A system and method for visually and mathematically correlating website performance datasets with analytics datasets and optionally with back end application performance datasets in order to determine if variations in one dataset are caused by or related to variations in another dataset and simultaneously determines the cost of slow or unavailable websites by comparing expected traffic to actual traffic during the slow or errant period.