Each of the top comparison tables show a difference score that is calculated by several statistical tests depending on the comparison being made; however, no matter which test is used, the difference score is shown as a value between 0 and 1.
A score of 0 means there is no difference between the two segments and a score of 1 means there was a very large difference between the two segments. There are two types of statistical tests employed to generate these difference scores: for the Top Metrics table a Mann-Whitney U test is used, and for the Top Dimension Items and Top Segments table a risk difference comparison is used.
In the Top Metrics table, the Segment Comparison Tool uses a two sample Mann-Whitney U Test, which is a nonparametric equality test used to compare the one-dimensional probability distributions of each metric for each considered segment. The difference score in the metrics table is a combination of the p-value from the computed U statistic (which represents how stochastically different the two segments are distributed across a particular metric) and the relative magnitude of the observed difference. A large difference score (close to 1) means the particular metric has a large relative difference as well as a high statistical confidence that the segments are different.
To compute the difference score on the Top Dimension Items and Top Segment Difference tables, a relative risk differencing algorithm is used (similar to risk ratio, although using a difference rather than a ratio). A risk difference is calculated by subtracting the cumulative incidences of a dimension item (or overlap with a segment from the segment table) of one selected segment from the other. A high difference score (close to 1) means the particular dimension item or tertiary segment was very prominent in one of the selected segments and not the other.