bookmarksheet - manage your bookmarks with ease

Hacker News

i recently published bookmarksheet, a tool for adding your favorite web content to google sheet in a single click. why build it when there is a plethora of bookmarking apps out there? when i come across something interesting while browsing the web that i want to save for later, i want to easily do it in the simplest manner. bookmarksheet is perfect for that. it saves your bookmarks in the familiar google sheet and doesn’t need you to learn a new interface or sign up for yet another service. you know that your bookmarks are stored in your sheet even if the bookmarksheet stops service after a while, which is not the case for most apps which stores the bookmarks in their databases. bookmarksheet is reliable and secure. it is easy for me to access and manage my bookmarks and web highlights from anywhere. i think of it as a digital attic, where anything of interest can be stored without second-guessing its bookmark worthiness.

Visit product View on Hacker NewsFeb 29, 2024

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

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

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% 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

14%14% 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

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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