Check-all-that-apply (CATA) questionnaires have seen a widespread use recently. In this paper, we briefly review some of the existing approaches to analyze data obtained from such a study. Proposed extensions to these methods include a generalization of Cochran’s Q to test for product differences across all attributes, and a more informative penalty analysis. Multidimensional alignment (MDA) is suggested as a useful tool to investigate the association between products and the attributes. Comparisons of real products with an ideal are useful in identifying specific improvements for individual products. Penalty and penalty-lift analyses are used to identify (positive and negative) drivers of liking. The methods are illustrated by means of CATA study on whole grain breads.