This module will discuss how to identify the necessary components of a forecasting model based on patterns in the history data. You will also be able to evaluate the performance of a forecasting model using both in-sample and out-of-sample metrics.

"Meaningful Marketing Insights," This content will be familiar for learners who completed the first course; please think of this portion of the class as a review.

This module will discuss managing customer equity, acquisition, retention, & market value, and customer valuation. You will learn how to decompose customer value into its underlying components.

A common task in developing forecasting models is to use them to make decisions regarding the marketing mix activity. With a marketing mix model, organizations can assess the efficacy of different marketing actions. Included is a sample of data for a popular frozen food category. In addition to weekly sales and pricing, for the focal brand we have information on whether the product was featured in the store’s advertising (e.g., newspaper circular) and if the product was on display in the store. We also have pricing information from competitors. In this module, we will build a series of regression models to evaluate the impact of the brand’s actions and competitors’ actions.