Ne

New colorful unit converter

Hacker News

New colorful unit converter

Hello, my name is Mikhail Melanin http://twitter.com/mikemockup. Together with my friend, Artyom Keydunov http://twitter.com/keydunov, we made our first app - an amusing unit converter Inché. The app contains the primary units of measurement. The illusion of navigation is created by color change. The app is completely free and has no ads. Download link to App Store: https://itunes.apple.com/app/inche/id933515910 Link to the app website: http://inche.b1nary.io Link to the press kit: http://inche.b1nary.io/press-kit Contacts: mikeymela@me.com

Visit product View on Hacker NewsJan 28, 2015

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

70%70% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, new, using · Missing: mac, agents, macos

31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% 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, revenue

14%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, crypto

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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