After 2.5 years on my side project, it has hit £500/month revenue

Hacker News

It's been a long slow hog and I almost gave up a few times (more than a few) but when covid hit this year it gave me some time to really focus on my product. There were stupid user journey things that I knew needed fixed. There were some features I knew needed added. And I knew the pricing was wrong. I spent some hardcore time working on these things back in March / April and since then my MRR has continued to grow. My product is SongBox ( https://songbox.rocks ) - it's an alternative to things like bandcamp and soundcloud for creators who need to share audio files privately. I'm at a stage now where I've bottomed out all the work I've wanted to do and I'm looking for a fresh round of feedback. Would love you guys to check it out and see what you can think of. Thanks!

Visit product View on Hacker NewsDec 10, 2020

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

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best fitHighest predicted score across all platforms for this description.

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

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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal

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

Acquire.comPre-revenue stage for this audience · Strong signals: mrr, revenue · Missing: arr, profit, saas

26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

25%25% predicted probability of success on AppSumo, 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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