The best standup bot for keeping your team on track during daily async standup meetings. Sup can facilitate a standup meeting, retrospective meeting, or other meetings asynchronously for your team using either a chat-based interface or a dialogue window.
Conduct standups & follow-ups: Sup provides team standup updates. You can see how everything works with direct questions and answers. Asynchronous standups and multiple follow-ups are a click away.
Vacation Tracker: Request, approve, view, and manage vacations with Sup. Holiday tracking is easy with regular updates and a dashboard of employee holiday analytics.
Create surveys & polls: Remote working can become a lot easier when you can make quick decisions based on surveys and quick polls. Make it simple for your team to voice their opinions.
Track team mood: Sup? Is that what you want to ask your team? Using mood tracking, understand your team's emotions. To gauge team morale, use it with a follow-up like standups. The anonymity of responses allows for honest answers.
Integrations: Sup x GoogleSheets. Sup integrates with Google Sheets to create a new Google Sheet file at the end of every month and sync the follow-up responses. Trusted by small and big-leaguers like Iterable, Adobe, PWC, Stripe, MailChimp, Starbucks, Mixpanel, Dell, Warner Bros, Wise, Perceptyx, Udaan, and more.
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We use Sup bot extensively in our team to facilitate standup, End-of-day follow-ups, holiday tracking - all without leaving Slack.
Based on our record, Parse.ly Analytics seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I've also seen parse.ly pop up a bit, I might try it to see if it's any decent. Source: over 1 year ago
Parse.ly | Python Data Engineers (NA) & Machine Learning Engineers (EU) | Remote | Full-Time | https://parse.ly Are you a Python programmer based in North or South America, interested in large-scale data processing (terabytes per month, petabytes in our archive), and making use of massively-parallel computing architectures, such as those behind Spark and Dask? Or, are you a Machine Learning Engineer in Western or... - Source: Hacker News / almost 3 years ago
Would be really useful (not to mention polite) if sources were cited when you do this. For example, I think the early points are from the parse.ly report. People might want to click through for context if you let them. Source: about 3 years ago
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