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Slido – Live Polling and Q&A for Google Slides

Hacker News

Slido – Live Polling and Q&A for Google Slides

Hey HN community! Today, we're launching Slido for Google Slides (https://slido.com/google-slides), the easiest way to add live polling and Q&A to Google Slides. We started building Slido with the mission to help maximize the value people get out of joining a meeting or event. Since then, we helped engage participants at over 300,000 events, company all-hands, and training sessions, working with customers like SXSW, Spotify, and Zendesk. Over time, our user base extended from conference organizers and companies to individuals delivering presentations and talks. Slido became a regular part of their toolkit. But our product simply wasn't well-suited to their needs: it required that they constantly switch between Slido and their presentation using a separate device. Back in January 2019, we put together a team with a clear goal - make it (ridiculously) easy for presenters to create a dialogue with their audience. After months of hard work and many many improvements, we're excited to finally make Slido for Google Slides available to all users. Whether you're presenting to your team, in front of a class, or running a training session, with the new integration you can instantly create live polls and add Q&A to your presentation as you're working on your slides. And the best part - rather than switching between Slido and your presentation, you'll be able to run both with one click. We're still actively working on Slido for Google Slides and have plenty of improvements in the works. If you have any feedback or questions, we'd love to hear from you. Great job everyone working on this - Dominik, David, Anna, Mario, Andrej, Alex, Martin, Filip, Silvia, Samuel

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, new · Missing: mac, agents, macos
98%98% 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: started, para, maximize · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month, google, users · Missing: mobile apps, ios, personal
68%68% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, 000 · Missing: https docs, just released, exist
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training, active · 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
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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