Case Study: Burberry achieves faster marketing image insights with Labelbox

Burberry cuts image insight time from 2 months to 2 hours with Labelbox

Burberry, a British luxury brand, faced the challenge of manually classifying thousands of marketing images from various sources to use in its global campaigns. This high-volume, unstructured data required precise object detection and classification models to identify specific products, a process that was not feasible to do by hand. The company turned to Labelbox for a dedicated solution to this problem.

By implementing Labelbox within its Databricks Lakehouse Platform, Burberry connected the tool to its cloud storage via API and was operational within a month. This solution automated the generation of visual signal data for model training, turning a two-month analysis process into a two-hour self-service task for marketing teams. The results for Burberry included saving an estimated 10 headcount, a 70% improvement in time savings for generating insights, and four years of continually decreasing total cost of ownership. Labelbox provided the insights necessary to predict image engagement and continuously optimize marketing campaigns.

Burberry