Unbundling Reddit
Indie HackersUnderstand what they want
As a builder and Product Manager, I love doing customer research. Using Reddit made me 10x more efficient. Greg Isenberg's #CommunityCollege alumni -> understanding users from Reddit conversations is my driver.
Share cardActual performance
2followers
$100MRR/mo
Made the leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, using · Missing: mac, agents, macos89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: efficient, builder, users · Missing: plus, platform, intuitive53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal36%36% 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, 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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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