The themes AI attaches to your brand, and whether they help or hurt
Every theme AI attaches to your brand, with its polarity and trend.
Topic polarity mix
How models frame your brand across the top themes (last 30 days)
Illustrative data
- Positive
- Neutral
- Negative
From raw answer to actionable metric
Extract themes
We read every answer and surface the topics the model frames you around.
Score polarity
Each topic is tagged positive, neutral or negative with the verbatim sentence behind the call.
Watch the trend
See which themes lift your brand and which are quietly dragging deals down.
Every metric, with the exact line behind it
"Their onboarding is famously frictionless — most teams are live in under an hour."
"Pricing skews premium and can feel steep for solo founders, though larger teams see strong ROI."
"Customer support is consistently called out as a differentiator."
Every time a model answers a question about your category, it frames you around certain topics. Price. Support. Quality. Speed. Trust. Some of those themes work in your favor. Some quietly cost you deals. Topics shows you all of them.
What Topics does
We pull out every theme the models raise about your brand and tag each one with its polarity, positive, neutral or negative. Instead of one vague sentiment number, you see the actual subjects driving it, so you know whether the conversation is about your great onboarding or your confusing pricing.
You get the full mix at a glance, the topics trending up, the ones turning against you, and how the balance shifts over time.
Why it matters for GEO
A model does not just decide whether to mention you. It decides what to say. Owning the right topics is how you move from being listed to being recommended. When you can see which themes lift you and which drag you down, you know exactly what your content, your PR and your product messaging need to reinforce next.
Backed by the exact words
Every topic comes with the verbatim sentences the model used, so a positive or negative tag is never a black box. You can read precisely why a theme landed the way it did, and take that evidence straight into a content brief or a client report.
Pairs naturally with Topic Authority and Sentiment Analysis.
Built to move real numbers
No vague sentiment score
Polarity is grounded in actual topics, not an opaque verdict.
Backed by quotes
Every topic links to the exact sentence the model produced.
Built for content briefs
Export topics with evidence straight into your next brief or PR push.
Frequently asked
How are topics extracted?+
An LLM layer reads each answer and clusters mentions into stable themes, deduplicated across models and prompts.
Can I add my own topics?+
Yes. You can pin topics you want monitored explicitly, or let detection run automatically.