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Improve English Vocabulary by Reading Emails Daily

Hacker News

Improve English Vocabulary by Reading Emails Daily

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Actual performance

4points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
60%60% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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: email · Missing: mac, agents, macos
31%31% 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
26%26% 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
22%22% 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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