Maildown – email management using Markdown

Hacker News

I just launched the MVP of my new product: https://www.maildown.app As a serial hacker, I inevitably get to the stage where I have to use something like Mailchimp or Mailjet to start sending transactional or automated emails. I've never liked the WYSIWYG editors that apps like this offer, as I find them far too time consuming. This is why I've created Maildown, an email management tool that uses Markdown syntax, which I think make it much quicker to get going. At the moment, its at a very early stage - the functionality is quite limited and its probably still a bit buggy. However, I'm putting this out there now to see what appetite there is for a tool like this. Would be great to hear feedback from anybody, and whether you think it'd be of use to you Thanks, Chris

Visit product View on Hacker NewsApr 2, 2019

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% 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

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

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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