Just to make sure we’re on the same page, let’s define our terms.
As you try to understand various things in the world, you are trying to understand the effect of one variable on another (i.e. casualty).
In our world, you’re trying to understand the effect of a price recommendation you implemented on some financial metric.
In doing that analysis, you recognize that there are a ton of variables that might also explain the change in some financial metric.
Example - you observe that revenue went up in the following quarter after you implemented a price increase. Well, was it your price increase that was the reason revenue went up? Or was it some other factor?
Those “other factors” are called confounding variables (also known as hidden variables).
To learn more about how we control for confounders, sign up for a free pilot!
