A Command-Line Time Tracker

Hacker News

Let me start by saying thank you for taking the time to review it. I hope it is useful to someone. It can be downloaded and reviewed at no cost with the following offer code: hackernews, to be entered during the purchasing process. Reviews on the software itself, and marketing advice on how to grow sales is appreciated. Site: http://baileyssoftware.com/ Notes: - I am aware of the @gmail address used, but I don't want to pay for a service (e.g. https://gsuite.google.com/ ) until I have the monthly income to support it. - If there is enough interest I plan to add more features such as exporting to csv.

Visit product View on Hacker NewsDec 2, 2017

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Actual performance

6points

1comments

Did not reach leaderboard

Launch Intel predictions

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

65%65% 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 HuntOn track for Day 1 leaderboard · Strong signals: google, new, notes · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · 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 · Strong signals: month, google, monthly · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · 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

19%19% 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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