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Tabular – Email design tool that generates bulletproof email HTML

Hacker News

Tabular – Email design tool that generates bulletproof email HTML

Hi HN, I’ve developed http://tabular.email (Tabular), a new email design tool that generates hybrid mobile-first email HTML. Think of emails for your app, such as user verification or welcome, newsletters, or marketing emails. My goal was to make designing emails as quick and intuitive as possible. To make a tool where everything is done visually (adjusting margins, paddings, gaps, dimensions etc.), without the user having to worry about writing email HTML code. Cool thing is that you get full control over how your email looks on mobile devices. When designing, you can switch to mobile mode, and any styling changes that you make will overwrite how it looks on desktop. Tabular’s algorithm generates responsive HTML code that renders on all major email inboxes and devices, including older desktop Outlooks (e.g. Outlook 2010, 2013 etc.). At the moment, I’ve implemented 8 integrations so you can connect your email service provider (e.g. Sendgrid, Mailgun) to use it there directly, or download the HTML and upload it manually. You can create any design structures using the row and column blocks. Nest the blocks however you like without constraints on how you use them to create structures. Combine the blocks to create complex designs or data tables for example. I’d love to hear your feedback.

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Actual performance

88points
33comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, inbox · Missing: mac, agents, macos
87%87% 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: including · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: intuitive · Missing: plus, platform, reviews
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
55%55% 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 · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: margin, margins · Missing: arr, mrr, revenue
13%13% 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.

Correct prediction on native model

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