Feedpresso – RSS based smart news reader for techies

Hacker News

Hi all, since there are lots of discussions happening about news consumption, I would like to show you a project that I am working on - Feedpresso. https://www.feedpresso.com/ It focuses on content for techies and entrepreneurs so you can expect to get some interesting stuff right away. However, it is not a regular RSS reader - it heavily relies on algos to find exciting stories based on your reading history, from your sources. Also, it includes some abstractions over sources to make using RSS more natural. Give it a try. If there is an interest, I would gladly share some discounts with the community.

Visit product View on Hacker NewsApr 25, 2018

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

75%75% 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: io · Missing: https docs, excited, just released

60%60% 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: new, using · Missing: mac, agents, macos

47%47% 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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: entrepreneurs, way · Missing: mobile apps, ios, personal

38%38% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

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

Incorrect prediction on native model

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