I

I made a website recorder webapp you can use to create screencasts

Hacker News

I made a website recorder webapp you can use to create screencasts

Just something I put together quickly: https://webcast.browserprotect.me/ I made this in one day, now I'm wondering if It's interesting enough to make it a real product (Add new features like setting the size, zoom, annotations, fix bugs, export, voice-over, etc..) Here is an example screencast I just did: https://webcast.browserprotect.me/view/2764aa94dcd855959819fd91881f0882baa61a0e-44646 Do you consider this a viable product? I'm thinking about offering it for free and then add some premium features.

Visit product View on Hacker NewsFeb 9, 2015

Actual performance

42points

24comments

Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

51%51% 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 · Missing: plus, platform, intuitive

44%44% 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

14%14% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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