Shelf space is a valuable and limited resource in retail, especially for large-format home improvement stores with wide product assortments. Optimizing it through data-driven planograms ensures high-demand items are visible, accessible, and aligned with local customer needs. Traditional planogram methods often use static rules or national trends, missing regional nuances and shifting shopper behavior.
Modern planogram optimization uses granular sales data, store-specific patterns, and shopper insights to tailor product placement locally. This boosts sales per square foot, improves inventory turnover, and enhances the in-store experience. Our solution used localized demand trends to build dynamic planograms that increased shelf efficiency, improved product availability, and drove stronger sales at the store level.
Problem statement
Our client, a leading home improvement retailer, was facing various difficulties with optimizing shelf space across its extensive store network. The retailer had a high dependency on manual processes for building planograms, leading to significant delays and inefficiencies. Additionally, adapting planograms to reflect local store demographics and consumer preferences was proving to be a complex and resource-intensive task. Another key challenge was the lack of actionable insights into the relationship between product placement and sales performance, making it difficult to maximize sales potential. These limitations were hindering operational efficiency and the retailer’s ability to enhance customer experience through strategic product positioning. MathCo collaborated with the client and consolidated diverse datasets to understand product characteristics, sales patterns, & customer preferences, for developing a robust shelf space optimization framework.
Impact
- Reduced planogram design time by ~80%.
- ~10% improvement in compliance and KPI performance through intuitive tools and visual insights.
- Improved shelf space utilization by ~20% leading to an increase in revenue by ~7%.
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