A Cloud service can be classified by many different factors that represent its overall performance and features. An example of a classification of such factors is provided by the Service Measurement Index (SMI) . The SMI framework summarizes the most important QoS attributes for Cloud offerings on a high level, such like Accountability, Agility, and Assurance of service, Cost, Performance, Security, Privacy and Usability. SMI is used, among others, by the STRATOS framework , that focuses on provider selection based on these attributes. The actual decision process is complicated by a large number of factors and parameters defined on different levels, essentially resulting into a Multiple Criteria Decision Making (MCDM) problem . Because of the structured relationship between factors and parameters an Analytic Hierarchy Process (AHP) is a proposed approach for facilitating the problem of MCDM. A number of existing works use AHP to support the decision in selecting an appropriate Cloud service provider for a given set of requirements. In the SMICloud approach for example , AHP is used to compare parameters of different providers based on a value-based ranking method optimizing on cost for VM-oriented Cloud offerings. For the selection and combination of solutions, CloudGenius constructs a formal model to describe requirements, nonnumerical and numerical attributes. In both cases however, applying AHP requires a signifcant amount of user input in order to prioritize the different requirements. In the case of MDSS we opted to offer the simpler but easier to use ranking of candidate offerings instead.