Simon Figures

Simon Figures

Indie Hackers

Simon says meets stained glass

Share card

Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
78%78% 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.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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, podcasting
17%17% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.

Correct prediction on native model

Similar products

Pa
Paul Graham Says37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Paul Graham Says

Hacker News2
St
StumbleUpon Meets ProductHunt50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

StumbleUpon Meets ProductHunt

Hacker News1
Te
TechCrunch Meets the Onion46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TechCrunch Meets the Onion

Hacker News3
Ho
Hoodmaps Meets 4chan74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hoodmaps Meets 4chan

Hacker News8
Op
OpenVino - Yelp meets OpenTable for Wine53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpenVino - Yelp meets OpenTable for Wine

Hacker News2
Ve
VerticalChange, SurveyMonkey meets Highrise (and a LOT of AngularJS)47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

VerticalChange, SurveyMonkey meets Highrise (and a LOT of AngularJS)

Hacker News16
Sevenfold
Sevenfold31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tetris meets crosswords

Indie Hackers1games
InstaRoasts
InstaRoasts37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Where Humor Meets the Heat! 🔥

Product Hunt+6
ArcRefinery
ArcRefinery49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Storytelling meets AI

Product Hunt+7
Sh
Share, with Glass.48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Share, with Glass.

Hacker News2