Get more value out of end-of-season markdowns in fashion retail: How Torfs uses the Crunch Markdown Assistant to boost revenue & margins
How can you optimize markdown pricing and enhance retail efficiency?Â
Discover how Torfs, a leading Belgian shoe retailer, significantly improved its profit margins and streamlined operations by implementing the Crunch AI-driven Markdown Assistant. This strategic initiative leveraged advanced analytics to revolutionize Torfs' end-of-season discounts, boosting revenue by up to 30% and margins by up to 8%.
Client Introduction
Luc, Head of Buying Stijn, CFO & Head of Analytics
- Industry: Fashion Retail
- Role: Head of Buying & CFO
- Company Size: €190M in revenue; 650 employees
Torfs, a mid-size Belgian shoe retailer, is known for its proactive approach to maintaining leadership in a highly competitive market. The company has consistently embraced innovative strategies to enhance customer satisfaction and profitability, especially facing challenges from global competitors like Zalando and Amazon.
The Challenge of Getting More Value out of End-of-Season Markdowns
As a fashion retailer, Torfs has regularly dealt with the complexities of pricing strategies, particularly end-of-season markdowns. The traditional approach, while reliable, often led to suboptimal profitability and excessive inventory. With the market dynamics evolving rapidly, there was a critical need for a more efficient and data-driven approach to markdowns to optimize both revenue and stock levels.
The Crunch Markdown Assistant as a Tool That Assists the Pricing Team
Our team at Crunch came into the picture as a trusted advisor, tasked with fundamentally reviewing Torfs' markdown process using advanced AI technology. The Crunch Markdown Assistant was engineered to transform Torfs' approach to markdowns through advanced AI algorithms and improved dashboarding:
- Algorithmic Pricing Framework: Using predictive analytics, the tool predicts the optimal markdown for each item in a catalog. It analyzes historical sales, current inventory data, and pricing trends to determine optimal discount levels, given a chosen objective.
- Strategic Implementation: An A/B test setup validated the tool’s effectiveness. Two groups of products were tested - one using the Crunch Markdown Tool and the other using traditional methods. This approach provided clear insights into the performance enhancements driven by the AI tool.
- Operational Integration: The Markdown Assistant integrates seamlessly into Torfs’ existing infrastructure. It supports easy adjustments and pre-season planning, allowing Torfs to strategize effectively based on comprehensive data analysis.
- User-Focused Design: The tool features intuitive dashboards that present critical data points and performance metrics in an accessible format. These dashboards enable scenario testing before a markdown campaign and quick decision-making during a campaign. They are particularly useful in managing large-scale pricing decisions without substantial increases in staff workload.
The Results
Implementing the Crunch Markdown Assistant yielded significant improvements for Torfs:
- Increased Revenue and Margins: Compared to the control group, the AI-driven group saw a 30% increase in revenue and an 8% improvement in margins, showcasing the financial benefits of optimized markdown strategies.
- Enhanced Operational Efficiency: The automation of pricing decisions significantly reduced manual efforts and allowed the team to focus on other strategic initiatives, improving overall business efficiency.
- Scalability and Future Growth: The success of the pilot project has led Torfs to expand the use of the Markdown Assistant across more product categories. Torfs is also exploring other potential AI applications within its operations to continue driving innovation and efficiency.
Conclusion
The Crunch Markdown Assistant has proven to be a vital tool in optimizing markdown strategies. It allows the team to test scenarios before changing a bunch of prices, analyze a product individually, and accept a broad set of markdown recommendations in a few clicks. It demonstrates that AI can significantly enhance both financial outcomes and operational efficiency in retail.
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