Marketing Data Science is a specialization of the Econometrics and Operations Research master's programme. This hands-on study into econometric methods for analyzing marketing data to facilitate better marketing strategies let you become the quantitative marketing specialist and place you at the forefront of a successful professional career.
Marketing Data Science connects many academic disciplines including mathematics, statistics, economics, and marketing, and is primarily concerned with the use of microeconomics, consumer behaviour and statistical techniques to analyse data sets with multiple hierarchies such as product, brand, location, distribution, etc. The econometric methods can be used to analyse volume shares, advertising effects, sale strategies, consumer behaviour, brand loyalty schemes, TV and social media advertising, and many other topics.
Three core 6 EC courses (compulsory):
- Advanced Econometrics
- Multivariate Econometrics
- Time Series Models
Five specialization courses (of which one is compulsory and 2 or 3 elective):
- Marketing Strategy
- Large Scale Data Engineering
- Web Data Processing Systems
- Branding and Advertising
- Marketing Data Case (compulsory)
One elective 6 EC course (or additional specialization course):
- Digital Marketing and Technology
- Geographic Information Systems
- Regional and Urban Economics
- Transport Economics
- Big Data Analytics in Geographic Information Systems
- Big Data Analytics
- Data Mining Techniques
Thesis (18 EC): an in-depth study on a challenging topic in econometrics with an emphasis on theory, methodology or computing.
Typical placements include:
PhD student, Customer Intelligence analyst, Quantitative analyst, Marketing Modeler, Consultant Data Analytics, Statistical researcher, Quantitative marketing analyst, Quantitative researcher, Data analyst, Quantitative methods instructor, Data scientist, Sales Management consultant, Statistician, Quant Sales analyst, and many more.
Why VU Amsterdam?
The programme can be characterized as follows:
A programme that will enhance your analytical skills, will invest in your quantitative insights, will learn you how to design and apply econometric methods in a marketing context, and will broaden your quantitative horizons.
A programme that will learn you how to analyse marketing data, how to use statistical tools for market, advertising and product-life questions of relevance, how to approach big data problems, how to interpret quantitative results, how to present the results of an econometric analysis, how to deduct conclusions and to make marketing decisions from a quantitative analysis.
A programme that will learn you to be a leading person in helping others to understand and work with quantitative methods in marketing.
Admission with an International Degree
We welcome motivated and ambitious students who are interested in advancing their knowledge in Econometrics and related subjects and are aware of their role in society. In order to be successful in this programme, you will need a solid basis in mathematics, statistics and econometrics. In particular, we expect that you have passed courses in mathematics (calculus, analysis), probability, mathematical statistics, and econometrics. Basic knowledge in computer programming is also required.
The track Econometrics of the Master's programme Econometrics and Operations Research, with specializations Econometric Theory, Financial Econometrics, Empirical Marketing, and Quantitative Economics, is open to students with a university Bachelor's degree that provides a thorough knowledge in mathematics (analysis, calculus), probability, (mathematical) statistics, econometrics and computer programming. You need to have successfully completed courses and studied literature related to the core of this programme, which is based on the following books.
- Calculus Early Transcendentals, James Stewart, Cengage Learning, International Metric Edition - 7th Edition, 2011.
- Linear Algebra and its Applications, David C. Lay, Steven R. Lay and Judi J. McDonald, Pearson Education, 5th Edition, 2016.
- A First Course in Probability, Seldon M. Ross, Pearson Education, 9th Edition, 2013.
- Fundamentals of Probability, with stochastic processes, Saeed Ghahramani, CRC Press, Taylor and Francis Group, 3rd Edition, 2016.
- Statistical Inference, George Casella and Roger L. Berger, Cengage Learning, 2008.
- Introduction to Econometrics, James H. Stock and Mark W. Watson, Pearson Education, 3rd Edition, 2014.
- Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge, Cengage Learning, 2013.
- A Guide To Modern Econometrics, Marco Verbeek, Wiley, 5th Edition, 2017.
Basic skills in Computer Programming in Python, R, Matlab, Ox or Java.
If you can show certified exam results for courses that are related to the subjects and are of a comparable level (each course with a workload of 6 EC or close to it), this is satisfactory. The equivalence will be evaluated by the Examination Board and its approval determines the admission.
English language proficiency
The admission board wants to stress the intensity of the programme: reading scientific articles and writing papers will be a key part, all in a very high pace. Your English language skills, both oral and written, are extremely important in this programme. As you will have to communicate frequently with your fellow students and you will be working with and for international companies.
VU Amsterdam requires all applicants to take an English test. You can already apply online without having the test results. We do advise you to plan a test date as soon as possible. Below you will find the minimum English test scores for the programme:
- • Minimum general score 6,5
- • Minimum score speaking 6,5
- • Minimum score listening 6,5
- • Minimum score writing 6,0
- • Minimum score reading 6,0
- • Paper-based test 580
- • Internet-based test 92-93
- • Cambridge Proficiency Exam A, B, C
- • Cambridge Advanced Exam A, B, C
Program taught in: