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Within the framework of database marketing, that is, data mining applied to large databases for marketing purposes, we analyze the database of clients of a financial institution, trying to extract from it indications which could help to establish its marketing policies in an efficient way. The application of multiple correspondence and cluster analysis leads to a classification of clients based on a few easily identifiable variables. As suggested by other authors in marketing research, the clients’ position in the life cycle emerges as one of the main factors inducing their financial behaviour.