Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).The “Taguchi Quality Loss Function (TQLF)” methodology has been used primarily to improve quality from a manufacturing standpoint, giving engineers a way to understand how process variation affects customer satisfaction. In the proposed “Taguchi Customer Loss Function (TCLF)” methodology, a similar analogy is applied for developing requirements on the design such that variation in customer preference is accounted for. Also, trade-offs can be made with other business constraints while keeping the customer dissatisfaction to minimum. Example problems are presented to demonstrate its simplicity and its potential for understanding customer clinic data.