The EAN (European Article Number, now known as GTIN in the international GS1 nomenclature) is the unique numerical identifier assigned to every product on the market. The most common format is EAN-13 (13 digits), which appears beneath the barcode. It unambiguously identifies a product throughout the entire value chain: manufacturing, logistics, distribution, checkout, and e-commerce.
When it comes to pricing, the EAN code is the key that links internal data (inventory, sales) to external data (competitor reports, market panels).
A hypermarket chain wants to compare the prices in its yogurt section with those of three competitors. Without its own EAN codes, it must manually match each product by name, size, and packaging, with a success rate of
Reliable competitive monitoring and product matching prevent the comparison of non-equivalent products and ensure that repricing is based on verified matches at the product detail, EAN, and attribute levels.
With EAN codes, matching is instantaneous: the EAN 3033710065530 identifies a 4×125g plain yogurt from a specific brand, regardless of which retailer sells it. Matching 4,200 SKUs across four retailers takes just a few minutes instead of several days.
Using EAN codes for pricing requires two prerequisites:
1. a clean and up-to-date product database (each SKU must have its EAN entered, validated, and consistent over time) and
2. A matching system capable of handling special cases (changes to the EAN following product modifications, and items without an EAN, such as open-pack or bulk products).
Matching tools primarily use the EAN as the first matching key, then fall back on descriptive attributes if the EAN is not available.

The success of a pricing project depends not only on the tool, but also on a rigorous methodology that combines data quality with team buy-in. This structured approach allows you to move away from risky manual management and implement automated rules, thereby ensuring long-term profitability and commercial consistency. Talk to a pricing expert (Booper demo).

Excel limits retail performance by optimizing only 10% to 30% of catalogs. Switching to a dedicated solution automates decision-making and safeguards margins in the face of market complexity.
This shift is critical because 21% of retailers were still using spreadsheets in 2025, leaving themselves vulnerable to critical manual errors.

Effective pricing management requires the rigorous integration of internal/endogenous data (costs, historical data) and external/exogenous data (competition, demand). This essential integration helps secure margins and provides an objective basis for decision-making in the face of market fluctuations. By structuring these signals, the organization transforms raw data into a lever for operational profitability, which can be effectively implemented in less than sixty days.