Improving Shopping Mall Revenue by Real-Time Customized Digital Coupon Issuance

被引:2
|
作者
Seo, Daeho [1 ]
Yoo, Yongmin [2 ]
机构
[1] Yonsei Univ, Grad Sch Informat, Seoul 03722, South Korea
[2] NHN Diquest, AI Res & Dev Team, AI Res & Dev Grp, Seoul 08390, South Korea
关键词
Customer churn prediction; deep learning; digital marketing; ecommerce; recommendation system; MARKET-SEGMENTATION; CHURN PREDICTION; RECOMMENDATION;
D O I
10.1109/ACCESS.2023.3239425
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:7924 / 7932
页数:9
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