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The Orbital Index Reaches Issue #40

Hacker News

The Orbital Index Reaches Issue #40

Hey HN, I started Orbital Index 40 weeks ago based on feedback that I received on HN (https://news.ycombinator.com/item?id=19227434) and I've been sending it out weekly ever since. The response has been great, and readership just hit 2500 people. I just wanted to say "thank you" to HN for the motivation to start this, I've learned a ton. Here's issue #40! https://orbitalindex.com/archive/2019-11-26-Issue-40/ -Andrew

Visit product View on Hacker NewsNov 26, 2019

Actual performance

1points

1comments

Did not reach leaderboard

Launch Intel predictions

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

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

38%38% 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, 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 · 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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