I
I built an app to ask for and share recommendations
Hacker NewsI built an app to ask for and share recommendations
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos68%68% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released41%41% 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, intuitive33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting12%12% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
As
Ask anyone for book recommendations or give one57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Ask anyone for book recommendations or give one
Hacker News3Ev
Every Ask HN about book recommendations56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Every Ask HN about book recommendations
Hacker News4Scoot24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Share traveling recommendations with 1 link
Indie Hackerscommitment-side-projectQu
Quora for Recommendations43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Quora for Recommendations
Hacker News1Ti
Tired of Netflix recommendations? Televisor57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Tired of Netflix recommendations? Televisor
Hacker News1Sc
Scotch2Vec – AI Scotch Recommendations29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Scotch2Vec – AI Scotch Recommendations
Hacker News2Ap
App from Ask HN Socialdistance.app35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
App from Ask HN Socialdistance.app
Hacker News1
TasteLanc47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
An app providing personalized dining and nightlife recommendations in Lancaster, PA.
TrustMRR15$750/moArtificial IntelligenceKINPEN14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Travel app to get recommendations from locals.
Indie Hackers2travelI
I made a book recommendations app47%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 book recommendations app
Hacker News2