AppFeedback.io
Easily gather and analyse your user feedback
It was a tool born out of a game I was making. I wanted a simple way to gather user feedback on my app easily and present it in a useful format
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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