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TimeTurtle, a time tracking app with a focus on interactivity (beta)
Hacker NewsTimeTurtle, a time tracking app with a focus on interactivity (beta)
Hi, I've been working on a time tracker - an app of which there are many already, so I've tried to distinguish it by putting in my experience/love with viz and UX to create a very interactive workflow, which I believe helps get a better overview. It's in beta now, feedback is much appreciated (especially if you're using tools like this). The first 200 users get a lifelong free account. https://timeturtle.app Cheers, Almar
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, activity, using · Missing: mac, agents, macos66%66% 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.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: time tracking · Missing: web3, chat, crypto0%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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