Actual performance
243upvotes
21comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto73%73% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal32%32% 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, revenue26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Customer Discovery Sprints41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Done-for-you customer interviews.
Indie Hackerscommitment-side-projectCustomer Discovery Sprints61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Done for you customer interviews.
Indie Hackerscommitment-side-projectTa
TargetBite, Automating Customer Interviews36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
TargetBite, Automating Customer Interviews
Hacker News1Sh
SharpSkill – I was bored to fail my interviews for no reasons58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
SharpSkill – I was bored to fail my interviews for no reasons
Hacker News3Al
Algorithms for Interviews57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Algorithms for Interviews
Hacker News3Diaform70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Run customer interviews on autopilot
Indie Hackers1$801/moaiCustomer Segmentation and Targeting for Marmeting59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Segment And Target Customer, identifying target customer
Indie HackersPeridot57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The searchable memory for your customer interviews
Indie Hackers1aiForgeBlog38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Get your first customer for free
Indie Hackers1advertisingPr
Product Loop – Automated AI customer interviews35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Product Loop – Automated AI customer interviews
Hacker News1