As consumer preferences shift rapidly and product lifecycles shorten, retailers need more than intuition to decide what to stock and where. Traditional store-level planning often falls short of capturing local nuances. MathCo’s data-driven assortment optimization framework empowers retailers to align inventory with demand, respond faster to changing trends, and deliver personalized in-store experiences that boost revenue.
Problem Statement
A leading US-based apparel retailer aimed to refine its assortment planning to better reflect evolving consumer preferences. Store managers often relied on assumptions rather than data, leading to inconsistent product availability and missed opportunities. With over 5,000 stores and multiple in-house brands, the retailer needed a scalable, data-driven approach to localize assortments and boost customer satisfaction.
Impact
- ~$5M incremental revenue from improved assortment planning.
- 7% sales growth across optimized store clusters.
- 75% of total revenue captured by top 10 optimized clusters.
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