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Geekbot for MS Teams

Hacker News

Geekbot for MS Teams

Hi HN, I'm Nick - co-founder and CEO of Geekbot. Geekbot lets teams automate standups, retros, surveys, and 1-on-1s in Slack and MS Teams, helping you spend less time in meetings, save time on reporting, and still see who’s working on what, entirely asynchronously. For context on why it exists, my background is in start-ups. My team and I have been working together for almost a decade, building several companies over the years. And one challenge we've always faced has been communicating across different timezones. We were spending way too much time in online calls and note-taking apps, all just to stay in sync. And all that meant was we were struggling to find any time to get real work done, which ultimately led us to build Geekbot. Initially, Geekbot was meant to be nothing more than an internal tool to help us be more productive, there to replace endless meetings with asynchronous reports. But soon after we started using it, we knew it could become so much more. This one chatbot was saving us so much time and helping us cover way more ground, which is why we felt we should offer it to other teams to try. Now — over 1,600 different companies (including Asana, Shopify, and GitHub) use Geekbot in Slack. Beyond standups, retros, and surveys, everyone from Product Owners to People Officers are using it to share meeting notes, improve the quality of internal 1-on-1s, even track team happiness and employee engagement. We've spent much of this year preparing to launch Geekbot in MS Teams. And now, we're super proud to say it's good to go, so if you're looking for a way to keep your team in sync asynchronously, we'd love you to add Geekbot to MS Teams. https://geekbot.com/geekbot-for-microsoft-teams/ If you do, let us know your thoughts. We're constantly improving the product based on feedback, so we'd love to hear from each and every one of you. I'll be here all day responding to comments, or feel free to email me directly at nikolas at geekbot dot io. Thanks for reading! Nick

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting
94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, apps, new · Missing: mac, agents, macos
92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, io, including · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon, calls · Missing: plus, platform, intuitive
23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: shopify · Missing: arr, mrr, revenue
18%18% 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.

Incorrect prediction on native model

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