Actual performance
371upvotes
18comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, cursor · Missing: mac, macos, claude91%91% predicted probability of success on Product Hunt, 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, crypto72%72% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting20%20% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue14%14% 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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