Trade promotion optimization

This article is a deep dive into dynamic pricing algorithms that use reinforcement learning and Bayesian inference ideas and that were tested at scale by companies such as Walmart and Groupon. We focus on the engineering aspects through code snippets and numerical examples; the theoretical details can be found in the referenced articles.

In this article, we discuss the common process by which retailers set their pricing, the challenges that they are facing in the area of price and promotion management, and how they incorporate big data analytics and machine learning into their pricing strategy to achieve stable growth and competitive advantage. This article can be used as a blueprint for trade promotion optimization processes and solutions.

This article describes a reference implementation of a price and revenue management tool that showcases the main capabilities of AI-based price optimization software and features several advanced techniques. We start with a strategic vision of a price analytics solution, then build a demand model, and finally develop a fully automated optimization application.