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Sam Vise shares how AI can generate dynamic, location-specific plans that optimize product placement
What are the biggest challenges brick-andmortar retailers face with traditional planograms? Traditional planograms have long been a tool for brick-and-mortar retailers to help ensure consistency across stores. The problem, however, is that they take a one-size-fits-all approach, which doesn’ t always work in today’ s vast and distributed retail environment. Every store is different- with variables like location, shopper demographics, and inventory needs influencing each location- yet traditional planograms don’ t account for these differences. That can lead to product placements that don’ t resonate with local shoppers, ultimately affecting sales and the overall shopping experience.
Additionally, given their static nature, they make it difficult for retailers to quickly adjust to real-time inventory changes, shifting trends, or evolving shopper behaviors. This rigidity also makes it challenging for stores to achieve compliance as static planograms fail to account for inventory and capacity levels. As a result, store associates are tasked with making on-the-spot decisions about what to replace planned products with, leading to suboptimal and inconsistent placements.
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