
Actual performance
110upvotes
14comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
55%55% predicted probability of success on BetaList, based on ML models trained on real launch data.
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
11%11% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Pi
Pick Your Paranoia40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Pick Your Paranoia
Pi
Pick One40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Pick One
To
Toronto - Drop off things you don't need and pick up those you do47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Toronto - Drop off things you don't need and pick up those you do
Dr
Drop-in caching for R functions42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Drop-in caching for R functions
Dr
Drop-in sticky headers and footers for UICollectionView44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Drop-in sticky headers and footers for UICollectionView
So
So many models, which to pick?25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
So many models, which to pick?
Pi
Pick a Category, Explore the Indieweb44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Pick a Category, Explore the Indieweb
Pi
Pick Me lk l. An Uber clone57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Pick Me lk l. An Uber clone
I
I made a faster way to pick 30k+ Unicodes57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I made a faster way to pick 30k+ Unicodes
Pick Radar45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.