Contextual – Personal task management based on GTD principle

Hacker News

Hello HN! I just released a beta for a personal task manager. Screenshot attached can be seen here https://twitter.com/philipyoungg/status/860445511769235459 . Currently, it works fully online—but I plan to develop online sync capabilities & mobile app after I got feedbacks and nail basic features from early adopters. You can check it as an online web app on http://beta.getcontextual.com , or Twitter DM / email me on (hello@philipyoungg.com) for offline beta version. I used React/Redux/Ramda to develop this and wrap the desktop app on Electron :)

Visit product View on Hacker NewsMay 8, 2017

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: email, context · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

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

11%11% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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