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Hakn, an iOS reader for Hacker News
Hacker NewsHakn, an iOS reader for Hacker News
Share cardActual performance
6points
3comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto57%57% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos32%32% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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