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I made a simple feedback platform for designers

Hacker News

I made a simple feedback platform for designers

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Actual performance

24points
9comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews
77%77% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
61%61% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
51%51% 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
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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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