A domain-specific modeling language for customer journeys in digital data ecosystems

Digital ecosystems considerably shape customer journeys, linking diverse actors like customers, providers, and third parties in complex value co-creation interactions. Digital data ecosystems, such as data spaces, enable actors to exchange data to co-create superior value-in-use for each other. While customers face an unprecedented number of potential providers and intermediaries to interact with, touchpoints also multiply, comprising analog and digital channels. Digital data ecosystems’ complexity not only makes modeling customer journeys increasingly challenging but also indicates that current modeling languages are not fully able to represent customer journeys at an ecosystem level. Thus, we design the Data Ecosystem Customer Journey Language (DECJL), a domain-specific modeling language that enables representing, analyzing, and designing customer journeys in digital data ecosystems. The DECJL is designed based on combining and extending constructs from related modeling languages and adding constructs that specifically represent a digital data ecosystem perspective. We present a meta-model, graphical notation, and sample models substantiating our modeling language. Finally, we evaluate the DECJL through a three-phase approach that integrates conceptual, ontology-based theoretical, and empirical steps to holistically assess both the theoretical robustness and practical applicability of our modeling language. We contribute a tool for strategic analysis and design of modern customer journeys.