ExtSpot
Chrome Web Store analytics for extension research
I’m building ExtSpot because Chrome Web Store data is full of useful market signals, but hard to search and compare. It helps founders and developers find trends, study competitors, and understand extension opportunities
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Launch Intel predictions
Analyze your own launch →49%49% 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 TrustMRR, 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.
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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