Big Data Analysis To Enhance The Effectiveness Of Bank Xyz Credit Card Promotion
Credit cards as a payment card are products issued by banks and become favorite customers choice to pay multiple transactions offline and online. Many promotion programs are done by banks to raise card issuances for a new customer and to attract card usage for current credit card holders. Bank XYZ, as one of credit card issuer in Indonesia, is intensively offering promotions to its customer to use their credit cards through communication media such as SMS blast and email notifications. Media content may affect customer decision to purchase in any merchant using Bank XYZ credit card. By utilizing Big Data analysis with Recency, Frequency and Monetary(RFM), and Association Rules, Bank XYZ may send credit card promotional content fit with a customer profile. Clustering customer loyalty based on their transaction history using RFM analysis divide customer in two category, low and high loyalty. Combining customer loyalty with sex and merchant city generates numerous association rules. Association rules describe transaction pattern consist of antecedent and consequent. Acknowledge what is the next transaction give Bank XYZ opportunity to promote its promotional content. Sending proper promotional content fit with a customer profile will raise customer spending using their credit cards. Transactions are rising to contribute to Bank XYZ revenue.
Keywords - Big Data, RFM, Association Rules, Credit Card Promotional Content, Targeted Marketing.