AI insights: make sense of open-text responses at scale
Open-text responses hold the most valuable feedback your users give you. AI auto-tagging, response translations, and an MCP server turn that unstructured text into patterns you can act on.
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- Qonto
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- Shine
- Copy.ai
- Moqups
- AutoScout24
- Resident Advisor
- Caya
- Livestorm
- Merci app
- OneFootball
Open-text feedback is where the real insights are, and where they get stuck
Rating questions tell you the score. Open-text questions tell you the why. But most teams collect open-text responses and then struggle to do anything with them at scale.
Manual categorization doesn't scale
Reading every open-text response and sorting them by topic works when you have 20 responses. At 200 or 2,000, it's a bottleneck that delays decisions.
Language barriers hide insights
Your users write in their own language. If your team can't read every language your users speak, you're missing feedback from entire segments.
Survey data stays locked in one tool
Your team uses AI assistants and LLMs to work faster every day. But survey data sits in its own silo, disconnected from the tools where analysis actually happens.
Auto-tag open-text responses by topic
Every open-text response is analyzed and tagged automatically. Define the topics that matter to your team and let AI handle the categorization as responses come in.
Define your own tags
Create tags with plain-language descriptions. You control what gets categorized and how.
Tags applied in real time
Each new response is evaluated against your tag definitions the moment it arrives.
Spot recurring patterns
Identify the top issues and requests without reading every answer.
Trigger actions from tags
Route tagged responses to the right team on Slack, Teams, or email.
Translate response text to your team's language
Your users give feedback in their native language. Response translations make every open-text answer readable by your entire team, regardless of what language it was written in.
Automatic translation
Open-text responses are translated on the fly so your team can read and analyze feedback in one shared language.
Global teams, one view
Product teams in Berlin, customer success in New York, and growth in Singapore can all read the same response in their working language.
Preserve the original
The original response text is always kept alongside the translation. Nothing is lost.
Connect survey data to AI tools with the MCP server
The Refiner MCP server lets AI assistants and LLMs access your survey data directly. Ask questions, run analysis, and pull insights from your responses without switching tools.
Query responses in natural language
Ask your AI assistant "What are the top complaints from enterprise users this month?".
Feed survey data into your AI workflows
Connect Refiner's MCP server to Claude, ChatGPT, or other AI tools your team already uses.
Build on top of your data
Use the MCP server to create custom reports, summaries, or alerts powered by AI.
Start getting more from your open-text responses today
Set up AI auto-tagging in minutes and let every open-text response work harder for your team.
Super easy two-way integration with Segment and great support in setting up and launching our in-app surveys, made it a success!
— Coralie Blanc, CRM Lead @ Qonto