CashCloser, a full react-native app with all the trimmings

Hacker News

I was a cashier for 5 years, and always loathed counting and balancing a till, which was extremely error-prone. I originally wrote a small spreadsheet that made counting out easier, but wanted something that was easier and (potentially) in my pocket. Fast forward many years later, and CashCloser 2.0 is out, with all the fancy stuff an app can have (in-app purchase, some backup features, and more). It's written in react-native, and uses a pretty "modern" front-end stack. http://joelgriffith.net/cash-closer/ I'd love to answer any questions or talk about the project/motivation in general!

Visit product View on Hacker NewsFeb 10, 2017

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

53%53% 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 · Strong signals: way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

25%25% 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

23%23% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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