Hy
Hyper minimalist habit tracker for Chrome
Hacker NewsHyper minimalist habit tracker for Chrome
I'm an undergrad at cal who's trying to get better at React and building apps. I'd love any feedback on the general UI and user experience, new to coding products! If you don't want to download it, but still want to give me feedback, app demo vid & pictures in official launch https://tinyurl.com/reactlaunch Please let me know your thoughts, critical or supportive! Looking to learn
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Made the leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, new · Missing: mac, agents, macos83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released44%44% 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, revenue16%16% 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, crypto0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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