An important management technology for trading business development is category management, focused on identifying groups of related or replacement products, based on consumer preferences analysis. Traditional method, including a survey of customers at the supermarket exit, is expensive and not very reliable due to the coverage of only relatively small groups. An alternative approach is the analysis of cash checks, which are essentially digital traces of purchases made while visiting a hypermarket. For identifying groups of related products, it is proposed to apply methods of hierarchical cluster analysis with the use of binary similarity measures, results of experiments on real data are presented, effectiveness of the Jacquard and χ2 measures are compared, methods for optimizing the number of clusters are analyzed.
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