Digital technologies have profoundly changed the way and pace of companies interacting with their customers and innovating their products. For instance, today's marketers and researchers are faced with an enormous amount and variety of data that consumers share online - from product feedback via text messages and reviews, to images and videos posted by branded experiences on social media. At the same time, companies also strive to interact with their customers on various social media channels by producing compelling and relevant multimedia content for their target audiences, and to incorporate customer feedback and needs in their product development.

This course intends to provide the theoretical foundations behind state-of-the art marketing and innovation in the digital economy to address these challenges in digital management practice. In particular, our course will cover the following modules:

- Marketing strategy implications of moving from the traditional to the digital economy

- Social network theory, targeting, and social influence

- Digital customer-brand relationships, user-generated content and mechanisms behind virality of digital content

- Social monitoring, social listening, and metrics to measure success on social media

- Personalization in mobile marketing, online reviews, and chatbot interactions

- Customers as co-producers, feedback validation loops, and the minimum viable product

- Handling unstructured data, machine learning and predictive analyses

The course will be based on marketing/management articles in leading academic journals, case studies and several guest lectures from marketing and innovation practice.

After completing the course, you will have gained proficiency in analyzing customer decision making and relevant trends in marketing and innovation. This course also intends to develop in-depth knowledge for the assessment of opportunities and threats and for making well-grounded predictions of market outcomes.

Specifically, students will be able to:

1. Analyze and apply processes and techniques for generating and communicating innovative ideas;

2. Understand concepts behind social media interactions, social networks and network related phenomena, and how these can impact customer behavior;

3. Identify and differentiate between different ways to utilize consumer interactions, and their potential and limitations;

4. Understand and discuss based on strategic choices from empirical findings how social media interactions can be effectively mined for value;

5. Critically analyze and interpret media messages, critique current trends, and produce new solutions for effective innovation marketing;

6. Evaluate innovations based on their potential for monetization (feasibility, marketability, desirability) and select appropriate courses of action.

Participation in all sessions is mandatory.

You may miss up to max. 20% of class hours, but please note that content is build-up in a modular way. Thus absences should be minimized to ensure your optimal learning outcomes. According to WU rules, you have to attend 80% of the sessions in this course.

Under exceptional circumstances, you may be permitted by the instruction team to join an individual class in another section instead of your own. However all assessment items must be completed within your own section. 

· Self-study (reading of scientific articles, case studies, and own researches of articles to prepare group project case study)

· Lectures and in-class discussions

· Team presentation of group project

Weights for each grading component used to compute your final grade:

- Case presentations: 50%

- Bi-weekly assignments related to mandatory reading: 40%

- Video watching and peer review participation: 10%

The quizzes and in-class participation is graded at the individual level, while the group project work is graded at the group level.

We also want to ensure equal contribution of group members to the group work. Thus, a peer assessment will be conducted among group members, which enters into the computation of the individual grades for your group work. This means that the members of a group are required to assess other students regarding their relative contribution.

No specific analytical skills and software knowledge required.

No specific analytical skills and software knowledge required.