Targeted reminders of electronic coupons: using predictive analytics to facilitate coupon marketing

Li Li, Xiaotong Li (), Wenmin Qi, Yue Zhang and Wensheng Yang
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Li Li: Nanjing University of Science and Technology
Xiaotong Li: University of Alabama in Huntsville
Wenmin Qi: Nanjing University of Science and Technology
Yue Zhang: California State University, Northridge
Wensheng Yang: Nanjing University of Science and Technology

Electronic Commerce Research, 2022, vol. 22, issue 2, No 5, 350 pages

Abstract: Abstract Electronic coupon (e-coupon) is one of the most important marketing tools in B2C e-commerce. To improve the e-coupon redemption rate and reduce marketing costs, it is crucial to retarget customers who have received e-coupons and have higher propensity to redeem their coupons. Using log data and transactional data to extract the features of past purchase behavior, past coupon redemption behavior and browsing behavior during coupon validity period, we investigate the factors influencing customers’ propensity for e-coupon redemption. Our results show that almost all the variables used in our analysis (except the visit time) affect consumers’ coupon redemption propensity. Our study can help companies develop promotional strategies that better retarget those customers who are more likely to respond to coupon marketing. It also highlights the potential of using predictive analytics to enhance marketing effectiveness in the era of big data.

Keywords: Coupon marketing; e-Coupon; Predictive analytics; Targeted reminders (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10660-020-09405-4

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