Timely – Day Planner (iOS App)

Hacker News

About the app - Timely is a day planner app on which you can manage your daily schedule. You can create tasks and assign a tag to each task. For example, "Study Physics" can have a tag assigned as "University". Inbox is a place to add your unscheduled tasks. Get notifications sent for your tasks to get reminded about them. About the beta - Looking for iOS users to test and provide feedback. About the project - I started this project as a personal need. I tried and used dozens of day planner apps available on the App Store to manage my days but none of them suited my needs. Whereas on the Android platform there were many personal scheduling apps which I liked. Those apps tend to have a specific format. So I decided to create one for the Apple platform as I have an iPhone as my primary phone. And this is how my app was born. Also, I wanted to learn iOS development so the opportunity couldn't have been any more perfect.

Visit product View on Hacker NewsApr 12, 2023

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

91%91% 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.

TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, video

79%79% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, user · Missing: mac, agents, macos

74%74% 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: ide, io · Missing: https docs, excited, just released

35%35% 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: platform, users · Missing: plus, intuitive, reviews

33%33% 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

21%21% 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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