Actual performance
329upvotes
104comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
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BetaListSuited for BetaList early-adopters · Strong signals: audio · Missing: web3, chat, crypto89%89% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, video · Missing: mobile apps, ios, personal60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% 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, revenue22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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