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Turn your un-used domains into Reddit-like clones

Hacker News

Turn your un-used domains into Reddit-like clones

Hey there, HN people! I would like to share with you a little tool I've been working on this year. It's called Newsy https://www.newsy.co Problem I have more than 30 domains that I've bought over the years. I plan to (eventually) do something with them, but meanwhile, they are un-used and just sitting there. I want to use them somehow. I know there are a few impulsive domain buyers out there! :) My Solution I wanted to turn my un-used domains into something useful without me having to do too much work. So I created Newsy https://www.newsy.co It turns your un-used domains into a Reddit-like content aggregator. It automatically crawls the web based on the keywords I provide (or RSS feeds) and creates a Reddit-like content-based website. Over the past few months, we've added following features - memberships, voting, comments, themes, automated newsletters, integration with other tools & monetization by bringing your own ads. Examples Check out some of mine and some of other users who have their domains on Newsy https://www.dataloco.com https://www.heystartup.com https://www.getinfosec.news It's still early days for us, but I'm glad that I am now using most of my 30 un-used domains for somewhat interesting things and everything is pretty much automated so I don't really have to do much work on them. Would love for you guys to check it out! Thanks!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
80%80% 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: user, new, using · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, users · Missing: mobile apps, ios, personal
36%36% 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
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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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