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Apptimize: A/B testing for native Android, iOS apps
Hacker NewsApptimize: A/B testing for native Android, iOS apps
Share cardActual performance
126points
50comments
Made the leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Strong signals: ios, apps · Missing: mobile apps, personal, entrepreneurs81%81% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue36%36% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto19%19% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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