Mobility as a service (MaaS) is gaining interest around the world because it offers integrated services including searching, booking and payment across modes. This study introduces MaaS and deliberates on the framework, components, and design of bundles. Key findings from literature are presented from studies that were conducted to understand customer preferences for MaaS. A case study using stated preference data collected to understand customer preferences for MaaS in Queensland is discussed. An extensive hypothesis testing and statistical analysis are presented to obtain inferences regarding customer preferences and provide important insights which could potentially help in the design of attractive MaaS plans and thereby improve uptake. The extensive hypothesis testing involves optimization and advanced econometrics to extract as much insights from the data as possible. This enable the simultaneous consideration of multiple behavioral aspects such as latent classes, nonlinearities and correlations across important factors.