Retail Pricing: Getting the Most Out of Machine Learning


Retail Pricing: Getting the Most Out of Machine LearningMachine learning is here to help retailers become more productive and profitableIf you are reading this article, you are probably looking for new approaches to optimizing pricing. Simply put, traditional methods are not good enough anymore. It is true that they are still working well enough to let you survive, but they are insufficient to put you ahead of tech-savvy competition. In this article, I’d like to cover two things as Competera’s price optimization expert: the tremendous potential of machine learning in retail dynamic pricing, and how you can get ready for the adoption of the technology to take advantage of every opportunity it provides.Machine learning in retailBig names have been using machine learning in dynamic pricing for years. Among the brightest examples is Amazon, which was among one of the earliest adopters of the technology. This was, for sure, one of the factors which contributed to the company’s stellar growth in the market value: from 30 billion in 2008 to almost 1 trillion in 2019. Other players using machine learning include Walmart, Jet, and Newegg.What makes the algorithms so efficient and popular? It is their ability to process massive amounts of …

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