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Indie HackersOne Post All Social Networks
Social platforms are great at showing content, but terrible at helping you understand it. Important insights get buried in noise, and there’s no simple way to extract value from what you see.
Share cardActual performance
1followers
$1,000MRR/mo
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews48%48% 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 released34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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