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Stackeo 2.0 is now online
Hacker NewsStackeo 2.0 is now online
http://stackeo.me Stackeo is a daily curation on the latest and best coding tools and libraries out there. We've been looking into our community feedback and we've improved our service towards our users requests. Stackeo is now more mobile friendly and authentication it became easier. You can login with Github, Twitter, Facebook and Google. Users can save items in there own Stack and check them later. Try it out and please give us your feedback. http://stackeo.me hello@stackeo.me
Share cardActual performance
4points
Did not reach leaderboard
Launch Intel predictions
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting73%73% predicted probability of success on Indie Hackers, 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: google, user, coding · Missing: mac, agents, macos64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly, users · Missing: plus, platform, intuitive40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal31%31% predicted probability of success on TrustMRR, 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, crypto1%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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