Burberry's Bold Fashion Marketing Transformation with IoT
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Virtual Private Cloud
Applicable Industries
- Apparel
- Consumer Goods
Applicable Functions
- Sales & Marketing
Use Cases
- Clinical Image Analysis
- Time Sensitive Networking
Services
- System Integration
- Training
About The Customer
Burberry is a British luxury brand headquartered in London. Known for its bold, high-fashion apparel, Burberry uses thousands of images from multiple sources in its marketing campaigns. The company aims to capture the imagination, command attention, and win sales with its daring apparel. To do this effectively, Burberry needs to classify and annotate these valuable assets precisely. The company was already using Databricks, a single, unified analytics platform for all its stakeholders, and was looking for a solution that would integrate well with this existing system.
The Challenge
Burberry, a British luxury brand, faced a significant challenge in managing and annotating its thousands of marketing images. The company needed to classify these assets accurately to use them effectively in its marketing campaigns and drive the right action by the right audience. Burberry initially tried using an open-source tool for image annotation, but it had serious drawbacks. The company was looking for a solution that could improve the data for training its models quickly and easily. They wanted to produce labels for thousands of images and place them seamlessly into a model development pipeline for convenient reuse. The challenge was to find a solution that would integrate well with Burberry's existing Databricks implementation, a single, unified analytics platform for all its stakeholders.
The Solution
Burberry implemented Labelbox within its Databricks Lakehouse Platform environment to efficiently annotate its marketing assets. Labelbox was chosen due to its tight integration with Databricks and its customer-centric purchase process. The implementation process was straightforward, with Burberry importing images to Labelbox from their Amazon S3 bucket via API. Once Labelbox was officially selected, Burberry connected it to the company's core virtual private cloud and S3, treating images just like any other data set within its Databricks Lakehouse Platform. The solution was up and running within a month for the data science team members, and business and marketing users were also onboarded expediently. Burberry continues to rely on Databricks Unity Catalog to keep data secure and comply with data privacy regulations.
Operational Impact
Quantitative Benefit
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