Metrics

A/B testing is a powerful tool for learning about your users, understanding your features’ impact, and making informed business decisions. To ensure you make the best decisions and are extracting the most insights from your experiments, some experimental design guidelines are essential. These guidelines can be cumbersome or confusing at…

Today we’re introducing My Work, an overview of your features within Split. My Work will become the default view where you land when you log in to Split.

Find faulty features before your customers do. One of the most common reasons that our customers move  towards feature flags is risk mitigation: the need to make sure releases don’t cause errors for users. Given how frequently organizations are now deploying features, the ability to limit the blast radius of…

With today’s release, you can now create a range of metrics from a single event, providing a deeper analysis of the results of your experiments. These additional insights into knowing how people are using your application is vital to shaping your product development priorities. For example, if you wanted to…

In this post, we will talk about key experimentation concepts including how to choose your Overall Evaluation Criteria (OEC) for your experiments and how to increase the sensitivity of those metrics through metric filtering and metric capping.