The dataset of customers consisted of approximate 5 million transactions, 600,000 receipts and 10,000 customer cardholders. Data mining techniques were used to build advanced mathematical models for predicting customer behaviors based on Class Association Rules developed in-house using SCALA/ MongoDB and R.