Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesising this “raw” data into chemical information necessitates the use of advanced, statistics-based data analysis techniques. Here we present an example of combining data dimensionality reduction (factorisation) with exploratory classification (clustering) and show that the results complement and broaden our current perspectives on aerosol chemical classification.