IMPROVING SHOPPING MALL REVENUE BY REAL TIME CUSTOMIZED DIGITAL COUPON ISSUANCE

Abstract

In the modern retail environment, shopping malls face growing competition from e-commerce platforms, making it essential to adopt innovative strategies to attract and retain customers. Traditional coupon distribution methods are static and lack personalization, often resulting in low redemption rates and limited impact on sales. To address this challenge, this project proposes a real-time customized digital coupon issuance system designed to enhance customer engagement and boost mall revenue. The proposed system leverages customer data such as purchase history, location within the mall, visit frequency, and preferences to generate personalized digital coupons instantly. Using technologies like Internet of Things (IoT) sensors, mobile applications, and data analytics, the system detects customer presence in real time and issues relevant offers directly to their smartphones. Machine learning algorithms analyze customer behavior to predict interests and deliver targeted discounts that are more likely to convert into sales. This intelligent and data-driven approach increases coupon utilization, improves customer satisfaction, and helps retailers optimize marketing efforts. Experimental results and simulations indicate that real-time, customized coupon issuance can significantly increase footfall, encourage repeat visits, and ultimately maximize overall mall revenue while reducing marketing waste