Abstract: 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.

Abstract: Embodiments of the present invention relate to forecasting metrics, such as web metrics, using causality-based feature selection. In embodiments, a set of potential features from which to generate a forecasting model is referenced. The set of potential features includes lags of observed features. A subset of features is selected, from among the potential features, that causally relate to a target web metric for which a forecast is desired. The selected subset of features causally related to the target web metric is used to generate the forecasting model. Such a forecasting model can be used to forecast an outcome associated with the target web metric.

Abstract: Techniques for brand scoring for social media users are described. In at least some embodiments, brand-related content that users post to a social media environment (e.g., social media website(s)) is identified and characterized. Based on attributes of a user and brand-related content posted by the user, a brand score for the user may be calculated. In at least some embodiments, a user's brand score provides an indication of the user's perception of a brand and/or the user's influence on perception of the brand in a social media environment.