Pr
Product Graveyard – Commemorating the most memorable dead products
Hacker NewsProduct Graveyard – Commemorating the most memorable dead products
Share cardActual performance
265points
126comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos70%70% 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.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto48%48% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Ca
Carl Jung's Seven Sermons to the Dead55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Carl Jung's Seven Sermons to the Dead
Hacker News1I
I resurrected one of the top dead Show HNs53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I resurrected one of the top dead Show HNs
Hacker News8I
I resurrected one of the top dead Show HNs53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I resurrected one of the top dead Show HNs
Hacker News5Th
The Dead Sea Scrolls Visualized66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Dead Sea Scrolls Visualized
Hacker News1Al
Alternatives to Google's dead products60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Alternatives to Google's dead products
Hacker News2A
A dead code killer for Erlang75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A dead code killer for Erlang
Hacker News103Ne
NewsFeeder – Dead simple product updates77%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
NewsFeeder – Dead simple product updates
Hacker News4Th
The Dead Web62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Dead Web
Hacker News2In
Inject Me Timbers – Dead simple dependency injection28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Inject Me Timbers – Dead simple dependency injection
Hacker News1Re
Resurrecting a dead Dune RTS game51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Resurrecting a dead Dune RTS game
Hacker News485