Abookmark – advanced bookmark and tab/session manager

Hacker News

Abookmark is a chrome extension. It uses the native bookmarks as database. main features: - Labels/Tags. - Sticky notes in web pages. - Trash/Recycle. - Tab managments. (store & restore tabs/sessions.) - Sailing. (update saved bookmarks automatically while surfing) - Advanced bookmark bar (spread view & top bar) - Data text editor. (edit bookmarks in your favorite text editor) - Import selected bookmarks from a file. - Monthly backup. - Recent bookmarks. - Link hint. (vi-like keyboard) In Abookmark a bookmark is a sleeping tab and a tab is a living bookmark. The two can be converted into each other. Please backup your bookmarks before you try it.

Visit product View on Hacker NewsAug 29, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

89%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, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, monthly · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

26%26% 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, crypto

18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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