Fe
Feedriv.com – Simple RSS Feed Reader
Hacker NewsFeedriv.com – Simple RSS Feed Reader
FeedRiv is an open source RSS feed reader that I built as part of my 12 Startups in 12 Months Challenge (Open Source Edition). The open source code can be found on Github: https://github.com/dashboardq/feedriv It is very minimal and probably a bit rough in some areas. I use it to track freelance jobs through RSS so it does what I need it to do.
Share cardActual performance
9points
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive40%40% 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, revenue19%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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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