My
My PyCon 2013 diary
Hacker NewsMy PyCon 2013 diary
http://cjdrake.blogspot.com/2013/03/pycon-day-zero-opening-reception.html http://cjdrake.blogspot.com/2013/03/pycon-day-one.html http://cjdrake.blogspot.com/2013/03/pycon-day-two.html http://cjdrake.blogspot.com/2013/03/pycon-day-three.html
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released45%45% 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 · Missing: plus, platform, intuitive42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto27%27% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting26%26% 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, revenue22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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