Measuring the effects of customized targeted promotions on retailer profits: prescriptive analytics using basket-level econometric analysis

Alexander Chaudhry (), Carrie Heilman () and P. B. Seetharaman ()
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Alexander Chaudhry: Southern Utah University
Carrie Heilman: University of Virginia
P. B. Seetharaman: Washington University in St. Louis

Journal of Marketing Analytics, 2024, vol. 12, issue 4, No 19, 1028-1051

Abstract: Abstract This study empirically estimates the expected basket-level demand effects, as well as the expected store profit effects, of three different customization levels of retailer promotions. Using data from a national grocery retailer in the U.S., we estimate a household’s contemporaneous purchase incidence outcomes in 28 frequently shopped categories. Estimating the cross-category dependencies in purchase incidence as a function of exposure to levels of customized promotions, allows us to measure the effect of each campaign on expected retailer profit and implement prescriptive analytics to identify the appropriate multi-level coupon mix for maximizing profits. We find all three levels of coupon customization result in per-customer returns, but that medium customization leads to the highest incremental expected profit, while high customization generates the highest expected profit. The results provide insights to retailers about investing in more customized promotional efforts, with a detailed cross-category perspective into where such value is gained. Graphical abstract

Keywords: Customized coupons; Targeted promotions; Retail profitability; Basket-level demand modeling; Prescriptive analytics (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1057/s41270-023-00253-3

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