In many industrial sectors, the current digitalization trend resulted in new products and services that exploit the potential of built-in sensors, actuators, and control systems. The business models related to these products and services usually are data-driven and integrated into digital ecosystems. Quantified products (QP) are a new product category that exploits data of individual product instances and fleets of instances. A quantified product is a product whose instances collect data about themselves that can be measured or, by design, leave traces of data. The QP design has to consider what dependencies exist between the actual product, services related to the product, and the digital ecosystem of the services. By investigating three industrial case studies, the paper contributes to a better understanding of typical features of QP and the implications of these features for the design of products and services. For this purpose, we combine the analysis of features of QP potentially affecting design with an analysis of dependencies between features. The main contributions of the work are (1) three case studies describing QP design and development, (2) a set of recurring features of QPs derived from the cases, and (3) a feature model capturing design dependencies of these features.