Taskr - "Tasking Done Right"

Hacker News

Hello guys! I need some help reviewing, and refining the landing page for an app that I'm building: http://taskr.punchdev.com/ (and here's a screenshot in case my DNS hasn't updated yet: http://cl.ly/0M1w340S1M2T1m0W3G2I ) It's a to-do list app that differentiates itself from others by making sure you add new tasks daily. Plus, it makes it easy for the user (you) to see the status of a task thanks to colors (blue for week-long tasks, red for overdue, orange for nearly due, and green for not due yet. Bonus points: The screenshot on the right is actually made with Keynotopia! Thanks a lot guys! Georges Duplessy, PunchDev Labs :-)

Visit product View on Hacker NewsJun 23, 2012

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Indie HackersFits the IH revenue-focused audience · 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.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% 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

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

nativeThis product was originally launched on this platform.

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.

Incorrect prediction on native model

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