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I made a pizza icebreaker app for Slack
Hacker NewsI made a pizza icebreaker app for Slack
Hey guys. To address the difficulty of maintaining personal connections for remote teams—we made a little Slack app called HotPizza It sends fun icebreaker questions to a Slack channel daily or weekly (you can also /hotpizza for random icebreakers for meetings, team onboarding..etc). While we wait for approval in the Slack app directory, a few dozen teams are using the beta on an ongoing basis. Would love to see if anyone here would want to try it out and hear what you think! https://www.hotpizza.io
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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, using · Missing: mac, agents, macos79%79% 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.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting37%37% 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, intuitive28%28% 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, revenue25%25% 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, crypto9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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