365-1085-00L Business Experimentation
|Semester||Spring Semester 2018|
|Language of instruction||English|
|Comment||Exclusively for MAS MTEC students (2nd semester).|
Limited number of participants: a minimum of 10 persons and a maximum of 25 persons.
Please register by 16 February 2018 at the latest via myStudies.
|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.
|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.