Price optimization is the process of finding the price point that best achieves a business objective—typically maximizing revenue, profit margin, or market share. Modern price optimization relies on analyzing historical sales data, competitor pricing, demand patterns, and customer segmentation to identify optimal prices.
The optimal price balances multiple factors: pricing too high reduces volume, while pricing too low leaves money on the table. Advanced price optimization considers different optimal prices for different customer segments, time periods, inventory levels, and competitive situations.
For ecommerce brands, price optimization often involves A/B testing different price points, analyzing conversion rates across price tiers, and using machine learning models to predict demand at various prices. The goal is moving beyond intuition-based pricing to data-driven decisions that continuously improve.