Herbal preparations represent very complex mixtures, potentially containing multiple pharmacologically active entities. Methods for global characterization of the composition of such mixtures are therefore of pertinent interest. In this work, chemometric analysis of high-performance liquid chromatography with photodiode-array detection (HPLC-PDA) data from extracts of commercial preparations of Hypericum perforatum (St. John's wort) that originate from several continents is described. The spectral HPLC profiles were aligned in the elution mode using correlation optimized warping in order to remove peak misalignment caused by retention time shifts due to matrix effects. Furthermore, the warping was assisted by HPLC-PDA-SPE-NMR-MS (SPE = solid-phase extraction) experiments that yielded 1H NMR and 13C NMR data (from 1H-detected heteronuclear correlations), as well as ESI-MS and HRMS data, which enabled the identification of all major mixture constituents. The preprocessed HPLC-PDA data were subjected to parallel factor analysis (PARAFAC), a chemometric method that is a generalization of principal component analysis (PCA) to multi-way data arrays. PCA of the peak areas obtained from the PARAFAC analysis was used to facilitate sample comparison and allowed straightforward interpretation of constituents responsible for the differences in composition between individual preparations. In addition, loadings from the PARAFAC analysis provided pure elution profiles and pure UV spectra even for coeluting peaks, thus enabling the identification of chromatographically unresolved components. In conclusion, PARAFAC analysis of the readily accessible HPLC-PDA data provides the means for unsupervised and unbiased assessment of the composition of herbal preparations, of interest for assessment of their pharmacological activity and clinical efficacy.