ØAM111 Consumer Behaviour and Analytics

Contents and structure

The course aims to provide students with a thorough introduction to the theories related to consumer behavior and how these can be connected to businesses’ marketing efforts. The course includes a combination of classical theories in consumer behavior and a modern focus on digital channels and analytical tools, based on AI and deep learning, such as sentiment analysis and social network analysis.

Key concepts within consumer behavior are introduced, with emphasis on psychological, social, and cultural influences. The consumer decision-making process is reviewed in detail. The course also emphasizes the ability to communicate a message, as well as the application of theories to practical challenges faced by marketers in the field. Additionally, the course focuses on understanding consumer processes in digital channels. Relevant issues include: How can we analyze consumer responses to digital content? How are consumers connected on social media and influencing one another? Who are the most influential individuals?

The course also emphasizes how to design studies in digital channels to develop insights that can serve as the foundation for business strategy.

Learning Outcome

Learning outcomes

Knowledge

• Be familiar with the general decision-making process of consumers.
• Be able to describe various psychological mechanisms that explain consumer behavior.
• Have knowledge of contextual factors that influence consumers.
• Be familiar with how consumer research is conducted using qualitative and quantitative methods in digital channels.
• Be familiar with how consumer insights can be used as a basis for business strategy.
• Have basic knowledge of analytical tools based on AI and deep learning, such as natural language processing (NLP), particularly text mining and sentiment analysis.
• Have basic knowledge of analytical tools for social network analysis (SNA).

Skills:

• The candidate should be able to apply various theories of consumer behavior as tools to segment a market, adapt products and services, and design different types of marketing communication.
• The candidate should be able to conduct studies to develop consumer insights, including in digital channels.
• The candidate should be able to assess the potential for using AI- and deep learning-based analytical tools (e.g., ChatGPT) and code-based software (e.g., R) for sentiment analysis and social network analysis (SNA) to develop consumer insights.

General competence:

On completion of this course students will be able to:

• Master critical thinking in the practical task of marketing products and services in physical and digital channels.

Entry requirements

None

Recommended previous knowledge

Marketing Management I (BØA116) or similar course

Teaching methods

Lectures, case discussions and other types of group work.

Compulsory learning activities

Two submissions must be approved before taking the exam. A maximum of 20% absence is permitted.

Assessment

Written examination, 5 hours. The examination may be digital.

Time and place for the examination will be announced at Studentweb.

Grading scale is A-F where F is fail.

Examination support material

Simple calculator of model:

- Casio fx-82, Casio fx-85 (all models of both fx-82 and fx-85 are allowed: CW, ES, ES Plus, EX, Solar m.m.)

- TI-30Xa, TI-30XIIS, TI-30XS MultiView

- Sharp EL-531TG, Sharp EL-531TH, Sharp EL-531TS

More about examination support material

Course reductions

• ØAM102 - Markedsføring II - Reduction: 5 studypoints