Study Finds Markdowns Cost U.S. Retailers $300 Billion in Revenues in 2018

New Report by Coresight Research and Celect Reveals the Hidden Costs of Inventory Mistakes

Boston, MA – February 6, 2019 – Celect, a market leader in predictive analytics and inventory optimization for retailers, today announced the results of a U.S. retailer survey titled “Revealing the Hidden Costs of Poor Inventory Management.” The findings revealed key factors behind major inventory challenges retailers have experienced from excessive markdowns and incorrect merchandising decisions, highlighting the urgency for retailers to optimize inventories to effectively satisfy their customers and ensure their continued financial success.

“Our research underlines the scale of the challenge retailers currently face—as well as the opportunity to sell more products at full price,” noted Deborah Weinswig, CEO and Founder of Coresight Research. “Ever-expanding choice and rapid changes in consumer behavior are increasing the pressure on retailers to make smart merchandising decisions, and these pressures show no signs of easing.”

More than 200 senior retail decision makers shared their views on top areas of concern around inventory decisions and the correlation to key performance indicators such as full-price sell-through, markdowns, stockouts and margins. The key findings include:

  • U.S. non-grocery retailers lost $300 billion in revenues due to markdowns in 2018, equivalent to 12 percent of their total sales
  • Respondents cited inventory misjudgments as a primary markdown driver and barrier to selling at full price, accounting for more than half (53 percent) of unplanned markdown costs
  • Multichannel retailers had a lower propensity to sell inventory at full price, demonstrating the overbuying/underbuying inventory tightrope getting even more complicated with channel expansion
  • The majority, 86 percent, of survey respondents identified specific ways in which advanced analytics could help their retail sector sell more product at full price 

“Our findings suggest that retailers could benefit from deploying advanced predictive analytics tools that use artificial intelligence (AI) and machine learning in order to make more informed inventory decisions and anticipate where, when and what consumers want,” continued Weinswig. “Retailers in the highly competitive apparel sector particularly benefit from predictive analytics and advanced inventory optimization tools that can help ensure the products shoppers desire are always in stock.”

“To stay competitive in today’s challenging retail landscape, retailers need to understand the impact of complex inventory decisions and the potential for upside,” added John Andrews, CEO of Celect. “Celect is helping retailers circumvent many of these risks by optimizing inventories and predicting localized demand throughout the entire merchandising process.”

For the survey methodology, complete analysis, corresponding charts and additional insights, download the report here.

About Celect

Celect offers a cloud-based, predictive analytics SaaS platform that helps retailers optimize their overall inventory portfolios in stores and across the supply chain, resulting in double-digit percentage revenue increases. This groundbreaking advance in machine learning and optimization allows retailers to understand how an individual customer shopping in store or online chooses from an assortment of products, revealing true demand. The technology builds on a fundamental advance in customer choice modeling called by MIT's Computer Science and Artificial Intelligence Laboratory one of the 50 greatest innovations it has ever produced. 

See your ROI from optimized inventories:

About Coresight Research

Coresight Research is a research and advisory firm specializing in disruptive technologies reshaping today’s retail landscape. Coresight Research has a global presence spanning the U.S., Europe and Asia, including deep expertise in the fast-changing China market.


Media Contact:

Erica Camilo
Connexa Communications for Celect
C: 610.639.5644

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