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Dollar Lean Club Mobile App
Hacker NewsDollar Lean Club Mobile App
Just launched the 'Dollar Lean Club' app on Google Play Store. Sorry no iOS version yet. Looking for as much critique as possible. New features that weren't part of initial web app idea includes workout programs that you can apply to your week per availability. I also added my personal plan in there. I am a competitive bodybuilder. I promise to respond to all comments. Especially about features you think should be included. Ie. Logging workout Thanks guys
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Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting74%74% 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.
TrustMRRLess likely to generate early MRR · Strong signals: ios, personal, google · Missing: mobile apps, entrepreneurs, apps46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: google, new · Missing: mac, agents, macos37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released34%34% 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, revenue21%21% 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, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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