Ri

Ribbon – Video chat with your own users

Hacker News

Ribbon – Video chat with your own users

Hey HN, I’m Axel, founder of Ribbon (https://tryribbon.com). Ribbon is a user research platform for people who build websites and apps. It allows people who build products to quickly set up video chats with their own users so that they can get a better understanding of who their users are and how their products can be improved. Here’s a demo of how it works: https://www.youtube.com/watch?v=JR-5VNZp8iQ Working as a product manager I grew frustrated with how hard it was to get a good understanding of who was using my products. Booking in user interviews took up to a day each week of emailing potential participants back and forth to coordinate the interviews, and only gave us access to users who we’re willing to book up their time days in advance. I built Ribbon to solve this. Ribbon makes it super simple for anyone who runs a website to spin up a video chat with people who are browsing that website in seconds instead of days. I’d love to hear about any ideas, experiences and feedback you might have!

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Actual performance

5points
5comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% 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: apps, user, email · Missing: mac, agents, macos
84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, video, users · Missing: mobile apps, ios, personal
46%46% 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
16%16% 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 · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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