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Maildown – email campaigns with Markdown syntax

Hacker News

Maildown – email campaigns with Markdown syntax

Hi, I just launched the MVP version of my startup, Maildown: https://www.maildown.app , and I'm looking for a bit of feedback on the product. As a serial hacker, I've made a few different products over the years, but have never been happy with any of the email campaign management tools that I've used in support of these - they all seem to be based on WYSIWYG editors, which I find very time consuming. I created Maildown as a solution to this - it allows you to generate your email content using Markdown syntax, meaning that you can create and send your content a lot more quickly. At the moment, its at a very early stage - the functionality is a bit 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. Thanks, Chris

Visit product View on Hacker NewsApr 3, 2019

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

79%79% 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

67%67% 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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

37%37% 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

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

10%10% 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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