The retail landscape is undergoing a significant transformation. Supercenters, supermarkets, and drug stores are witnessing a decline in square footage, with drug stores experiencing a double-digit decrease. This reduction in space is exerting pressure on available merchandising, necessitating a shift in retailers' approach to category management.

According to Nielsen Consumer TDLinx insight, from 2009 to 2022, square footage per store has reduced by:

• 5% in supercenters,
• 3.5% in supermarkets, and a staggering
• 13% in drug stores.

This trend is not just a result of changing consumer behavior but also the increasing role of stores in fulfilling both online and in-store purchases, further challenging the shelf-holding power.

In this evolving retail environment, getting items on the shelf and ensuring their effectiveness in driving category growth is becoming increasingly challenging. The key lies in proving incrementality and demonstrating how a product can contribute to category growth. However, the shrinking space and the pressures resulting from the pandemic have added layers of complexity to this task.

This is where the power of Artificial Intelligence (AI) and store-level data comes into play. By leveraging these technologies and understanding store-level constraints, retailers can optimize their merchandise placement, ensuring that every item on the shelf contributes to category growth and overall store success.

In an era of reducing square footage, it's crucial that category plans are always locally relevant, effectively merchandised, and operationally efficient. To navigate the challenges of the changing retail landscape and make the most of the available space, retailers need advanced tools that can help optimize their merchandise placement and drive category growth.

One such tool is HIVERY Curate, an AI-driven solution that provides hyper-local, store-level data insights to optimize merchandise across any number of stores, considering space rules. HIVERY Curate allows retailers to simulate dynamic strategies by incorporating real-world merchandise constraints, including space. This aligns with category goals and enables retailers to qualify the impact of each category strategy, negotiating with suppliers transparently. In fact, HIVERY Curate offers over 100 different space/assortment constraint combinations. It can support space rules like controlling facing, adding specific shelf height, allowing specific merchandise styles, or even shelf appearance constraints. Additionally, it contains assortment rules like forcing Points of Distribution (PODs) in or out or overrides like availability constraints. With AI, retailers can now optimize and address the decline in square footage and/or at least qualify the financial impact rapidly.

The future of the retail industry lies in the effective use of AI and advanced analytics to navigate the challenges of shrinking retail spaces. Tools like HIVERY Curate lead the way, ensuring the success of retailers' categories despite the pressures of the changing retail landscape.

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