Feature
Brand Perception
Not just whether AI mentions you — what it says when it does.
Two brands can have identical visibility scores while one is described as "the industry standard" and the other as "a budget option with mixed reviews". Perception is the layer of AI search that mention counts can't see — and it shapes every buying decision the answers influence.
Geonimo analyzes the qualitative side of every tracked answer: the attributes engines associate with your brand, the caveats they attach, how they frame you against competitors, and how all of that shifts over time and across engines.
Perception profile
The recurring qualities, use cases and positioning AI engines attach to your brand, aggregated from every tracked answer into a readable profile per engine.
Caveat & risk detection
Recurring negatives — pricing complaints, missing features, outdated facts — surface explicitly, so you can fix the source before it compounds across engines.
Competitive framing
How engines position you against each competitor: who's "the premium option", who's "best for beginners", and whether that framing matches your actual strategy.
Crisis lens
When something goes wrong publicly, track how fast and how strongly it propagates into AI answers — and when your corrective content starts winning.
Perception is the conversion layer of AI search
A mention gets you into the consideration set; the framing decides whether the buyer clicks. Engines don't just list brands — they characterize them, drawing on reviews, editorial coverage and forum sentiment. If that characterization is stale ("limited integrations" from a 2023 review) or wrong, every AI answer in your category repeats the error. AI brand perception tracking makes the characterization visible and correctable.
Changing what AI says about you
Perception problems trace to sources: the reviews, articles and community threads engines learned from. Geonimo pairs each recurring negative with the likely source material and the content strategy to displace it — fresh authoritative pages, updated third-party coverage, corrected entity data. Combined with sentiment analysis, you get both the quantitative trend and the qualitative substance of how AI talks about you.
Frequently asked questions
What is AI brand perception?
The qualitative picture AI engines paint of your brand: the attributes, use cases, strengths and caveats they mention when describing you. It's distinct from visibility (whether you appear) and sentiment score (positive/negative) — perception is the actual content of the characterization.
How is this different from sentiment analysis?
Sentiment scores each mention on a positive–negative scale; perception analysis extracts what is actually being said — the specific qualities, comparisons and caveats. "Positive but described as expensive" and "positive and described as best-in-class" score similarly on sentiment while meaning very different things for conversion.
Can I fix a wrong or outdated AI perception?
Usually, yes. Perceptions trace to source material engines read. Publishing authoritative current content, updating third-party listings and earning fresh coverage displaces stale characterizations — and daily tracking shows when the answers actually change.
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