The cloud paradigm fundamentally changes the way software is developed, deployed, and priced. For cloud providers, this shift demands well-defined services with clearly specified features, delivery methods, and pricing models. Yet, traditional requirements engineering methods, which rely on close interactions with users, are difficult to apply for mass-market cloud services. Therefore, market research techniques can effectively support the design of high-utility cloud services through the incorporation of user preference measurements. For instance, conjoint analysis (CA), a widely used consumer research technique, allows for the estimation of user utilities, market segmentation, and analysis of willingness to pay. In this article, we present a method component that extends existing requirements elicitation techniques for cloud services through CA. We document this method component through a meta-model and procedure and demonstrate its application in a study on secure cloud storage services. Additionally, we evaluate its feasibility, usefulness, and ease of use of method component with experts. This research advances cloud product management by adapting and refining CA techniques for the specific context of cloud services.