Multiple-response questions are a common feature of survey-based research, as its advantages of information collection are well known. Statistical analysis of the responses, however, tends to be either one or two-dimensional, with the restrictions that this entails. This paper presents a multidimensional analysis protocol that provides the researcher with tools to identify more and better profiles about 'who says what'. The strategy begins by coding the response options as a set of metric binary variables. The ideal methodological duo for the exploration of the resulting data is Principal Component Analysis coupled with an Ascending Hierarchical Cluster Analysis, incorporating, in addition, supplementary variables. When applied to the analysis of three different multiple-response questions included in a Spanish National Survey, this proposal provides evidence not only of the interpretation potential of the coding/analysis protocol but also of the limitations of some multiple-response question formats.