We're rolling out the second in a series of new views that enable meta-analysis across your corpus of experiments. This lets you visualize and scan for correlation across metrics.
Often the metric you want to move isn't very sensitive and takes a while to measure. It is helpful to find metrics that are more sensitive and faster to measure - and run experiments on this.
This view lets you plot two metrics on the same chart - each data point is an experiment's impact on them. You can quickly get a sense for whether the metrics tend to move together - or not. You can also remove outliers, filter down to a team's experiments or download the underlying dataset.
In this hypothetical example - "Checkouts" is the metric you want to move, but it's not very sensitive. "AddToCart" correlates well with "Checkouts", while "ViewItemDetail" doesn't.
Also see - Meta-analysis Experiment Timline View.
(Reach out in Slack if you'd like to get early access to this)