Bookends – Book discovery and bookmarking app

Hacker News

Android: https://play.google.com/store/apps/details?id=com.bookends Apple: https://itunes.apple.com/us/app/bookends/id1417646662 Content discovery is powered by user-content, via collaborative filtering. The app is written in react-native and the server is Python3 with the bottle micro-framework. It requires Facebook login but we only ask for your pic, name, and account number. What do you like about it? What do you dislike? Suggestions? Warnings? Thanks for trying it out!

Visit product View on Hacker NewsSep 13, 2018

Share card

Actual performance

1points

1comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

80%80% 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.

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

53%53% 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

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

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

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

40%40% 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

20%20% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Bookscope46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your AI-powered book discovery app

Indie Hackers1ai

Disco50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Artist Discovery App

Indie Hackers1b2c

Discovery for Periscope, Meerkat, Twitch44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Discovery for Periscope, Meerkat, Twitch

Hacker News2

The Hawaii Project – A personalized book discovery system51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Hawaii Project – A personalized book discovery system

Hacker News32

Metamorphosis by Kafka (FREE book app)62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Metamorphosis by Kafka (FREE book app)

Hacker News1

EDM Hunters35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Music Discovery App

Indie Hackers6$1,500/mob2c

I made an app discovery app, any feedback?30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made an app discovery app, any feedback?

Hacker News4

Joelbooks43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI Book Discovery Platform

Indie Hackers

My first ever e-book, Hacking Obamacare65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first ever e-book, Hacking Obamacare

Hacker News6

I Wrote a Book on ReactiveCocoa75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I Wrote a Book on ReactiveCocoa

Hacker News1

Browse all products Analyze your launch