Traditional U.S. grocery retailer

Using data science to improve pricing competitiveness of Fresh Beef category, resulting in a 35% unit sales uplift.

Traditional U.S. grocery retailer case study - customer data science and insights led to growth in sales

unit sales uplift


sales $ uplift

A traditional grocery retailer wanted to improve the pricing competitiveness of their Fresh Beef category. Efficiently optimizing any category can be challenging, especially when you don’t have the right tools, actionable insights, and proven approaches. And due to the complexities of reviewing a category with PLU and random weight products, prior category reviews with a previous analytics partner yielded little insight, and were therefore rarely done

But seeing the size of the prize in this category, the retailer collaborated with dunnhumby to create a detailed workplan to optimize prices.

Watch the video below to learn how dunnhumby’s unique mix of science, software, and consulting helped to deliver a customer-centric category review with a 35% unit sales uplift.

Are you ready to put the right products at the right prices and unlock your category’s potential?

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