Smart Pricing in Retail Predictive Analytics to Optimize Price Most retailers, whether in brick-and-mortar stores or in e-commerce, determine prices 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 optimize sales. While these strategies can sometimes be relatively effective, they are not optimal. For example, price optimization based on averages does not take into account subtle nuances in different geographies or in specific stores. And considering markdowns only when there’s inventory to get rid of is a reactive solution instead of a proac

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