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Precious Metals Manager

Hacker News

Precious Metals Manager

All-in-one app that provides analytics and metrics to manage precious metals portfolio efficiently. The app offers an intuitive UI, enabling users to input their coins, bars, or rounds and instantly obtain real-time insights into their value evolution. Users can assess their assets based on dealer prices, generate exportable reports for tax filing, access charts for strategy overviews like dollar-cost averaging, and use tools to track live prices of gold, silver, platinum, and palladium. Additionally, the app provides a catalog for identifying bullion coins.

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Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: efficiently · Missing: supports, reddit linkedin, podcasting
76%76% 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.
AppSumoStrong fit for a featured deal · Strong signals: intuitive, efficient, users · Missing: plus, platform, reviews
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
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.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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