RS

RSS Feeds in Notion.so

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RSS Feeds in Notion.so

I recently built a tool to manage and store RSS Feeds in Notion. The only problem is that it doesn't auto save the HTML into notion page (this would required parsing HTML into Notion objects). I started on this with [html2notion]( https://github.com/Jeadie/html2notion ), but it turned out to be alot of work. With Notion already having a [Notion web clipper]( https://www.notion.so/web-clipper ), I was wondering if it was worth implementing? Personally I read a small fraction of the blog posts from my RSS feed, and I like the spare page to take notes. For me, notion-rss solves the one core problem I have, acquiring and filtering high quality RSS feeds. What does HN think?

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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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
70%70% 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: notes · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, 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
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% 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
17%17% 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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