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Multiplex networks arise when there exists more than one source of relationships for a common set of nodes. For such data, the usual approaches consist of dealing with each relationship separately or of merging the information in a unique network. In the present contribution, we propose using factorial methods to visually explore the complex structure in multiplex networks. Specifically, the derived adjacency matrices from one-mode multiplex networks are analyzed using the DISTATIS technique, an extension of multidimensional scaling to three-way data. This technique allows the representation of the different types of relationships in separate spaces for each layer and in a compromise space. How the analytic procedure works is illustrated using a real-world example.