Videos with Friends – reaction videos, watch parties and more

Hacker News

Hi HN! We built Vidberrys (https://vidberrys.com/about) during the pandemic to make it fun for students to watch school videos with their friends. It is evolving as a place for videos with friends in general. Here’s what you can do on Vidberrys: - Produce reaction videos: Quickly produce reaction videos with friends for any video without having to fiddle with complex software like iMove or After Effects. Experience your friends' reactions while watching your favorite shows. Creating a reaction video today is a cumbersome process to say the least. - Synchronized watch parties: watch videos as a social activity while video chatting with friends and with a single remote control (pause, ff, playlist). Existing web conference technologies like Zoom or Google meet cannot be used for social watching as it degrades the quality of audio/video significantly. - Host school watch parties: Have fun watching school videos with your friends and do homework faster. Today, students do not have an easy way for group study or group notes. We are imagining a videos with friends platform at Vidberrys, users can start a channel and build their friends and fan network and in the future monetize their video content. We love to get your feedback. Try https://vidberrys.com. Note: Vidberrys runs only in a Chrome browser today. No mobile device support yet. You can send feedback directly from the web site (from the left panel link). This is an alpha release of Vidberrys. If you run into any issues, you can reach us from the site. https://vidberrys.com

Visit product View on Hacker NewsFeb 13, 2021

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

89%89% 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: google, user, single · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews

70%70% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, google, users · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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