In the course Consumer Analytics, participants will learn how to use data analysis and statistical techniques to understand the behavior and preferences of their customers. The course gives an overview of the methods and equipment used to evaluate consumer data, such as data mining, machine learning, and statistical analysis.

The course covers various topics related to customer analytics, including data collection and management, customer segmentation, predictive modeling, customer lifetime value, and customer loyalty. It also explores the ethical considerations involved in collecting and analyzing customer data.

In addition to theoretical concepts, the course provides hands-on experience with customer analytics tools such as R and Python. Students will learn to use these tools to manipulate and analyze customer data, create visualizations, and develop predictive models.

Upon completion of the course, participants will be able to identify patterns and trends in customer data, make data-driven decisions about marketing strategies, and optimize customer experiences. They will also be familiar with the ethical considerations involved in collecting and analyzing customer data.