FeedbackIQ vs. Canny
Track customer feedback
Canny is a mature feedback-and-roadmap tool built for PMs. You install a widget, customers file requests, your team prioritizes, and you publish a changelog. It stops at the PM handoff — engineering picks up from Canny's Jira/Linear integration.
The FeedbackIQ case
FeedbackIQ ingests the same kind of feedback, then closes the loop. Claude reads the report, writes the fix or feature, and opens a PR on your repo — dedup'd with pgvector so 500-errors don't spam the roadmap.
The Canny case
Canny ships a polished voting UI, prioritization scoring, and a changelog. Great if your bottleneck is understanding what users want. Doesn't touch code.
Feature-by-feature
| Feature | FeedbackIQ | Canny |
|---|---|---|
| Feedback widget | ||
| Public roadmap | ||
| Public changelog | ||
| Upvoting | ||
| Auto-deduplication (vector similarity) | Manual merge | |
| AI auto-tagging of submissions | Add-on | |
| Auto-generated pull requests | ||
| AI-generated changelog from merged PRs | ||
| Screenshot attachments | ||
| Free tier | Yes | Yes (limited) |
| Self-hosted option |
Verdict
Choose Canny if your engineering throughput isn't the problem — you need prioritization. Choose FeedbackIQ if the bottleneck is the gap between 'we know what to build' and 'it's merged.'