Black Friday might be the biggest shopping event of the year, but blanket discounts can do more harm than good to your bottom line. So how do you know which products to discount, when, and by how much? Discover how retailers can move beyond one-size-fits-all promotions by bringing product information and pricing intelligence together.
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It is the same reflex every November: 30% off the entire site. The revenue chart looks impressive by Cyber Monday. Then January arrives, and the margin report tells a different story.
The real question is not how much to discount. It is which price, for which product, at which moment of its lifecycle. Answering it requires something most retailers still lack on Black Friday: product data and pricing working from the same page.
A blanket discount treats every product the same way. Your shoppers do not. According to BCG (2025), about 77% of consumers say they sometimes or often delay purchases earlier in the year to take advantage of year-end sales. Part of your Black Friday volume is demand you would have captured at full price, just a few weeks earlier.
The damage adds up fast. Margin disappears on products that never needed a discount. Prices drop to match a competitor, even when the products are not truly comparable.
Underneath sits a structural problem. The product lives in the PIM. The price lives in a spreadsheet. Black Friday is the moment that disconnect gets stress-tested, at scale and under time pressure.
If your pricing team cannot see what makes a product different, how can it decide what that product is worth?
Black Friday starts in October. In the EU, any advertised discount must be based on the lowest price applied in the previous 30 days. The European Commission’s 2026 sweep found that 30% of the 314 online traders checked presented discounts incorrectly. Your October prices set the reference for your November promotions.
Akeneo PricingHUB handles these price regulations natively: your teams set each constraint once as a business rule, and it applies to every price and promotion. Compliance stops being a last-minute check.
Trust is fragile too. Simon-Kucher’s 2025 Holiday Shopping Report found that only 46% of US shoppers believe advertised discounts fully reflect true savings. A credible discount starts with a credible everyday price.
Picture a grocery or DIY retailer with two rules: keep a 20% margin on organic products, and price its private label 15% below the equivalent national brand. Without structured data, the pricing team tags thousands of SKUs by hand before it can set a single rule. When attributes like “organic” or “private label” already live in the PIM, the rule is set once and applies across the whole catalog. Your price ladder survives the promotion.
Now take a running shoe sold in 15 sizes, 3 colors and two versions, Standard and Pro. Size 42 should never cost more than size 43. The Pro should always sit above the Standard. With a clean product structure, these consistency rules apply automatically, so your discounts start from a coherent range rather than a patchwork.
Every discount should earn its place. BCG (2025) recommends targeted promo plans that guide consumers toward assortments where the retailer has surplus or margin advantage. In practice: discount where stock is high or margin can absorb it, and hold your price everywhere else.
Price elasticity measures how much a price change shifts what people buy. On Black Friday, a TV is highly elastic: shoppers compare it across retailers, and a small price gap moves volume. The HDMI cable sold with it is not. Few people compare cable prices, so a discount there gives away margin for almost no extra sales.
Products also influence each other. Discount one TV, and part of its extra volume comes from a similar model you still sell at full price. This transfer, called cannibalization, is easier to anticipate when the system knows which products are true substitutes. That knowledge comes from product attributes: screen size, technology, brand, range.
Picture a seasonal campaign where merchandising, product marketing and pricing each work from their own files. Reconciling product lists with promotional prices can take up to 14 days of manual alignment. When product and pricing teams work from the same data, there is nothing left to extract or reconcile. The same campaign can go live in hours.
Your stores, your website, your country sites and your marketplaces do not face the same competition. Each deserves its own price. When optimized prices flow back into the PIM, they reach every channel alongside the right product content, with no manual exports.
It is Black Friday week, and your best-selling white t-shirt is priced at €15. A competitor drops its white t-shirt to €5. A disconnected pricing tool sees only the gap and matches it, wiping out €10 of margin per unit.
Now add product context. Your t-shirt carries the “organic cotton” attribute. Instead of slashing the price, your team enriches the product page to highlight that quality and holds the €15. The difference between destroying margin and protecting it is product context.
Black Friday ends, but the stock does not disappear. Some products leave the week with more inventory than planned, often in specific stores or regions. A blanket markdown before Christmas would repeat the same mistake twice.
A planned markdown starts at category level, not SKU by SKU. It accounts for the stock left on each product, in each location. It also measures how a price cut on one product shifts demand across the whole category, so a markdown does not simply pull sales away from similar products still at full price. The result is a discount path that clears remaining stock before the winter sales while protecting as much margin as possible.
Products that sell well keep their price. Slow movers get the discount they actually need.
None of this means handing Black Friday to a black box. Automation does not mean losing control. The AI surfaces patterns and recommends prices. Pricing experts validate them and turn them into lasting business rules.
Black Friday is also a workload peak. Thousands of prices to check, adjust and push to every channel, often by hand and against the clock. Akeneo PricingHUB automates that execution: one of our European retail customers now rolls out its optimized prices more than 50 times faster.
Automation does not mean handing Black Friday to a black box. The AI recommends prices and explains every one of them. Your teams validate, adjust and keep the final say, supported by a dedicated team of pricing experts.
Black Friday rewards retailers who know exactly what they sell and what it is worth. When product data and pricing are connected, every discount becomes a deliberate choice: which product, which channel, which moment. That is how Black Friday becomes a controlled decision rather than a bet on your margin.
Our platform is designed to optimise prices throughout the product lifecycle for retailers and e-commerce businesses. Our objective? To optimise your prices in a simple, automated and data-driven way. Our intuitive solution is centred around AI, a consumer-centric approach and pricing expertise.
👉 Meet our pricing expert here
