  Recently, economic depression, which scoured all over the world, affects
business organizations and banking sectors. Such economic pose causes a severe
attrition for banks and customer retention becomes impossible. Accordingly,
marketing managers are in need to increase marketing campaigns, whereas
organizations evade both expenses and business expansion. In order to solve
such riddle, data mining techniques is used as an uttermost factor in data
analysis, data summarizations, hidden pattern discovery, and data
interpretation. In this paper, rough set theory and decision tree mining
techniques have been implemented, using a real marketing data obtained from
Portuguese marketing campaign related to bank deposit subscription [Moro et
al., 2011]. The paper aims to improve the efficiency of the marketing campaigns
and helping the decision makers by reducing the number of features, that
describes the dataset and spotting on the most significant ones, and predict
the deposit customer retention criteria based on potential predictive rules.
