2021/2022 KAN-CIBCV1519U Data-driven market segmentation
English Title | |
Data-driven market segmentation |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Full Degree Master |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
Study Board for Master of Arts (MA) in International Business
Communication in English
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Course coordinator | |
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Teaching methods | |
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Last updated on 15-02-2021 |
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Learning objectives | ||||||||||||||||||||||
Upon successful completion of the course,
students will be able to:
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Examination | ||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||
Consumers increasingly expect to be addressed and met on their own terms. This can only be achieved if businesses can handle complex insights into culturally diverse subgroups (segments) of consumers and their behavior across the global market place. The identity formation and thereby value formation of modern consumers are becoming increasingly complex due to their belongings to various local, national and global communities accessible via contemporary media technologies and the world-wide web. This implies that the key challenge to develop a successful marketing and communication strategy is to obtain a systematic understanding of the complex consumer segments and a decision-making mechanism of their preferences and choice of consumption behaviors.
The same applies to the policy making. For example, to overcome a challenge like the Covid-19 crisis, but also e.g., the long-term crisis on climate change, a socially responsible behavior is required. However, individuals’ attitudes to a crisis may substantially differ, and manifest itself in different behaviors. Therefore, a modern policy maker needs to differentiate messages suitable for respective target segments and seek to optimize their potential effects on the citizens’ responsible behaviors.
The course reviews theoretical concepts from three aspects: 1) market segmentation addressing within- market heterogeneity and across-homogeneity; 2) consumers' interpersonal psychology addressing personal values, beliefs and norms, and their relations with their attitudes and behavioral choices in our contemporary society; and 3) consumers' perception and cognition of various marketing stimuli.
The course will support students to design an empirical study by selecting (or combining) appropriate methods relevant to an identified research issue.
For example:
NOTE: The elements to be taught in this course are identical to the course: "KAN-CIBCV1514U Consumer Culture and Communication: Segmenting, Targeting and Positioning across the Global Market" offered in the Spring semester. However, this elective course generally addresses the topic of market segmentation applied not only to consumer marketing, but also to the policy making and communication for nudging behavioral changes of citizens under the Covid-19 crisis and the Green Transition (see relevance of this course in the Business of Society blog).
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Description of the teaching methods | ||||||||||||||||||||||
The course aims at providing students a process-based learning experience where their own backgrounds and experiences will contribute to their knowledge acquisition process. In this way, the course will implement a blended learning-based approach on top of an activity-based course design (Margaryan et al. 2004). The course consists of a combination of lectures, exercise lessons (group assignments and peer-reviews) and a workshop. | ||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||
Through a group-based assignment, the course will create an activity-based learning place and will facilitate knowledge co-creation via activities such as "student-to-student feedback" and teacher's feedback for each group assignment in the class and online. | ||||||||||||||||||||||
Student workload | ||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||
Expected literature (theories):
Expected materials (methods):
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