June 28 – July 9, 2021
This course unlocks a huge range of quantitative techniques to expand your experience in marketing and advertising.
This course introduces hands-on approaches to solving marketing problems using quantitative data. Multiple specific problems/cases will be showcased from various fields of marketing analytics: marketing research, customer analytics, social network analysis, advertising, etc. The course will give good insight into quantitative methods (statistical analysis of substantial volumes of sales/survey/customer data).
The course is taught by Evgeny A. Antipov.
The course features a unique set of computer exercises using R, Excel and other packages that will give our students skills that are immediately applicable in the industry
Why Choose This Course?
- Hands-on: students will use Excel and R during most classes
- Templates for solving real-world problems will be provided
- Lecturers are open for future research collaborations leading to peer-reviewed journal publications
- Students will be granted free access to DataCamp.com platform for learning data science for the period of the course and several months after the course
- Advanced Excel functions useful for marketing analysis
- Optimization modeling in marketing
- Exploratory analysis of marketing data
- Data processing of customer data
- Customer segmentation
- Introduction to predictive modeling and its applications: modeling customer lifetime value, churn, etc.
- Sales modeling
- Marketing Mix Modeling
- Introduction to text mining for marketing
Skills and Competence
Upon completion of this course, students will be able to:
- Use Excel and R for solving some of the key marketing problems
- Extract maximum insight from various data sources available to a company
- Apply basic statistical and machine learning method to increase profit
- Interpret the results of data analysis, followed by reporting and communicating the results
The course will contain tutorial sessions where students will conduct analysis along with the instructor followed by a session where they will solve similar problems on their own to check their understanding.
- Mandatory: basic knowledge of Microsoft Excel
- Some training in general management is recommended, but participants with other backgrounds are also welcomed
- Introductory knowledge of R programming is preferable but not mandatory. We recommend at least studying A (very) short introduction to R
Final problem set solved in class (time limit: 80 minutes). The test will include multiple-choice and open-ended questions that will test problem-solving skills. Some problems may require using MS Excel or R.
Final Grade Background
To complete the course students, must attend no less than 70% of lectures and seminars and solve problem sets given to them in class regularly. The final grade will be computed according to the following scheme: 0.5*Final Test + 0.5*Classwork.
Recommended Reading List
Hodeghatta, U. R., & Nayak, U. (2016). Business Analytics Using R-A Practical Approach. Apress.
Chapman, C., & Feit, E. M. (2015). R for marketing research and analytics. New York, NY: Springer.