When an exploratory data analysis is performed where there are more than two qualitative variables, the application of univariate, bivariate and multivariate statistical techniques allows to successfully describe the data table. Particularly, the single correspondence technique gives important correlation and dimensionality reduction results, which help to give an objective interpretation of the data. In this paper we use the technique known as factor analysis of multiple correspondences which is a generalization of the single correspondence technique used to corroborate results. We also use log-linear adjustment, with the purpose of continuing with the Principal Components and Cluster Analyses [An?lisis Factorial de Correspondencias Simples en el procesamiento de datos cualitativos sobre funcionalidad en comercio electr?nico]. The binary variables under study are the result of the e-commerce sites' evaluation process for the quality attributes of the "Functionality" feature [Requerimientos de Calidad en Sitios de E-commerce, T?cnicas Estad?sticas para el An?lisis de la Calidad de Sitios Web]. This data is concentrated in a binary table of 49 sites and 17 attributes [An?lisis Factorial de Correspondencias Simples en el procesamiento de datos cualitativos sobre funcionalidad en comercio electr?nico, Requerimientos de Calidad en Sitios de E-commerce].