Analytics-based services (ABS) apply analytical methods to data in order to enable customers to make better decisions and solve more complex problems. While it is widely acknowledged that ABS pave the way for new value creation opportunities, surprisingly little is known about their systematic design. Service design teams still struggle to create ABS solutions systematically, i.e. to define what is to be done, how this is going to be achieved and how decisions are taken during ABS design projects. In this research, we report on the first iteration of our design science research project which aims to build design knowledge on methodological tools that can support service design teams in this particular context. We derive and evaluate four meta-requirements and four design principles – thus contributing to a more profound design knowledge base that can support researchers in developing new methodological tools in the field of ABS in the future.