Customer feedback analysis provides insights into customer satisfaction and helps improve the quality of services and products. The major issue of concern in analyzing customer feedback is the ability to identify their implicit requirements. While the literature revealed that multidimensional scaling (MDS) has been extensively utilized to summarize qualitative data in order to help identify general structures of dataset, researchers are often tempted to represent scatters in two dimensions. Such reduction in dimensionality may hide new requirements or cause them to falsely merge with others. This research proposes a new framework for performing MDS with the objective of discovering new requirements. The framework builds on the advantages of the MDS procedures and can be utilized to validate known requirements. Research efforts resulted in the development of a special algorithm, using MATLAB, to support applications of the new framework. An illustrative application is used to demonstrate the steps involved and highlights the ability of the framework to discover emerging requirements. It is hoped that the new framework would help product and process designers as well as quality practitioners gain a better understanding of customer requirements and attend to their needs.