Databricks Case Studies Burberry's Bold Fashion Marketing Transformation with IoT

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	Burberry's Bold Fashion Marketing Transformation with IoT Databricks

Burberry's Bold Fashion Marketing Transformation with IoT

Databricks

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	The implementation of Labelbox within Burberry's Databricks Lakehouse Platform environment has significantly improved the company's marketing operations. Image annotation projects that used to take months now take hours, and marketing team members now have access to powerful content insights without needing help from data scientists. The solution has also enabled Burberry to annotate a massive volume of images efficiently while finding edge cases that boost model performance. Furthermore, Databricks Lakehouse Platform continues to exceed Burberry's expectations, offering a lower total cost of ownership than initially projected. The company appreciates that Databricks and Labelbox price their solutions aligned to business value, which further enhances operational efficiency.

Impact #1

The implementation of Labelbox within Burberry's Databricks Lakehouse Platform environment has significantly improved the company's marketing operations. Image annotation projects that used to take months now take hours, and marketing team members now have access to powerful content insights without needing help from data scientists. The solution has also enabled Burberry to annotate a massive volume of images efficiently while finding edge cases that boost model performance. Furthermore, Databricks Lakehouse Platform continues to exceed Burberry's expectations, offering a lower total cost of ownership than initially projected. The company appreciates that Databricks and Labelbox price their solutions aligned to business value, which further enhances operational efficiency.

Benefit #1	10 head count saved by implementing Labelbox rather than building in-house
Benefit #2	4 years of continually decreasing total cost of ownership (TCO) with Databricks
Benefit #3	70% improvement in time savings for generating insights from images

Benefit #1

10 head count saved by implementing Labelbox rather than building in-house

Benefit #2

4 years of continually decreasing total cost of ownership (TCO) with Databricks

Benefit #3

70% improvement in time savings for generating insights from images

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Overview

Burberry's Bold Fashion Marketing Transformation with IoT

Operational Impact

Quantitative Benefit