This case requires to develop a customer segmentation to define marketing strategy. The sample Dataset summarizes the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral variables. Following is the Data Dictionary for Credit Card dataset :- **CUST_ID** : Identification of Credit Card holder (Categorical) **BALANCE** : Balance amount left in their account to make purchases ( **BALANCE_FREQUENCY** : How frequently the Balance is updated, score between 0 and 1 (1 = frequently updated, 0 = not frequently updated) **PURCHASES** : Amount of purchases made from account **ONEOFF_PURCHASES** : Maximum purchase amount done in one-go **INSTALLMENTS_PURCHASES** : Amount of purchase done in installment **CASH_ADVANCE** : Cash in advance given by the user **PURCHASES_FREQUENCY** : How frequently the Purchases are being made, score between 0 and 1 (1 = frequently purchased, 0 = not frequently purchased) **ONEOFFPURCHASESFREQUENCY** : How frequently Purchases are happening in one-go (1 = frequently purchased, 0 = not frequently purchased) **PURCHASESINSTALLMENTSFREQUENCY** : How frequently purchases in installments are being done (1 = frequently done, 0 = not frequently done) **CASHADVANCEFREQUENCY** : How frequently the cash in advance being paid **CASHADVANCETRX** : Number of Transactions made with "Cash in Advanced" **PURCHASES_TRX** : Numbe of purchase transactions made **CREDIT_LIMIT** : Limit of Credit Card for user **PAYMENTS** : Amount of Payment done by user **MINIMUM_PAYMENTS** : Minimum amount of payments made by user **PRCFULLPAYMENT** : Percent of full payment paid by user **TENURE** : Tenure of credit card service for user