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Convertme2it– weight comparison tool for visualisation and funkiness
Hacker NewsConvertme2it– weight comparison tool for visualisation and funkiness
Ever wondered how much you weigh in comparison to everyday items? Like, how many bags of sugar do you weigh right now? Are you on a weight loss journey and want to know a VISUAL equivalent to how much weight you have lost? Well, ConvertMe2it IS FOR YOU ! It’s the easiest comparison tool to use, is great fun & seeing a visual representation of your weight loss may just motivate you to shed even more KG’s !
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1points
Did not reach leaderboard
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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal54%54% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual · Missing: mac, agents, macos36%36% 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, podcasting26%26% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue10%10% 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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