1. A computer-implemented method for evaluating an advertising campaign event, comprising: receiving a selection of a business metric, wherein the business metric is a single business metric among a plurality of business metrics; receiving data indicative of customer activity occurring after the advertising campaign event, wherein the customer activity data is actual point of sale or Internet-based customer activity data associated with the selected business metric, and wherein the advertising campaign event involves promotion of a product over a communication medium; receiving promotion exposure data for the advertising campaign event; fitting a statistical model to the customer activity data and to the promotion exposure data for the advertising campaign event; forecasting, using an automated forecasting module in a computer-implemented system, one or more expected values for the business metric, wherein the forecasting is computed from the fitted statistical model, standard errors for forecast estimates, and corresponding prediction intervals including predictions at different time lags and at a plurality of different desired levels, and wherein a time lag is a lag in time between the advertising campaign event and the customer activity; generating a directional indicator based upon the one or more forecasted expected values for the business metric and metric directional data, wherein the metric directional data is a determination of whether a business metric value is changing in a positive or negative direction; determining standardized differences between the one or more expected values for the business metric and one or more observed values for the business metric; associating a statistical significance with the business metric; associating a statistical significance with one or more other business metrics in the plurality of business metrics, wherein at least one business metric is statistically significant and at least one business metric is statistically insignificant; generating a weighted value for each business metric having an associated statistical significance, wherein a weighted value is generated by mathematically relating a weight to a business metric based upon the statistical significance associated with that business metric; calculating an overall score by aggregating the weighted values; and using the standardized differences and the overall score to generate one or more visual indicators for the business metric, wherein the one or more visual indicators and the directional indicator are used to generate a score card for the business metric.