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Business analytics: online promotion with gift rewards

Author

Listed:
  • Huan Yu

    (University of Science and Technology of China)

  • Ye Shi

    (University of Science and Technology of China)

  • Yugang Yu

    (University of Science and Technology of China)

  • Jie Liu

    (University of Science and Technology of China)

  • Feng Yang

    (University of Science and Technology of China)

  • Jie Wu

    (University of Science and Technology of China)

Abstract

This study analytically examines online promotions with gift rewards based on data from a Chinese tea retailer, Huiliu. Gift rewards benefit Huiliu by improving promotional performance. However, they generate operational problems, especially by increasing the costs of holding gift inventory. To address Huiliu’s concerns about gift rewards, we first conduct an empirical study based on Huiliu’s promotional data to examine the effect of gift rewards on customer purchase behavior. The empirical result suggests that gift rewards induce more repeat customer purchases; however, they do not induce customers to spend more money. This empirical result reveals that the effect of gift rewards on customer purchase behavior leads to Huiliu’s intensifying gift inventory pressure. Based on this empirical finding, we develop a theoretical model that addresses gift inventory management. Because of the difficulty of precisely estimating the distributions of some key random variables (e.g., customer demands), we employ a robust approach to solve this model and provide near-optimal robust solutions. We finally present a case study to illustrate how to improve Huiliu’s gift allocation based on the robust inventory solutions. The numerical results show that the improved gift allocation significantly increases Huiliu’s profits (the average profit increment is 3.58%).

Suggested Citation

  • Huan Yu & Ye Shi & Yugang Yu & Jie Liu & Feng Yang & Jie Wu, 2020. "Business analytics: online promotion with gift rewards," Annals of Operations Research, Springer, vol. 291(1), pages 1061-1076, August.
  • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03193-3
    DOI: 10.1007/s10479-019-03193-3
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    References listed on IDEAS

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    1. V. Kumar & Rajkumar Venkatesan & Tim Bohling & Denise Beckmann, 2008. "—The Power of CLV: Managing Customer Lifetime Value at IBM," Marketing Science, INFORMS, vol. 27(4), pages 585-599, 07-08.
    2. Berger, Paul D. & Bechwati, Nada Nasr, 2001. "The allocation of promotion budget to maximize customer equity," Omega, Elsevier, vol. 29(1), pages 49-61, February.
    3. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    4. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    5. Tat Y. Chan & Chunhua Wu & Ying Xie, 2011. "Measuring the Lifetime Value of Customers Acquired from Google Search Advertising," Marketing Science, INFORMS, vol. 30(5), pages 837-850, September.
    6. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    7. S Delanote & R Leus & F Talla Nobibon, 2013. "Optimization of the annual planning of targeted offers in direct marketing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1770-1779, December.
    8. Mauricio M. Palmeira & Joydeep Srivastava, 2013. "Free Offer ≠ Cheap Product: A Selective Accessibility Account on the Valuation of Free Offers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(4), pages 644-656.
    9. Jinfeng Yue & Bintong Chen & Min-Chiang Wang, 2006. "Expected Value of Distribution Information for the Newsvendor Problem," Operations Research, INFORMS, vol. 54(6), pages 1128-1136, December.
    10. Sharad Borle & Siddharth S. Singh & Dipak C. Jain, 2008. "Customer Lifetime Value Measurement," Management Science, INFORMS, vol. 54(1), pages 100-112, January.
    11. Praveen K. Kopalle & Yacheng Sun & Scott A. Neslin & Baohong Sun & Vanitha Swaminathan, 2012. "The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs," Marketing Science, INFORMS, vol. 31(2), pages 216-235, March.
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