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Email marketing as code (open source Customer.io alternative)
Hacker NewsEmail marketing as code (open source Customer.io alternative)
After getting frustrated with Customer.io's limitations, I built an open-source alternative that lets you write marketing automation in pure code. Define user segments in SQL, write email flows in TypeScript, and template emails in React+Tailwind. Support for campaigns, segments, events, users, and transactions. SMS support planned.
Share cardActual performance
7points
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Made the leaderboard
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, email, code · Missing: mac, agents, macos92%92% 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 · Missing: supports, reddit linkedin, podcasting76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released74%74% 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 · Strong signals: users · Missing: mobile apps, ios, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto24%24% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive22%22% 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, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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