IMPROVING SHOPPING MALL REVENUE BY REAL TIME CUSTOMIZED DIGITAL COUPON ISSUANCE

Abstract

With the development of big data and deep learning technology, big data and deep learning
technology have also been applied to the marketing field, which was a part of business administration. Customer
churn management is one of the most important areas of marketing. In this paper, we proposed a method to
prevent customer churn and increase purchase conversion rate by issuing customized discount coupons to
customers with high churn rate based on big data in real time. After segmenting customer segments with twodimensional
segment analysis, a real-time churn rate estimation model based on clickstream data was generated
for each segment. After that, we issued customized coupons to our customers. Finally, we tested the conversion
rate and sales growth. A two-dimensional cluster analysis-based churn rate estimation combined with a
recommendation system was found to be significantly more useful than the respective simple models. Using this
proposed model, it is possible to increase sales by automatically estimating the customer’s churn probability and
shopping propensity without the burden of marketing costs in the online shopping mall.