For eCommerce businesses, especially those navigating the competitive landscapes of the UK, USA, and Canada, there’s a constant tension between clearing inventory and preserving profit margins. At the heart of this struggle lies the markdown rate – the percentage by which you reduce a product’s price from its original. While necessary, excessive or poorly timed markdowns can silently, but relentlessly, erode your bottom line.
The Markdown Merry-Go-Round: A Mid-Market eCommerce Challenge
Overstocking is a significant problem, costing businesses an estimated $362.1 billion annually. For a mid-market eCommerce company (let’s say, in the $100 M-$250 M revenue range), this is a critical issue. You’ve invested heavily in a new product line, but sales aren’t quite hitting projections. Inventory starts to pile up in your warehouses. Every day it sits there, it’s costing you money in storage, insurance, and lost opportunity. These inventory carrying costs can be a staggering 20% to 30% of your inventory’s value annually.
To free up capital and space, you initiate a markdown. It works! Products move. But did you discount too much, too soon? Or perhaps not enough, and now you’re looking at even deeper cuts later? This cycle leads to:
- Eroding Profitability: The most obvious casualty. Every percentage point off the original price directly hits your gross margin. According to McKinsey’s “Why Markdown Pricing Matters More Than Ever,” 74% of consumers (rising to 87% among Gen Z) are actively trading down, seeking lower price alternatives or waiting for sales. That shifts the balance: aggressive markdowns may move volume, but they erode full‑price selling and set new customer expectation baselines. AI-driven solutions can help improve incremental margins by 300 to 500 basis points. Think of it like a leaky faucet: each markdown is a drip, and while one drip won’t empty the bucket, a thousand tiny drips over time will leave you with nothing. These small, frequent leaks from an over-reliance on markdowns can cumulatively drain your entire profit potential.
- Devalued Brand Perception: Consistent, deep markdowns can teach your customers to wait for sales, making them reluctant to ever pay full price. When your brand becomes synonymous with discounts, customers stop associating your products with quality or value at the full price. This erodes the perceived value of your entire catalog. Instead of being a brand that commands full price, you become a “discount brand” in the eyes of your most loyal customers.
- Operational Headaches: The unpredictable nature of sales and returns from markdown events can strain your logistics and customer service teams. Imagine trying to run a marathon with a sprained ankle. That’s what a reactive markdown strategy does to your operations. A sudden spike in demand for a discounted item can overwhelm your fulfillment center, leading to shipping delays and a flood of customer inquiries. Conversely, a markdown that fails to move product leaves you scrambling to free up warehouse space.
- Cash Flow Constraints: Capital tied up in slow-moving inventory prevents investment in new, high-potential products. This is the opportunity cost of overstocking. Every dollar stuck on a shelf is a dollar you can’t use to innovate, market a new product, or improve your website. It’s like a traffic jam on your business’s financial highway—the slow-moving inventory blocks the flow of capital, preventing you from reaching new and profitable destinations.
The core problem? Uncertainty. You’re often reacting to inventory issues rather than proactively managing demand. This is where the power of advanced analytics, specifically demand forecasting, can be a game-changer. Despite the clear benefits, Gartner research indicates that only 40% of high-performing businesses have adopted AI in this area, highlighting a significant opportunity.
Breaking the Cycle with Smarter Demand Forecasting
What if you could predict, with a high degree of accuracy, how many units of each product would sell over a given period? This is the promise of robust demand forecasting, and it’s no longer just for retail giants. Zara, for instance, has long been a case study in leveraging data for lean, responsive supply chains. Gartner’s 2024 Data & Analytics Trends report stresses that decision intelligence (forecasting + proactive scenario modelling) is increasingly a differentiator for organizations.
Brands that embed forecasting and pricing optimization into their operating model outperform peers in margin retention.
By leveraging machine learning, mid-market eCommerce businesses can move from reactive discounting to proactive, profitable inventory management. AI-driven forecasting can reduce forecasting errors by 20% to 50%, leading to leaner inventories (by 20% to 30%) and fewer stockouts (up to 65%).
How AWS Can Turn the Tide: Forecasting & SageMaker
Here’s how modern cloud-based AI/ML services can empower your business to tackle markdown woes:
AWS Forecast: Your Predictive Powerhouse
AWS Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts. It’s built on the same technology as Amazon.com’s own forecasting systems.
- Automated ML: You don’t need a team of data scientists to get started. Feed it your historical sales data, pricing data, promotional events, even external factors like holidays or weather, and Forecast automatically trains models, selects the best algorithm, and provides predictions. This automation takes the guesswork out of the process, allowing even smaller teams to leverage powerful predictive capabilities without a massive upfront investment in talent.
- Granular Insights: Predict demand at the SKU level, for specific regions (UK, USA, Canada), or even down to individual product variations. This precision allows you to identify slow movers much earlier, preventing them from becoming an overstock liability. It’s like having a crystal ball for every single item in your warehouse, giving you the foresight to make smart decisions long before a problem arises.
- Proactive Inventory Planning: With accurate forecasts, you can optimize your purchasing and production, reducing overstocking and the subsequent need for heavy markdowns. You’ll know precisely what to order and when. This shifts your business from a reactive state—always putting out fires—to a proactive one, where you’re consistently two steps ahead of the market. This disciplined approach builds a foundation for long-term, sustainable growth.
Amazon SageMaker: Customization and Optimization
While AWS Forecast offers powerful out-of-the-box solutions, Amazon SageMaker provides the flexibility to build, train, and deploy custom machine learning models at scale.
- Tailored Markdown Optimization: Beyond just predicting demand, SageMaker can be used to build models that optimize markdown strategies. For example, it could predict the optimal discount percentage for a specific product category to maximize profit given its predicted sales velocity. This fine-tuned control is the difference between a blunt instrument and a scalpel—it allows for precise, profitable actions instead of broad, margin-damaging discounts.
- Dynamic Pricing Strategies: Integrate SageMaker models to adjust prices dynamically based on real-time inventory levels, competitor pricing, and predicted demand elasticity. This allows for more nuanced markdowns that respond to market conditions. This is the difference between a static price tag and a smart, responsive pricing engine that constantly seeks to maximize revenue.
- Experimentation and A/B Testing: Use SageMaker to run experiments on different markdown strategies and measure their actual impact on sales and profitability before rolling them out widely. This data-driven approach removes emotion from the equation, ensuring that every pricing decision is backed by evidence. It’s like having a scientific lab for your pricing strategy, allowing you to test hypotheses and discover the most profitable paths.
The Path Forward: From Reaction to Precision
By integrating AWS Forecast and potentially SageMaker into your eCommerce operations, you can transform your approach to inventory and pricing:
- Reduce Markdown Depth and Frequency: Sell more at full price by accurately aligning supply with demand.
- Improve Cash Flow: Free up capital that would otherwise be tied up in excess inventory.
- Enhance Brand Value: Maintain consistent pricing and avoid the perception of being a “discount retailer.”
- Boost Profitability: Directly impact your bottom line through optimized pricing and reduced losses from overstocking.
The McKinsey State of Fashion 2024 report forecasted global fashion growth stabilizing in the low single digits (2‑4%). This means brands need to tighten control on costs and avoid markdown overhangs – margins will not get easier just because volumes slow. eCommerce businesses struggling with markdown dependency have a path forward – precision forecasting powered by AI. By combining predictive intelligence from tools like AWS Forecast with customization from SageMaker, businesses can build a scalable markdown strategy that preserves margin, improves agility, and elevates brand value.
