Identifying Drivers for a Metric-of-Interest

摘要

In one or more implementations, data is obtained for metrics that describe visitor interaction with a web site. From these metrics, a user selection is received of a metric-of-interest, which describes a particular visitor interaction with the website. The user selection indicates that driving metrics, which describe visitor interaction that is determined to be influential in causing the particular visitor interaction, are to be identified. Once the metric-of-interest is selected, the data obtained for the website is processed to identify the driving metrics. The processing involves application of a feature selection technique to ascertain candidate driving metrics from the metrics for which the data is obtained. The candidate driving metrics are the metrics likely to be influential in causing the metric-of-interest. The processing also involves application of a statistical causality technique to determine whether the candidate driving metrics are influential in causing the metric-of-interest. The candidate driving metrics that are determined to be influential in causing the metric-of-interest are identified as the driving metrics. A graphical user interface is then generated to present the driving metrics to a user.