Actual performance
252upvotes
13comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto89%89% predicted probability of success on BetaList, 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 · Strong signals: stripe · Missing: mac, agents, macos70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comFits revenue-generating acquisition profile · Strong signals: arr · Missing: mrr, revenue, profit59%59% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting54%54% predicted probability of success on Indie Hackers, 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 · Missing: mobile apps, ios, personal49%49% 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.
Correct prediction on native model
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