We
We put together a messaging app over a beer brainstorm
Hacker NewsWe put together a messaging app over a beer brainstorm
https://itunes.apple.com/dk/app/id880331892 One of those side projects that turned out fun, but have absolutely no idea on how to get people using it. (we keep sharing it on our social networks, and got close to a 100 downloads) Funny story about the name is that we made up a name before we knew what the app was going to be. It was just a fun exercise we indulged in at the pub, a bunch of laughs over silly app names for imaginary projects.
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting69%69% 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: ide · Missing: https docs, excited, just released52%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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apple, new, using · Missing: mac, agents, macos28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% 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, crypto6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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