Privacy principles: search, learning, and intelligence
Our mission is to build a product that makes work life simpler, more pleasant and more productive. To do so, we analyze Customer Data submitted to Slack as well as Other Information (including usage information) to find patterns that help us make our customers’ experience better.
Customer Data and Other Information
How Slack may use Customer Data (e.g. messages, content, files) and Other Information to update our services
Here are a few examples of improvements and privacy protective techniques our product and analytics teams may use to develop and update Slack:
- Slack may suggest emoji reactions based on the aggregate of what other people with the same job title or operating similar workflows have used. For example, when using the emoji picker, an Engineer may see the bug emoji 🐛to flag bug reports while a member of the Business Development team may see the handshake emoji 🤝to indicate a vendor agreement has been signed.
- Slack may recommend naming a channel "#help-[something]" because it's a naming pattern we've detected in aggregate across many companies. Recognizing and recommending things like channel naming conventions may help customers in certain industries more effectively manage projects, workflows, and other things in Slack. That said, these improvements must be based on large and diverse data sets to ensure that no individual customer is identifiable, so we wouldn’t suggest something as specific as "#shared-channel-acmecorp".
- Slack may suggest that members join channels that other individuals with the same job title or operating similar workflows tend to join. Or, if we detect certain types of links (e.g. links to Google Docs) being shared routinely across various workspaces, we may suggest to users that they install the Google Drive app for Slack.
- Slack may provide certain search results if we recognize that users across many companies routinely misspell words or use synonymous terminology. When you search in Slack, you’ll see a list of results that match your search terms and any close matches. For example, if you search for report, you may get results that include reports or reporting.
These types of thoughtful personalizations and improvements are only possible if we study and understand how our users interact with Slack.