2024/2025 KAN-CCMVV2447U Brand Analytics
English Title | |
Brand Analytics |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Full Degree Master |
Duration | One Quarter |
Start time of the course | Second Quarter |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 150 |
Study board |
Study Board for cand.merc. and GMA (CM)
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Course coordinator | |
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Teaching methods | |
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Last updated on 13-02-2024 |
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Learning objectives | ||||||||||||||||||||||||
The main objective of this course is to provide
an overview of marketing research techniques dedicated to
collecting and analyzing data for branding purposes and learn how
and when they can be applied. At the end of the course the student
is expected to be able to:
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Course prerequisites | ||||||||||||||||||||||||
The course will be based on freely available software (including R) that will be discussed in the course (no previous experience is required). Basic statistical knowledge is required. Further required knowledge will be taught and practiced in the course. | ||||||||||||||||||||||||
Examination | ||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||
The course Brand Analytics offers insights into the multifaceted nature of brand equity, exploring the drivers behind it, and mastering the analytical methods needed to track and manage brands in the digital era. This approach is highly relevant for both large corporations and smaller startups, laying a solid foundation to understand the ways in which brands drive organizational value.
At the heart of the curriculum are analytical and experimental methods for measuring brand value. Students delve into brand image measurement, web scraping, sentiment analysis, social network analysis, and customer journey mapping gaining insights into consumer perceptions and online brand presence. Experimental approaches like A/B testing and conjoint analysis are also central, providing tools to understand consumer decision making, e.g., brand purchases, that can be quantified into monetary brand value. These techniques form a comprehensive toolkit for students to measure and manage brand equity efficiently and effectively and lay the foundation for marketing accountability.
Furthermore, the course also prepares students for emerging trends in digital marketing, including the integration of artificial intelligence, equipping them to adeptly face the future challenges and opportunities in the realm of brand analytics and management. |
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Description of the teaching methods | ||||||||||||||||||||||||
The teaching will be blended and consists of a mixture of prerecorded lectures, dialog-based in-class lectures, presentations, and computer tutorials. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
Students will receive feedback via in-class discussions and during exercises. Additional individual feedback can be obtained after the lectures, during office hours, or individual meetings that can be requested via email. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
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Further Information | ||||||||||||||||||||||||
Part of Minor in Excellence in Brand Strategy & Analytics |
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Expected literature | ||||||||||||||||||||||||
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