Leading Footwear Retailer Captures 14x ROI with Syrup’s AI Demand Forecasting + Inventory Management

Challenge

A prominent North American footwear retailer, with annual revenues exceeding $3 billion and a portfolio of premium lifestyle brands, faced significant challenges with their traditional inventory management approach. Operating across multiple sales channels including retail stores, e-commerce, and wholesale partnerships, the company manages a complex network of both full-price and outlet locations.

The retailer’s peak season strategy reflects the complexity of its operation. Each year, the team executes a massive inventory build in August and September, pushing hundreds of thousands of units through their retail network. This approach requires maintaining 13-14 weeks of supply to cover the critical period through the cyber holiday season. Around 60% of the retailer’s annual revenue is concentrated during peak season

To accommodate this substantial inventory position, the company invests in additional storage facilities near their retail locations as well as seasonal help, creating significant operational overhead.

Several operational inefficiencies have emerged:

• Heavy reliance on manual processes for inventory decisions
• Demand forecasts not at the SKU level
• Over-deployment of inventory as a risk mitigation strategy
• Inconsistent stock levels across store locations
• Capitally inefficient mix of under- and overstocks stemming from inaccurate initial allocations

Solution

The retailer partnered with Syrup, an AI-powered decision support system specialized for apparel and footwear brands, to transform their inventory management approach. Syrup’s technology was particularly well-suited to address the retailer’s challenges due to its footwear-tuned machine learning models and ability to process complex, non-linear relationships in purchasing behaviors.

The implementation leveraged Syrup’s advanced demand sensing capabilities across two key areas:

• Initial allocations to support monthly drops
• Dynamic replenishment to maintain optimal stock levels multiple times per week

The solution was designed to not just provide predictions, but to deliver actionable recommendations that would directly impact the retailer’s top and bottom lines.

Quantitative Impact

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Qualitative Impact

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White Glove Service, From Integration Through Results

• Ingestion services curated for the client’s data infrastructure
• Integration of data sources including historical transactions, e-commerce performance data, promotional calendars, and store analytics
• Implementation of footwear-tuned machine learning models configured to the client’s specific business requirements

Syrup partnered closely with the retailer throughout the project to ensure close strategic alignment. The retailer’s team benefitted from weekly calls with a dedicated Success Manager and Solution Architect covering success reports and diagnostics. These meetings supported recurring strategy conversations that unlocked hidden insights for the allocation team — including temporary store closure recommendations. Feedback from the working team informed product and UI improvements that were delivered during the course of the project.

Looking Forward

Following the successful pilot, the retailer is moving forward with a global implementation of Syrup’s solution, expecting to realize similar benefits across their entire retail network. The implementation roadmap includes staged rollouts across North America, EMEA, and APAC regions, with potential expansion into buying optimization.

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