2023/2024
Advanced Marketing Models
Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Type:
Mago-Lego
Delivered by:
Department of Management
When:
1 module
Open to:
students of all HSE University campuses
Instructors:
Elena B. Pokryshevskaya
Language:
English
ECTS credits:
3
Contact hours:
24
Course Syllabus
Abstract
The primary focus of this course if on quantitative models that can be used by managers to support marketing decisions. In addition to having conceptual skills, modern managers must increasingly master techniques of data-driven decision modeling to do strategic planning based on information from corporate information systems as well as external data sources. This course teaches how to apply econometric, machine learning and optimization techniques to marketing problems.
Learning Objectives
- Choose methods adequately corresponding to the objectives of a research project
- Collect, store, process and analyze data according to high standards
- Conduct empirical business research using modern analytic software tools
- Develop and apply new research methods
- Solve managerial problems using best practices of data analysis using modern computational tools
Expected Learning Outcomes
- Choose methods adequately corresponding to the objectives of a research project
- Collect, store, process and analyze data according to high standards
- Conduct empirical business research using modern analytic software tools
- Develop and apply new research methods
- Solve managerial problems using best practices of data analysis using modern computational tools
Course Contents
- Optimization modeling for Marketing
- Advanced Excel functions for analyzing marketing data
- Econometric modeling of scanner sales data
Interim Assessment
- 2023/2024 1st module0.25 * Empirical case studies solved in class + 0.25 * Exam + 0.25 * Midterm exam based on Data camp + 0.25 * Quizzes
Bibliography
Recommended Core Bibliography
- Quirk, T. J., & Rhiney, E. (2016). Excel 2016 for Marketing Statistics : A Guide to Solving Practical Problems. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1261494
Recommended Additional Bibliography
- Chapman, C., & Feit, E. M. (2019). R For Marketing Research and Analytics (Vol. Second edition). Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2093001