Re

Realtime Audience Feedback

Hacker News

Realtime Audience Feedback

Share card

Actual performance

1points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
83%83% 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.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
14%14% 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, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

on
onslyde - realtime audience feedback29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

onslyde - realtime audience feedback

Hacker News6
Fe
Feedbackyard - Audience Feedback and Interaction Toolkit25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Feedbackyard - Audience Feedback and Interaction Toolkit

Hacker News4
Backtalk
Backtalk63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Get feedback from your audience in a snap.

Indie Hackers4analytics
Lo
Lobste.rs for an African audience23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lobste.rs for an African audience

Hacker News3
Pe
Pebble realtime bus departures in Sydney65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pebble realtime bus departures in Sydney

Hacker News3
Re
Realtime DAO52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Realtime DAO

Hacker News3
Re
Realtime Spheretracing in WebGL66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Realtime Spheretracing in WebGL

Hacker News1
Re
Realtime Blackboard58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Realtime Blackboard

Hacker News3
Re
Realtime busses (websockets, leaflet and d3) (59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Realtime busses (websockets, leaflet and d3) (

Hacker News1
Stria
Stria48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Collect feedback from your audience and analyse website

Indie Hackerscommitment-full-time