Markdown Optimization Solution Vastly Improves Retailer’s Sell-Through and Margin
Client Challenge
The client is a multibillion-dollar specialty retailer operating over 800 stores across the United States and Canada. Over the last year, the client engaged Parker Avery to optimize its regular pricing. This capability allowed the retailer to invest in price reductions for key value items (KVI) and fully offset the price optimization investment with additional margin generated by non-KVIs.
Based on this impressive performance, the retailer tasked Parker Avery to optimize its markdown process to improve end-of-season sell-through and margin. The company traditionally relied on a blanket markdown approach, using the same discount for all items. This method resulted in significant margin losses, and the company’s leadership wished to improve the approach using Parker Avery’s Enterprise Intelligence-based markdown optimization solution and deep industry experience.
Parker Avery Solution
The Parker Avery team partnered with the client’s merchandising, pricing, and IT teams to implement a markdown optimization solution for the retailer’s seasonal markdown process.
Over six months, the team performed the following key activities:
- Staged and cleansed weekly inventory data for every item in every store
- Utilized Parker Avery’s Enterprise Intelligence platform to measure markdown price elasticity and to predict end-of-season remaining inventory for every seasonal item of every store
- Developed and implemented an inventory-at-risk algorithm to identify a subset of the total number of items across all stores, representing 72% of the total predicted remaining inventory
- Utilized the solution’s markdown optimization engine to determine the optimal discount for each store/item within the subset, equally considering impacts to unit sales and margin dollars
Once the markdowns were executed, the team monitored item performance and provided insights to help the retailer plan for future seasons.
Results
With Parker Avery’s Enterprise Intelligence demand platform as the foundation for the client’s AI-driven markdown optimization solution, the team significantly improved the client’s markdown process effectiveness.
Marking down only items with significant projected end-of-the-season inventory allowed for increased sales while keeping the remaining items at a regular price, which resulted in significant margin savings.
As measured post-season completion, executed markdowns delivered an approximate 20% point increase in the sell-through rate, a 15% lift in revenue, and a 2x margin improvement for markdown-eligible items.
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