Price promotion optimization model for multiperiod planning: a case study of beauty category products sold in a convenience store chain

Abstract

Pricing strategy is vital in the retail sector as prices play an important role in driving revenues and profits. However, few studies have been conducted on retail promotion optimization, particularly amid the COVID-19 situation. This study aims to leverage statistical models to examine the effects of price promotion and other factors on sales during the COVID-19 period. In addition, an optimization model is proposed to maximize the profitability of a retail store through strategies for optimal promotional pricing. In this study, monthly sales data in four product categories with 245 stock keeping units from July 2020 to June 2022 from a case study convenience store chain were retrieved and preprocessed. Subsequently, statistical models, such as the autoregressive distributed lag model OWN and the autoregressive distributed lag model CROSS, were implemented to examine the effects of price, promotion and other factors on sales. In addition, factors such as price elasticity and cannibalization were extracted and analyzed from the demand models. An optimization model was built in accordance with the demand model to maximize the total profit of the retailer over a certain period by determining the strategy for optimal promotional pricing. Finally, sensitivity analyses were performed to explain the dynamics of the parameters involved in the optimization model. The methodology, results and insights from this research provide a preliminary framework to facilitate Thai retailers in optimizing their pricing strategies and achieving key business objectives.