Songcraft – Online Songwriting Platform and Guitar Tab Builder

Hacker News

Hi HN! I'm Gabe, the creator of Songcraft ( https://songcraft.io/home ). I recently dove headfirst into songwriting, and I quickly grew frustrated with my process. I found songwriting difficult enough without having to wrangle a mess of different tools, and there's no great solution to build chord sheets and tabs (unless you love pure text input). So, I built Songcraft - an online songwriting platform and tab builder. The drag-and-drop editor makes it easy to jump from chords to lyrics to melodies. I added a chord progression generator and chord recommendation engine to ensure the ideas keep flowing. The integrated tuner, rhyming dictionary, metronome, and audio recorder allow you to stay focused without distraction. A few months ago I shared the beta on Hacker News and got some incredibly helpful feedback and some amazing beta users. Since then, I've revamped the product and made a ton of improvements and additions. Today is launch day, and I wouldn't be here without Hacker News! I'd love to hear your thoughts and answer any questions you may have. Drop a line here or at gabe@songcraft.io.

Visit product View on Hacker NewsMar 20, 2019

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

81%81% 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.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: platform, builder, users · Missing: plus, intuitive, reviews

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · 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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