Scrim TV - Connect, Collaborate and Create

Hacker News

Hey HN! Scrim TV (www.scrim.tv) is a place for creators to connect, collaborate and create. I started working Scrim TV after trying to get into video content creation. Growing up watching SNL every weekend I wanted to try and create my own sketch comedy videos. It was a lot harder than I thought it would be to find people with that same interest. So instead of making a few friends, I made a website. That felt super reasonable. There's still a ton to iron out and a few wonky behaviors, but you can create an account and browse/message other creators. Right now all messaging is just done through the email you use to sign up, I wanted to see if there was any interest before building out a messaging platform. Let me know if you have any suggestions! HN probably isn't the exact target demographic, but I respect the hell out of you guys and would love any feedback that you're willing to give as I launch this project. Thanks for your time, hope you check it out! https://www.scrim.tv/

Visit product View on Hacker NewsFeb 25, 2019

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Actual performance

6points

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

85%85% 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: email · Missing: mac, agents, macos

55%55% 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: ide, io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: collaborate · 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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