With yearly over 100’000 inquiries, the MFK BL is facing a significant problem. The enterprise has an internal requirement, which states that the current workload and direct customer contact must be reduced. Rising workloads due to the increased vehicle population in the canton of Basel-Landschaft and other demographic reasons demand the reallocation of its internal resources to other more critical tasks. To ensure high quality and a great 24/7 customer experience throughout the first inquiry, a chatbot solution needs to be implemented.

To address the problem areas as precisely as possible, a qualitative interview approach is chosen. An as-is analysis will be created with the purpose to give the reader enough information about the current situation on how customer-facing tasks are handled. The answers gathered in the interviews will help to showcase the possible areas of application of the future chatbot. Furthermore, an evaluation of the different answers should provide enough insight to create user stories, which later on will help to create conversational designs.

1.) Different types of chatbots have been explained according to literature review/research. 2.) According to qualitative interviews, standardized and repeated customer-facing tasks have been specified. The outcome is a department-based list of inquiries, which can be moved to a chatbot. The enterprise can use this list to design chatbot scenarios in the future. 3.) Clear use cases have been established regarding what a chatbot is capable of and what it cannot handle. The use cases have been prepared with user stories where fictive characters simulate their needs. 4.) Conversational designs of three specific inquiries of each department have been created to see how the chatbot would handle the conversation. The scenarios were the following: • One fallback scenario. • One scenario where human help is needed. • One happy scenario where the chatbot could solve the problem. The enterprise can benefit from the paper by having a better understanding of the whole technology as well as possible conversational design for future real-case scenarios.