I built a tool to send you daily digest of your saved bookmarks

Hacker News

Bookmarks which you wanted to read, but simply forgot... It happened to me all the time. I bookmarked the articles to read later and simply forgot about them. Forever. I built Mailist to help with that. Already 2350 users enjoy their "weekly digests" composed from their bookmarks. It makes me super happy! So now, https://mailist.app Pro account allows you to send an email newsletter every day, built from your bookmarks. Does it sound interesting? The free version (weekly email) is available for everyone! Let me know what you think. PS. Unlike other tools, we care about your privacy and don't suggest promo content based on your saved links.

Visit product View on Hacker NewsApr 27, 2020

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Actual performance

65points

23comments

Made the leaderboard

Launch Intel predictions

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

62%62% 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

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

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% 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, personal

42%42% 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

16%16% 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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