Data-Driven Pricing for Improved Profitability in Apparel Retail

Solution Price Optimization
Solution Price Optimization
Industry Retail
Region US
Technology Microsoft Azure
Context

Effective pricing is essential for improving profit margins and staying competitive in the fast-paced apparel retail sector. Retailers often face challenges in making timely and accurate decisions due to large product assortments, regional demand variations, and evolving customer preferences. Traditional approaches frequently overlook key factors like product life cycle stages, promotional impacts, and price elasticity. This leads to missed revenue opportunities.

Our data-driven pricing optimization solution addressed these challenges by analyzing demand patterns. It aligned pricing strategies with product performance and market trends. The solution focused on stable-phase products and accounted for seasonality, regional differences, and macroeconomic indicators. It delivered clear, actionable recommendations. This helped the client shift from intuition-based decisions to structured, data-informed price marking. As a result, they improved margins and achieved long-term profitability.

Problem statement

Our client, a large apparel retailer, was encountering challenges in refining its pricing strategy across a broad and diverse assortment of products. Despite having access to transactional and promotional data, the absence of a systematic, data-led approach made it difficult to identify optimal pricing across regions and product segments. Determining the right level of product grouping, accounting for life cycle stages, challenges with accounting for the seasonality of a product, and extracting clean promotional signals further added to the complexity. These challenges limited the retailer’s ability to make confident pricing decisions that aligned with customer demand and margin goals. MathCo partnered with the client to design a pricing optimization solution that addressed these constraints through structured modeling and scalable analytics. 

Impact

  • ~$2.5 M of bottom line (Margin) benefit annually   
  • Provided recommendations on product groups that contribute to 24% of the company’s annual revenue 
  • Achieved a ~10% increase in newly launched product revenue from optimal pricing strategies 
  • Strategic pricing helped improve customer value perception, boosting CSAT and loyalty 

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