Targeting and personalization are highly significant in (digital) marketing. While “hard customer factors” – i.e. how customers behave digitally – can already be quickly captured and analyzed today, reliable data on the increasingly important “softer factors” such as emotions are lacking. However, these often provide information about the “why”, i.e. the reasons users have for their (purchase) decision. Affective Computing aims at automated, real-time-based measurement and recognition of emotions by sensors and learning algorithms in order to enable adapted reactions. Affective computing is regarded as a necessary condition for empathically designing human-computer interactions, such as conversational interfaces or virtual personal assistants (chatbots), with the overriding goal of enriching artificial intelligence with emotional intelligence.
The aim of the project is to demonstrate the methods of modern emotion capture and to “apply” them in the context of current use cases and user scenarios, especially in connection with Chatbot Communication. The latest findings from brain and emotion research will be included as well as aspects of digital (performance) marketing and user experience (UX) design. Based on numerous studies, concrete action implications for feasibility and scalability are given and exemplary areas of application in various industries, product categories and scenarios are worked out. The project is divided into three phases:
Project responsibility: Prof. Dr. Katharina Klug