Beyond Discounts: A Comprehensive Guide to Effective Markdown Optimization

The State of Markdown

Today, retailers face growing pressure to make quick merchandising decisions as consumer behavior evolves. Retail planning has become increasingly complex, with increased touchpoints and constantly expanding markets. Even the most minor errors can lead to excess inventory, high logistics costs, reduced margins, and a dependency on flash sales. As a result, Markdown Optimization becomes more crucial, allowing retailers to adjust prices, manage inventory, and protect profits strategically.

Overall, consumer sentiment is becoming more price-sensitive, thanks to factors like rising living costs. Retailers also face challenges in selling full-price inventory and managing the rising return rates. Cautious shoppers then pursue cost-saving strategies like opting for discounts, budget brands, or smaller packages.

Effective markdowns, especially in sectors like fashion, electronics, and home goods, are vital as consumer demand shifts increasingly faster. In 2015, 67% of retail orders included markdowns, reducing margins by 24%, and by 2018, U.S. markdown costs totaled $300 billion, based on a study by Coresight Research and Celect . The 2020 pandemic further intensified markdown reliance, with sales dropping 16.4% in April. The story continues as in 2021, U.S. retailers accumulated a significant inventory surplus, leading to markdowns averaging 25% to 35% to clear stock. 

Markdowns are an inherent part of today’s retail and fashion operating model. In this context, data-driven markdown strategies and tools are no longer optional, but essential. Globalized supply chains have reduced reaction time but also lowered costs, making overstocking more acceptable than missing a sale. This shift has led to lower sell-through targets, effectively planning for markdowns. Compounding the issue, suboptimal demand and supply planning often result in poor inventory placement and misaligned commercial strategies, driving excessive markdowns.

Given these challenges, robust markdown optimization capabilities are critical to protect profitability and brand perception. Relying on manual tools, outdated logic, and limited responsiveness only accelerates margin erosion and weakens customer perception.

Understanding Markdown Optimization

Markdown optimization involves strategically lowering prices on products approaching the end of their lifecycle to maximize margins or revenue while reducing excess inventory. Markdowns temporarily boost demand for slow-moving items, aiming to clear all stock through a permanent price reduction as the product's season ends.

Imagine an apparel retailer pricing a winter jacket at $200, sourced for $80, maintaining a 60% margin. As spring nears, demand dips, prompting a 40% markdown to $120 to clear stock. But is this optimal? A 25% markdown in colder areas or an earlier reduction in winter-prone regions might achieve similar results. By tailoring markdowns by region and timing, the retailer could better preserve margins and optimize ROI without compromising demand across locations. 

Key markdown factors involve setting guidelines like minimum price thresholds, maximum discount limits, and timing strategies aligned with inventory levels. In stock-limited situations, strategic markdowns boost demand, drive complementary sales, and maintain brand integrity. Additionally, markdowns enhance sustainability by reducing unsold inventory waste that is often discarded or destroyed at season’s end.Thus, retailers must carefully consider several factors when making clearance decisions: which items to mark down based on seasonal performance, where to apply clearance across locations, when to initiate clearance for budget balance, and how significant price reductions should be to meet margin and sell-through goals.

While markdowns may deliver similar sales lifts to promotions or seasonal discounts, their permanent nature adds complexity. Markdown optimization involves challenges such as inventory misalignment, timing issues, and excessive discounting, which can harm brand perception. Seasonal demand shifts further complicate inventory balance, making data-driven markdown strategies essential. Integrating AI and analytics helps retailers predict demand patterns, optimize pricing phases, and increase customer satisfaction.

Strategic Approaches to Effective Markdown 

Retailers have often applied uniform pricing strategies across products, ignoring item or store performance. Markdowns frequently become reactive responses to end-of-life stock, driven by limited data, tools, or clear strategy. As a result, markdowns are rarely pre-planned, leading to unnecessary profit losses during clearance cycles. Retail markdown strategies should align with a product’s lifecycle to avoid over-reliance on discounts, which can lead shoppers to expect constant sales and weaken brand perception. The challenge lies in finding the right balance between lowering prices and strategically enhancing inventory management and profits without compromising the brand’s value.

The primary triggers for retail markdowns include clearing stock for new collections, selling seasonal products, moving items before expiration, and driving sales for underperforming goods. Although markdowns are often seen as a loss center, these triggers are inevitable. However, advancements in technology provide new opportunities. With strategic planning and optimized solutions, markdowns can transform into proactive tools for recovering lost sales and revenue.

1. Set clear indicators to strategize markdown - Defining and monitoring measurable metrics, such as inventory targets, ROI, margins, and sales trends, helps guide future markdown strategies and ensures alignment with overall company goals. Monitoring these KPIs before, during, and after markdowns allows timely adjustments if needed.

2. Automate markdown pricing strategy - Markdowns can target margin maximization or inventory clearance, but an optimization solution should automate triggers to initiate markdowns. Machine learning can track aging inventory and recommend markdowns(which product/when), ensuring timely sales while minimizing costs. This approach enables multichannel retailers to adjust markdowns dynamically based on market conditions, dates, sales, or inventory levels, efficiently optimizing margins and clearing stock.

