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A Rapid Response to COVID-19 Supply Chain and Market Shocks

In this white paper, we provide practical recommendations to technology and business leaders on how advanced data analytics and engineering capabilities can be leveraged to rapidly and efficiently respond to the COVID-19 disruption

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Case studies

A Guide to dynamic pricing algorithms
This article is a deep dive into dynamic pricing algorithms that use reinforcement learning and Bayesian inference ideas, and were tested at scale by companies like 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.
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Retail price modeling for replenishable and seasonal products
In this article, we discuss the common process with 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.
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Predictive analytics for promotion and price optimization
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 also features several advanced techniques. We start with a strategic vision of a price analytics solutions, then build a demand model, and finally develop a fully automated optimization application.
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