GRA 8277 Marketing
GRA 8277 Marketing
In increasingly competitive and AI-transformed markets, successful leaders need to understand customers and markets while making difficult, data-informed choices about where to compete, how to differentiate, which customers to prioritize, and where to invest for growth. This Executive Course in Marketing equips participants to make these choices across business and consumer markets by combining customer and market intelligence with strategic and commercial judgment.
Participants learn how to identify attractive customer opportunities, develop compelling value propositions and competitive positions, design and price offerings, build valuable customer relationships, and evaluate trade-offs across products, brands, channels, communication, and customer investments. AI capabilities are integrated throughout these decisions to augment customer and market insight, analysis, ideation, and decision support. Importantly, participants learn in what way AI-generated outputs need to be challenged or validated against customer data, experimentation, and managerial judgment.
Key Takeaways from the Course:
- A stronger ability to make consequential choices about where to compete, which customers and relationships to prioritize, and where to allocate resources for profitable growth.
- Practical approaches for evaluating trade-offs across positioning, offerings, pricing, brands, channels, and customer investments in business-to-business (B2B) and business-to-consumer (B2C) markets.
- Hands-on experience using customer and market data, analytics, AI prompting, synthetic customer samples, experiments, and market simulations to inform and challenge managerial decisions.
- Greater confidence in judging when data and AI-generated insights are credible enough to act on, which tasks can be delegated to AI agents, and where human judgment and oversight remain essential.
- The ability to translate marketing analysis into recommendations that can be communicated and defended across finance, sales, operations, technology, and senior management.
Upon completion of the course, participants will be able to:
- Explain how customer needs, segmentation, positioning, brand, relationships, and customer value shape growth and competitive advantage.
- Understand how customer and market data, analytics, and AI can augment marketing decisions and where their limitations require managerial judgment.
- Assess how data quality, privacy, bias, transparency, governance, and regulation affect responsible marketing decision-making.
Upon completion of the course, participants will be able to:
- Frame marketing problems and identify the information needed to choose between alternative courses of action.
- Apply customer analysis, segmentation, targeting, and positioning to identify attractive market opportunities.
- Evaluate product, service, pricing, brand, and customer-investment alternatives based on customer preferences, expected response, and business value.
- Analyze customer value and relationship opportunities in B2C and B2B markets, including customer profitability, future value, business buying, and relationship dynamics.
- Use AI prompting and AI-supported analysis to interrogate data, generate alternatives, and challenge recommendations.
- Evaluate marketing actions and investments and translate results into managerial action.
Upon completion of the course, participants will be able to:
- Integrate customer and market intelligence, analytics, AI capabilities, and managerial judgment in strategic marketing decisions.
- Connect marketing decisions with finance, sales, operations, and technology to communicate and defend recommendations to senior management and other stakeholders.
- Make responsible choices about data and AI use, including when human judgment, oversight, and accountability are required.
The course examines core marketing decisions from a general-management perspective, integrating B2B and B2C applications throughout.
Understanding customers, markets, and where to compete:
Use customer and market data to identify and profile segments, assess their attractiveness, select priority customers, and evaluate alternative competitive positions. Apply AI prompting to frame managerial problems, design customer surveys, interrogate data, generate alternative explanations, and challenge initial recommendations.
Designing and pricing offerings that customers value:
Examine customer preferences and buying criteria to make decisions about products, services, value propositions, pricing, brands, and channels. Apply customer surveys, conjoint analysis, willingness-to-pay estimates, experiments, and market simulations to compare alternatives. Use synthetic customer samples to assess how AI-generated responses compare with evidence from actual customers.
Building valuable customer and business relationships:
Assess which customers and relationships the firm should acquire, retain, develop, and invest in, considering customer value, buying processes, relationship dynamics, and long-term profitability. Examine how AI agents are changing buying and customer interactions, including situations where an AI agent (bot) searches, evaluates alternatives, or acts on behalf of a customer or organization.
Evaluating marketing impact and investment choices:
Determine what outcomes marketing actions generate and how scarce resources should be allocated across customers, products, markets, and activities. Evaluate performance using measures such as growth, margin, Customer Lifetime Value/customer equity, retention, brand impact, and return on marketing investments. Responsible decision making is integrated throughout, including data use, privacy, bias, accountability, AI governance, and evolving regulation.
The course combines in-class and online teaching, discussion, case analysis, and hands-on exercises. Participants work with realistic business problems and data, drawing on their professional experience in class discussions and group work. AI is used as an augmentation tool rather than a substitute for managerial reasoning: participants use it to generate, analyze, or challenge possible solutions and then evaluate those outputs using customer and market evidence and managerial judgment.
The syllabus and reading materials may be adapted to the backgrounds, executive roles, and strategic priorities of each cohort.
The course is part of a comprehensive Executive MBA program, and passing examinations in all courses is required to obtain certification.
At BI Executive, both students and course leaders share a responsibility to integrate the students' professional experience into the planning and delivery of the courses, modules, and programs. This means that students are expected to actively engage, contributing their knowledge and practical experience to enrich the learning environment for themselves and their peers.
Software tools:
Executives will use selected AI and analytics tools in course activities. No advanced statistics or programming are required.
Literature and readings:
The course uses a curated compilation of academic articles, managerial readings, cases, and other relevant materials selected by the course instructor. Readings may be updated to reflect current developments in marketing, analytics, AI, and managerial practice.
Granted admission to the EMBA programme. Please consult our student regulations.
Disclaimer
Changes in exam type can be made until the course starts. In addition, unforeseen events or external conditions may call for deviations in teaching and exams.
This course would be suited for managers who have basic skills and knowledge in business administration. No advanced understanding of marketing methods or AI skills is required. The basic understanding of strategic and business administration concepts may facilitate learning.
| Assessments |
|---|
Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: Second Semester Weight: 70 Grouping: Group (2 - 6) Duration: 1 Semester(s) Exam code: GRA xxxxx Grading scale: ECTS Resit: Examination when next scheduled course |
Exam category: Submission Form of assessment: Portfolio Assessment PDF Exam/hand-in semester: Second Semester Weight: 30 Grouping: Individual Duration: 1 Semester(s) Comment: Portfolio assessment, counts 30% of the final grade. The portfolio assessment consists of three short individual exercises/submissions during the course. On the first two submissions, students will receive formative feedback. The third submission is graded. The exercises require executives to apply course concepts and tools to different managerial decisions, interpret customer and market information, and justify recommended actions. Exam code: GRA xxxxx Grading scale: ECTS Resit: Examination when next scheduled course |
All exams must be passed to get a grade in this course.
| Activity | Duration | Comment |
|---|---|---|
Prepare for teaching | 30 Hour(s) | |
Teaching | 32 Hour(s) | |
Student's own work with learning resources | 23 Hour(s) | |
Examination | 25 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 4 ECTS credit corresponds to a workload of at least 110 hours.
An applied project in which executives address a marketing challenge from a real or realistic organization. Teams define the managerial problem, use relevant customer and market information, evaluate alternative courses of action, and develop and justify a clear recommendation. Analytics and AI may be used where they add value, with attention to the quality and validation of resulting insights.