SurveyMoji – An easy way to get realtime feedback with a link/QR code

Hacker News

Hi HN - I've been working on this site on and off for awhile. It started out as a personal tool and fun thing to hack on in my spare time. I recently added some UI improvements and a landing page and thought maybe it would be nice for other people to use as well. The idea was to create the fastest/easiest way to share a link to collect realtime feedback from a person's phone during a presentation or video call. Would love to hear any feedback, especially on UI design as it is the first time I've tried to create something that has a modern SaaS look to it. Built with go/htmx/alpinejs

Visit product View on Hacker NewsNov 30, 2024

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

71%71% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting

67%67% predicted probability of success on Indie Hackers, 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

49%49% 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

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: personal, video, way · Missing: mobile apps, ios, entrepreneurs

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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 · Missing: web3, chat, crypto

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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