Fashion Retailers Use Kimaru.ai to Optimize Markdown Strategies and Reduce Unsold Inventory Waste

AI-powered markdown optimization helps fashion retailers enhance profitability, reduce unsold stock, and support sustainability initiatives.

The fashion industry is highly seasonal, with constantly shifting trends and customer preferences. Kimaru.ai enables fashion retailers to optimize markdown strategies, balance inventory clearance with profitability, and minimize waste from unsold stock. By leveraging AI-driven markdown optimization, retailers can confidently manage their pricing decisions, ensuring they maximize sell-through rates while reducing environmental impact.

The Challenge

Fashion retailers frequently struggle with inventory that quickly becomes obsolete due to changing trends and seasonal demand shifts. Excess stock often results in steep markdowns, eroding margins, or, worse, large quantities of unsold products ending up in landfills. Traditional markdown processes rely on intuition and manual planning, making it difficult to apply strategic, data-driven pricing at scale.

The Solution

By integrating Kimaru.ai’s Decision Intelligence Agents, fashion retailers can analyze historical sales data, real-time demand signals, and external factors such as weather patterns and promotional activity. Built on Dr. Lorien Pratt’s Decision Intelligence methodology, which maps causal decision diagrams and action-outcome connections, and enhanced by Agentic AI, Kimaru.ai delivers highly accurate, real-time SKU-level pricing recommendations that help retailers:

Apply the right discount at the right time to maximize sell-through rates while protecting margins.
Dynamically adjust markdown strategies based on current sales performance and customer demand.
Minimize unsold inventory, reducing the environmental and financial impact of overstock.

During peak sales seasons and clearance events, Kimaru.ai’s AI-driven recommendations allow retailers to take a more strategic, data-backed approach to markdowns. Instead of relying on broad percentage-based discounts, retailers can optimize pricing for each SKU, ensuring maximum revenue retention and improved inventory turnover.

The Impact

By leveraging Kimaru.ai’s markdown optimization AI, fashion retailers experience:

Higher profit margins by reducing unnecessary deep discounting while improving sell-through rates.
Lower unsold inventory, helping retailers reduce product waste and decrease their environmental footprint.
More sustainable operations, as fewer unsold products translate to less textile waste ending up in landfills.

Sustainability and ESG Alignment

AI-driven markdown optimization aligns with global Sustainable Development Goals (SDG) and Environmental, Social, and Governance (ESG) initiatives by:

Reducing textile waste: By preventing unsold stock from being discarded, retailers contribute to SDG Goal 12 (Responsible Consumption and Production).
Lowering carbon emissions: Optimized inventory turnover leads to reduced energy use in logistics and storage, contributing to more sustainable operations.
Supporting ethical and circular fashion practices: Efficient markdown strategies enable retailers to explore resale, donation, and recycling initiatives for slow-moving inventory.

Fashion retailers are also integrating Kimaru.ai’s Decision Intelligence Agents beyond markdowns, applying them to broader pricing, demand forecasting, and inventory management strategies. This unique combination of Decision Intelligence methodology and Agentic AI enables businesses to manage seasonal inventory more efficiently while ensuring profitability and sustainability.

For more information on how Kimaru.ai can help fashion retailers optimize markdown decisions and reduce unsold inventory waste, please contact us.