I built an easy straightfoward email monetization tool

Hacker News

I built MailShare to solve a problem I encountered while trying to monetize my own email list: existing solutions were either too complex or i had to setup my email sending provider completely from scratch again. What MailShare does: Provides a simple way to set up paid subscriptions for your email content Integrates with Stripe for secure payments Offers a free tier with a fee and a $89/month premium tier with only Stripe fees Automates welcome emails and subscriber management Key features: One-click audience setup Customizable payment links Automated subscriber management Basic analytics dashboard I'm particularly interested in feedback on: The pricing model (free with 20% fee vs $89/month flat fee) Essential features for email monetization that I might be missing Potential integrations that would make MailShare more useful As a solo founder, I'm excited to share this with the HN community and eager to hear your thoughts, criticisms, and suggestions. I'm here to answer any questions and discuss the challenges of building a product in the email monetization space.

Visit product View on Hacker NewsJul 25, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

45%45% 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: month, way · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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