Designers exert substantial effort to define an intended user experience (UX) for a product, service or system. However, discontinuities can arise when the actual UX of users differs from the design intent. This paper presents a `Semantic Discontinuity Detection' (SDD) method capable of locating discontinuities between (i) realized product semantics, based on users' initial visual impression of a product, and (ii) intended product semantics, based on the originating designer's visual product expression. The experimental design includes a new technique termed 'Semantic Network Clustering' (SNC) to organize diverse product appraisal lexicon. Data generated by the method provides evidence to assist re-designing for reduced semantic discontinuity. The method is suggested to be suitably agile for a wide range of UX intent-realization research. (C) 2019 Elsevier Ltd. All rights reserved.