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2024/2025  KAN-CCMVA2412U  Mastering Sales in a Digital and AI-Driven World

English Title
Mastering Sales in a Digital and AI-Driven World

Course information
Language English
Course ECTS 2.5 ECTS
Type Elective
Level Full Degree Master
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 30
Max. participants 60
Study board
Study Board for cand.merc. and GMA (CM)
Course coordinator
  • Milena Micevski - Department of Marketing (Marketing)
  • Selma Kadic-Maglajlic - Department of Marketing (Marketing)
For academic questions related to the course, please contact course responsibles Milena Micevski (mmic.marktg@cbs.dk) or Selma Kadic-Maglajlic (skm.marktg@cbs.dk).
Main academic disciplines
  • Marketing
  • Service management
Teaching methods
  • Face-to-face teaching
Last updated on 07-11-2024

Relevant links
Learning objectives
After the course, the student should be able to:
  • Acquire a thorough understanding of AI and its transformative impact on sales and service management.
  • Gain insights into how AI generates growth and value for organizations, enhances the customer experiences and relationships with customers.
  • Understand, reflect upon, and contrast different forms of AI that can be used in the B2B and frontline setting.
  • Discuss the impact of AI on privacy, ethics, and biases.
Course prerequisites
Completed Bachelor degree or equivalent.
Examination
Mastering Sales in a Digital and AI-Driven World:
Exam ECTS 2,5
Examination form Active participation

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation - based on an overall assessment - in the class activities fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
The student must participate in A combination of assignment and presentation
Individual or group exam Individual exam
Grading scale Pass / Fail
Examiner(s) Assessed solely by the teacher
Exam period Summer and Summer
Make-up exam/re-exam Oral exam based on written product
In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Size of written product: Max. 5 pages
Assignment type: Essay
Duration: 20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
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.
Description of activities
A combination of assignment and presentation: The student must participate in minimum 80 % of the scheduled teaching.

In addition, the student must attend the following: 

The student will receive a case study and will be tasked with developing a sales lead generation and opportunity management strategies based on that case. Finally, they have to present their strategies and what the role of AI is in achieving those strategies.
Course content, structure and pedagogical approach

In the context of today’s swiftly evolving digital landscape, the ability to effectively harness artificial intelligence (AI) is essential for organizations seeking to maintain a competitive edge in sales and services. This course aims to equip participants with an in-depth understanding of how AI can act as a transformative agent in enhancing sales processes and driving substantial revenue growth in a B2B and frontline management context.

 

In this course, students will engage in an exploration of the diverse landscape of AI technologies. They will, for example, discover the capabilities of natural language processing and analyze the benefits of predictive analytics. Attendees will gain essential insights into the various applications of AI within the sales and service sector. Whether it involves improving frontline selling, sales prospecting methods, enhancing lead generation tactics, fostering customer engagement, or refining sales forecasting approaches, students will develop a sophisticated understanding of how AI can be leveraged to achieve measurable outcomes and promote business success. They will also be able to critically assess under which circumstances an AI solution is a valuable solution to sales organization.

 

The main topics that will be discussed in the course;

 

  • Grasping the fundamentals of AI
  • Overview of AI applications in sales and services
  • Application of AI in the contexts of frontline selling, prospecting, lead generation, building customer relationships, fostering customer engagement, sales forecasting etc.
  • Ethical considerations of AI-driven selling

 

This course DOES NOT focus on programming AI tools or the statistical concepts underlying AI. Instead, it adopts a practical approach, exploring how and where AI can be effectively applied in contemporary marketing.
Description of the teaching methods
At the beginning of the course, students will form their own sales teams. Each team will consist of up to five members. The groups will participate in the sales simulation, including the following activities: information gathering, sales presentation, customer complaint handling, and sales planning. Each phase of the project will be discussed in class, and additional instructions will be uploaded on Canvas. The group project's focus is to create trust and leverage confidence in another party while realizing their inherent needs and selling them an appropriate product, service, experience, or idea.
Feedback during the teaching period
The design of the course follows a proactive feedback philosophy through ex ante mirroring of the exam. Students are repeatedly exposed to the learning objectives through weekly sales project assignments that resemble exam assignments, online quizzes, and role-playing.

In the wrap-up session dedicated to exam preparation, students are debriefed and encouraged to seek detailed feedback on their own performance. This gives them the opportunity to reinforce what they have learned in the course and prepare for the actual exam. In the final debriefing session, the material is recapped, overarching feedback is provided.


Student workload
Teaching 18 hours
Preperation 20 hours
Exam 32 hours
Further Information

2-week course that cannot be combined with other courses.

 

Course and exam timetable is/will be available on https://www.cbs.dk/en/study/international-summer-university/courses-and-exams

 

We reserve the right to cancel the course if we do not get enough applications. This will be communicated on https://www.cbs.dk/en/study/international-summer-university/courses-and-exams in start March.
Expected literature

Indicative literture list include:

  • Ingram, T. N., Avila, R. A., Schwepker, C. H., & Williams, M. R. (2019). SELL, 6th Edition, Cengage Learning (selected chapters).
  • Brynjolfsson, E., & Mcafee, A. N. D. R. E. W. (2017). The business of artificial intelligence. Harvard Business Review.
  • Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
  • Syam, N., & Sharma, A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management, 69, 135-146.
  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.
  • Singh, J., Flaherty, K., Sohi, R. S., Deeter-Schmelz, D., Habel, J., Le Meunier-FitzHugh, K., ... & Onyemah, V. (2019). Sales profession and professionals in the age of digitization and artificial intelligence technologies: concepts, priorities, and questions. Journal of Personal Selling & Sales Management, 39(1), 2-22.
  • Campbell, C., Sands, S., Ferraro, C., Tsao, H. Y. J., & Mavrommatis, A. (2019). From data to action: How marketers can leverage AI. Business Horizons.
  • Hagen, David, and Rick Stefanik. "Artificial intelligence dialogue processor." U.S. Patent Application 10/852,300, filed January 13, 2005.
  • More literature will be announced upon enrollment
Last updated on 07-11-2024