AI for User Research & Insights
You already ship insight reports at Mentimeter. This module is about 10x-ing that process — synthesizing interviews at scale, auto-tagging feedback, building living insight repositories, and extracting signal from noise.
Step 1 of 5 · Read the lesson
The real bottleneck
It's not collection. It's synthesis. AI is uniquely good at compressing 50 transcripts into a JTBD map in minutes.
Auto-tagging feedback
Define a taxonomy once. Have AI classify every new piece of feedback into it with a confidence score. Suddenly qualitative data becomes a quantifiable signal you can chart.
Living insight repository
Pipe tagged feedback → weekly digest → Notion database. Insights compound. Patterns surface that no single human would notice.
Reuse the architecture you already have
Your Contentful translation agent is the same shape: input → AI → structured output → destination. Insight automation is a sibling, not a new beast.