COURSE NUMBER: EWMBA261.11

COURSE TITLE: Marketing Research: Tools and Techniques for Data Collection and Analysis

UNITS OF CREDIT: 3 Units

INSTRUCTOR: Ming Hsu

E-MAIL ADDRESS: mhsu@haas.berkeley.edu

CLASS WEB PAGE LOCATION: http://bcourses.berkeley.edu

PREREQUISITE(S): EWMBA206 Marketing

CLASS FORMAT: A mixture of lectures and cases.

REQUIRED READINGS: A course reader and textbook: Marketing Research, Aaker, 11th Edition.

BASIS FOR FINAL GRADE: Approximately 20% assignments, 30% exams, 20% class participation, 30% group Project

SAMPLE SYLLABUS: bCourses Electives Forum

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:
The potential for marketers to collect and analyze marketing data has never been greater. Accordingly, the ability to generate and deal with data and make data-driven decisions is becoming an increasingly necessary part of marketing. This class will equip you with tools in marketing research that can be used to generate actionable insights. Because information collection is costly, it is important to understand when it is and when it is not worthwhile conducting marketing research. More information does not always imply higher profit! If your career will involve understanding preferences and behaviors of customers using a data-driven approach, this course is for you.

BIOGRAPHICAL SKETCH:
Ming Hsu is an Assistant Professor of Marketing at Berkeley-Haas.  He earned his doctorate in economics from Caltech. His research explores one of the most important but least understood parts of marketing—what goes on inside the minds of consumers, and how to measure these thoughts, feelings, and behaviors? His work has appeared in leading marketing as well as scientific journals, including Journal of Marketing Research and Science, and has been covered extensively in the media.

Toolkit	Regression	Conjoint	Factor Analysis	Cluster Analysis	Perceptual Maps
Product Design/Positioning	✓	✓	✓	✓	✓
Price Elasticity	✓
Promotion Responsiveness	✓			✓	✓
Promotion Design			✓	✓	✓
Market Segmentation			✓	✓
Competitive Analysis		✓			✓
Customer Perception			✓	✓	✓
Customer Utility Function	✓	✓
Questionnaire Design			✓
Forecasting	✓
Cannibalization					✓