Affective Chatbot Communication in Creative Industries

How to ensure Digital Empathy 

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: 

  • The first phase is dedicated to the perspective of management practice and shows the relevance of emotional company-customer contact in general and the digital user experience in particular and gives an overview of the empathic options for action of companies in the context of conversational commerce, performance marketing, and user experience design. 
  • In the second phase, the research perspective will be taken up by conducting own studies on affective chatbot communication based on current findings from emotion and brain research as well as on UX design.  
  • The third phase transfers the findings of the own studies into business practice and creates an application-oriented user guide for the (own) use of Affective Chatbot Communication and its optimization. 

Project responsibility: Prof. Dr. Katharina Klug