Retailers have a love-hate relationship with markdowns. Love to quickly clear out unwanted inventory (and recoup at least some money) and hate not getting full price.
Markdowns are virtually inevitable; it’s just not possible to always satisfy customer demand exactly. So they are both a useful tool and a necessary evil.
You mustn’t treat the process as an afterthought. Doing so is both inefficient and ineffective, costing you in diminished profits and margin losses. Just to move inventory that could have yielded profit with the right approach.
But even using traditional markdown methods—relying on experience and consistent trends over the years—is problematic in today’s dynamic environment, which demands extraordinarily nimble, well informed, and data-driven, insightful decision making.
As we entered 2023, only 30 percent of US retailers were confident about maintaining positive margins and profits1. Thanks to inflation, even though average weekly income in the US rose 8.3 percent since December 2020, real earnings have fallen by 5 percent2. Not surprisingly, many consumers are prioritizing essentials over discretionary purchases.
Retail inventories are piling up. Out come the markdowns.
Five Components to Creating a Smart Markdown Strategy
A smart markdown strategy requires you to have a holistic view of your portfolio and an understanding of the factors affecting various SKUs. One-size-fits-all approaches will not work.
1) Focus on the Right KPIs
Start by identifying the right key performance indicators (KPIs) for every product across its entire lifecycle and continuously monitor, measure, and adjust. Do this properly and you won’t miss opportunities or unexpectedly be forced to accept margin losses. Something as simple as having monthly targets works towards ensuring you keep track of expected vs. actuals.
Bear in mind you’ll have to fine-tune your KPIs for different stores and markets
to get the best out of any markdown strategy. What works for one store or market likely won’t be as effective for others; you’ll need to consider factors such as seasonality, local events, and demography. Localizing your markdown strategies will prevent margin losses from a high demand market while also ensuring you clear out inventories from markets with fading demand.
2) Know the Price Elasticity of Key Value Items
There’s no substitute for knowing the price point at which a product has the highest propensity to sell. Price elasticity is a key factor here. Understanding elasticity—elastic products really move when you reduce the price; inelastic products, not so much—in your portfolio’s Key Value Items (KVIs) will maximize the odds you get the most profit per product.
We’ve developed a simple tool for determining the ideal price change required to maintain the margins at the same level for a given product. Try out the Impact Analytics pricing inflation and elasticity calculator.
3) Know the Product Lifecycle for Long-Term Strategy
Before you’re able to plan a product’s markdown strategy, you must know its lifecycle. No product stays at the top of its game unchanged forever. To know when to expect a sales slowdown—the best time to plan for markdowns—you need insight into when a product is likely to achieve maturity and then saturation and decline.
A comprehensive, AI-powered pricing solution will be enormously useful here. AI finds trends and patterns in huge amounts of historic data and generates iterative markdown scenarios in support of your targets for sell-through, margins, revenues, and more.
4) Use Scenario-Based Planning
To get a clear picture about what constitutes the right markdown—how much to discount for what products in which stores, for how long, and when—requires you know the demand for every product over a range of prices during the year. Retailers have typically followed a blanket markdown approach for various categories of products but, thanks to differing price elasticity, lifecycles, and other factors, different products respond differently to the same markdown.
The key is to evaluate which scenario works best in every situation. For example, a markdown that’s effective in the initial phases of a product’s lifecycle may fall flat when applied toward the lifecycle’s end. Buy one get one (BOGO) free offers, while similar to flat 50 percent offers, clear out double the inventory for every transaction, which may be exactly what you need. Same for smartly pairing low-demand products with hot sellers in a way that accelerates sales for both.
5) Continuous Demand Forecasting
Accurate demand forecasting is a key to retail profitability. And, here again, AI is a key to success.
AI, and especially machine learning (ML) algorithms, quickly generate highly granular forecasts based on a mind-boggling array of historic and real-time data. And unlike time-bound spreadsheet-based predictions, ML models are always and automatically refreshed with the latest information to continuously improve forecast reliability.
Retail Price Optimization with Impact Analytics PriceSmart
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1. Survey of 50 retail industry executives commissioned by Deloitte and conducted online by an independent research company from October 21 to October 31, 2022.
2. Bureau of Labor Statistics, “Establishment Survey,” sourced through Haver Analytics in November 2022.
