EarlyFinder

EarlyFinder

Product Hunt

Track startup growth from first tweet to first million

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Actual performance

133upvotes
21comments
Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
87%87% 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.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, 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
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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Cyberpunk Tweet
Cyberpunk Tweet30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

𝙈𝒶ḵẹ_ÿōửȑ__Ṯ𝙬ḗéṫ𝙨▁𝗆ŏrẹ┈𝗰𝚢ḅ𝐞r𝗉ǔń𝒌!

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