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Course module: 201500080
201500080
Advanced topics in Digital Marketing
Course info
Course module201500080
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr. E. Constantinides
E-maile.constantinides@utwente.nl
Lecturer(s)
Contactperson for the course
dr. E. Constantinides
Lecturer
dr. E. Constantinides
Lecturer
dr. A. Priante
Lecturer
dr. S.A. de Vries
Academic year2018
Starting block
2A
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Aims
The main objective of the course is to educate future marketers in skills and knowledge underpinning the Digital Transformation.
The course reviews and teaches the current and emerging technology-based business aspects of Digital Marketing. The course assesses   the importance, impact and pervasiveness of  ICTs in today’s business environment and in particular in the Marketing domain. Students will develop knowledge and insight in current theories, models and management approaches in the field of marketing in digital environments and the understand  the importance of applied data science for the future marketer. This knowledge and insight are important in order to understand the background and impact of data-driven marketing.
Students will furthermore will get in touch with various aspects of ‘Social, Big- and Open Data’ based tools, the domain of cognitive computing and its importance in management decision processes. Other focus areas of the course are the Consumer Neuroscience (Neuromarketing), the Networked Society / Internet of Things (IoT)

 
Content
For students without previous affiliation with Digital Marketing ( for example students who followed the module DMNB in the Bachelor) the course will provide a review of the traditional Digital Marketing topics like E-Commerce and Social Media Marketing but the main focus of the course will be to offer an advanced view on a number of emerging areas of Digital Marketing. These areas can be designated as a Smart Marketing domain:  The course  underlines the strategic and managerial approach in dealing with Smart / Digital Marketing issues, offering to participants knowledge and competencies on digital marketing topics, technologies and tactics.
Next to the theoretical content of the course the students will carry out two group assignments; groups must chose two such assignments out of a list of three. Next to this there will be an obligatory assignment introducing students to cognitive computing as a tool in management decision making processes. This assignment is based on the IBM Watson cognitive computing technology.
As to the two obligatory assignment, the groups will be asked to work on an assignment and produce a group report. The topic of the assignment will be relevant to one of the focus areas of the course
The assignments will bring the students in touch with data sets where effective analytics methods will play a vital role in translating market data to management information and strategies. Guest lecturers from the field will provide students with tacit knowledge and introduce them to problems that require solution using new smart approaches.
 
Lectures and Guest Lectures main topics
•         Introduction: Summary on Web 1.0 marketing,
•         Introduction Search Engine Marketing, Web 2.0 / Social Media Marketing
•         Cognitive Computing and Web Analytics
•         Big Data and Social Intelligence
•         Consumer Neuroscience (Neuromarketing): Techniques and Strategies
•         Networked Society /Internet of Things (IoT) / Embedded systems: Techniques and Strategies
 
The course will be concluded with a session (or symposium)  where the groups will present their group work and findings.
 

 
Assumed previous knowledge
Mandatory. Introduction to Marketing or equal introductory course in Marketing Management
Recommended: Per session scientific publications or reports
Participating study
Master Business Administration
Participating study
Master Communication Science
Required materials
-
Recommended materials
Course material
Course Material consists of scientific articles and selected publications
Instructional modes
Assessment
Presence dutyYes

Lecture
Presence dutyYes

Project supervised
Presence dutyYes

Project unsupervised
Presence dutyYes

Self study with assistance
Presence dutyYes

Self study without assistance

Tests
Assignment

Remark
Grades will be based on an individual assignm. (ind. grade)

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