Track the time and temperature of your cold showers and ice baths

Hacker News

Hello there, I'm working on an android app that allows to easily track the time and temperature of your cold showers and ice baths. Main features include the possibility to visualize your progress over time, achievements when you reach new time and temperature limits, a “badass score” that makes it easy to compare your progress with others, and a Voice Coach that keeps you motivated and makes you feel less alone in the cold. I’d appreciate any feedback on the app. More specifically, I would like to know how intuitive the user interface is, and what UI changes would make it a better app. Thanks for your feedback!

Visit product View on Hacker NewsMar 29, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, visual · Missing: mac, agents, macos

83%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, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% 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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

37%37% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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