Mobility service bundling has received a lot of attention from researchers and practitioners due to its centrality to Mobility as a Service (MaaS) business models and potential to foster sustainable travel behavior. Stated choice studies have to date been used to explore the willingness to pay for MaaS bundles and their components. Despite an increasing number of academic studies and commercial trials, there is a surprising dearth of research on how to design MaaS bundles in the first place. Comparative learning is further limited as the designs of choice experiments and studied bundles differ widely. What are the underlying design dimensions and how can we separate differences in outcome from differences in design? We address this gap by extending the Design of Designs literature to distinguish between two categories of design dimensions for stated choice experiments: statistical and behavioral. We argue that not only statistical design (how many alternatives, attributes and levels) but also behavioral design (i.e., which attributes and levels) influences outcome. Behavioral ‘master designs’ are seldomly made explicit, yet precisely this situation leads to seemingly disjointed landscapes of stated choice studies in specific areas of application, limiting scientific advances, relevant policy-making and commercial realization. We demonstrate the practical value of our conceptual contribution by developing a behavioral master design for MaaS bundles. We show that every MaaS bundle is a permutation along ten design dimensions and every stated choice study is a permutation in a statistical and behavioral master design. Using the resulting grid, researchers can systematically compare studies, identify empirical research gaps and design new experiments accordingly and practitioners can obtain practical guidance for the design of new bundles.