PackageThieves
Website dedicated to uncovering those who steal packages
I became tired of seeing people have packages stolen from their doorstep, while all the while, you could see WHO the person is! The hope is to connect the dots between thief and occurrence, and identify them.
Share cardActual performance
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Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
27%27% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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