Re
Replacements for Google Analytics (Borrowed from Rapnie)
Hacker NewsReplacements for Google Analytics (Borrowed from Rapnie)
Instead of being buried in a comment, here's a list assembled by rapnie. Following up from a recent 'stop using GA' post. https://usefathom.com/ https://goaccess.io/ https://github.com/NYPL/google-analytics-proxy http://matomo.org/ https://ackee.electerious.com/ https://www.goatcounter.com/ https://count.ly/
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: google, using · Missing: mac, agents, macos45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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