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 two-dimensional 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.