Visibility tracking is the measurement layer that answers how often an assistant names you: your buyers’ real questions, run across every engine on a schedule, sampled enough to give a rate with an interval.
Visibility tracking is the measurement half of MentionBeat: a suite of the questions your buyers actually ask, run across every answer engine on a schedule, each prompt sampled several times so the result is a rate with a confidence interval rather than a screenshot. It answers the only question that matters at the start — when someone asks an assistant about your category, how often does your name come out, and is this week's change real? A run is a defined experiment, not a crawl. You control every part of it, and the console prices it before it starts.
MentionBeat reads your site, derives a product brief, and proposes prompts from it — grouped by buyer intent and journey stage, and tagged to an ICP. You approve, reword or retire each one. Reworded prompts are retired and re-added rather than edited in place, so a trendline never silently changes what it was measuring.
Each prompt is put to the engines you enable. Web-grounded engines search live and cost more; parametric ones answer from training alone. Both are worth tracking and they routinely disagree — the split is reported, never averaged into one misleading figure.
Every prompt is asked several times per engine. One answer is an anecdote; a sample is a measurement. The repeats are what make a week-on-week move interpretable instead of a coin flip.
Each answer is parsed for whether you were named, where you appeared, whether the mention was a recommendation, and how you were characterised. Rivals in the same answer are scored the same way, which is what produces share of voice.
Four rates and one roll-up. They move independently, and the differences between them are usually the interesting part.
| Metric | What it counts | What a drop usually means |
|---|---|---|
| Mention rate | Share of sampled answers that name you at all | You are missing from the retrieval set, or the category framing moved |
| Recommendation rate | Share of answers that name you as a suggested option, not just in passing | You are known but not preferred — usually a comparison or proof gap |
| Share of voice | Your mentions as a proportion of all brands mentioned | A rival got louder, even if your own rate held |
| Sentiment when mentioned | How you are characterised in the answers that do name you | A negative source is being retrieved and repeated |
| Visibility Index | A 0–100 weighted roll-up of the above — published arithmetic, not a black box | The one-line trend for a status update — always decomposable |
Every rate is reported with a 95% confidence interval built from bootstrap resampling, clustered by prompt. A change is flagged as movement only when it clears that interval.
Not every engine is equally steady, and the unsteady ones make a single run misleading. Each engine gets a volatility read from three things we already measure: how often repeats of the same question disagree, how far its mention rate swings between runs, and how much its cited sources churn.
Use it to decide where extra repeats buy you precision, and which engine's one-off number to treat with caution before you quote it in a meeting.
Each score names the components it stands on. Where a component cannot be computed — a memory-only engine cites nothing, so it has no source churn — it is left out rather than counted as zero.
A single headline rate hides the disagreement that makes the number actionable. Every metric can be broken down by:
Runs are scheduled on an interval you set — fortnightly by default, because page and retrieval fixes take days to land and that is the shortest gap where a change is usually real rather than noise. When a tracked rate moves beyond its interval, or a rival overtakes you on a prompt you used to win, you get told rather than discovering it a month later in a dashboard.
Alerts name the prompt, the engine and the size of the move, so the notification is the start of the investigation instead of a nudge to go and look.
On its own, no share-of-voice number answers that. So every measured project is placed against the others we measure — same suite construction, same judging, same repeat sampling — and you are told your percentile rather than left to guess whether your rate is strong or embarrassing.
Set a target on a metric — mention rate on a topic, share of voice, the index — with a date. Progress is not something you update in a spreadsheet: it reads from your runs, and a goal is only marked achieved by a measured run that clears it.
Because the benchmark knows what the cohort looks like, a goal can also be proposed rather than guessed: a target that would move you from the middle of the field to the top quartile is a more useful number than a round one someone picked in a planning meeting.
1,500 free credits is enough for a real first suite across every engine. No card, no site changes.