I
I made a collection of kick-ass designs
I made a collection of kick-ass designs
Share cardActual performance
4points
2comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →74%74% 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.
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Co
Collection of visualizations for IPython51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Collection of visualizations for IPython
Co
Collection of augmented performances48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Collection of augmented performances
Vi
VimFeed – collection of Vim-related newsfeeds47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
VimFeed – collection of Vim-related newsfeeds
Ja
Java Collection Overhead33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Java Collection Overhead
Th
The Lightest - a collection40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Lightest - a collection
nishthastore_01 Halloween Collection29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Limited Edition Halloween Designs - All Costumes
OurToolkit16%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
OurToolkit - Your All-in-One Tool Collection
MI
MIT-licensed distributed atmospheric data collection61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
MIT-licensed distributed atmospheric data collection
CORONAMOOD15%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Data collection
Ki
Kitlab a Collection of Tools for Webdevs41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Kitlab a Collection of Tools for Webdevs