ep

epistly, hand written notes for busy people

Hacker News

epistly, hand written notes for busy people

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Actual performance

3points
9comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos
71%71% 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.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
29%29% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
23%23% 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
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
20%20% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Incorrect prediction on native model

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Find the people written into your story

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