Veuillez noter : Ce cours est actuellement désigné sous le nom de « Analyse prédictive du comportement du consommateur » dans votre programme et votre emploi du temps.

This course introduces students to predictive analytics applied to marketing such that marketers will be able to deliver more relevant and meaningful customer experiences, at all customer touchpoints, throughout the customer life cycle, boosting customer loyalty and revenues. In particular, predictive analytics is a set of tools and algorithms used to make predictive marketing and predictive customer analytics possible. In this course, we will cover the core principles of predictive data analytics through the discussion of the different steps in the Cross-Industry Standard Process Model for Data Mining (CRISP-DM) that links business understanding, data, and methods to business value. Furthermore, several use cases of predictive customer analytics will show practical applications in marketing.

What you will learn

By the end of this course, you will be able to:

• Understand the art and science of predictive analytics to define clear actions that result in improved business results;
• Describe the core principles of predictive customer analytics;
• Embrace the Cross-Industry Standard Process Model for Data Mining (CRISP-DM) steps to building predictive models;
• Apply concepts to real-life customer analytics cases.