AI for Strategic Marketing Leadership
Develop a thorough understanding of how AI can transform marketing strategy, with particular focus on customer acquisition, retention, and relationship management.
What you will learn:
- How AI can transform marketing strategy, including customer acquisition, retention, and relationships.
- Knowledge of key AI methods (e.g., text mining, ad response modeling, conjoint analysis) and their use in solving marketing challenges.
- Evaluate how AI enhances business performance through data-driven decisions, better customer experiences, and resource optimization.
- Assess and communicate how AI tools align with marketing goals, organizational needs, and data requirements.
Despite the surge in interest around artificial intelligence within the business community, many implementations still fall short of expectations. Often, this is because the focus remains heavily on data and methodologies, while real value creation is overlooked.
Additionally, a communication gap exists between data and computer scientists and decision-makers, as they don’t always speak the same language.
This course is designed to bridge that divide. With a managerial focus, it equips future leaders with the knowledge to leverage AI’s potential in addressing critical marketing challenges.
Specifically, you’ll discover how AI can drive customer acquisition, boost retention, and deepen customer relationships.
The curriculum offers insight into a wide range of AI techniques, emphasizing intuitive understanding and practical requirements without discussing the technical details.
Admission requirements
- You are at least 25 years old
- You have completed a bachelor's degree
- You have 4 years of full-time work experience (3 years if you already have a master's degree)
Students without a completed bachelor's degree can, in some cases, be admitted based on prior learning and work experience.
Take the course or build a degree
This course can be integrated in an Executive Master of Management.
The course awards 15 credits, and a master's degree consists of 90 credits. Should you choose to take more master's level courses later, you can accumulate a complete master's degree. The combination of courses is up to you, based on your learning goals and career plans.
Modules and course content
The course consists of two in-person modules of three full days each, supported by digital sessions. Teaching includes lectures, webinars, group work, and practical exercises.
In addition to lectures and guest presentations, this course will feature hands-on exercises based on real-life case studies. The emphasis will be on identifying marketing problems that can be effectively addressed with AI solutions.
Instead of delving into technical details, the primary focus will be on interpreting the results of AI analyses and implementing actionable strategies based on those insights.
Please note that while attendance is not mandatory for all modules, students are responsible for obtaining any information shared in class that is not available on itslearning or other course materials.
The course will use the AI tool ChatGPT UiO.
The syllabus is made available as soon as you have been admitted to the course.
Exams consists of a term paper, counting 60% of the total grade and a portfolio exam counting 40%. The term paper is written in groups of 1 - 3 students. Each group will receive approximately two hours of supervision for the term paper.
All evaluations must be passed to obtain a certificate for the course.
Modules
This module explores how to align offerings with customer needs and identify the right products for each customer. You will learn how to uncover meaningful patterns in customer behavior, segment customers effectively, interpret complex information, and use these insights to make informed decisions that improve product selection and marketing impact.
- Market response modeling for resource allocation
- Cluster analysis for segmentation
- Text mining for analyzing user-generated data (reviews, etc.)
- PCA for dimensionality reduction
- Network analysis for understanding innovation diffusion
In this module, you will learn how to identify the features that influence customer choices, anticipate potential churn, and design offerings that better meet customer needs. You will apply practical methods to analyze customer preferences and use these insights to guide product development and retention strategies.
- Choice modeling for churn analysis
- Conjoint analysis for new product development
Faculty
Time and effort required
All our courses are designed to be combined with a job and a personal life. Still - you'll need to dedicate some time.
You'll spend a total of 6 workdays on the in-person sessions, plus an additional day for the written exam.
Additionally, you'll need to make time for webinars, reading the course material and writing the term paper.
How much time this takes varies widely from student to student, and you can adjust this to fit your other commitments.
Tuition fee
The tuition fee is invoiced per semester and adjusted annually. It includes access to lectures and the standard examination fee.
Want to know more?
We regularly host informational webinars that you can join. There you will meet a guidance counsellor and have the opportunity to ask questions.
Similar courses
Not quite the course you were looking for? We offer a range of courses in the same subject area - from short courses to part-time master's level studies.