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I built an iOS app that helps YouChoose faster

Hacker News

I built an iOS app that helps YouChoose faster

Hey, This is Yash here. I built YouChoose because I was confused about how to have my eggs - scrambled or as an omelet. This made me realize..... In life, we spend too much time thinking about our choices rather than making a choice. These things take up too much mental bandwidth that is better utilized elsewhere. In most circumstances, we just need to make the call - the more we delay, the more it exerts us. Input your two choices. Hit the Choose button. And that's it. There's only one caveat - you can't go back (for the same choices). YouChoose is my micro effort to introduce some randomness in people's life. I am eager to hear your thoughts and comments!

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Actual performance

4points
6comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
73%73% 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
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% 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 · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
33%33% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto
0%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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