Free Planning Poker app for agile teams

Hacker News

Hey HN! I've built a free Planning Poker app, PlanninPoker, designed to make agile team estimations as painless as possible. It's a zero setup, ad-free tool. I've added a lot of advanced features but kept it super user-friendly. Features include: Easy setup with no signup required. Jira integration to streamline your workflow. Real-time team communication with in-built chat and comments. Customizable game settings, including anonymous voting. Mobile-friendly, so you can join sessions from anywhere. Would love for you guys to check it out and share your thoughts!

Visit product View on Hacker NewsDec 27, 2023

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Actual performance

3points

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Launch Intel predictions

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

60%60% 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: including · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

39%39% 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, including · Missing: https docs, excited, just released

33%33% 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

15%15% 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.

Correct prediction on native model

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