Morning Reader 3 – Curated Blockchain News (beta)

Hacker News

Hi there, I'm João, maker of Morning Reader ( http://morningreader.com ), a technology news curation app. We're working on Morning Reader 3, which adds a new channel focused on blockchain and crypto news from top sources like CoinDesk, Bloomberg, CoinTelegraph, and more. The private beta is live here: https://beta.morningreader.com User: mr3beta Pass: mr3beta Would love to hear your feedback. Thanks!

Visit product View on Hacker NewsFeb 8, 2018

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

48%48% 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 · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new · Missing: mac, agents, macos

26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

9%9% 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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