first cycle, Master
Digital Marketing (E)
Niveau
Learning outcomes of the courses/module
The participants:
• understand what customer experience means and why it is central to digital marketing.
• recognize that the customer experience includes all touchpoints along the customer journey—from initial contact to purchase and beyond.
• can identify the most important digital touchpoints (e.g., social media, website, email, search engines) and explain their importance for a positive customer experience.
• are familiar with the key instruments of the online marketing mix (including SEO, SEA, social media, email marketing, content marketing, performance marketing).
• understand the respective advantages, opportunities, and possible applications of these tools.
• learn how to adapt the selection and combination of tools to corporate goals, target groups, and budgets.
• understand how a marketing strategy works as a long-term, goal-oriented plan and what role market analysis, target group understanding, positioning, and value proposition play.
• can explain the difference between strategy, plan, and tactics and know how individual measures are embedded in a holistic strategy.
• gain insight into the development and implementation of marketing strategies, especially in the digital environment.
• understand the basics of artificial intelligence and its potential applications in marketing, e.g., in data analysis, personalization, automation, and trend forecasting.
• recognize the opportunities AI offers for more efficient marketing processes, better customer centricity, and optimized budgets.
• gain an overview of current examples and trends in AI-supported marketing.
• understand what customer experience means and why it is central to digital marketing.
• recognize that the customer experience includes all touchpoints along the customer journey—from initial contact to purchase and beyond.
• can identify the most important digital touchpoints (e.g., social media, website, email, search engines) and explain their importance for a positive customer experience.
• are familiar with the key instruments of the online marketing mix (including SEO, SEA, social media, email marketing, content marketing, performance marketing).
• understand the respective advantages, opportunities, and possible applications of these tools.
• learn how to adapt the selection and combination of tools to corporate goals, target groups, and budgets.
• understand how a marketing strategy works as a long-term, goal-oriented plan and what role market analysis, target group understanding, positioning, and value proposition play.
• can explain the difference between strategy, plan, and tactics and know how individual measures are embedded in a holistic strategy.
• gain insight into the development and implementation of marketing strategies, especially in the digital environment.
• understand the basics of artificial intelligence and its potential applications in marketing, e.g., in data analysis, personalization, automation, and trend forecasting.
• recognize the opportunities AI offers for more efficient marketing processes, better customer centricity, and optimized budgets.
• gain an overview of current examples and trends in AI-supported marketing.
Prerequisites for the course
not applicable
Course content
The course presents:
- An overview of the digital marketing tools currently in use
- The framework conditions when using digital marketing
- The special challenges regarding interaction and fast pace in digital marketing
Based on case studies, current best practice digital marketing campaigns are discussed, and own marketing concepts are designed.
- An overview of the digital marketing tools currently in use
- The framework conditions when using digital marketing
- The special challenges regarding interaction and fast pace in digital marketing
Based on case studies, current best practice digital marketing campaigns are discussed, and own marketing concepts are designed.
Recommended specialist literature
Chaffey, D. & Ellis-Chadwick, F. (2022): Digital Marketing: Strategy, Implementation and Practice. 8th Edition. Pearson Education Limited.
Hemachandran, K., Choudhury, D., Rodriguez, R.V., Wise, J.A., & T, R. (2024): Predictive Analytics and Generative AI for Data-Driven Marketing Strategies. 1st Edition. Chapman and Hall/CRC.
Kingsnorth, S. (2022): Digital Marketing Strategy: An Integrated Approach to Online Marketing. 3rd Edition. Kogan Page.
Kotler, P.; Armstrong, G.; Harris, L. C. & Piercy, N. (2016): Principles of Marketing. 7th European Edition. Pearson Education Limited.
Krug, Steve (2013): Don’t Make Me Think: A Common Sense Approach to Web Usability. 3rd Edition. New Riders.
Pulizzi, J. (2013): Epic Content Marketing. McGraw-Hill.
Provost, F. & Fawcett, T. (2013): Data Science for Business. O’Reilly Media.
Roetzer, P. (2022): Marketing Artificial Intelligence: AI, Marketing, and the Future of Business. BenBella Books.
Tavsan, N. & Erdem, C. (2018): Customer Experience Management: How to Design, Integrate, Measure and Lead. Tasora Books.
Venkatesan, R. & Lecinski, J. (2021): The AI Marketing Canvas: A Five-Stage Road Map to Implementing AI in Marketing. Wiley.
Hemachandran, K., Choudhury, D., Rodriguez, R.V., Wise, J.A., & T, R. (2024): Predictive Analytics and Generative AI for Data-Driven Marketing Strategies. 1st Edition. Chapman and Hall/CRC.
Kingsnorth, S. (2022): Digital Marketing Strategy: An Integrated Approach to Online Marketing. 3rd Edition. Kogan Page.
Kotler, P.; Armstrong, G.; Harris, L. C. & Piercy, N. (2016): Principles of Marketing. 7th European Edition. Pearson Education Limited.
Krug, Steve (2013): Don’t Make Me Think: A Common Sense Approach to Web Usability. 3rd Edition. New Riders.
Pulizzi, J. (2013): Epic Content Marketing. McGraw-Hill.
Provost, F. & Fawcett, T. (2013): Data Science for Business. O’Reilly Media.
Roetzer, P. (2022): Marketing Artificial Intelligence: AI, Marketing, and the Future of Business. BenBella Books.
Tavsan, N. & Erdem, C. (2018): Customer Experience Management: How to Design, Integrate, Measure and Lead. Tasora Books.
Venkatesan, R. & Lecinski, J. (2021): The AI Marketing Canvas: A Five-Stage Road Map to Implementing AI in Marketing. Wiley.
Assessment methods and criteria
Portfolio exam
Language
English
Number of ECTS credits awarded
3
Semester hours per week
Planned teaching and learning method
integrated course
Semester/trimester in which the course/module is offered
3