Stop optimizing keyword by keyword. Start owning topics.
Performance breakdown by semantic topic cluster. Win clusters, not keywords.
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The problem
Monitoring at the prompt level misses the forest for the trees. You may have three hundred prompts but only fifteen topics. AI engines think in topics (semantic clusters), not in prompts. Analyzing at the topic level matches how AI actually operates.
What it does
Topics Analysis groups your prompts into semantic clusters and measures performance at the topic level. Understand not just which prompt wins but which topic you own, the unit of thinking AI engines actually use.
Inside the feature
- Auto-clustering of prompts into topics
- Topic-level share of voice and sentiment
- Custom topic taxonomy per brand
- Topic gap identification vs competitors
Why Qwairy is different
Most tools
Analyze at the prompt level.
Qwairy
Auto-cluster prompts into semantic topics (the unit AI actually uses).
Most tools
Fixed keyword taxonomy.
Qwairy
Custom topic taxonomy per brand with merge and split controls.
Most tools
One topic per prompt.
Qwairy
Multi-topic assignment with per-topic performance views.
How it works
Auto-cluster prompts
Qwairy groups your prompts into semantic topics automatically at onboarding.
Review and refine
Accept, rename, merge or split clusters. Build the topic taxonomy that matches your business.
Analyze per topic
All dashboards switch to topic-level views. Rankings, sentiment and share of voice aggregate per topic.
Use cases
Topic ownership scoring
Rank topics by your share of voice. Identify the three topics you own, the five you contest, the seven you lose.
Content cluster planning
For each weak topic, generate a six-article cluster plan from the topic highest-demand prompts.
Board-level reporting
Executive reports get one metric per topic (not per prompt). Ten rows instead of three hundred.
Frequently Asked Questions
Common questions about Topics Analysis.
Ready to unlock Topics Analysis?
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