EBA 3640 Marketing Analytics
This course aims to teach basic skills in marketing decision-making based on a systematic analytical approach to harnessing data that help managers to increase the effectiveness of marketing decisions. The course is tailored towards students who are not trained as computer engineers but rather as business professionals who have to acquire know-how in using data to improve marketing decision-making in their everyday tasks (e.g. deciding which customer segments should be targeted, how to evaluate the potential costs versus return-on-investing in different marketing activities e.g. from online or offline campaigns, or testing how to develop a new product and improve the existing one).
We use an “Explain-Show-Do-Practice” approach to learning that encompasses explanations in the lectures followed up by a combination of class discussion, case study analysis and practical hands-on exercises with practice datasets in using statistics software. We do not go deeply into the statistics and mathematics behind the methods used in the academic models behind the tools, but rather provide you with an understanding of what the model could be used for, intuitively how it works and which data do you need to have as an input and how to evaluate the output that you would get from the software. We use an add-on module in Excel to make this course highly relevant and applicable to manager’s actual decision-making.
After completed course students shall:
- Understand how different analytical approaches can inform specific marketing decisions.
- Know which type of data are needed for each method and understand how to structure such data.
- Understand the key intuition behind different analytical methods.
- Understand how to find, interpret, reconcile, and assess key numbers from statistical output.
After completed course students shall be able to:
- Select the appropriate analytical approach to answer specific managerial questions
- Structure and clean data required
- Run data analysis using statistical software
- Validate, assess, interpret, and present the results
- Articulate an analysis' limitations and strengths
- Formulate strategy recommendations
- Customer Value Assessment and Valuing Customers
- Segmentation and Targeting
- Analyzing brand-, offering-, and relationship-based competitive advantage
- Market Response and Marketing Mix Models
- Online Marketing Data and Analytics
- Experimentation and A/B-testing
(the above list is tentative and could change)
- Participants will learn how to carry out marketing analytics using real-life data and a statistical analysis package (e.g., Enginius).
- Participants/study groups are required to submit their solutions to written assignments in written.
- Participants will perform asynchronous learning activities throughout the semester.
According to BI's policy, students have to purchase access to the marketing analysis suite (e.g., Enginius) at their own cost.
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
- Introductory statistics
- Introduction to Marketing
|Mandatory coursework||Courseworks given||Courseworks required||Comment coursework|
|Mandatory||5||3||Participants will submit 5 different work requirements (i.e., exercises) over the course of the semester. They will need to get approved for 3 of these in order to participate in the final exam.|
|Comment coursework:||Participants will submit 5 different work requirements (i.e., exercises) over the course of the semester. They will need to get approved for 3 of these in order to participate in the final exam.|
|Exam category||Weight||Invigilation||Duration||Support materials||Grouping||Comment exam|
Form of assessment:
Examination every semester
|100||Yes||2 Hour(s)||Individual||Final exam: At the end of the course, there will be a final exam compromising a mixture of open- and close-ended questions.|
|Form of assessment:||Structured test|
|Support materials:|| |
|Comment:||Final exam: At the end of the course, there will be a final exam compromising a mixture of open- and close-ended questions.|
|Exam code:||EBA 36401|
|Resit:||Examination every semester|
Feedback activities and counselling
Student's own work with learning resources
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.