PROMOTION FORECASTER is a tool utilizing the causal data available from syndicated data sources like IRI and Nielsen.  That causal data is the basis upon which a multiple regression model is built and then used to predict and prescribe the desired outcome. This model will fit the data as closely as it can and will show that fit in the measure R2. The closer this measure is to 1, the more variance that is explained by the model.

The graphic below is from an actual set of data for a dry pasta product sold to a key account in a specific market/geography.

Using weekly data along with the five causal factors available from the syndicated data, a predictive statistical model is generated.  By manipulating these causal factors the user can predict the outcome under a number of scenarios and choose which scenario they want to have happen, or prescribe the desired outcome.

The unit sales generated can be converted to dollars sales and margin for both the supplier and the retailer.