Feature launches in leading engineering teams increasingly look like a ramp rather than a one time switch, going through dogfooding, debugging, max power ramp, scalability and learning phases.
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.
Learn how experimentation platforms help development teams test ideas directly with customers and enable continuous delivery with lower risk.
The effects of burnout can be significant for any software development organization, large or small. In this blog post, we discuss how burnout can be alleviated with an agile workflow powered by feature flags, a robust feature experimentation platform and incremental feature rollouts using continuous delivery.
We built Split’s feature experimentation platform with this fundamental assumption: the data you capture to measure and understand your customer experience is collected across many touch points, and any tool you use to release feature flags and measure impact must be able to capture data from all of them.