Advanced Marketing Modeling

Instructor: 
Time I: 
Wednesday, 12:00pm to 02:00pm
Time II: 
Thursday, 12:00pm to 02:00pm
Venue I: 
online
Venue II: 
online
Description: 

Evaluating marketing decisions and developing goal-oriented marketing strategies, e.g. maximizing firm profits, depend on the measurement of causal relationships between firms' objectives and marketing activities. In this course, we discuss in depth advanced methods to empirically determine the causal relationship between marketing activities and firms' objectives. In exercise courses students learn how to apply these methods to real data. Special attention is given to modeling the effects of marketing on sales and market share data. In this course we also focus on discrete choice models for individual purchase data and aggregate sales data. Successful participation in this class will enable students to quantify the impact of marketing on key performance measures and to evaluate the success of marketing activities.

Exam:

Portfolio exam: 3 assignments

  1. assignment: learn and understand how to use the statistical package R for data prepration and data analysis (non-graded)
  2. assignment: learn and understand how to estimate price elasticities and promotional uplifts with log-log-models applying modern econometric tools, make use of modern statistical software packages and learn how to document and interpret the estimation results carefully.
  3. assignment: learn and understand how to estimate parameters of an aggregate logit demand models using of modern statistical software packages and learn how to document and interpret the results from these models carefully.

The final grade will be given for the portfolio of all three assignments.

More information can be found on Moodle: tba

Credits: 
6.00
Program: 
Semester: 
Spring 2021
Affiliation: 
Humboldt-Universität zu Berlin