Boards – A Modern Textboard Inspired by Classic BBSes

Hacker News

Hey HN! I’d like to introduce you to Boards, a textboard that blends the culture of classic Japanese BBSes like 2Channel and Strange World with a modern chan-style interface. With over 13,000 monthly visitors, it's the second-largest English-speaking textboard, offering an active space for all kinds of text-based discussions (and a few silly posts too :P) I've recently added several new features, including live multiplayer cursors, and there's more to discover as you explore the site! Please check it out and give me your opinions. Thank you! (*´ ∀ `)

Visit product View on Hacker NewsAug 25, 2024

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, new · Missing: mac, agents, macos

88%88% 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 · Strong signals: 000, io, including · Missing: https docs, excited, just released

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, monthly · Missing: mobile apps, ios, personal

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: interface · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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