Vi
Visualizing activity and reviews from a user base of four million users
Hacker NewsVisualizing activity and reviews from a user base of four million users
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: user, visual, activity · Missing: mac, agents, macos80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released57%57% 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 · Strong signals: reviews, users · Missing: plus, platform, intuitive43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto40%40% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting34%34% 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, revenue13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Vi
Visualizing activity and reviews from a userbase of four million users58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Visualizing activity and reviews from a userbase of four million users
Hacker News7Sc
Scaling Meteor to 2 Million Concurrent Users73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Scaling Meteor to 2 Million Concurrent Users
Hacker News9Pr
Predicting what user reviews are about with LDA and gensim40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Predicting what user reviews are about with LDA and gensim
Hacker News22On
One Million Sliders36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
One Million Sliders
Hacker News1On
One Million Emojis50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
One Million Emojis
Hacker News4On
One Billion Checkboxes: A Bigger Take on One Million Checkboxes57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
One Billion Checkboxes: A Bigger Take on One Million Checkboxes
Hacker News13
3 Million ESPN Brackets61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
3 Million ESPN Brackets
Hacker News1HowManyOfMes58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
See if your name is one in a million
Indie Hackers1entertainmentFlyboarding in Goa29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Watersports Activity in Goa
Indie Hackerscommitment-side-projectRe
Reviews stats on about half a million reviews47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Reviews stats on about half a million reviews
Hacker News5