Product Matching Farm for Retailers

Product Matching Farm for Retailers

High-quality, timely delivered competitor data is crucial for crafting a winning pricing strategy. Competera collects, processes and provides product matches with guaranteed 95% accuracy for brick-and-mortar and online retailers to optimize their pricing, outperform competitors and increase revenue.
Get a Demo
Competitive data crawling

Matchings updated*:


Scheduled scans

*last 24h
Product match and data processing

What is a product match? It is an identical or the same product sold by a competitor. Product matches are critical for retailers to map their position on the market and set optimal prices for revenue-driving products, as they provide data on how competitors price them.

Detecting identical products is time-consuming and challenging.

Retailers need to factor in many parameters, including a model name, version, color, technical characteristics, ISBN, availability, and discount. Exact matches are products with entirely the same features, while similar matches can bear a slight difference, for example, in color.

There are five main challenges retailers face when matching products:

  • Non-identical, but semantically similar product titles
  • Inaccurate, irrelevant, delayed or missing incoming data
  • Different product images
  • A significant difference between prices which indicates a mismatch

Data matching

Pain points

Data quality defines the profitability of a business since it is a basis for analytics and tactical decisions. A retailer with five competitors and 100 products in assortment requires 500 product matches. Thus, 20% of matches errors cause wrong prices for at least 20 products (sometimes the whole set of products, 100, is priced wrongly if all the matches mistakes do not intersect). If the retailer sells thousands of products, such errors lead to significant revenue losses on a much bigger scale.

Percentage of accurate comparisons is one of the primary indicators of data quality.

Competitor monitoring dashboard

Free White Paper Manual vs. Automated Matches Download Now

The Most Efficient Product Matching Approach

Hybrid product matching, which combines automatic data collection and further visual (manual) comparison, is a zero-mistake approach which ensures the best-in-class data quality by providing the highest possible percentage of relevant comparisons by many parameters.

Data comparison

How Competera Matches Products

The platform automatically collects and processes competitor data of any format from any source and presents it through custom visualized reports, which are later analyzed by human operators.

Retailers can choose between automatic, manual or hybrid product matches.

Visual Comparison Benefits

While automatic matching allows full crawling of a website right after retailers add a new competitor to the dashboard, a visual comparison has its advantages.

Relevant to any product categories from different industries (fashion, jewelry, among others), where automatic matching usually fails.
Access to extremely secured or complex competitor websites.
Ready-made matches available two hours after the products are added to the dashboard (as opposed to automatic matching which may take up to five days to set up).
Large capacity: over 50,000 high-quality daily comparisons.

Competera’s special algorithm of product search and multilevel checking uses an updated continuously comparisons data catalog, which improves the platform’s capacity and results.

Our product match team has expertise in different industries and markets.

Competera Product Match Pool’s Main Goals

Competera seeks to provide retailers with timely, transparent and accurate competitive data to enable their revenue-generating pricing decisions. To ensure the best quality of the service, we take the two following steps:

  1. We use the results of human-made visual comparisons to create learning schemes for automatic matching algorithms. It revamps the quality of machine-made matches and increases Competera’s capacity.
  2. We compare products manually if it is impossible to match them automatically, for example, if the data is collected from complex web pages with many buying options, e.g. perfumes or pet food.

We use the mixed matching approach to deliver a high percentage of comparisons by many parameters, with a small number of zero (unidentified) prices and an insignificant number of errors in the collected data.

Get a 95% accurate competitive data

Quick product comparisons, completeness, and data quality

Try Competera
Data crawling