Effective marketing decision-making requires accurate data, careful analysis of these data, and adequate information on the underlying marketing problem to be solved. This course focuses on how marketing decisions are supported by research techniques. We will discuss different research designs, data collection methods, measurement and scaling techniques, as well as methods for analyzing empirical data (i.e., hypothesis testing, analysis of variance, correlation & regression, factor analysis). The course helps you to acquire a thorough understanding of the marketing research process and the analytical techniques that are frequently used by marketing analysts to support marketing decisions, such as marketing-mix planning, market segmentation, brand positioning, and new product development. Further, we focus on how to use andto interpret the information provided by these techniques in practical business settings.

The aim of this course is to teach students the methods, principles, and theories of modern marketing research and to apply these to practical business settings. The objectives of the course are:

• To develop an understanding of the marketing research process and the most commonly used research techniques
• To learn how information is obtained and delivered tosolve marketing problems
• To enhance your analytical skills, to develop the ability to translate business problems into actionable research questions andto design an adequate research plan to answer these questions
• To understand methods and tools for data collection and analysis
• To train your ability to analyze and interpret marketing research data using R, a leading software package for statistical data analysis
• To improve your communication, presentation and team working skills

You need to attend at least 80% of all classes to pass the course.

The course is taught using a combination of interactive lectures, class discussions, case analyses, computer exercises, and student presentations. The sessions will be held in the computer lab and include an introduction to questionnaire design, online survey methods, data handling, and data analysis using the statistical software package R. The aim is to familiarize students with the conceptual foundations of the analytical techniques before applying the acquired knowledge to real-world data sets. Furthermore, students are required to design and conduct their own market research projects in groups and present the results in class. If written assignments are requested, they need to be submitted via the learn@wu platform within the indicated deadline.

The course covers practical applications of data analytics for which the software R is required. R is a powerful tool for data analytics and visualization, which will be pre-installed on the computers in the lab where the sessions will be held. However, since R is an open source software, you may also choose to download and install the software on your computer for free. We recommend to use R via the integrated development environment (IDE) RStudio, which is also available for free:

• Download R: https://cran.r-project.org/
• Download R Studio: https://www.rstudio.com/products/rstudio/download/

Please also make use of the abundance of web resources regarding R (e.g., http://r4ds.had.co.nz/). For students who would like to further train the materials covered in class, we recommend DataCamp (www.datacamp.com), an online platform that offers interactive courses in data science at different levels. To facilitate the learning process you will obtain full access to the entire DataCamp course curriculum for the duration of the course. 

To be prepared for class, you must read the material assigned for the day and ready to answer questions about it. We will call on students at random, so please be prepared all the times. It is also suggested to come with questions or comments about the material that you think might be interesting and helpful to the class. Attendance and participation in class discussions is critical to the success of the course and will be part of your grading. Please remember to bring your name card to class.

Grading is based on the following components:

• Market research group project (questionnaire design, data collection & analysis, reporting & presentations) [weight: 30%]
• Individual computer exercises (statistical analysis of data sets) [weight: 20%]
• Final exam (concepts & methods) [weight: 40%]
• Class participation (quantity & quality of contributions in class and short quizzes) [weight: 10%]

These grading components will be weighted with the respective weights to arrive at the final grade percentage.

Please note that to ensure an equal contribution of group members for the group assignment, a peer assessment will be conducted among group members, which enters into the computation of the individual grades for the project. This means that the members of a group are required to assess other students regarding their relative contribution. 

To successfully pass this course, your weighted final grade needs to exceed 60%.

This course is designed for students of the WU Master's Program (MSc) in Marketing. Admittance to the program is a prerequisite for successful participation of the course.

I am happy to answer your questions, so feel freeto send me a short email (nils.wloemert@wu.ac.at), or drop by my office if you would like to talk to mein person. I will also try to be available in the classroom after each class orduring the breaks of each class.