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FAQ

FAQ1: What criteria are your algorithms based on to compare my products with those of my competitors?

We start with the product from your own repository and compare it to the vacuumed information. Several comparison criteria are taken into account: wording, price, nomenclature, characteristics, etc.

Product line complexity

Retailers can have a wide range of products, and each product can have many variations. Identifying the exact match between two similar products can be difficult.

Variability of product descriptions

Different retailers may use different terminologies or abbreviations to describe the same product. This makes matching difficult. For example, a built-in dictionary would be needed to translate commonly used abbreviations.

Differences in product codes

Some industries use different types of codes to identify their products, such as EAN 13, CIP 13, CIP7, etc. Matching these codes requires a cascade approach.

Products without direct correspondence

Some products, such as private labels (Private Brands), may not have exact equivalents among competitors, requiring manual matching based on a proximity score.

Constant inventory update

With the constant addition of new products to the market, a monitoring system is necessary to quickly detect these new products.

An effective matching system offers several major advantages for retail brands:

  1. Competitive pricing – By accurately identifying competing products that match those in your inventory, you can adjust your prices accordingly to stay competitive.
  2. Effective Competitor Analysis– With effective product matching, you can quickly compare your competitors’ assortment, allowing for more in-depth market analysis.
  3. Responsiveness to new products – An effective monitoring system alerts you to new products entering the market, allowing you to react quickly.
  4. Reduced Errors– Using tools such as the built-in dictionary, matching errors due to terminology can be reduced.
  5. Strategy customization – With proximity score calculation methods, you can adjust the criteria according to your pricing strategy, guaranteeing personalized matching.

Use of unique codes: EAN codes are commonly used to uniquely identify products, facilitating automatic matching.

Built-in dictionary: To translate common abbreviations and terminologies, reducing matching errors.

Cascade matching: This technique manages different types of codes to identify products, allowing precise matching between various types of codes.

Calculation of the proximity score: This method takes into account criteria such as codes, labels, etc., to determine the similarity between products.

Product differentiation: The tools allow you to distinguish identical, comparable and comparable products with coefficient, taking into account variations such as capacity or quality.

New product monitoring: Monitoring systems quickly detect new products on the market, allowing retailers to stay up to date with market trends.

Thus, by combining these techniques, retailers can obtain a robust and efficient “product matching” system.

The proximity score module uses different calculation methods to evaluate the similarity between products. These methods take into account various criteria such as codes, labels, EAN codes and many others.

The aim is to make it easier to find and compare products. In addition, you can adjust the weights assigned to different criteria to obtain a matching adapted to your pricing strategy.

This feature is designed to handle different types of product codes, such as EAN 13, CIP 13, CIP7, etc.

These codes are commonly used in various industries. Although we have integrated a wide range of codes to cover as many sectors as possible, we recommend that you contact us directly to discuss your specific needs.

Our team is always ready to work closely with you to ensure successful integration into your field of activity.