Pelin vs Canny: Which Feedback Tool Fits Your Workflow?

Choosing between feedback tools often comes down to a fundamental question: Do you want to collect feedback in a structured way, or analyze feedback that's already flowing through your organization?

Pelin and Canny take distinctly different approaches to this problem. Let's break down what each does well, where they fall short, and who should use which.

Quick Comparison

What Canny Does

Canny provides a public (or private) feedback portal where your users can submit ideas, vote on features, and see your roadmap. It's a clean, well-designed system for structured feedback collection.

Core features:

• Feature request boards
• User voting and commenting
• Roadmap visualization
• Changelog announcements
• Single sign-on integration
• Custom domains and branding

The appeal is clear: instead of feedback scattered across emails, Slack, and support tickets, users have one place to submit and track their requests. Product teams get quantified demand through vote counts.

What Pelin Does

Pelin takes the opposite approach. Rather than asking users to submit feedback somewhere new, it analyzes the feedback that's already happening across your support tickets, sales calls, Slack channels, and more.

Core features:

• 15+ integrations (Intercom, Zendesk, Slack, Gong, etc.)
• Automatic AI categorization
• Topic clustering and trend detection
• Sentiment analysis
• Company-level tracking
• Semantic search across all feedback

The idea: your customers are already telling you what they need—in support conversations, sales calls, and casual mentions. Pelin finds those signals without requiring anyone to change their behavior.

The Fundamental Tradeoff

This comparison really comes down to one question:

Are you optimizing for signal quality or signal quantity?

Canny gives you cleaner, more structured data. Users explicitly tell you what they want, and votes quantify demand. But you're limited to what users bother to submit—and highly engaged users aren't always representative of your broader base.

Pelin gives you higher volume and catches feedback from users who would never fill out a feature request form. But the data is messier, and AI interpretation isn't perfect.

When Canny Makes More Sense

You have a community-driven product. If your users are engaged enough to participate in feedback portals, Canny's voting system is genuinely useful. Open source projects, developer tools, and products with passionate user bases often thrive with this model.

You need public accountability. Canny's public roadmap feature creates transparency that some teams value. Users can see you've heard them, even if you haven't built their request yet.

Your feedback volume is manageable. If you're getting dozens of requests per week rather than hundreds, the manual overhead of Canny is reasonable and gives you hands-on understanding of what users want.

You want users to self-segment. Voting naturally bubbles up the most popular requests, saving you from having to analyze everything.

When Pelin Makes More Sense

You're drowning in feedback already. If customer feedback is scattered across Intercom, Zendesk, Slack, sales calls, and email—and you're struggling to keep up—Pelin's automation is the point.

Your users won't use a portal. Let's be honest: most users don't submit feature requests. They mention problems in passing during support conversations. Pelin captures these signals without requiring user behavior change.

You need to track sentiment over time. Pelin's continuous analysis lets you spot trends: Is satisfaction improving after that last release? Is confusion around a feature growing or shrinking?

You care about account-level insights. For B2B teams, Pelin's company tracking connects feedback to specific accounts—valuable for customer success and understanding which customers care about what.

Feature Deep Dive

Feedback Collection

Canny: Users actively submit via a portal. Clean data, but limited to engaged users.

Pelin: Passive collection from existing tools. Higher volume, more diverse sources, but requires integration setup.

Organization & Categorization

Canny: Manual tagging plus user votes for prioritization. You're in control, but it's work.

Pelin: Automatic AI categorization into pain points, feature requests, confusion points, etc. Less control, more scale.

Search & Discovery

Canny: Traditional search across submitted requests. Works fine for structured data.

Pelin: Semantic search across all connected sources. Ask natural language questions like "what are users saying about our onboarding?"

Roadmap & Communication

Canny: Strong here—built-in roadmap visualization and changelog features for closing the loop with users.

Pelin: Not a roadmap tool. Focuses on insights, not planning.

Integrations

Canny: Integrates with project management tools (Jira, Asana, etc.) for pushing approved requests.

Pelin: Integrates with customer data sources (Intercom, Zendesk, Slack, Gong, etc.) for pulling feedback in.

The Hybrid Approach

Some teams use both. Canny for direct user input and roadmap communication; Pelin for analyzing the feedback that doesn't make it to the portal.

This isn't crazy if:

• You have budget for both
• You have the bandwidth to manage both
• You genuinely value both structured requests and unstructured signals

But for most teams, one approach fits better than trying to do everything.

Pricing Reality Check

Canny prices by number of tracked users, starting around $79/month for their Growth plan. Costs scale with your user base.

Pelin prices by organization, with tiers based on data volume and integrations. Check current pricing at pelin.ai.

Neither is cheap, but both can save significant time if they match your workflow.

Questions to Ask Yourself

1. Where does feedback currently live? If it's already in a few key tools, Pelin can tap in. If it's scattered or nonexistent, Canny might help centralize it.

2. Will your users participate? Be honest about whether a feedback portal will actually get used.

3. How much feedback do you get? More volume favors automation; less volume makes manual review feasible.

4. What's your primary goal? Quantified feature demand? Canny. Surfacing hidden patterns? Pelin.

5. Do you need a public roadmap? Canny has this built in; Pelin doesn't.

The Bottom Line

Choose Canny if: You want a structured feedback portal, your users are engaged enough to use it, and you value public roadmaps and feature voting.

Choose Pelin if: You have feedback flowing through existing tools, you want AI to surface patterns, and you need insights without changing user behavior.

Both are good tools solving different problems. The right choice depends on where your feedback lives and how you want to interact with it.

Looking for AI-powered insights from your existing customer feedback? Try Pelin and connect your support, sales, and communication tools in minutes.