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Every tool counts mentions. Then what?

MentionBeat is the GEO platform that answers what comes after the rate every tool reports — whether it moved, what moved it, and what to publish next.

After the number

The four questions a rate cannot answer

  • Is this change real, or inside the noise?
  • Which page or source caused it?
  • What should we publish next?
  • Did last month’s work measurably do anything?

Answering these is the whole product. Counting is the easy half.

Trackers tell you the score. MentionBeat moves it.

Category norms as of mid-2026. Tools evolve — treat this as a checklist for evaluating any of them, including us.

What you getVisibility trackersMentionBeat
Mention, citation and recommendation tracking across the major enginesYesYes
Confidence intervals on every number — so you can tell movement from noiseRareYes, on every headline rate
A prioritised fix queue — findings become tracked workUsually notYes, and it closes only on a passing re-check
Content production — verified facts into GEO-scored, publishable pagesUsually notYes, scored 0–100 before it ships
Corrections — drafted requests for wrong facts on pages you do not ownUsually notYes, verified by re-reading the page
Experiments — baseline, change, treatment, attributed liftUsually notYes, with the null results reported too
A published score formula — the arithmetic behind the headline number, so you can recompute itRareYes — 0.4 share of voice + 0.4 mention rate + 0.2 recommendation
Published methodology, including its limitsVariesPublic, no account required

Evaluating a specific tool? Hold it to the six-point measurement bar we publish and meet — or ask us and you will get a straight answer, including where we lose.

Numbers built to survive scrutiny

The reason to care about the statistics is not elegance. It is that someone senior will eventually ask whether the number is real, and you need an answer better than "the dashboard says so".

8
engines and answer surfaces on one schedule — queried directly, never inferred from search rankings.
each prompt asked repeatedly, per engine. One answer is an anecdote; a sample is a measurement.
95%
confidence interval on every headline number — a change is flagged only when it clears the noise.
2,000
bootstrap resamples behind every interval, clustered by prompt rather than pooled.

The honesty architecture

This is the part we would keep if we had to drop everything else. In a category this new, the easiest thing to sell is a confident number, and the most valuable thing to own is a number you can defend.

  • Every result is labelled live, modeled or estimated — in the product and in our marketing
  • Gaps are reported as gaps — an engine we could not reach says so instead of being averaged away
  • Null results are published — an experiment that found nothing says it found nothing
  • No invented statistics — if a number is ours it came from a run; if it is not, it is cited and dated
  • The method is public, limitations section included
  • We audit ourselves — mentionbeat.com is graded by our own scorer on every change, and a page below 85 does not ship

What we will not do

Stated plainly, because the category is full of quiet over-promises:

  • Claim we can delete something from a model's memory
  • Guarantee a position in an AI answer
  • Attribute revenue to a mention we cannot trace
  • Show you an estimated number styled as a measured one
  • Write to your website without a connection you configured

If any of these is a requirement, we are not the right tool, and you should be suspicious of whoever says yes.

When someone asks "did any of this work?", you open Experiments.

Every shipped change measured against its own baseline. The answer is a number with a confidence interval — not a hunch, and not a screenshot.

Fair questions

How do you compare to a specific tool?
We describe categories rather than name rivals, because a dated claim about a competitor is out of date within a quarter and unfair by the time anyone reads it. Hold any tool you are evaluating — including this one — to the six-point measurement bar we publish, and ask for a straight answer where it falls short.
Why does the confidence interval matter so much to you?
Because without one you cannot tell a real improvement from the natural variance of a stochastic system. A tool that reports mention rate moved from 41% to 47% with no interval has told you nothing about whether anything happened, and teams have reorganised quarters around exactly that kind of noise.
What are you deliberately not good at?
We do not do social listening, PR distribution, or classic rank tracking, and we do not claim to edit what a model remembers. We are narrow on purpose: measure AI answers rigorously, produce the changes they imply, and prove whether those changes worked.
Can I see the methodology before buying?
Yes, all of it, without an account — including the limitations section. If a measurement vendor will not show you how the number is produced before you pay, that is the answer to your evaluation.

Judge it on your own data.

The free tier runs a real suite across every engine. No card, and the methodology is public before you start.