Documentation
Brand perception: the role AI assigns to your brand
Being mentioned is not enough. This section shows whether AI recommends the brand or names it as a fallback, who gets the recommendation, which qualities describe you and which pages that comes from
Contents
1.Presence quality: five levels
AI may call your brand the benchmark or a fallback option with a caveat. The Presence quality block puts every answer mentioning the brand on one of five levels and shows the split for the period: the bar at the top, and below it the same ladder per provider and versus competitors. The section uses the same period, prompt-group and provider filters as the home page.
- Benchmark — others are compared to the brand (“X falls short of the brand”, “X is behind the brand”) or it gets the direct recommendation and is named first. Primary pick — AI explicitly names the brand as its choice (“my favourite”, “I recommend”) but not first on the list — that is already the benchmark
- With arguments — recommended under a condition ("if you need a quiet PC, take X") or with concrete reasons to choose it. This is the level that content grows most easily
- Secondary option — the brand is called weaker than a rival or with negative sentiment, or the direct recommendation in that answer went to someone else. Mention — merely named, without arguments or comparison
- Hover the bar or a provider's mini bar: the tooltip shows the percentage and count per level. The Strong column = benchmark + primary + with arguments, Secondary = secondary option
- The Versus competitors tab shows the same levels for the top competitors by mentions. The brand and competitors are scored by the same rules, so the shares are directly comparable: whoever has 30% strong on the same mentions is winning the recommendation
Don't chase the mention rate: 1,000 mentions with 70% "merely named" are weaker than 300 mentions with 40% strong. The strong share is your perception metric.
2.Presence quality over time
The answer to the main GEO question — did it get better after the changes. The chart below the ladder shows how the levels move over time: by day for short ranges, by week and month for long ones.
- Brand levels over time — a stacked share of the five levels among the brand's mentions in each period. The wider the green, teal and blue bands at the bottom, the more often AI recommends the brand rather than just naming it
- Strong share: brand vs competitors — lines of the strong-level share for the brand and the top 5 competitors by mentions. You see who is growing at your expense; clicking a competitor in the legend opens its card
- Each point's tooltip shows the mentions and answers: periods with a handful of mentions swing sharply, so use weekly and monthly buckets for conclusions
Note the date a page was published or fixed and compare the shares after two or three runs: With arguments and Primary pick should grow while Secondary option falls. If only Mention grows, the content was noticed but AI found no arguments in it.
3.Who gets the recommendation and what AI says against you
Two blocks under the ladder explain why the brand doesn't get the recommendation: who exactly takes it and in what words AI places the brand lower.
- Who gets the recommendation — competitors AI picks outright in answers where your brand is mentioned but not directly recommended: the number of such answers, their share of the brand's mentions and the qualities they are praised for
- The “brand is called weaker” note — in how many of those answers AI also explained why your brand is weaker. These are the most valuable answers to review
- AI's reservations about the brand — verbatim wordings: "lags behind X in cooling", "comparable to Y, but…", reasons for a negative. A weaker / on par / caveat / negative badge, provider, date and prompt; click opens the full answer
- The Sources of negative answers button shows the pages AI cited in negative answers, with a verdict on whether the brand is mentioned on them
Two or three recurring reservations about the same thing ("lags behind in cooling") point to a topic to close with content or fix on the cited pages more precisely than any metric.
4.Attributes, gaps and the sources of wording
The lower part of the page is about the words AI uses to describe the brand and competitors, and where those words come from. Qualities are extracted from the answers themselves and grouped into attributes; objections ("expensive", "noisy") are listed separately.
- How AI describes the brand — the brand's top attributes with the number of answers describing it that way; Brand shape — a per-attribute radar with relative axes: the leader on an attribute among the selected brands is 100%, the tooltip shows the share and the raw score; objections are excluded
- What explains competitors' choice — attributes where a competitor leads the market and your brand is lower or not described that way at all. A ready-made topic list for the content plan
- “Brand comparison by attribute” (the heatmap) — the brand and the mention leaders against every attribute: where you beat the market, where you lag, which objections are attributed to you
- Clicking any attribute opens the "Where AI gets…" panel: the domains and pages AI cited in answers with that wording, with their share of answers and a “brand present / absent on page” verdict; clicking a “present” badge expands the page fragments where the brand is named
- The same data is available to the in-dashboard AI agent and via MCP: ask "compare presence quality with ASUS over the month" or "where does AI get 'noisy' about us"
Start with gaps where a competitor leads and you have no attribute at all, and with pages marked "brand absent on page": these are the cheapest fixes — AI already reads those pages, it simply has nothing about you to take from them.