Course ObjectiveTo advance in the empirical practice of Marketing Data Science using
statistical and econometric methods with an emphasis on statistical
learning and prediction.
Course ContentA real-life quantitative marketing project is considered and carried
out. The focus is on the use of state-of-art data science methods
relevant to Marketing such as sentiment analysis based on written texts
from magazines, newspapers and social media. All aspects of marketing
data research will be considered. The main
steps of a marketing data science project will be taken, including the
formulation of marketing research questions, the data cycle process, the
analysis, modelling, and forecasting of data, presentation of the
empirical results, the evaluation and the formulation of answers to the
questions. Particular attention is given to the data cycle process:
retrieve data, clean data, aggregate data, visualisation, and
evaluation. Besides the practices of marketing data science, also the
interpretation of empirical results, how to value their relevance and
how to translate these into practical solutions will be discussed.
Teaching MethodsEach week consist of two-hour lectures and four-hour working groups. All
work will be carried in groups of 2-3 students. A report must be
Method of AssessmentGroup assessment of the report.
LiteratureA collection of papers and chapters from books.
Target AudienceMSc Econometrics students, the Marketing Data Case is compulsory for the
specialisation Marketing Data Science.
Additional InformationThe Marketing Data Case is for the MSc Econometrics and compulsory for
the specialisation "Marketing Data Science"
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||prof. dr. S.J. Koopman|
|Examiner||prof. dr. S.J. Koopman|
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Lecture, Study Group|
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