.
Should we report traffic from assistants?
Include it, but do not lead with it. Assistant referral volume is modest next to organic search, and the recommendation itself is the outcome the traffic only partially reflects.
How do we show ROI?
Tie movement to the specific work that caused it — a corrected fact, a citation earned — and to pipeline where the attribution genuinely exists. Modelled attribution on small referral volumes tends to collapse under scrutiny.
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À lire ensuite
Measuring AI share of voice
What share of voice means in AI answers, how to calculate it honestly, and why the denominator is the part most people get wrong.
Building an AEO strategy
How to sequence answer engine optimization work so the fast wins come first and the slow compounding work starts early.
Running an AI visibility audit
A first pass at finding out what AI assistants say about your brand: what to check, in what order, and what the results mean.
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