DRIVING SHOPPING MALL REVENUE GROWTH WITH PERSONALIZED REAL-TIME DIGITAL COUPON ISSUANCE

Abstract

The marketing department has long been seen as an outgrowth of the accounting department. The marketing industry shifted to make use of new technologies like big data and deep learning. Monitoring customer churn is an essential part of any marketing strategy. This research details a data-driven, real-time system that employs personalized discount coupons to increase spending and engagement from returning customers. In order to classify the customers, we employed two-dimensional segmentation. Live estimates of each group's attrition rate were obtained using click stream data. The next step was to provide each customer a unique voucher. Lastly, we examined the increase in sales and the rate of conversion. When combined with a two-dimensional cluster analysis churn rate estimate, a suggestion system outperformed the basic models by a significant margin. By adopting this method, online malls can automatically determine a customer's likelihood of leaving and the items they purchase, which can boost revenue.