While the marketing literature has advocated for decades that new products should be designed for intended and anticipated consumer usages, the engineering literature mostly proposes optimization of product performances independent of specific users' skills, anticipated usage scenarios, and competing products on the market. In contrast to tedious market studies which assume an existing market experience for products and optimization approaches based upon static product performances, we propose an adaptable approach to designing a product or product family: the set-based design by usage coverage simulation. It starts with generating a usage scenario space for a set of representative users. Next, considering a candidate set of products, one proceeds to the CSP computations of feasible usage scenarios, assuming that physics-based models of performances are available. The comparison between the expected and feasible usage scenarios at the scale of a single user leads to Usage Coverage Indicators and finally to a preferred product which best covers the usage scenario space. At the level of a targeted consumer group, the approach provides a market share simulation for competing products or members of a scale-based product family. The design of a family of jigsaws thoroughly illustrates our approach.