HABARI
Indie HackersUne nouvelle manière de consommer l'information
Dans ce monde remplis de publicité, de média qui défendent des idéologies au lieu d'informer le public, il arrive un moment où on se noie dans l'information. Habari existe pour fournir de l'information bref et concis
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto57%57% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, io · Missing: https docs, excited, just released42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos33%33% 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, intuitive31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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information guide
Indie Hackers