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2023/2024  DIP-D1FMV5022U  Artificial Intelligence in Marketing

English Title
Artificial Intelligence in Marketing

Course information

Language English
Course ECTS 5 ECTS
Type Elective
Level Graduate Diploma
Duration One Semester
Start time of the course Spring, Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for Graduate Diploma in Business Administration
Course coordinator
  • Johannes Hattula - Department of Marketing (Marketing)
Main academic disciplines
  • Marketing
Teaching methods
  • Online teaching
Last updated on 01-03-2023

Relevant links

Learning objectives
On completion of this course, students will be able to:
  • apply AI and its tools in a marketing context
  • design the structure for an effective implementation of AI in marketing (e.g., data environment)
  • understand the value of AI in personalizing the consumer experience and journey
  • effectively incorporate AI into marketing strategy (including in product, price, communication, and sales marketing) 
  • critically evaluate the benefits and risks of AI in marketing and for consumers 
Examination
Artificial Intelligence in Marketing:
Exam ECTS 5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Written assignment
Release of assignment The Assignment is released in Digital Exam (DE) at exam start
Duration 24 hours to prepare
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer and Winter
Make-up exam/re-exam Oral Exam
Duration: 20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Preparation time: No preparation
Examiner(s): If it is an internal examination, there will be a second internal examiner at the re-exam. If it is an external examination, there will be an external examiner.
Course content, structure and pedagogical approach

Aim of the course:

 

Artificial intelligence (AI) is changing the way how businesses interact with consumers and vice versa. According to a recent Accenture global survey among 1500 C-suite executives from companies across several industries, 84% of executives believe they will not achieve their growth objectives without scaling AI in their organization. Importantly, 76% of the surveyed executives report that they struggle with how to scale it. Moreover, a recent McKinsey analysis of more than 400 actual AI use cases shows that marketing is the functional area in an organization where AI would contribute the greatest value. Given the growing importance of AI in business and especially for marketing activities, it seems fundamental for today’s marketers to understand how and where AI can be applied in the field of marketing to provide substantial benefits for companies (and consumers) and to stay competitive in the market. This course is designed to provide such understanding and help students to get an overview on how AI can be effectively used and applied in a marketing context. This course is not about programming AI tools or statistical issues behind AI; the course takes a more practical approach and looks at how and where AI can be applied in today's marketing.

 

Content and structure:

 

The course focuses on how and where AI can be applied in the field of marketing. Programming or methodological skills are not required for this course.

 

The course starts by introducing students to the basics of marketing and AI, followed by a discussion of how AI evolved in the marketing field over the last decades, and an illustration of the impact AI has on today's marketing to create value for both organizations and consumers. Students become familiar with the main tools AI relies on and learn what role accurate data play for an effective AI implementation. The course further concentrates on strategic and operational marketing elements and how AI can support these elements. For example, students gain an understanding of the importance of AI for marketing organization, marketing automation, and market segmentation. Moreover, by integrating several case studies, students learn how and where AI can be implemented and scaled in different marketing decisions, including product marketing (e.g., improving fit of product offering and consumer preferences), pricing (e.g., dynamic and intelligent pricing), communication (e.g., automated digital campaigns), sales (e.g., sales forecasts), and customer relationships (e.g., chatbots for customer support). The course also covers psychological elements of AI by examining consumers' interaction with AI and the benefits and costs it may have for consumers.

Description of the teaching methods
This course is delivered in an online learning format, integrating various lectures, materials, activities (e.g., online discussions), and guest talks. The class is designed to be highly interactive with a corresponding expectation that students engage in these interactions.
Feedback during the teaching period
Several feedback activities are included to increase the learning experience. For example, during a class, there will be several breakout sessions to give students the opportunity to debate cases and business examples of AI in marketing. Groups will then present their findings in class and receive feedback either directly or collectively to allow students to learn from the discussion. Moreover, every week, students will be able to perform learning check activities to reflect on the topics discussed throughout the course. A peer-graded group assignment with group feedback will give students additional opportunities for feedback.
Student workload
Class 30 hours
Preparation and exam 95 hours
Last updated on 01-03-2023