Everyday decisions, as well as major changes in most companies today, are directed by data. To make smart marketing decisions, one should understand the market situation, monitor the competition, be familiar with the preferences of the target group, and objectively evaluate the capabilities of a product.

This course offers an introduction to basic research methods and focuses on the initial development of skills relevant to data collection, analysis, and critical interpretation necessary for marketing decision-making.

After completing the course, students should be able to plan and conduct a marketing research project: collecting, analyzing, and interpreting data, and presenting the results convincingly.

In particular, students will be able to:

• Define research questions and hypotheses
• Develop a questionnaire
• Collect data
• Prepare and evaluate data using available statistical software (MS Excel)
• Run various statistical tests (T-tests, Chi-square test, Analysis of variance, Correlation, and Regression analyses)
• Make critical conclusions and present research outcomes in a comprehensive way

For the successful completion of the course, students are required to attend a minimum of 80% of the lectures. This includes the completion of in-lecture individual exercises; failure to complete these dynamic lecture flow exercises will be considered as failure to attend the lecture.

Flexible Scheduling:
Students will have the flexibility to complete online lecture flows (lectures 3 through 6) at their preferred time and pace within the allotted completion period. Specifically, each online lecture flow should be completed within 4 days (from Tuesday morning to Friday night of the respective lecture weeks).

Fixed Scheduling:
Students must be available to complete the online course quizzes for one hour starting at the scheduled class time. Specifically:

• Quiz I - scheduled time of Lecture 2 (15.10.2024)
• Quiz II - scheduled time of Lecture 5 (19.11.2024)
• Quiz III - scheduled time of Lecture 6 (03.12.2024)

Students must be available for the entire duration of the scheduled in-class sessions:

• Lecture 1 - 08.10.2024
• Lecture 2 - 15.10.2024
• Mandatory Coaching Session (Quiz II) - 12-14.11.2024*
• Mandatory Coaching Session (Final Project) - 10-12.12.2024*
• Final Project Presentation - 17.12.2024

*Individual time slots will be communicated at a later date. Please note that you only need to be available for your booked time slot.

Most of the course will take place online through dynamic lecture flows that facilitate interactive hands-on learning and timely personal feedback.

The core topics of the course will be introduced by the lecturer, with further in-class examples, video explanations, and exercises. The use of statistical software will also be introduced in the online class flow, with further opportunities for training both during the sessions in the form of in-class exercises and as part of homework.

Students are required to study theoretical reading material and practice statistical analysis in preparation for the sessions and for the successful completion of the final group project.

The course provides:

• Opportunities for individual lecturer-to-student interaction based on a dynamic lecture format
• Hands-on learning of data analysis, evaluation, and interpretation
• Two group projects (creation of a survey and a final group project)
• Accessible theoretical literature
• Coaching sessions before quizzes and the final project presentation

Individual Work:

• Home assignment - 5%
• Class participation (especially completion of in-class (online) exercises) - 10%
• Quizzes (including theoretical knowledge and practical use of statistical software) - 40%

Teamwork:

• Development of the questionnaire - 10%
• Final Project - 35%

ATTENTION: Team projects will receive a team grade; however, individual grades for team tasks may vary. Upon completion of the team work, students will be asked to provide peer evaluations. If multiple group members report that a member has contributed more or less than their fair share, that member's grade will be adjusted accordingly. The degree of increase or decrease will be based on the average peer ratings.

Grades:

• from 90%: Excellent
• from 80%: Good
• from 70%: Satisfactory
• from 60%: Sufficient
• < 60%: Not Sufficient

Aufnahme in die SBWL Marketing

Basic MSExcel Knowledge is necessary for this course: if absent, materials for self-study will be provided at the beginning of the course

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marie.louise.brand@wu.ac.at

olga.bergmeier@wu.ac.at