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LVMH Strikes Deal With Google Cloud to Ramp Up AI Efforts

A wide-ranging deal between LVMH and Google Cloud includes codeveloping algorithms.

'Dior Recommendations'

Courtesy of LVMH

PARIS — LVMH Moët Hennessy Louis Vuitton has forged a strategic partnership with Google Cloud centered on artificial intelligence, throwing down the gauntlet as the luxury industry races to shore up its digital arsenal for a post-pandemic era.

Aimed at speeding up the development of cloud-based AI solutions to scale up LVMH brands, the deal covers issues ranging from demand forecasting to personalizing offers for clients, and includes the launch of a “Data and AI Academy” to share expertise.

“This new, unprecedented and significant partnership with Google Cloud is the reflection of our high ambitions in this area,” said Toni Belloni, group managing director of LVMH, in a joint statement. “By combining our best-in-class approaches in our respective industries, it will take us a step forward in the use of data and AI,” he added.

“Together we can help drive the future of customer experience in the luxury industry,” said Thomas Kurian, chief executive officer of Google Cloud.

LVMH will also draw on the partnership to update its IT infrastructure with a view to “fostering the agility, security, cost efficiency and performance at scale required to support its business ambitions,” according to the statement.

While LVMH has been working on subjects related to data and AI for the past three or four years — particularly in the realm of client relations, but also related to supply chains and production — the pandemic has sped up the issue, noted Franck Le Moal, IT director for LVMH.

“For the past 14 months, something happened that we didn’t expect — it’s true,” said Le Moal, speaking to WWD through Zoom.

The executive recalled that the luxury industry was faced with a challenge it hadn’t seen before — shifting to an omnichannel format from one day to the next. This called for daily interaction between sales people and clients, as well as drawing up extra services using data, he explained.

“We understood that we could go even further with better use of client data,” he said.

Le Moal cited Sephora, Louis Vuitton and Dior as leaders in the group in some areas, with Vuitton and Sephora employing machine learning to improve the efficiency of sales previsions, adjust production and improve merchandising.

“We thought that if we are able to do such things with these three labels, we must be capable of doing something through a significant investment at the group level, with the technological means, talent, a center of expertise, global data computing, we can offer these services and accelerators in the other houses,” the executive said.

Asked why the group chose to work with Google Cloud, Le Moal cited the possibility of codeveloping algorithms and components of artificial intelligence and machine learning directly with the company’s labs in Mountain View, Calif.

The partnership includes a training and education program centered on data, for executives working on issues like merchandising, client relations and omnichannel services, for example, according to the executive.

“We want to help our managers understand data, the use of artificial intelligence and machine learning more quickly,” he said. Such programs will be available virtually, as well as physically, perhaps at Station F.

The number of employees working on issues related to the digital realm at LVMH has grown significantly in five years — with a notable acceleration over the past two — noted the executive.

Asked to highlight some key areas where the partnership could make a difference, Le Moal cited increased personalization when it comes to offering the right product or look; merchandising with an eye to drawing up the right product assortments for a store; improving the accuracy of sales forecasts, and managing production.

“Our production system is very sophisticated and complicated, we use high-quality materials so the more accurate we are with sales forecasts, the better we will be able to adapt the materials we need,” he added, drawing a link to improving the environmental impact of the process.

The same goes for distribution, he noted.

“We are increasingly vigilant when it comes to the environment, we are increasingly vigilant when it comes to supply chains, transport — of course, we will use data to be as pertinent as possible — why send merchandise to a region where it won’t sell?”

“The power of data to help us adjust our commercial potential and distribution potential to make sure we have the right product in the right store and minimize returns and transfers — we think this can have a direct impact, and it’s starting to have a direct impact on some of our brands,” the executive explained.

Asked about sharing data between the brands, each label is in charge of its client data, the only sharing between houses would be anonymous data, like what kind of client likes a certain type of product, for example — no names or addresses, the executive stressed.

“We don’t want a client of Louis Vuitton, from one day to the next, to become a client of Dior Couture — the brands remain in a silo,” he said.

When it comes to the design process, marketing and design teams have access to data as “complementary information,” he said, like what worked well and what didn’t, why something worked well and what kind of client purchased a certain type of product.

“Design first, data after,” he said.

Le Moal cited sectors like high-end banking, tourism, and hotels as well as the car sector and tech companies as places outside the industry to look for best practices.


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