(spring semester lecture and exercises)
"Data are just summaries of thousands of stories – tell a few of those stories to help make the data meaningful."Chip & Dan Heath
This course is an introduction to marketing analytics. Today, companies heavily rely on data-driven marketing to better understand the needs of their customers. Through various data collection methods, they gather data on, e.g., purchase behavior, social relationships, or attitudes. By analyzing such data, firms gain market insights and can enhance marketing decisions such as segmentation and targeting of customers, positioning of products based on customer preferences, or developing the right marketing mix. This class offers a practical introduction into understanding, applying, interpreting, and documenting quantitative research methods to analyze Marketing data.
Dr. Margot Löwenberg
BA students assigned to the “Wahlpflichtbereich" BWL 4.
Each spring semester
Field A, Miles J, Field Z (2012), Discovering Statistics Using R, 1st ed., London: Sage.
Hair JF, Black WC, Babin BJ, Anderson RE (2014), Multivariate Data Analysis. A Global Perspective, 7th ed., Upper Saddle River: Pearson.
Basic knowledge in R is a prerequisite for the Marketing Analytics class. The required skills are on par with our class "R - A non-technical introduction with applications to Marketing". We strongly recommend participating in this class or to complete similar online course (e.g. free R Intro classes available on www.datacamp.com).
Installation of the necessary software:
Please visit http://cran.r-project.org as well as http://www.rstudio.com and ensure that you have successfully installed the latest versions of R and R Studio on your personal laptop.
Individual evaluation based on daily multiple-choice tests, a practice exercises during class, and online exercises.
Dates and Location
Block-course: 15 - 19 February 2021, 09:00 - 17:00
Location: ONLINE class Vorlesungsverzeichnis
Officially register using the booking tool at the University of Zurich. An individual application for this class is not necessary.
The information on this website or syllabus supports the official information in the electronic university calendar (VVZ – Vorlesungsverzeichnis). In cases of doubt, the official information at the VVZ is valid.