2024/2025 KAN-CSAAO2402U Sales and Marketing Analytics
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Sales and Marketing Analytics |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory |
Level | Full Degree Master |
Duration | One Quarter |
Start time of the course | Third Quarter |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
Study Board for cand.merc. and SAM
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Course coordinator | |
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Teaching methods | |
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Last updated on 28-05-2024 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||||
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Prerequisites for registering for the exam (activities during the teaching period) | ||||||||||||||||||||||||||
Number of compulsory
activities which must be approved (see section 13 of the Programme
Regulations): 1
Compulsory home
assignments
The student must get 1 out of 2 assignments/activities approved in order to attend the ordinary exam. 1. Individual analytical home assignment: During the course, an individual analytical home assignment is administered that consist of analytical exercises in which students apply the methods and tools that were covered during class. Students report their quantitative findings. Faculty will assess the assignment and provide feedback to students. The purpose of the assignment is to further develop analytical skills of students and let them reflect on the usability of methods and tools. The assignment helps students to prepare for the final exam. 2. Multiple choice test: At the end of the course a mandatory multiple-choice test is administered. The purpose of the test is to provide students with an overview of which topics they master and which not. More specifically, the multiple-choice test examines students’ capabilities with respect to (i) knowledge, (ii) comprehension, (iii) application, and (iv) problem solving for the topics covered in the course. This helps students to better prepare for the final exam. Students will not have extra opportunities to get the required number of compulsory activities approved prior to the ordinary exam. If a student has not received approval of the required number of compulsory activities or has been ill, the student cannot participate in the ordinary exam. If a student prior to the retake is still missing approval for the required number of compulsory activities and meets the pre-conditions set out in the program regulations, an extra assignment is possible. The extra assignment is a 10 page home assignment that will cover the required number of compulsory activities. If approved, the student will be able to attend retake. |
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Examination | ||||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||||
The aim of the course is to gain an understanding of how marketing analytics can be used to create customer insights and thereby improve business intelligence to allow for more effective and efficient marketing activities. Specifically, the course aims at (1) providing students with knowledge about different types of marketing analytics and data visualization; (2) giving students an understanding of the core processes, frameworks, and techniques used in marketing analytics; (3) providing students with basic skills to apply different types of statistical and visual analytical techniques and interpret the results; and (4) providing students with knowledge about how different companies employ marketing analytics to create customer insights and business intelligence.
Companies today are facing oceans of data about, for example, customers, sales activities, transactions, markets, or competitors. These data offer numerous opportunities to inform marketing decision-making by providing insights and creating business intelligence. At the same time, however, the risk of information overload has substantially increased. In order to shift from intuitive decision-making to fact-based decision processes, marketers need to adopt an analytical marketing approach.
This course will give students a deeper understanding of how marketing analytics can be used to create customer insights and thereby improve business intelligence to allow for more effective and efficient marketing activities.
Students will learn how to apply different approaches to marketing analytics; learn how to use digital tools, techniques, and frameworks essential for transforming data into relevant information; learn how marketing analytics and data visualization can help companies to understand not only how customers have behaved in the past, but also to make accurate predictions about how customers will behave in the future, which in turn can help to optimize marketing activities.
Analytical techniques that students learn in the course will be based on the open-source statistical platform R. Students do not need to have prior experience with this program/platform. |
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Description of the teaching methods | ||||||||||||||||||||||||||
This course is delivered in a blended learning format that combines online material and lectures with in-class discussions. Blended learning creates a powerful learning environment for students, which we intend to use to its fullest potential. The course consists of online lectures and materials, online activities (e.g., online self-assessments), as well as on-campus group work and in-class discussion. The class is highly interactive both online and offline with a corresponding expectation that students engage in these interactions. | ||||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||||
Quizzes are used to give students a better overview of whether they are following the expected learning curve. During the online and offline sessions students will get feedback from teachers. | ||||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||||
Text books and research papers (Indicative literature - more literature and required readings will be announced upon enrollment):
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