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Sirius Scope – Analyze Private Businesses and Public Stocks

Hacker News

Sirius Scope – Analyze Private Businesses and Public Stocks

It’s a website that aims to offer a suite of financial calculators and analysis tools. So far it has some real estate calculators, manual calculators for vertical analysis of your business and it can retrieve you similar data for public stocks. As someone who is not a professional at this I wanted to get some feedback from technical people. Your insights on improving the functionality and user experience would be highly valuable. Thank you in advance

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Actual performance

1points
Did not reach leaderboard

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
19%19% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released
17%17% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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