Optimization of CPG budgets in Retailer-led marketing programs

Abstract

Grocery retailers and Consumer Packaged Goods (CPG) companies have a symbiotic relationship. Retailers need CPGs to supply the products, and CPGs need retailers’ customers to grow their brands. Since shelf space is limited, CPGs offer trade and marketing funds to prominently feature their brands. As part of loyalty programs, retailers offer coupons to customers that are often funded by CPGs. In return, CPGs expect a return on their investment(ROI). Since budgets are limited and are also expected to be utilized, it becomes a challenge for the retailer to find the right size of a mailer which can balance costs and relevance to customers. This thesis explores how knapsack problems can be used in an non-adaptive setting to help maximize the reach of print and email campaigns. Seeking inspiration from existing literature, multiple simulations were set up to evaluate budget-constrained allocation and compare two approaches, the multiple-choice Knapsack (MCK) and a greedy algorithm. Considering uncertainty in redemption, the Newsvendor model was also explored to review the possibility of over-allocation to improve budget utilization and increase reach. The preliminary analysis findings offer promising results and provide a setting for further research.