Sonepar is an independent family business of 145 operating companies in 48 countries with worldwide market leadership in B2B distribution of electrical products, solutions and related services. Sonepar has one million customers, 48,000 employees and 3,000 offices worldwide.
Sonepar has a range of many millions of products. Sonepar uses the ETIM standard in order to properly exchange product data in the chain. All products are classified in the ETIM class structure and are described in a standardized manner. Suppliers are asked to supply the product data in ETIM format. However, not all suppliers are able to deliver in this way. Products are often provided with one long product description in which both the name of the product and some product characteristics are incorporated. Unraveling these unstructured product data had to be done manually, which took an enormous amount of time, with the result that products were sometimes incomplete or not even included in the range at all. That is why Sonepar was looking for a smart software solution where the product data can be identified and extracted in an easy and clear manner.
The PowerImprove.ai solution from Squadra Machine Learning Company uses artificial intelligence to understand the different phrases, spellings and abbreviations and knows how to identify and map them in a smart way with the Sonepar ETIM standard. As a result, the product characteristics are automatically extracted from the long product descriptions, which are presented to product data stewards for validation.
The system is trained on the Sonepar ETIM data model and in the languages in which the products are described. A data steward can also add rules that make the extraction even smarter.
With the help of the Powerextract.ai software, Sonepar can also include products from suppliers who do not yet use the ETIM standard faster and better in its range. The result is that more products have a richer specification and can therefore be sold faster and easier. This saves a lot of time compared to entering the properties manually. This saves time and money and ensures a higher turnover.