How the fashion industry is applying Big Data and AI

Season after season, retailers come up with loads of new products ready to hit shelves worldwide. While at one time, designers had no idea what their customers would like and their creations were merely assumptions based on inspiration, now with the support of data, it’s easy for a retailer to cater exactly to what the customer needs.

The fashion industry, like many industries we’ve mentioned before on the blog, is also undergoing an important shift on various levels. Reduction of waste, shopping platforms and technology are only some of the changes we, as consumers, will experience in the coming years. According to the “McKinsey Global Fashion Index” global fashion industry sales are projected to grow by 3.5 to 4.5 percent this year.

Today we will focus on how technology will create a positive impact on the fashion industry, and what brands have already incorporated Big Data and AI into their DNA. Business of Fashion (BoF) estimates that more than 75% of fashion retailers plan to invest in AI in 2018/2019.

We are living in a connected world, and there is no denying that a large percentage of our day is spent near a screen. This has created a shift towards online shopping, sustainable brands and behavioral changes such as “showrooming”, when a customer visits a brick and mortar shop only to complete a purchase online. According to the “The state of Fashion 2018” report by BoF, “$1 trillion USD are expected to be spent by global consumers across e-commerce platforms by 2020” this means that traditional points of sale need to be reinvented, to offer better experiences if they want to keep thriving.

By introducing and investing in Big Data and AI, brands now have the power of added knowledge about their products, their customers, and the demand, and with it, make changes in their business model, supply chain and procedures to make more profits, generate less waste, and personalize experiences, which is exactly what clients demand today.

“What artificial intelligence (AI) can do is help turn large and diverse data sets into enriched information that can be used to improve the entire supply chain, from design and manufacturing to sales, marketing and customer service.”

Certain brands that have received significant recognition have started online, and once consolidated, have moved into opening retail shops in prime locations. The true value from being an ecommerce first, and opening a retail location second, is the power to identify where to find your customers. Retailers like Warby Parker (glasses), Everlane (apparel) and Glossier (cosmetics) who all started out as an e-commerce, have been able to build a long list of faithful clients. These particular brands have been able to determine where a physical shop would generate the most profit, by identifying which cities make the most purchases, which products people like the most, and which sold-out items to keep producing again and again.

Combining data with personalization, two American brands have created successful e-commerce shops by providing personalizes outfit boxes. Rockets of Awesome and Stitchfix use data from surveys, style quizes and sales, to identify which items resonate most with each customer, to give them an “personal shopper” experience right at home. In the case of Rockets of Awesome, dedicated to children only, their data helped them figure out why a particular sweatshirt kept selling out (the soft cotton material) which led to the buying department to purchase that same fabric in several colors and patterns. This purchase was data-based, and assured them it would only bring in profits, and satisfied customers.

Stitchfix, focused on apparel for all ages, uses a similar technique, and depends on their algorithms to tell them what customers are more likely to choose, and even how high or low is their level of risk taking.

These online interactions, like picking clothes from a screen, no longer feel impersonal. AI and Big Data have allowed the customers in e-commerce sites, to become highly personal experiences. Another clear example of this is the way Amazon recommends items that each particular user might enjoy. There is not one Amazon homepage, but one homepage customized for every user with their preferences.

Artificial Intelligence, has also been able to create an impact on a company’s the value chain. Rue La La, US based retailers, worked together with MIT to develop a prediction model for product demand, especially during their flash sales. The introduction of AI helped the brand increase their revenue in 10% without the usual problem of having extra stock and unused inventory.

It will be interesting to see how more and more companies become data-driven, and increase their investment in AI and Big Data, to not only create better online experiences, but better in-store experiences as well.

Escrito por Eugenia Bollmann

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