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Brand reputation monitoring in AI
How the "Reputation" tab on the home page shows the tone in which the AI engines talk about your brand, and exactly where negativity surfaces
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The "Reputation" tab: where and why AI talks about the brand negatively
A mention isn't the same as a positive mention. The "Reputation" tab on the home page (next to "Overview" and "Reports") shows not just that the brand is mentioned, but in what tone — and gathers every negative AI answer into one feed with an explanation of what exactly is negative in each.
- At the top — a reputation-risk summary: "Negatives" (count of negative answers), "Share of negatives among mentions" (%), and "Worst provider" — the engine that most often speaks about the brand negatively
- "Negative answers" — a feed of every negatively-toned answer. Each shows the prompt ("What reviews does the brand get from entrepreneurs?"), the provider (Claude, DeepSeek…), when it happened, and the "Negative" and "Brand mentioned" badges
- "Why negative" — the system explains what exactly works against the brand: e.g. "the summary table rates the brand's support and pricing transparency lowest, pointing to hidden fees". No need to reread the whole answer by hand
- You see the full answer text with the brand highlighted and a "Sources" block — the pages the model leaned on to form the negativity. That's the lead: negativity usually traces back to a specific outdated review or a competitor comparison
- Why it matters: an engine can consistently frame the brand negatively on specific queries and providers, which coverage-level dashboards don't reveal. Here you see exactly where, why, and from which sources — so you can address it with content and publications
Tip
Start working on negativity from the "Sources" block, not the answer itself. Open what the model referenced: it's often an old review or a competitor's roundup. Closing the negativity means giving the engine a fresh, more authoritative piece it will cite instead of the outdated one.