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I made a books recommendation app based on your mood

Hacker News

I made a books recommendation app based on your mood

Hello HN, I noticed that I often looked for new books, depending on my mood (e.g., if I'm feeling tired, I want to find books that'll help me fix that and improve my sleep). So, I created my 1st indie project, BooksByMood. BooksByMood will help you find your next read based on your mood w/ - Books averaging 4.09/5 on Goodreads - Each book comes with an explanation of why it's selected for your mood - 18 moods to explore I hope you'll enjoy using the website, Cheers!

Visit product View on Hacker NewsMar 26, 2024

Actual performance

173points

69comments

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

52%52% 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.

TrustMRRLess likely to generate early MRR · 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

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.

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.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos

38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · 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 · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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