  Finding a suited software solution for a company poses a resource-intensive
task in an ever-widening market. Software should solve the technical task at
hand as perfectly as possible and, at the same time, match the company
strategy. Based on these two dimensions, domain knowledge and industry context,
we propose a methodology for deriving individually tailored evaluation criteria
for software solutions to make them assessable. The approach is formalized as a
three-layer model, that ensures the encoding of said dimensions, where each
layer holds a more refined and individualized criteria list, starting from a
general softwareagnostic catalogue we composed. Finally, we exemplarily
demonstrate our method for Machine-Learning-as-a-Service platforms (MaaS) for
small and medium-sized enterprises (SME).
