Ho
Honbako
TrustMRRHonbako is a manga collection tracker with barcode/ISBN scanning, metadata lookup, and Notion sync. Users can track, organize, and manage their manga library — available as a freemium SaaS with monthl
Honbako is a manga collection tracker with barcode/ISBN scanning, metadata lookup, and Notion sync. Users can track, organize, and manage their manga library — available as a freemium SaaS with monthly subscription or credit-based feature unlocks.
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →TrustMRRFits verified-revenue profile · Strong signals: month, monthly, users · Missing: mobile apps, ios, personal70%70% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto30%30% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, code · Missing: mac, agents, macos28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue19%19% 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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