One on One

One on One

Indie Hackers

A substack to share my experiences.

To indulge in writing without any pressure.

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Actual performance

1followers
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
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.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
38%38% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
35%35% 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
32%32% 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
14%14% 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
13%13% 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

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