The number of sellers and goods being sold on the e-marketplaces is growing, so the volume of data stored and processed by e-commerce information systems is increasing drastically. That is why the development of performance solutions is quite relevant. The given paper provides the approach of item matching based on the human perception of item images. The main goal of the study is to build a model for assessing the similarity of items. This paper provides a description of a software product for comparing product images collected on online trading platforms. The user evaluates the product visually. The developed software implements the crowdsourcing data collecting based on the comparator identification method. The use of this method involves an experiment in which the user is offered two images, by comparing which the determined binary reaction is obtained. The results show the perspective of the mobile client application as part of an item matching system that aims to optimize the search for products on the Internet.