The Advent of Machine Learning At Burberry: How New Technology Is Impacting Luxury Brands

British brand Burberry is one of the biggest flag-bearers of machine learning and has transformed the brand across various aspects including client servicing, promoting personalized shopping and ensuring to steer clear of counterfeit products.

The executives at Burberry are trying to place the business as an end-to-end digital brand, making it one of the firsts in the retail industry.

The idea of adapting to machine learning algorithms allows for multiple advantages, some of the most unique one being letting brands discover the products that are trending so that they can then design their products accordingly.

How Burberry Is Adapting

Some of the major changes that executives have implemented at Burberry lie across various segments of the brand, leading from marketing and sales to strategy and development.

The brand is now collecting increased customer data through various loyalty programs and tracking relevant information at its digital and offline stores in order to better their services for customers.

Further, they are also using image recognition technology which allows them to recognize the authenticity of a product by merely looking at a small piece of the suspended products picture.

SVP of IT at Burberry, David Harris shares how customers at Burberry will now have the opportunity to create personalized ads allowing customers to see themselves next to their favorite celebrity.

Some of the main segments across which the brand intends to bring about machine learning techniques are chat bots in service functions, security and fraud prevention, image recognition, IT operations and logistics.

It is important to pay attention to the underlying fact which is to identify if machine learning truly streamlines functions across retail luxury brands where cost is not a consideration.

Apart from that, it is also beneficial to know the correlation between luxury products and customer preferences and how these function in real time.