Syllabus
Registration via LPIS
In the past decade, the shift of advertising dollars to measurable digital marketing channels has suddenly made experiments an economically feasible way to inform marketing decisions such as how advertising should be designed and targeted, what types of promotions are most effective, what products should be offered, how sales staff should be compensated, which sales channels should be emphasized, etc. Many marketers engaged in online retailing, direct marketing, online advertising, media management, and service operations are rapidly embracing a “test and learn” philosophy and a number of platforms such as Adobe Target, Optimizely, APT and Google Content Experiments, have been developed to facilitate rigorous field experiments in the online environment. The rapid rise of the “test and learn” philosophy in marketing has created a huge demand for those who can design, field, and analyze experiments.
Tentative Schedule
Day 1: AB Testing
- Session 1: Why experiments?
- Session 2: Designing A/B tests (7 key decisions)
- Session 3: Analyzing A/B tests (confidence intervals)
- Session 4: Hands-on design workshop
Day 2: Multivariate Experiments
- Session 5: Designing experiments when N is small (blocking and matching)
- Session 6: Two-level multivariate experiments
- Session 7: Optimal design for multivariate experiments (including conjoint design)
- Session 8: Sequential experimentation (bandit models)
Through this course, you will learn about, discuss and practice a wide range of critical skills for experimentation, from the statistical methods used to design and analyze experiments to the management and strategy required to execute an experiment and act on the results. Although our cases and examples will focus on marketing problems, the material covered can be applied in a number of other domains particularly operations, management and product design.
Your grade is calculated as follows:
- 30% of the final grade is based on an entry exam covering the pre-readings
- 30% of the final grade is based on in-class assignments
- 40% of the final grade is based on a take-home exam
This course REQUIRES students to have statistics knowledge and first-hand experience using SPSS, STATA or R.
Pre-requisites for exchange students:
At least 4 ECTS in Marketing Research (e.g., a course that covers the following topics: https://learn.wu.ac.at/dotlrn/classes/pool/1094.16w/syllabus/)
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