
New Feature
Tone + face + diction
Captures multi-modal signals to detect nuanced human emotions that any single signal would miss.
Ekman-based framework
Grounded in the standard used across clinical psychology and UX research, with recognized across cultures.
Fully traceable
This is not a black box – you can see why Listen detected “happiness”, not just that it did.
Per question analysis
Get a side-by-side emotional breakdown across stimuli, segments, and markets.
100+ languages
Designed for global research and localization, with consistent methodology across markets.
Multi-signal emotion detection
Analyzes subconscious micro expressions, tone of voice, and word choice together to identify emotional reactions that transcripts alone miss. Available across 50+ languages.


Research-grounded and fully traceable
Built on Ekman's 6 core emotions, extended with UX research emotions. Every emotion links to the exact timestamp, verbatim quote, and AI reasoning.
Structured for comparison
Emotions are quantified per question and per concept with pre-built visualizations. Filter by segment to compare across markets, demographics, or personas and see which ad made people light up and which one fell flat.


Creative/Ad Testing
See which creative resonates emotionally and which falls flat.

Concept Comparison
Compare reactions side-by-side across concepts and markets.

Brand Research
Understand how people emotionally connect to your brand versus competitors.

UX Research
Detect confusion, frustration, and delight during task-based research
Use Case
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