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Slack App for Scrum Poker
Hacker NewsSlack App for Scrum Poker
Hey I am Ben and I have built a slack app for scrum poker (slack.thisiseffort.io). You can anonymously vote on software development tasks within slack, it is used by a few remote software developments teams currently and I am keen for more feedback. It is very easy to start a voting session using the /effort command, followed by the title of your task. This then invites everyone in the channel to start voting anonymously, ensuring that no one influences anyone else. Really keen for more feedback and it is also free to use! Enjoy. Ben
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Did not reach leaderboard
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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, tasks, using · Missing: mac, agents, macos66%66% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal39%39% 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, podcasting34%34% 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, intuitive18%18% 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, revenue18%18% 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, crypto17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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