Mentioned started as a one-off checker and is now a tracking surface: frozen prompts re-asked on a schedule, three metrics that disagree usefully, a competitive field built only from brands a model actually named, and a receipt behind every figure. Here is all of it.
The rail picks the section and only that section’s data is loaded, so a view is a smaller page rather than a taller one with parts painted over. The section, the brand and topic filters and the trend window are all URL state — a view you are reading is one you can bookmark and send.
How often AI assistants name Pickleland when a buyer asks about the category — measured on frozen questions, so week over week means one thing.
Share of answers naming each brand, last 12 weeks. Days where nothing was measurable break the line rather than being drawn through.
Every scored answer from the last 12 runs of each keyword, by the rank the model gave you. “Not named” is counted here rather than dropped — it is the denominator.
The top of the Actions ranking: how much went the wrong way, in points times the answers it spans.
Claude named Pickleland in 9 of 12 answers; ChatGPT in 0 of 12. Same five frozen questions.
75 pt × 12 answersSee the 12 answers →67% last run, 27% this one, over 15 answers. Nothing else about the keyword changed — the questions are frozen.
40 pt × 15 answersSee the prompt →Named 47 times to your 39 across the most recent run of each keyword, at a better average rank on four of them.
8 namings × 4 keywordsSee the landscape →Sample data for a demo account, never a customer’s result. This screen is shown whole; the nine below are shown by the panel that matters.
One card per screen: what it answers, and the panel from it that does the answering. Every fragment is the real component, at the size it actually renders.
Each re-runs on a schedule — weekly on our key, or daily once you have saved your own key for every model it asks. A free account tracks up to 5.
indoor pickleball courts in Austin Austin courtsdaily | 84% | |
pickleball lessons in Austin Lessonsweekly | 47% | |
pickleball leagues in Austin Leaguesdaily | 33% |
The five questions are frozen when you create the keyword. Most tools rewrite theirs each run, which is why part of every movement in their charts is the question changing.
Horizontal is times named, vertical is average rank inverted, and bubble area is how many of your keywords the brand appears in.
The same frozen questions asked of each assistant you hold a key for. A model at 0% is never averaged with one that cites you.
Each column is one day’s classified sentences. Column width is fixed and the count sits underneath, so three sentences cannot look like thirty.
Printed verbatim and marked by the same matcher that scored the run. “Not named” is a result with evidence behind it, not a blank.
Blind spots, drops, rivals pulling ahead, weak topics. Scored by points lost times answers spanned.
Save one and a keyword’s frozen questions can be re-asked on a model we hold no key for — and that keyword can move to a daily cadence, because the run spends your budget.
Sealed with AES-GCM, with a secret that is not in the database.
Three metrics that disagree usefully: each catches a loss the other two miss.
The right axis is inverted — rank 1 at the top — so up is better on both lines, and position is dashed because the two series are in different units. Below it: a row per frozen question with its own visibility, average position and rivals, and the stored answers printed verbatim.
indoor pickleball courts in Austin · 5 questions frozen 29 Jun · asked daily on Claude and ChatGPT · 9 runs recorded
The right axis is inverted — rank 1 at the top — so up is better on both lines. Position is dashed because the two series are in different units.
The stored answer the top row was counted from, printed verbatim and marked by the same matcher that scored it.
“Best indoor pickleball courts in Austin, Texas?” — Claude, Aug 24
An unlabelled reversed axis is a trap rather than a chart, so this one says so in words.
A dashboard is mostly small choices about what to do when a number is missing. Here are the ones that shaped this one.
The section you are on, the brand and topic filters, the model filter and the trend window are all URL state. That is what makes a view bookmarkable, reloadable and sendable — and it is why the dashboard renders the same for a reader with scripts blocked as for everyone else.
“Not measurable” and “measured, and zero” are different findings and this product never prints one as the other. A bar at 0% renders as a bare track rather than a sliver of ink, because a mark where nothing was measured reads as a small result instead of no result.
The export carries whichever brand and topic filters you are reading, correctly quoted, so the file matches the screen rather than the whole account.
One timed-out request used to leave a keyword idle until the following week. Failures now retry at the next sweep and then back off — and only the requests that can clear on their own are ever re-sent.
Raw IP addresses are never stored. A key you paste into the one-off checker is used for that request and thrown away; a key you save is encrypted with a secret that is not in the database.
A tour that only lists strengths is a brochure. These are the limits as they stand today.
Which sites an assistant leaned on when it answered would be the tenth view, and it is deliberately not shipped: nothing in the product stores a per-citation domain today. A sources screen built from anything other than a link a model actually returned would be the one screen here that estimates.
They are generated, not looked up in a ranked list. That is why a keyword asks five questions with three samples each rather than one question once, and why the trend is the number worth reading rather than any single run. It is also why the questions are frozen: it removes the one source of variance we control.
It counts listed praise and criticism cues in the sentence that names you, and shows you every cue that fired. It will miss sarcasm and it will miss praise phrased in words that are not on the list. Showing the whole classifier is the compensation: you can see exactly why a sentence was called what it was called.
There is no outbound mail anywhere in the product, so nothing here promises to send you anything. When that changes, this page changes with it.
3 checks on our key for all time, 5 tracked queries, weekly sweeps. Every run spends real API budget, and the unattended sweep is capped in dollars per month — a query we cannot afford this month is deferred rather than failed, because a red mark on a healthy query would be a lie about the query. Add your own API key and the free plan keeps running indefinitely; a paid plan buys the allowance on our key instead.
A free account gives you 3 checks on us and 5 tracked queries on your own key. No card, and no anonymous check — every check spends real API budget, so it has to belong to someone.