Markdown Optimization Kicks Off Savings for Athletic Apparel Factory Outlets

Aging inventory and shrinking clearance margins don’t just affect traditional retail stores—factory outlets are equally susceptible. We recently completed an engagement for an international athletic apparel company that demonstrates the significant revenue lift that factory outlets can realize through pricing analytics and markdown optimization.

For many brand retailers, factory outlets are the most profitable brick and mortar operation—it’s where most of the product is sold, and where there’s the greatest potential to drive revenue and margin increases. The challenge: Knowing the correct lifecycle of your products and pulling the right pricing levers to meet financial targets.

One of our clients recently faced this dilemma. Managers wanted to reduce aging inventory, establish seasonal product lifecycles and define a profitable clearance strategy in the Western European market, but didn’t have the right people or technical capability to do so.

Pricing was a laborious process, with just a handful of staff manually pricing tens of thousands of articles each seasonin almost 30 countries and many different currencies. Fifty percent of inventory was more than two seasons old, and significant quantities of marked-down stock never left the distribution center.

The company sought the right tools and expertise to improve business processes and remedy the situation. We were hired to implement a markdown optimization solution, and build a solution that delivered optimized pricing based on a sophisticated forecasting methodology with business rules to:

  • Minimize end-of-season inventory
  • Increase stock turn
  • Increase regular price and clearance revenue
  • Consider markdown budget in optimized pricing decisions

During this implementation, our team went through an intensive process of sanitizing data, building forecasting models, running optimization scenarios and identifying precise business rules and product lifecycles to meet the company’s goals.

compositional-forecasting

Advanced analytics can decompose demand to establish baseline sales in addition to price elasticity, which is used to determine optimized price.

This empowered the client to take early profitable markdowns and drive higher revenue and margin. In the measurement period of just over 8 weeks, they generated $1 million net margin, and expect to generate 6-7x ROI on the project within the first year.

This retailer isn’t unusual; most of our clients are grappling with an immature pricing strategy, and that’s understandable—there’s a huge business process component involved in pricing and most companies lack the correct technology to ease the process.

By leveraging our expertise in pricing analytics and deep understanding of the business, we partner with retailers—outlets, resellers, concept and online stores—to translate business requirements into a software solution that streamlines decision-making and optimizes human capital.