Driving 6.7% Higher Gross Margin in Kidswear with Retail Pricing Software

The Background

A prominent kidswear retailer with a wide assortment of clothing, footwear, and accessories was managing thousands of products across age groups, sizes, colors, and seasonal collections.

The same style could perform very differently by size or color. Some variants sold quickly, while others moved toward markdowns. At the same time, frequent competitor price changes made it difficult to know when to react and when to hold price.

The retailer adopted Hypersonix Pricing AI and Competitor AI to make more precise pricing decisions across its assortment.

Industry: Kidswear & Apparel Retail

Product Implemented: Pricing AI, Competitor AI

Goal: Protect margin, improve competitive visibility, and make faster SKU-level pricing decisions.

One Style. Many Sizes. Different Pricing Needs.

• The same dress, T-shirt, or footwear style could sell quickly in some sizes while slower sizes remained in stock.
• Collections had short selling windows, especially around back-to-school, festive, summer, and winter seasons.
• Similar-looking products often differed by fabric, age group, size range, set configuration, or design, making competitor comparisons difficult.
• Broad markdowns sometimes reduced prices across an entire style even when popular sizes were still selling well.
• Thousands of style-size-color combinations made it difficult for teams to review pricing opportunities manually.

Pricing AI

• Analyzed demand, sales velocity, inventory, elasticity, and margin goals to recommend prices at the SKU level.
• Helped teams hold price on popular sizes, adjust slower-moving variants, and avoid discounting an entire collection unnecessarily.

Competitor AI

• Tracked comparable kidswear prices across relevant retailers and marketplaces.
• Matched products using details such as garment type, age group, material, size range, color, style, brand, and set configuration to identify true like-for-like products.

The Hypersonix Impact

Popular sizes and fast-selling styles could remain at stronger price points instead of being pulled into early markdowns.

Teams could respond differently to slower colors or sizes within the same style rather than discounting every variant.

Product matching helped distinguish between similar-looking items with different fabrics, size ranges, age groups, or pack configurations.

Teams identified pricing opportunities earlier across back-to-school, festive, and seasonal collections before markdown pressure increased.