VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Abstract
This seminar teaches students how to design, conduct and analyze small but insightful experiments in business environments.
Objective
After participating in this course, students will be able to: 1) Recognize situations in their work routines in which empirical testing is helpful or even necessary 2) Translate the business problem into a research question 3) Identify structural, situational, and contextual factors that might influence the outcome and formulate hypotheses 4) Select the proper experimental design 5) Develop experimental treatments and stimuli 6) Determine sample characteristics 7) Collect data for business experiments 8) Analyze experimental data 9) Derive managerial implications from the empirical results 10) Consider ethical issues in the context of business experiments
Content
Seemingly ubiquitous "big data" from human and technical sources promise radically new insights into the customer's mind but come with some strings attached: collecting and analyzing "big data" is expensive and complex; translating results into managerial implications is usually difficult. In this seminar, we present a more efficient way to create knowledge about customers: marketing experimentation - the systemic variation of marketing parameters, which are expected to have an impact on central customer variables such as buying behavior, customer value or brand image. In contrast to big data marketing analytics, smart business experiments are easy to handle and the results are easy to implement. In this seminar, students will be given the necessary skills and knowledge to plan, conduct and analyze their own business experiments.
Resources
Literature
Anderson, Eric T. and Duncan Simester (2011), "A Step-by-Step Guide to Smart Business Experiments," Harvard Business Review, 89 (3), 98-105-105. Davenport, Thomas H. (2009), "How to Design Smart Business Experiments," Harvard Business Review, 87 (2), 68-76.
General Information
- Language
- English
- Levels
- NDS
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 25
- Signup End
- 09.02.2025
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar |
Business Experimentation
Does not take place this semester.
|
No time listed | 24 h semesterly |