Course 2024-2025 a.y.

30228 - MARKETING RESEARCH

Department of Marketing

Course taught in English

Student consultation hours
Class timetable
Exam timetable
Go to class group/s: 31
CLEAM (6 credits - I sem. - OP  |  SECS-P/08) - CLEF (6 credits - I sem. - OP  |  SECS-P/08) - CLEACC (6 credits - I sem. - OP  |  SECS-P/08) - BESS-CLES (6 credits - I sem. - OP  |  SECS-P/08) - WBB (6 credits - I sem. - OP  |  SECS-P/08) - BIEF (6 credits - I sem. - OP  |  SECS-P/08) - BIEM (6 credits - I sem. - OP  |  12 credits SECS-P/08) - BEMACS (6 credits - I sem. - OP  |  SECS-P/08) - BAI (6 credits - I sem. - OP  |  SECS-P/08)
Course Director:
SUNGTAK HONG

Classes: 31 (I sem.)
Instructors:
Class 31: SUNGTAK HONG


Suggested background knowledge

During the course, there are several in-class exercise sessions in which students gain hands-on experience analyzing real-world data sets on their laptops. During these sessions, the students make extensive use of spreadsheet applications such as Microsoft Excel (with the Analysis ToolPak add‐in) and SPSS. For this reason, to get the most out of the course, attendance is highly recommended. Also, to feel comfortable in this course students should be familiar with contents from prior statistical or empirical courses in which they gained a basic knowledge of linear regressions and t-tests. This helps the students gain a more insightful understanding of the course material.

Mission & Content Summary

MISSION

Marketing research drives communication with customers, identifies business opportunities, and reduces risk of managerial decisions. As data availability explodes from a variety of sources, analytical research skills are among the most sought-for in designing and executing marketing research projects. The goal of this course is to understand the concepts and the techniques required to conduct marketing research and to know how to apply them in real world marketing research problems in order to make better business decisions. In this course students are introduced to different stages of the marketing research process. They get familiar with different types on research designs. They learn how to collect and scrutinize data. Subsequently, they also learn quantitative research methodologies and their applications to various data sets to solve real-world business problems.

CONTENT SUMMARY

The contents of this course comprises theory, concepts and frameworks relevant to marketing, and empirical methodology and their applications to real-world datasets. The topics include but are not limited to:

 

  • Exploratory/ descriptive/ causal research: research design and data collection.
  • Experimental design
  • Sampling
  • A/B testing
  • Consumer segmentation: cluster analysis
  • Perceptual maps: factor analysis
  • Market response modeling
  • Field experiments
  • Conjoint analysis

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Assess the quality of existing marketing research (in newspapers, consulting business cases, and internal analyses).
  • Recognize limitations and room for improvement in marketing research
  • Understand the best methodology to be applied to a given marketing problem

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Develop autonomously a set of research questions and derive the appropriate corresponding research design.
  • Identify and measure consumer preferences using survey or market transaction data.
  • Contribute to larger (field) marketing research projects.

Teaching methods

  • Lectures
  • Guest speaker's talks (in class or in distance)
  • Practical Exercises
  • Individual works / Assignments
  • Collaborative Works / Assignments

DETAILS

The class sessions comprise lectures and in-class discussions and exercises.

 

  • There will be a session with a guest speaker to complement the teaching by offering a chance to hear additional insights from managers.
  • The goal of the discussions and exercises is to apply important theory, concepts and frameworks to different business contexts and to provide students with hands-on practice in producing research output based on both qualitative and quantitative data. For in-class exercises, students are asked to bring a computer with Excel (make sure to install the Analysis ToolPak add-in) and SPSS, and they analyse the data and discuss analysis output under a guidance of the instructor.
  • An assignment on a marketing research will ask students to select a research design, to collect data, to analyze data and to report the results.

*Detailed instructions for the assignment are to be provided at the beginning of the course.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
    x
  • Individual Works/ Assignment (report, exercise, presentation, project work etc.)
x    
  • Collaborative Works / Assignment (report, exercise, presentation, project work etc.)
x    

ATTENDING STUDENTS

  • Assignments: 60%
  • Final Exam (Written): 40%

 

The assignments assess students’ ability to apply the methods learned during the course.  

The written exam includes questions referring to cases, talks and related concepts, models and tools presented and discussed in class. 

 

Note: The exam for attending students is only available on the first two exam dates; after the second exam date, only the non-attending exam is available.


NOT ATTENDING STUDENTS

Final Exam (Written): 100%

 

The questions are aimed at verifying the ability to apply the knowledge students learned when studying the teaching material.


Teaching materials


ATTENDING STUDENTS

  • All material discussed and distributed in class (slides, articles, hand-outs etc. will be available via Bboard).
  • N.K. MALHOTRA, Essentials of Marketing Research, Global Edition, Pearson Prentice Hall, 2015 (Corresponding chapters, to be communicated in class).

NOT ATTENDING STUDENTS

  • N.K. MALHOTRA, Essentials of Marketing Research, Global Edition, Pearson Prentice Hall, 2015 (all chapters).
Last change 27/05/2024 17:06