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Walker.js – open-source, vendor-agnostic autotrack library
Walker.js – open-source, vendor-agnostic autotrack library
Share cardActual performance
3points
5comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →82%82% 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.
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
14%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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