Ackee
Indie HackersPrivacy-focused website analytics
We believe that you don't need to track every aspect of your visitors. Ackee keeps tracked data anonymized to avoid that users are identifiable, while still providing helpful insights.
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting59%59% predicted probability of success on Indie Hackers, 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: users · Missing: mobile apps, ios, personal50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive45%45% 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, revenue14%14% 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, crypto7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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