I got an interesting question this week from a PM this week, asking if we could run an experiment with a traffic allocation of 10% to control and 90% to the variation, rather than a traditional 50–50 split. TL;DR: Probably best to keep it 50–50, since your typical A/B test design involves enough factors to consider already.
Netflix recently posted an article on their tech blog titled Reimagining Experimentation Analysis at Netflix. Most of the post is about their experimentation infrastructure, but their example of a visualization of an experiment result caught my eye. A/B test results are notoriously difficult to visualize in an intuitive (but still correct) way. I’ve searched for best practices before, and the the only reasonable template I could find is built for Excel, which doesn’t fit my python workflow.