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The retail industry has always collected vast amounts of data to determine customer behaviour, future inventory needs, and


forecast trends. But when pricing comes into play, simply taking a data-driven approach is no longer enough.


By Jennifer Roubaud, VP sales & partnership at Dataiku T


he best retailers are moving into the world of real-time predictive analytics to please their customers and increase their profits. As online shopping becomes a standard part of our lives, retailers are discovering new ways


to collect all of their data and deliver value to their customers with predictive analytics. Because of this, the market for predictive analytics technologies is expanding quickly. It’s estimated that by 2022, the global predictive analytics market will reach $10.95 billion – growing at an annual rate of 21% between 2016 and 2022. In a survey of retailers by JDA Software Group and PricewaterhouseCoopers, 86% of retail executives claimed they plan to increase their investments in big data tools over the coming year alone. Most retailers determine prices, whether in bricks-and-


mortar stores or in ecommerce, with macro-level predictions - that is, based on averages of large swaths of customers. Additionally, when it comes to when and what to mark down, the decision often hinges on a store or product manager, and it can be based more heavily on the need to get rid of excess inventory than to optimise sales. While these strategies can sometimes be relatively


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