Every mention is scored across the aspects that matter (pricing, quality, support, whatever fits your business) into a strengths-and-weaknesses map.
7-day trial, no card
Strengths and weaknesses, mapped
Mentions are classified into aspects (pricing, support, reliability and more) and scored, so you see at a glance where AI sells you and where it undermines you.
The sentences behind the score
Every aspect score is backed by the actual sentences AI wrote, by engine and by model. Click through from any score to the quotes behind it.
Your taxonomy, not ours
Rename aspects, add your own, or regenerate the set. The perception matrix tracks the dimensions your customers care about.
Being named is the first hurdle. The second is how you are described in the same breath, because an assistant does not hand over ten links for the buyer to weigh up. It hands over a characterisation, and they take it. AI sentiment is that characterisation: the tone of the mentions you get, broken down by what they were about.
Named first and described as expensive with slow returns is not a win. Third on the list and called the durable one is a different problem to solve.
Pick an aspect and read the sentences that produced its score, in the engine that wrote them. Nothing here is a summary of a summary.
Knowing you are losing is the easy part. Referenced ranks the prompts you lose most often, shows you the answer that beat you, and names the page or review that would win it back.
The same brand reads differently depending which model is doing the talking. Scores and quotes are kept per engine as well as blended overall, so you can tell a universal weakness from one model's house style.
How sentiment is classified, and what to do with it.
Every mention is classified positive, neutral or negative against the aspect it's about, from the exact sentences AI wrote, not a summary of the answer as a whole. Each aspect's score is the net of its positive and negative classified mentions.
Being named often but described badly is worse than not being named at all. A confident wrong answer is what buyers act on. High visibility paired with negative sentiment on a core aspect like pricing or support is the clearest signal to act, not a vanity metric to ignore.
Yes: rename aspects, add your own, or regenerate the set from scratch. The perception matrix tracks the dimensions your customers care about, not a fixed list you're stuck with.
Yes. Each engine can characterise you differently, so aspect scores and quotes are kept per engine as well as blended overall, useful for telling a universal weakness from a single model's house style.
The share of classified mentions that were positive, minus the share that were negative, so it runs from −100 to +100. Neutral mentions count towards the sample but pull the score neither way.
Nothing is scored on fewer than five classified mentions. Below that a single sentence would swing the number, so the aspect reports its count and waits for the next scans rather than show a score you can't trust.
The actual words an engine used about you ("durable", "pricey", "slow") lifted from the sentence and kept with their tone. They show what a score is made of, and which words you'd want to change.
Yes. Every brand named in an answer is classified the same way, so the perception matrix puts your aspects beside theirs and shows the gap on each one.
It can be, and it's kept separately. Prompts that name you are scored on their own, so you can tell how AI describes you to someone who already knows you from how it describes you to someone who doesn't.
On every scan. Each new answer is classified as it comes in, so the score moves as the answers move, daily on the current schedule.
Free 7-day trial, no card: the first scan runs on all prompts across three engines.
Feature
Visibility
Your score across every AI engine.
Feature
Sentiment
What AI thinks of your brand.
Feature
Competitors
Share of voice, brand by brand.
Feature
Citations
Which pages AI actually cites.
Feature
AI Traffic
GA4 + Search Console, overlaid.
Feature
Opportunities
The fix for every gap, ranked.