In this preliminary work, we present an approach for the augmentation of clustering with natural language explanations. In clustering there are 2 main challenges: a) choice of a proper, reasonable number of clusters, and b) cluster analysis and profiling. There is a plethora of technics for a) but not so much for b), which is in general a laborious task of explaining obtained clusters. We propose a method that aids experts in cluster analysis by providing an iterative, human-in-the-loop methodology of generating cluster explanations. In an illustrative example, we show how the process of clustering on a set of objective variables could be facilitated with textual metadata. In our case, images of products from online fashion store are used for clustering. Then, product descriptions are used for profiling clusters. © 2022 Copyright for this paper by its authors.