By Hemang Nathwani, CEO and Co-Founder at Price Trakker
Accurate product matching is a great starting point for any reliable pricing strategy. Yet even the best eCommerce teams face challenges when products lack identifiers such as EANs, MPNs, or GTINs. When items are incorrectly matched, pricing decisions can quickly become distorted. A product that seems overpriced might actually be a better specification, while one that appears competitive could be wrongly compared to something entirely different. The result is a pricing strategy built on flawed comparisons that can erode both margin and customer trust.
Why poor product matching skews your price strategy
For many retailers, accurate product matching is the foundation of any reliable pricing strategy. Yet even experienced eCommerce teams struggle with this when products lack standard identifiers such as EANs, MPNs, or GTINs. When a product is matched incorrectly, every related pricing decision becomes distorted.
Imagine a situation where your system believes a 10-piece cookware set from one brand is comparable to an 8-piece set from another. The price difference might seem to signal a competitive risk, but in reality, the two products are not equivalent. Reacting to that misinformation could lead to unnecessary price cuts or missed opportunities to improve margin.
This issue has become more visible as retailers expand across multiple marketplaces. Product data on each platform often varies in structure, naming conventions, and completeness. Even small inconsistencies in titles, sizes, or model numbers can cause automated matching systems to link unrelated products. The result is an inaccurate view of competitor pricing and unreliable market insights.
The impact extends beyond individual products. When mismatched items feed into wider pricing analysis, margin reports and category performance summaries become misleading. A brand might appear more expensive than competitors when, in fact, its products are simply higher specification.
To manage this, many eCommerce teams are turning to AI-based product matching systems that learn from detailed product attributes rather than relying on single identifiers. These systems compare features such as size, power, colour, and specification to determine whether two items are true equivalents. This helps make pricing intelligence far more accurate and allows retailers to benchmark performance fairly.
Consistent and verified product matching can also improve communication between buying, pricing, and merchandising teams. Everyone works from the same version of the truth, which helps strengthen decision-making and reduces the risk of over-reacting to competitors’ moves.
Price Trakker has spent more than a decade refining its approach to product mapping, working with thousands of retailers to improve matching accuracy across millions of products. That experience has now been enhanced with an advanced AI-powered engine designed to deliver even greater matching precision. By combining this depth of knowledge with automation, Price Trakker gives eCommerce managers the most reliable foundation for pricing and margin analysis.
For more information on AI-based product matching and data accuracy, visit Price Trakker, or learn more about our broader competitor price monitoring services at Price Trakker.
Data source: Price Trakker product matching research dataset, 2024
Published 11/11/2025
