La Redoute path of innovation trend forecast

La Redoute: How the French brand can continue its path of innovation through trend forecasting

Key takeaways

  • La Redoute has an impressive history, going from a household catalog to e-commerce retailer in its 180-year history through various digital innovation strategies.
  • Data-driven trend forecasting is one way that the French brand can more accurately plan collections for its diverse customer base.
  • The future of fashion is sustainable, and La Redoute has already made significant efforts to become more eco-conscious--with the exception of trend AI-based trend forecasting.

Over 180 years ago, the first worsted spinning mill was opened in the wool region of France by a man named Joseph Pollet, and the story has it that Pollet reconciled “variety, low prices and good taste.” Today, that spinning mill goes by La Redoute, a household name for all things lifestyle.

La Redoute now has over 10 million customers worldwide, and in 2019 their revenue stood at €875 million. The brand has managed to reinvent itself over the years to stay in line with the times, accommodating shifting tastes, social values, and new technologies, which explains La Redoute’s 180-year legacy that’s still going strong. But is it possible to improve even further?

La Redoute catalog 1978
La Redoute catalog 1978

La Redoute’s savoir-faire in digital innovation

La Redoute is remarkably agile in its integration of data in the business model. The evidence is weaved into the brand’s lexicon: according to an official statement on their website, “At La Redoute, we consider data to be an important key to performance, as it informs each and every decision we make.” For instance, in 2018 La Redoute joined “Lafayette Plug and Play,” a platform designed to connect retail and e-commerce companies with innovative startups to accelerate their digital transformation. And the list goes on, from in-app voice recognition to facilitate online shopping, to a dialogue interface on Google Home and Siri. 

La Redoute’s digital prowess is impressive, and in their words, the brand is “committed to advanced data processing, which allows us to learn from the past in order to accurately perceive the future.” This sort of approach is the right mentality to have when it comes to delivering desirable products: combining past data to accurately predict the future is the most rounded approach in the fashion and lifestyle industries today. Evidently, La Redoute is on the right track to take their openness to AI in fashion one step further.

La Redoute SS20

Fashion trend forecasting is explained by its namesake, and when it’s powered by artificial intelligence, its technology can draw data to predict trends’ future behavior in a variety of different applications. The richness of this technology can enhance a brand’s entire strategy, from collection planning to marketing. And fortunately, La Redoute has already voiced a certain receptibility to such a technology: “…Data is key in helping us to integrate new technological innovations (voice interface, visual recognition, artificial intelligence) on an ongoing basis as they become relevant.” So how can AI-backed trend forecasting be applied to manifest tangible, positive results for La Redoute? 

Innovating the art of collection planning 

La Redoute is an impressive amalgam of in-house creations and external brands. With collaborations with top French brands such as Sézane, it’s no surprise that more than 70% of their turnover comes from their own brands and creations. La Redoute has a distinct French identity, derived not only from the aforementioned collaborations with the brand’s personal design team, but also from their own trend office.

La Redoute x Sézane

There’s no doubt that La Redoute has no shortage of creative inspiration when designing clothing collections. And with an injection of AI-based trend forecasting, the sky’s the limit. Visual recognition technology, in which La Redoute has already expressed interest, can be applied to images shared on social media to pinpoint different fashion attributes, from colors, to textures, to silhouettes, and more. This data can then be translated to predict a trends’ increase or decrease in desirability and visibility, their geography, and their customer segmentation, up to one year in advance.

For instance, the color indigo is predicted to rise +7% in Summer 2021 for womenswear in Europe. Pants will be the most desired clothing category for the color, particularly among mainstream consumers. La Redoute doesn’t currently have this soon-popular shade of blue in their pants category yet, affirming that this is the sort of data that can help guide designers’ creative visions, or back intuitions they may already have had. Merchandisers and marketers can more easily open their ears to the language of designers when concrete data is implicated, and as a result, collection planning becomes a more streamlined, more sure process. 

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A brand image that stands the test of time

If La Redoute has managed to remain relevant over 180 years, it’s because they’ve listened and responded to the ever-changing values and desires of consumers. Beyond fostering a successful digital transformation as well discussed, La Redoute has also democratized trendy fashion at affordable prices and pushed for a more eco-conscious fashion future. The brand has introduced more sustainable fabrics, excluding fur entirely, and is a member of a list of sustainability organizations. With their focus on sustainability already quite advanced, the addition of AI to their efforts could take La Redoute one step closer to a greener industry. 

Trend forecasting is an indispensable facet of a fashion brand’s eco-conscious vision. Why? Because trend forecasting provides data on where in the world a trend will be desirable, in which season and for how long, and for which type of consumer. With this data, La Redoute can accurately plan their collection assortments in terms of both quantity and types of products to reduce waste, every time.

photo profil de l'auteur, Mélanie Mollard

About the writer: Mélanie Mollard, Fashion Content Writer

Mélanie writes about the fashion industry and its many features through the lens of AI and applied data.

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