In a competitive business environment, the ability of retailers and brands to monitor and adjust their prices quickly has become a major strategic lever. This monitoring of competition is no longer limited to the simple observation of the prices charged by competitors, it now involves in-depth work on the matching between private labels (private labels) and equivalent products. This step is necessary for retailers looking to maintain their competitiveness and margin, adjust their pricing strategy and capture the attention of consumers, who are increasingly aware of price differences.
The challenge for retailers: the matching of private labels
In many areas, retailers are increasingly developing their own private labels to offer competitive alternatives to big brands. In sectors such as toys, for example, where each distributor offers its own references in addition to those of historical brands, it becomes complicated to make a direct comparison between similar products. This complexity lies mainly in the differences in coding: each private label product has its own EAN code, its own name and a separate title, even if, in essence, the product is identical.
To ensure effective competitive intelligence, distributors must be able to compare equivalent products and adjust their prices accordingly. And the real challenge lies in the ability to automatically match disparate SKUs, an essential step in applying rapid repricing strategies without having to go through tedious and lengthy manual operations. And without this correspondence work, retailers miss out on opportunities for alignment or price differentiation with their competitors.
Traditional tools struggle to meet this challenge, as they often rely on matches based solely on EAN codes. Fortunately, there are now advanced price monitoring solutions, powered by artificial intelligence, capable of analyzing product characteristics (dimensions, materials, ingredients, features, etc.) to suggest likely matches. For example, in the cosmetics sector, two beauty creams of different brands, but sharing similar characteristics (capacity, ingredients, fragrance, etc.) can be considered equivalent despite having different EAN codes. And this ability to identify matches will directly influence the repricing strategy. Without this, distributors risk either undervaluing their prices, losing margins, or overvaluing their products, at the risk of losing competitiveness. In addition, promotions and commercial actions require constant monitoring of the prices of equivalent products to maximize their impact.
The challenge for brands: comparing equivalent references
For brands, the challenge of matching is just as strategic. Identifying equivalent competing products allows you to adjust your price positioning and react quickly to market movements. However, this approach presents its own challenges: determining which products are actually comparable often relies on the end customer's perception. Brands must evaluate the similarity of products according to their own criteria and their knowledge of the customer, a time-consuming and subjective process.
Brands must also take into account the specific criteria of the market. For example, in industries where the brand is of little importance (such as office supplies), consumers mainly compare prices. Conversely, in sectors where brand image is essential (cosmetics, fashion), matching must be more refined, taking into account the notoriety, perceived quality and positioning of competing brands.
As with retailers, repricing solutions can offer brands artificial intelligence algorithms that can automatically submit product matches. These systems analyze various criteria (brands may have more or less latitude on the choice of these criteria upstream) such as technical characteristics, ingredients and uses to generate relevant suggestions. These proposals are then submitted to the client, who can validate or adjust them according to their needs.
Let's take a concrete example with office supplies: for a basic product such as a roll of brown "moving" tape, the end customer is often indifferent to the brand and focuses on the price. Brands must therefore monitor their direct competitors, but also all equivalent products (roll size, weight, packaging, etc.) to remain competitive. By adopting high-performance matching tools, brands can refine their competitive intelligence strategy, detect positioning opportunities and adjust their prices in a more dynamic and responsive way.
The different methods of reference matching
There are several approaches to matching equivalent references. Here are the main ones:
- Manual with Excel :
- The customer creates an Excel table in which he manually fills in all the correspondences between these products via the EAN codes. This method offers full control but is time-consuming and error-prone.
- Manual in the repricing application :
- The customer performs the matching directly in the repricing application. In case of no EAN code, it can copy/paste the URL of the equivalent product, the algorithms of the solution will take care of the rest. This method is more flexible but remains largely manual.
- Semi-automatic :
- Repricing tools equipped with AI algorithms generate matching suggestions. The customer then has a validation interface where he can accept or correct the proposed matches. This system lightens the workload while maintaining human control.
- 100% supported :
- Price Observatory offers full support for the process. The algorithms suggest matches, which Price Observatory's teams validate based on the information provided by the customer. This method completely frees the customer from the operational process while ensuring reliable results.
The matching of private labels and equivalent references is an essential pillar in competitive intelligence and repricing strategies. Whether for retailers or brands, the precise identification of competing products allows them to refine pricing strategies and optimize their competitiveness in the market. Between still manual methods and fully automated solutions, each professional must place the cursor in the best possible way, taking into account his budget, his needs and his internal resources to take full advantage of competitive data.
