Record how your day went and view GitHub-like graphs and stats

Hacker News

Hello HN! a day in my life is a daily mood tracker app that helps you record the quality of your life. With this app, you can easily track your mood on a daily basis and generate weekly, monthly, and yearly GitHub-like graphs and stats to gain insight into your emotional well-being. Features a simple and intuitive interface that allows you to quickly and easily record your daily mood. You can view stats and graphs that show how your mood changes over time, allowing you to identify trends and gain insight into your overall well-being. Take print-outs of your graphs or simply share with friends, family, or the world. Made with React Native. Let me know what you guys think! :)

Visit product View on Hacker NewsDec 29, 2022

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4points

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

61%61% 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.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: intuitive, interface · Missing: plus, platform, reviews

48%48% predicted probability of success on AppSumo, 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 released

39%39% 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, revenue

15%15% 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, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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