Promo Codes for my first iPhone App

Hacker News

Hi. I have read lot of great articles on HN and it has helped me a lot in my journey as an independent developer. That's why it feels so good to share few promo codes for my first iPhone app. Below is a small description of the app: Calci - A simple and beautiful calculator that shows result instantly. Features: ✓ A beautiful looking calculator that is fast and friendly to use. ✓ Saves your time as results are displayed for each keystroke. ✓ Automatically prevents you from entering invalid calculations. ✓ Clear and large buttons make it easier and faster to calculate. ✓ Swipe complete expression to check for mistakes. ✓ Beautiful background themes with Retina Display. ✓ Accessibility support for VoiceOver. ✓ And you will never need the "=" button again. Itunes link: http://itunes.apple.com/app/calci/id532226932?mt=8 Promo Codes: MYENR9PYMMAK 6FLK4X9E33EX LHPFEYKMMAXM K7A4XR7A4Y4M KWAHKMJ3WWRW 4NFTFXWPRNAP JKJYKWE6H47R FY9WN4FN4FW7 AR77J47L9Y7X K9EPFTFLMMY3 Thanks. Your honest feedback is always appreciated :)

Visit product View on Hacker NewsJun 10, 2012

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Actual performance

6points

9comments

Did not reach leaderboard

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

93%93% 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 HuntUnlikely to reach the leaderboard · Strong signals: apple, code · Missing: mac, agents, macos

49%49% 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 released

49%49% 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 · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% 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, 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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