KindMind, an online journal with a focus on mental health and wellness

Hacker News

Hey all, I'm Garrett and I'm a software engineer from Oregon. I've used journaling as a tool to help me untangle my thoughts for the last 15 years. I went from paper, to a notepad app, to Svbtle (blogging platform), to Google Docs, and finally decided to build my idea of the perfect online journal—one with an emphasis on minimalism, mental health, and self-discovery. Thanks for dropping by and happy journaling, G

Visit product View on Hacker NewsJan 17, 2024

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

56%56% 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

55%55% 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: google · Missing: mac, agents, macos

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

TrustMRRLess likely to generate early MRR · Strong signals: google · 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: platform · Missing: plus, intuitive, reviews

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

26%26% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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