I
I built a service to discover rapidly growing Google search topics
Hacker NewsI built a service to discover rapidly growing Google search topics
Share cardActual performance
446points
116comments
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Product HuntOn track for Day 1 leaderboard · Strong signals: google · Missing: mac, agents, macos60%60% 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.
TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto47%47% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting21%21% 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, revenue19%19% 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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