I made a tiny widget that facilitates frictionless user feedback

Hacker News

Hey HN, I plan on launching several things these coming months, but all of them need some way of gathering and organising user feedback. As an end user, I don’t want to login or click away from a page when reporting a bug or whatnot, unless I specifically choose to do so. And as a dev, I have a specific - almost rigid - list of needs in this regard: an embeddable widget, @project pages, SO-esque comment/vote system, mail-like inbox for user submissions, widget URL whitelist/blocklist, user leaderboards for marketing, noti emails every 24h… I’m launching Buggy.so as a one-size-fits-all answer to the needs of my users and myself. Needless to say I’ll be using it in those “several things these coming months”. Thanks for your time.

Visit product View on Hacker NewsAug 23, 2024

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Actual performance

3points

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, inbox, email · Missing: mac, agents, macos

87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, users, way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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