Data and Cloud Technology
Trade | Logistics
Binx.io and GoDataDriven |
Part of Xebia
For more than 100 years, Royal FloraHolland, a cooperative company of growers, has organized supply and demand to help deliver optimal price and low transaction costs for international flower and plant growers and buyers. With its online trading platform Floriday and world-famous live auctions, the company handles over 145,000 transactions per day from among 400,000 varieties of flowers and plants.
The enormous Aalsmeer auction facility, which sprawls across over 128 acres near Amsterdam, serves as a tourist destination where visitors can immerse themselves in the international flower trade.
Connecting Growers and Buyers Worldwide Through Data-Driven Systems
Royal FloraHolland needed to upgrade its digital technologies and adopt more data-driven practices to stay on the cutting edge. With the high volume of transactions on Floriday and the auction house floor, they needed the versatility and expandability of cloud-based infrastructure to collect and organize data and automate operations. The world’s largest flower auctioneer also wanted a way to gather feedback from buyers to better serve both customers and suppliers.
Leading the Floral Sales Marketplace
To provide the best service, the cooperative company was looking for ways to improve a variety of issues. Predicting trolley deliveries and checking efficiency internally, while improving flower photo quality and communicating with both growers and buyers for feedback were priorities. Royal FloraHolland knew that to continue to thrive and expand they would need systems that would grow and evolve with them.
Building Systems To Predict, Learn, and Communicate
Royal FloraHolland continues to lead the flower industry utilizing Xebia’s microservice-based architecture through Amazon’s S3 Elastic Container Service (Amazon ECS). The platform implements AWS architecture, CloudFormation, and automated deployment pipelines. Containerized machine learning technology and digital greenhouse applications enable the company to grow with accurate data for trolley predictions. Machine learning tools have increased the quality of flower photos used for auction, leading to higher customer satisfaction. With the recommendation application also built using a deep learning model, Royal FloraHolland’s buyers now share their experiences, helping other buyers find the right product and helping sellers meet supply and demand. Royal FloraHolland now operates more efficiently and effectively through data-driven applications and machine learning technology.