HelloInbox 2.0 – Email Deliverability Checklist for Marketers

Hacker News

Hey HN community, over a year ago, I built a checklist from all the valuable information I found online, and from my personal experience, trying to fix deliverability issues for my software business. Since then I've made updates and improvements and would love to get your constructive feedback and/or suggestions to improved it. Feel free to ask questions or comment, I'll be happy to respond.

Visit product View on Hacker NewsJul 11, 2023

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Actual performance

2points

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Launch Intel predictions

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

82%82% 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, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

14%14% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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