Feedback clusters
Classify comments into pain points, objections, competitors, feature requests, pricing feedback, and copy feedback with evidence snippets.
Tool task
Community Feedback Inbox
Turn post-launch comments, DMs, and trial feedback into a learning system: classify user language, find beta invite candidates, capture backlog evidence, and turn objections into landing page copy.
Turn community comments into growth learning assets
Paste Reddit, Indie Hackers, Product Hunt, X, or Discord comments. This review prototype classifies feedback into pain points, objections, competitors, feature requests, pricing feedback, and copy feedback, then suggests reviewable next steps.
Review prototype
What you get
Beta invite shortlist
Flag people who show a clear workflow, trial intent, or useful follow-up question, with an editable DM draft.
Build-in-public material
Turn high-quality comments into the angle, hook, and user language for the next public building post.
Backlog and FAQ candidates
Convert repeated feedback into backlog hypotheses, landing page FAQ, and objection-handling material.
For learning after a post, not just counting exposure
Useful for indie founders, early SaaS teams, developer tools, AI tools, open-source brands, and build-in-public creators.
Best for post-launch comments, DMs, trial feedback, Product Hunt comments, Reddit discussions, and Indie Hackers replies.
This is not a public voting board. It turns real community language into the next product and GTM decision.
If comments include usernames or sources, beta leads become more useful. Anonymous comments can still be clustered.
This version intentionally avoids scraping and auto-DMs
It does not connect to Reddit, Indie Hackers, Product Hunt, X, or Discord APIs, and does not bypass platform rules.
It does not message users automatically. Beta invites are candidate leads and drafts for manual judgment.
Classification uses local heuristics, not a formal AI research result. Review original comments before adding backlog items.
Before publishing build-in-public content, remove usernames, private details, and anything that could misquote a user.
Connect the result to Tomako's GTM workflow
Send content angles to the Social Platform Asset Adapter and rewrite them for X, LinkedIn, Reddit, or Product Hunt follow-up.
Turn high-signal beta candidates into a manual DM list. Ask about the workflow before inviting them to try the beta.
Move objections into landing page FAQ and comment replies instead of leaving them in internal notes.
Write repeated feedback as a hypothesis, evidence count, and acceptance criteria before adding it to backlog.
Why not just use a spreadsheet or feedback board
Built around the post-feedback loop
Classic feedback boards focus on collection and voting. This tool focuses on turning community comments into content, beta users, and the next validation loop.
Keeps the original language
The result includes evidence snippets, so you can return to the source instead of prioritizing from vague tags.
Turns objections into assets
When users are confused, concerned, or comparing alternatives, that language becomes FAQ, reply, and landing page material.
Avoids over-automation
Community growth breaks when real conversations become bulk workflows. Tomako organizes signals while keeping DMs and product decisions human.
A good community feedback tool helps you judge, not blindly obey
Evidence: every cluster should point back to original comments, not just abstract labels.
Restraint: feature requests should be merged and validated before entering a roadmap.
Actionability: results should become beta invites, FAQ, content angles, or backlog hypotheses.
Boundaries: the tool should be clear about no scraping, no auto-DM, and no replacement for product judgment.
Workflow: community feedback should return to GTM instead of staying as one-time exposure data.
Frequently asked questions
Does this tool scrape Reddit or Indie Hackers automatically?
No. The current version only processes comments you paste manually, which keeps platform rules, login access, and privacy boundaries clearer.
How is this different from Canny, Productboard, or Featurebase?
Those products are stronger for long-running feedback portals, roadmaps, and voting. This tool is lighter and focuses on turning community launch comments into GTM learning assets.
Can I put these results directly into backlog?
Not directly. The report gives candidates, evidence counts, and next actions, but you should still review original comments and product strategy.
Can this help invite beta users?
Yes, as a shortlist. Final outreach should stay manual, especially to avoid mass-DM behavior.
After organizing community feedback, turn one high-quality comment into a user interview record or rewrite the content angles for platform-specific follow-up.