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

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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.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China under Grant Nos. 71771122, # 71271115.

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Authors and Affiliations

  1. School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China

    Li Li, Wenmin Qi & Wensheng Yang

  2. College of Business, University of Alabama in Huntsville, Huntsville, AL, 35899, USA

    Xiaotong Li

  3. California State University, Northridge, 18111 Nordhoff Street, Northridge, CA, 91330-8372, USA

    Yue Zhang

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Li, L., Li, X., Qi, W. et al. Targeted reminders of electronic coupons: using predictive analytics to facilitate coupon marketing. Electron Commer Res 22, 321–350 (2022). https://doi.org/10.1007/s10660-020-09405-4

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