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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Li Li & Xiaotong Li & Wenmin Qi & Yue Zhang & Wensheng Yang, 2022. "Targeted reminders of electronic coupons: using predictive analytics to facilitate coupon marketing," Electronic Commerce Research, Springer, vol. 22(2), pages 321-350, June.
    • Handle: RePEc:spr:elcore:v:22:y:2022:i:2:d:10.1007_s10660-020-09405-4
    DOI: 10.1007/s10660-020-09405-4
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