Feature voting
Canny counts votes. Mimir finds the patterns voters miss.
Canny gives your users a place to suggest features and vote on them. It is a clean, well-executed model: the features with the most votes rise to the top. Your team gets a visible signal about what users are asking for, and users feel heard because they can track their requests on a public board. The changelog closes the loop — users see their feedback turn into shipped features.
The problem is that voting measures popularity, not importance. A feature requested loudly by free-tier users can accumulate more votes than a critical pain point mentioned quietly by your highest-value enterprise customers. Canny tells you what people say they want. It does not tell you what actually matters for your business. The ten users who churn silently over the same onboarding friction never cast a vote.
Mimir does not collect votes. It analyzes whatever feedback you already have — interviews, support tickets, survey responses, Slack threads — and synthesizes it into recommendations weighted by evidence, not popularity. The patterns Mimir surfaces often do not match the top-voted items in Canny, because the loudest signal and the most important signal are rarely the same thing.
Your Canny board has 400 requests. The top-voted feature has 85 votes, mostly from free users. Meanwhile, three enterprise customers mentioned the same workflow problem in separate support tickets, but none of them voted on Canny. Mimir reads all your support data and surfaces the enterprise pain point that never showed up in the voting board — the one that actually affects retention.
→ Mimir
Your most active community members keep upvoting the same feature. It feels urgent because the votes are piling up. But when you paste your last 20 customer interviews into Mimir, a completely different pattern emerges — the majority of customers care about something the vocal minority never mentions. Mimir gives you the evidence to make the right call instead of the popular one.
→ Mimir
You have thousands of users and you need them to feel heard. A public voting board, status updates on requests, and a changelog showing what shipped — this builds trust and reduces the volume of individual support tickets asking for the same thing. Canny is purpose-built for this community engagement loop. Mimir is an internal analysis tool, not a public-facing portal.
→ Canny
Export your Canny feature requests as CSV and upload them to Mimir as a source alongside your interview transcripts and support tickets — see which patterns the voting board missed.
Run one analysis cycle in Mimir using your recent customer feedback. Compare the recommendations against your top-voted Canny items. The gaps will tell you where voting bias is hiding signal.
Keep Canny for community engagement and public transparency. Add Mimir for the internal decision about what to actually build. The two tools solve different problems.
Canny is a great community engagement tool. If you need a public portal where users can request features and track progress, use Canny. But do not confuse popularity with importance. Mimir analyzes all your feedback — not just the self-reported requests — and finds the patterns that voting boards structurally miss.
Paste customer feedback and get ranked product recommendations in 60 seconds. No setup, no credit card.
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