Multivariate analysis was used for interpreting data from a pot experiment using samples of three Spanish soils. Samples of soil fertilized with compost were compared with untreated control samples. We also compared the effect of adding the compost to soil with a controlled moisture content of 50% of its water holding capacity (WHC), and to a near-saturated soil (95% WHC). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used; they perfectly differentiated sample groups both as a function of the treatment applied and by sampling date. The compost samples were characterized by higher pH, electrical conductivity (EC), organic matter (OM) content and cation exchange capacity (CEC), together with nutrient concentrations than the control pots. The pots with a soil-compost mixture at 95% WHC presented lower values of EC, CEC, inorganic N, K, Na and B than the mixtures at 50% WHC. Multivariate methods may therefore be useful for the analysis and interpretation of a large number of data in soil research.