Systems, methods, and media for comparing variations of electronic content in relation to a measured metric and/or generating a causal model to calculate the effect of an input variable on a desired outcome

Abstract

In an embodiment, a feature that is different between variations of web-based electronic content can be determined to be a true and significant cause of a difference of a measured metric when three conditions are met. The three conditions may be satisfied when a probability value for a false positive is less than a false positive threshold value, a statistical power is greater than a statistical power threshold value, and a difference between mean values determined for distributions is greater than a mean threshold value. In a further embodiment, and when there is no control group, a causal model can be generated for different interventions or values related to a desired outcome. The causal model can be executed to determine which intervention is most impactful on the desired outcome and/or to determine an overall impact of a categorical variable on the desired outcome.