Eileen Mandir

teamchatviz — slack stats visualized

Users clustered by their channel membership
Channel land: users clustered by their channel membership

How are culture and collaboration across an organization influenced by communication? What if the hidden communication patterns were visible? How might that change how we interact and share knowledge across the team in the organization?

Communication shapes cultures. Yet, how communication flows remains a secret for the most part. Here is a deep dive into your team’s Slack communication statistics. Explore how communication works in your team and learn how communication influences cultures.

How it works

»Slack« is an instant messaging tool that is used for team communication. Communication is organized via channels for certain topics that are open for every team member to join. #teamchatviz enables you to explore your team’s Slack jungle with appealing statistics. Analyze unique graphs and gain insights from your very own Slack team.

By integrating this tool into your Slack app, several data visualizations of all publicly available channels will automatically be created for you. #teamchatviz is not only great for new members to get an overview of the team but also enables long-time users to learn about what’s going on around them.

Visualizations of Slack-chat data

With #teamchatviz we created unique data visualizations showing how your team uses Slack. We tried to avoid creating graphics that imply any value judgments or that give meaning to the numbers. We also tried to find graphics that work universally for any Slack team. Some of the visualizations don’t even work without a human being making sense of them. So please be careful when you do so!

Slack channel heartbeat

Channel Heartbeat – What's going on in the different channels and when are the peaks? Find out which events created a buzz on different channels. If you know what you're looking for you can also filter by channels and look at a dedicated time frame.

Slack people land

People Land – People Land is a cluster analysis of your team's members. Clusters are created using different parameters of similarity, such as joined channels. Cluster analysis only works if you make sense of it. If done right, this can reveal a lot of lived culture through communication patterns. Zoom into each cluster and try to bring them to life.

Slack channel land

Channel Land – Channel Land is also created with cluster analysis, similar to People Land. Channel clusters are created by the similarities of channel members. Just as in People Land, you can zoom into each cluster and bring them to life by making sense of the details. Similar channels could give you a great insight into how teams are aligned with each other.

Slack people land

Messages & Reactions – Ever wonder what moves your team? In Top Reactions, you can find messages listed by the number of reactions. Maybe you missed a birthday or an important release? You will find them filtered by time and channel in this section.

Slack emoji timeline

Emoji Timeline – Feelin' great feelin' good! By collecting all the emojis posted on your team the emoji timeline will help you understand the vibes of your team. Gain insights from individual channels and find out where and when the good times roll.

Frequent speakers on Slack

Frequent Speakers – Find out who the key contributors are and what the communication hubs on your team are. Filtered by time and channel, this visualization will help you understand both team and channel structures by contributions.

Project Background

The project #teamchatviz was born out of the urge to create and maintain an agile working environment for a fast-growing company. But rather than being a management tool, this visualization served as an organizational intervention which led to more communication and collaboration among the team members from various sites and business units.

Project host:
moovel lab
People involved @ moovel lab:
Tilman Häuser, Eileen Mandir, Benedikt Groß, Flore de Crombrugghe, Josephine Hartung, Raphael Reimann
Collaborators:
Thorsten Heilig,Tobias Lauer, Oleksii Rudenko

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