3. Tiered markdown strategies - Retailers should pre-plan markdown timing and amount for products with set lifecycles to prevent last-minute price cuts. Strategic markdown optimization balances profitability and inventory, using tiered markdowns to gradually reduce prices based on demand trends and historical sales data. The following scenario illustrates what Markdown in-season entails:
   • Week 1:  Start exposing new inventory
   • Week 2-8: Full-price sales and promotions
   • Week 3-12: Start markdowns and clear room for new inventory
4. Segmentation strategies - Grouping stores by specific attributes, like Full-Price/Outlets or Hot/Cold stores, allows retailers to apply targeted markdowns. For example, geographical clustering enables localized markdowns that boost sales in low-demand areas while preserving profits in high-demand locations, maximizing relevance and customer engagement.

Getting Started with Markdowns 

Without a clear strategy, markdown processes often become reactive rather than proactive. Establishing specific rules and constraints allows markdown optimization to automate complex tasks, saving planners time and improving outcomes. 

The key elements are to define a pricing strategy or set clear markdown goals. A pricing strategy sets minimum and maximum markdown rates and optimization levels, while markdown goals prioritize either margin maximization or inventory clearance. Flexibility enables planners to optimize by product, location, or both and adjust goals. Additionally, the strategy should model the relationship between price and demand in three significant steps:

1. Estimating markdown price elasticity - Markdowns are non-linear; higher discounts don’t guarantee proportional lifts, which decline over time. Price elasticity gauges how demand shifts with price changes. Suppose a woman's cotton dress price drops from $50 to $45, increasing sales from 100 to 115 units. This 10% price drop yields a 15% demand boost, indicating elasticity with a price elasticity of 1.5. Machine learning-driven markdown solutions analyze past campaigns to estimate price elasticity, simulating optimal style-price combinations to balance demand and profitability and maximize key business metrics.

2. Predicting demand - With price elasticity established for each product, a predictive model is needed to accurately forecast demand over a set period at current prices. Advanced analytics and AI can deliver data-driven insights, enabling accurate demand forecasting for markdowns and understanding the overall forecasts post-price adjustments. Real-time dynamic pricing refines markdowns based on inventory and demand, optimizing profitability and ensuring strategic pricing decisions.

3. Optimizing Markdown - Understanding a product’s price elasticity, current price, and forecasted demand enables a price-response function to predict demand at different prices. Integrating this into an optimizer helps determine the optimal price reduction and timing. Optimization strategies can include overall profit by accounting for Return to Vendor (RTV) agreements and scrap value, reducing financial losses while maximizing profitability. Collaboration is crucial, as users may prioritize goals like profit maximization, inventory clearance, or balancing sell-through with margins.

The two additional key factors for achieving advanced markdown are:

• Attribute Elasticity Identification - For new styles lacking historical data, especially in fashion, it is essential to analyze how attributes like color, fabric, and style impact demand sensitivity. By mapping these items to past attribute performance, retailers can estimate elasticity or lift from price drops, enabling optimized pricing and markdown strategies.
• What-If Scenario Planning - In Markdown, comparing multiple scenarios allows planners to override markdown percentages, recompute profit and inventory metrics, and compare outcomes with original recommendations. This enables data-driven decisions for optimized profitability and effectively managing end-of-life inventory.

Why Markdown Matters

Markdown optimization enhances inventory management, customer satisfaction, and long-term profitability while safeguarding brand integrity. Automated markdown solutions shift retailers from reactive responses to proactive, data-driven planning, addressing overstocking before it becomes an issue. This strategic approach benefits both operational efficiency and the overall customer experience. Key advantages include:

1. Improved Inventory Management - Strategic markdowns minimize profit loss, maintain healthy margins, and reduce spoilage by accelerating inventory turnover, preventing unsold stock write-offs, and lowering both financial and environmental impact.
2. Maximized Profit Margins - Effective markdown timing and pricing minimize profit erosion, enabling retailers to reduce prices strategically while maintaining healthy margins and maximizing overall sales and profitability.
3. Enhanced Customer Satisfaction - Markdown strategies provide competitive pricing, appeal to price-sensitive customers, and boost conversion rates.
4. Data-driven decision-making - Advanced analytics and AI-powered markdown tools, such as those from o9, facilitate accurate pricing adjustments using real-time data, eliminating guesswork.
5. Brand Value Preservation - Controlled markdowns prevent excessive discounting, protecting brand value and trust while clearing end-of-lifecycle stock and avoiding the overuse of frequent sales that condition shoppers to expect discounts.
6. Proactive Planning - Transforms markdowns into proactive, well-timed strategies, leveraging automation and campaign tracking to address potential issues before they escalate effectively.

Conclusion

Markdown strategies often fail when retailers overlook critical factors and adopt inefficient or overly generalized approaches. Markdowns are product-specific, but manually planning for every SKU without specialized software is impractical, leading to a one-size-fits-all approach that leaves money on the table or incurs losses. Additionally, markdowns are context-sensitive, influenced by timing, seasonality, and price elasticity, and ignoring these factors disrupts strategies. 

Common missteps include discounting high-performing items, over-discounting beyond sell-through needs, or applying insufficient markdowns to clear low-performing SKUs. These errors often stem from inefficient processes or lacking data, analytics, and tools for informed pricing decisions.

By leveraging AI technology, retailers can automate and optimize markdowns across the product lifecycle. o9 delivers impactful results by integrating real-time data, demand forecasting, and price elasticity calculations into a single, end-to-end system. These advanced tools recommend intelligent markdown strategies that clear dead stock by season’s end while maximizing gross margins, enabling data-driven, flexible, and profitable pricing decisions. 
Book a demo with our retail experts today to explore this transformative approach.