In AB testing statistical significance represents the likelihood that an observed difference in conversion rates between a variation and the control is not purely due to chance. For AB tests (and ABn) Webtrends Optimize uses a students t-test to calculate statistical significance.
Specifically this is the more robust two tailed approach, meaning that both positive and negative directions are considered. Further calculations are made at a 95% level of confidence meaning that the risk of a false positive is limited.
In addition, we report on the the probability of an experiment beating control. Effectively this is the likelihood that the variation outperforms the live site.