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Website Hunt – Best websites you didn't know

Hacker News

Website Hunt – Best websites you didn't know

Hello HN ! This is my first post, (long time 'lurker') I decided to show you my weekend project (≈20h of work). Websitehunt.co The best websites you didn't know. https://www.websitehunt.co It is basically a newsletter where you receive the most upvoted websites each week. The websites submitted have to "stand alone", like tools. It generally cannot be a landing page for an app and such. If you know a cool little known website, this is the place to add it ! Autopromotion is welcomed. The submission are queued and 10 websites of the queue are released each day. I think this is good for the UX. The concept is old and very simple. It is just a ProductHunt for websites, but I think people will be interested, ( I am and was before building it ).

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
69%69% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
50%50% 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 HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
50%50% 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
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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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