Design systems are emerging as a vital tool for product design at scale. These systems are collections of components, styles, and processes to help teams design and build consistent user experiences. It seems like everyone is building one, but there is no playbook on how to take it from the first button to a production-ready system adopted across an organization. Much of the…
This post is a guest submission by one of our partners at Tray.io for Segment’s Chain Letter blog series. The Chain Letter series profiles clever uses of Segment Connections partner tools that, when chained together, lead to some pretty advanced programmatic models, custom messaging strategies, and more. Thanks to Tray.io for sharing DigitalOcean’s story!
You can’t make informed decisions when you don’t trust your underlying data. Unfortunately, finding data mistakes is far too common for most companies. Whether your Order Completed event was accidentally implemented as OrdreCompleted or your products property was coded as a string instead of an array, you likely have spent time cleaning up your data set just to make it useful.…
Companies that want to put their customers first need to start with the basics: understanding who their customers are. This seems straightforward, but the proliferation of channels where customers interact with your business makes this previously simple goal terribly complex.
Whether sending an email campaign, A/B testing a product feature, or conducting funnel analysis, your teams need access to customer data they can trust.
Segment is a hub for a tremendous amount of data. It processes peaks of 230,000 events per second inbound, and 280,000 events per second outbound between more than 200 integration partners. You may think of Segment as black box for delivering all this data. You send data once to its tracking API, and it coordinates translating data and delivering it to many destinations.
This is our fifth post in a series about integration categories. Revisit our blog post “Choosing the right performance monitoring tool” here to read about our series objectives.
Segment loads billions of rows of arbitrary events into our customers’ data warehouses every single day. How do we test a change that can corrupt only one field in millions, across thousands of warehouses? How can we verify the output when we don’t even control the input?
