Clearance planning has evolved into a strategic lever for large retailers, especially in the grocery and general merchandise space. Businesses managing high inventory volumes, seasonal shifts, and continuous product introductions need to optimize markdown and seasonal inventory decisions. Doing so can significantly impact both revenue and margins.
Many retailers still rely on tiered, time-bound discounting models. These overlook regional demand variations and product-level performance. Such rigid markdown approaches often lead to missed opportunities to recover value from unsold inventory. They also cause inconsistent execution across store locations and excess margin leakage. For multinational retailers operating at scale, building more responsive, data-driven clearance frameworks is essential to maintain agility and protect profitability.
Problem statement
The client, a Europe-based multinational grocery and general merchandise retailer, was facing persistent challenges in managing its clearance strategy. Depending on the store and product category, the goals of markdowns varied. Some locations required aggressive inventory reduction due to demand planning inaccuracies, while others focused on maximizing recovered revenue from unsold stock. The existing markdown process followed rigid, tiered discounting rules over predefined time windows, with triggers based primarily on product sell-through rates. While this approach offered structure, it lacked the flexibility to adapt to local demand shifts, assortment variations, and seasonal lifecycle timelines. As a result, the client experienced prolonged markdown cycles, reduced revenue recovery, and unnecessary margin erosion.
To address these challenges, the client partnered with MathCo to design a dynamic, data-driven markdown optimization solution. The objective was to enable localized pricing, support scenario planning, and align clearance decisions more closely with real-time business needs.
Impact
- A ~3x increase in recovered revenue through dynamic pricing at the product-store level
- Achieved a ~8% increase in profit margins and successfully adhered to the required clearance timeframes
- Reduced excess inventory holding costs by ~$750K annually by accelerating sell-through of slow-moving SKUs
Access the Case Study to Learn More about This Partnership
Driving Precision in Automotive Marketing: Strategies for Enhanced Customer Engagement
Explore how MathCo assisted a leading automaker in reducing irrelevant communications by 81%, increasing redemption rates by 6%, and driving sales through data-driven marketing. Learn how precision targeting enhanced customer engagement and maximized ROI.
Read more
IR and Customer 360 Platform Set Up
Learn about how we optimized marketing campaigns and improved advertising strategies for a renowned fashion retailer helping them bring about a 30% reduction in duplicate customer entries.
Read more
Impact of Operational Issues on Customer Behavior
Discover how our tailored data analysis helped a leading retail giant understand and quantify the impact of operational issues on customer behavior and NPS scores with relation to both existing members as well as those on a trial period.
Read more