Strategic Pricing of Perishable Products Using Inflection Point Analysis for Revenue Maximization

Abstract

This study presents a comprehensive approach to optimizing the pricing strategy for perishable products, specifically focusing on identifying the optimal age to apply discounts. Using a demand model based on logistic functions, this research captures the interplay between price and product age, effectively modeling how demand naturally decays as products age and consumer sensitivity to pricing intensifies. To achieve a robust analysis, a Monte Carlo simulation is employed, incorporating variability in parameters such as market size, price sensitivity, and age sensitivity, reflecting real-world uncertainties. The simulation generates a dynamic dataset to examine demand behavior across a range of product ages and prices, allowing the identification of critical "inflection points": specific ages where demand sensitivity shifts significantly, indicating ideal timings for price adjustments. These inflection points serve as actionable indicators for retail strategies, guiding discount applications to maintain consumer interest, enhance inventory turnover, and reduce waste by aligning discounts with consumer demand patterns. For lower-priced products, the model suggests that retailers can sustain original prices longer without significant demand loss, whereas higher-priced items benefit from early discounts to counter rapid demand decline. Mid-range products align with moderate timing adjustments to capture demand before it drops steeply. This data-driven approach not only aids in maximizing revenue but also offers a practical framework for managing perishable inventory more effectively. The findings hold significant implications for retailers in sectors where product perishability poses unique pricing and inventory challenges, equipping them with strategic insights for dynamic pricing in time-sensitive markets.