Business analytics: online promotion with gift rewards

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%).

[1]  HaeEun Helen Chun,et al.  Free Drink or Free Mug? Managing Service Experience with Experiential vs. Material Complimentary Gifts , 2016 .

[2]  F. Dwyer Customer lifetime valuation to support marketing decision making , 1997 .

[3]  Sharad Borle,et al.  Customer Lifetime Value Measurement , 2008, Manag. Sci..

[4]  Ying Xie,et al.  Measuring the Lifetime Value of Customers Acquired from Google Search Advertising , 2011, Mark. Sci..

[5]  V. Kumar,et al.  Practice Prize Report - The Power of CLV: Managing Customer Lifetime Value at IBM , 2008, Mark. Sci..

[6]  Min-Chiang Wang,et al.  Expected Value of Distribution Information for the Newsvendor Problem , 2006, Oper. Res..

[7]  Irwin P. Levin,et al.  Consumer evaluation of multi-product bundles: An information integration analysis , 1991 .

[8]  Nada Nasr Bechwati,et al.  The allocation of promotion budget to maximize customer equity , 2001 .

[9]  Melvyn Sim,et al.  The Price of Robustness , 2004, Oper. Res..

[10]  Arkadi Nemirovski,et al.  Robust Convex Optimization , 1998, Math. Oper. Res..

[11]  Peter S. Fader,et al.  RFM and CLV: Using Iso-Value Curves for Customer Base Analysis , 2005 .

[12]  Fabrice Talla Nobibon,et al.  Optimization of the annual planning of targeted offers in direct marketing , 2013, J. Oper. Res. Soc..

[13]  Joydeep Srivastava,et al.  Free Offer ≠ Cheap Product: A Selective Accessibility Account on the Valuation of Free Offers , 2013 .

[14]  Tuck Siong Chung,et al.  Marketing Models of Service and Relationships , 2006 .

[15]  Rajkumar Venkatesan,et al.  A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy , 2004 .

[16]  Praveen K. Kopalle,et al.  The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs , 2012, Mark. Sci..

[17]  G. Gallego,et al.  The Distribution Free Newsboy Problem: Review and Extensions , 1993 .