Su

Super simple social poll app

Hacker News

Super simple social poll app

I recently launched my first web app, polls.io. It's a super simple polling app that doesn't require sign-up. In my opinion, this is the most simple/social polling app out there. There are certainly many similar apps out there, but I think this one stands out as it straight-forward and doesn't have any unnecessary "mess" getting in the way of the actual poll. From idea to inception this took about a week. I'm pretty happy with how it turned out. We'll be listening to feedback in the coming days/weeks in order to make the proper changes. I'd love to hear your guys' thoughts and feedback! Here's a little sample poll: Pancakes or Waffles? http://polls.io/cdrbe

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos
69%69% 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.
TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, 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
41%41% 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
20%20% 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.

Incorrect prediction on native model

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