Definition
Why it's important
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.
A concrete example
An online retailer is selling the "Samsung Galaxy S24 Ultra 256 GB Black." At competitor A, the product is listed as "Galaxy S24U 256GB Black." At competitor B, it appears as "Samsung S24 Ultra 256GB Phantom Black." The matching algorithm uses EAN codes, product attributes (brand, model, capacity, color), and machine learning to identify that these three listings refer to the same product. Once the match is established, the system can compare prices reliably and automatically.
How to do it
Matching by EAN/GTIN: the most reliable method for manufactured goods. If two products have the same barcode, they are identical. Limitation: not all competitors display EANs.
Attribute matching: characteristics (brand, model, size, color, etc.) are compared. This requires standardizing the data (Samsung vs. Sam., 256 GB vs. 256GB).
AI-powered matching: Machine learning algorithms analyze product titles, descriptions, and images to identify matches even when no EAN is available. This is a powerful method, but it is more complex to implement.
Common Mistakes
Learn more
Frequently Asked Questions

Facing a sudden drop in conversion rates because your competitors are adjusting their prices in real time means you need to equip yourself with the best data-driven retail pricing strategy tool for 2026 to stay competitive. Price transparency in 2026: Retailers are automating pricing to protect their margins against inflation, improve omnichannel responsiveness, and generate a quick ROI.
Discover how these tools automate your specific business rules while ensuring complete strategic control over your brand image and delivering a measurable return on investment in less than six months.
This detailed comparison analyzes specialized platforms capable of predicting price elasticity and managing your omnichannel inventory to turn every piece of raw data into immediate, tangible profit.
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.