Survey at scale. Connected to every insight.
Run surveys, import your existing CSV data, and connect your tools — then watch it all flow into the same insights repository as your qualitative research. Numbers finally explain the why, not just the what.
Q1 · Single choice
How satisfied are you with our product?
2,847
responses
NPS Score
+4294%
Completion
3.2 min
Avg time
12 Q
Questions
2,847
Responses collected
+42 NPS
Live score
Trusted by enterprises that can't afford research slop
Pillar 1 — Surveys
Every question type. Live results. At any scale.
Design closed-form surveys with nine question types, distribute to thousands of participants, and watch aggregate results build in real time.
Question types
Scale questions support NPS (0–10), Likert (1–5 or 1–7), stars (1–5), and smiley (1–5) — each with labeled anchors and automatic mean calculation.
Q1 · NPS
How likely to recommend?
+42
2,847 responses
Q2 · Rating
Overall product satisfaction
4.2 / 5
2,614 responses
Q3 · Single choice
Primary use case
5 options
2,790 responses
Satisfaction by segment
Pillar 2 — CSV Import
Bring your existing quantitative data in
Upload any CSV — survey exports, analytics extracts, CRM snapshots — map columns to Usedge fields in one step, and make your data instantly chartable and linkable to qualitative insights.
First-class data. Imported CSV rows are treated identically to survey responses — segmentable, chartable, and linkable to qualitative insights and signals.
Click to upload or drag and drop
CSV up to 50 MB · UTF-8 or Latin-1
Pillar 3 — Integrations
Connect the tools you already use
Quantitative data flows in from your CRM, analytics stack, and product tools. Insights flow back out to where decisions actually happen — Slack, Notion, Jira, and AI agents querying your research via MCP.
HubSpot deals, Salesforce contacts, Gong call data
Product metrics, conversion events, segment attributes
Findings pushed to Slack, Notion, Jira, Linear
Claude, ChatGPT, Cursor pull from your research via MCP
MCP — the research layer for AI agents
The Usedge MCP server exposes your full insights repository to any MCP-compatible AI tool — Claude, ChatGPT, Cursor, Copilot. Your quantitative and qualitative data becomes queryable by every agent your team uses.
MCP
Model Context Protocol
The connective layer
Quant + qual. One unified insight layer.
Surveys, CSV imports, and integrations don't live in a silo. Every data point flows into the Usedge Insights Repository — auto-tagged, correlated with your qualitative research, and made queryable by your entire team and AI agents.
Quantitative sources
Surveys
Aggregate responses, NPS, ratings, open-ends
CSV Import
Analytics exports, CRM snapshots, any structured data
Integrations
HubSpot, Salesforce, Gong, product analytics, MCP
+ qualitative research
Insights Repository
Every quant and qual data point, unified, searchable, and connected
Connected outputs
Validated insights
Numbers auto-linked to qualitative findings. Evidence with context.
AI research agents
Research Agents synthesise quant + qual, surface patterns, flag gaps.
Signals & opportunities
Quantitative signals tagged and correlated with strategic opportunities.
A number without a why is just noise. When quant data enters the Insights Repository, AI Research Agents automatically correlate NPS drops with qualitative pain points, flag statistical significance, and surface evidence that bridges the gap between what users say and what they do.
Collect, unify, act
Three steps from raw data to connected evidence.
Step 1
Collect quantitative data
Design and distribute surveys to thousands of participants. Import existing datasets from CSV. Connect your CRM, analytics platform, or any MCP-compatible source. All three paths land in the same place.
Step 2
Unify in the repository
Responses are auto-tagged against your taxonomy, correlated with qualitative sessions, and indexed for AI search. A satisfaction score sits next to the interview where a user explained exactly why.
Step 3
Act on connected insights
Your team queries the repository in plain language. Research Agents surface quant-backed insights on demand. Numbers stop being orphan stats — they carry the context that makes them actionable.
Turn your quantitative data into connected insights
Surveys, CSV imports, and integrations — all unified with your qualitative research in a single, AI-queryable repository.