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I made a free tool to help you create beautiful badges for your website

Hacker News

I made a free tool to help you create beautiful badges for your website

Hi HN, My products this year didn't reach the top spots on Product Hunt... ...but I still wanted a badge on my website! So I did, added some code and voila, the "17th product of the day" badge is on the website. Simple enough. It probably should've ended there... But then I thought. "Maybe, someone else might also want a badge? Wouldn't it be cool to make a tool for this..." So I made Badge My App: A simple & free tool to help you create beautiful badges for your website. 1. Add a title 2. Choose stars or rank 3. Export, and voilà – your badge is ready to shine! Add a badge to your website and get: - Better conversions - More sales - Sometimes you need to give yourself a pat on the back Happy 2025! Auden

Visit product View on Hacker NewsDec 29, 2024

Actual performance

2points

2comments

Did not reach leaderboard

Launch Intel predictions

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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, 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

22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

14%14% 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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