Case
Sligro
- 20.000 non-food products
- 84% increase in product findability
- 18% increase in orders
Sligro is a leading Dutch wholesaler of food and non-food products, specializing in the hospitality and retail sectors. The company stands out with its broad assortment of more than 78,000 items, customer-oriented approach, and innovative solutions for the hospitality industry and related sectors. With 50 regional self-service wholesale outlets, 8 delivery wholesale centers, and 2 strong franchise formulas, Sligro plays an important role in the Dutch food industry.
Challenge
Sligro faced the challenge of enriching data for approximately 20,000 non-food products. Initially, these products had only limited product attributes available. To provide customers with sufficient information about these products and thereby enhance the customer experience, Sligro decided to supplement the existing product attributes using external sources such as PDFs, images, and external websites.
However, manually entering product attributes proved to be a very time-consuming process, also prone to errors. Therefore, Sligro sought a solution to collect relevant product data faster, more accurately, and more efficiently.
Solution
Sligro asked Squadra to conduct two proof-of-concepts (POCs) for the product categories “pans” and “drinkware.” For this purpose, Squadra Machine Learning Company implemented their software product PowerImprove.ai , which uses algorithms to extract data from texts, images, PDFs, and websites. This enabled Sligro to automate the enrichment of product attributes.
Result
Thanks to the collaboration with Squadra Machine Learning Company and the use of PowerImprove.ai , Sligro efficiently and accurately enriched its product data. This not only led to an improved customer experience but also to remarkable results: the findability of pans improved by 84%, resulting in an 18% increase in the number of orders placed.
