The transparency. I came to Confidence fairly new to it, and what struck me first was how quickly it made sense. Within days I understood how it worked, and I've never had to keep a mental list of quirks and workarounds to get a correct answer out of it.

By seeing exactly which units were assigned, when, and under which rule, and follow that straight through to the metric, Confidence also makes it easy to put trust in the numbers, instead of have to take it on faith. When something looks wrong, the path is right there to trace.

Cohort segmentation is simple and understandable, and it fits naturally with how we already track behavior. So when an experiment or a rollout is finished, we can get to the answer straight away instead of spending days preparing the data first. That holds whether it's a straight A/B test or a gradual rollout.

The review and comment flow has also made it much easier to work together on experiments. The discussion about metrics and design happens on the experiment itself, so the reasoning stays attached to the thing it belongs to instead of scattered across chat threads. It means people come to the analytics team earlier, while the design can still be changed, and everyone can see what was decided and why. Review collected by and hosted on G2.com.

Nothing really comes to mind, more features are being built into the product continuously and it keeps getting better and better Review collected by and hosted on G2.com.