Technology & the future of fashion

On the latest episode of Next20 we were joined by Business of Fashion’s Robin Mellery-Pratt to talk about the future of the fashion industry and the role technology will play.?

From personalised product recommendations to improved fit matching and enhanced customer service, AI has become a driving force behind the industry's evolution. Here’s an excerpt from the interview where we explore the profound impact of AI in fashion, delving into its diverse applications and the challenges faced by retailers in implementing these innovations.?

Companies like BoF and brand strategists like Robin have proven to be at the forefront of the fight against consumerism and overconsumption (subjects that the fashion industry has been synonymous with for decades) by promoting healthy values and raising awareness about the industry’s problems. Ideally, these technological advancements will become an opportunity to change society’s approach to fashion, use AI-driven fit to reduce returns and carbon footprints, use personalisation to choose better and more durable outfits and to decrease our fashion consumption. Lastly, let’s not forget that it’s up to us as consumers to set trends and demand accountability from businesses and the use they make of technology.

For the purposes of this interview Robin’s views are his own and not those of the Business of Fashion.

The luxury fashion industry has reached a turning point in the adoption of technology and integration of AI. Benedict Evans, a noted technology commentator, stated at a tech summit in New York that AI in fashion is a significant development, a structural change that occurs once every 10 or 20 years in, especially in comparison to the development of the metaverse or NFTs.

Technologically advanced fashion brands currently utilise AI for practical tasks such as demand forecasting and price setting. However, as AI continues to progress, the range of applications expands. One of the earliest significant applications is product recommendation, curation, and fit.

With consumers increasingly accustomed to personalised content on platforms such as Instagram and TikTok, they expect relevant recommendations tailored to their preferences.

While platforms like Netflix maximise the time users spend on their service, e-commerce and the fashion industry lags behind in personalisation. According to research, only 20% of brands and retailers customise product recommendations based on a customer's purchase history. However, a few retailers are taking the next step by offering individualised product recommendations and search results on their e-commerce websites, known as true personalisation. Implementation has been slow due to the complexity of building predictive algorithms or using software platforms that offer personalisation as a service.

Personalisation in e-commerce is complicated, involving the delicate balance of consumer intent and discoverability. It requires sophisticated technology as well as talent and can be costly for brands that lack the resources to build their own teams. Some brands are resorting to surveys to collect first-party data for personalisation. While few examples of successful personalisation exist among established brands, it presents an opportunity for differentiation and improved customer experience.

True personalisation in fashion will be unlocked through artificial intelligence. This leads us to another crucial aspect of curation and personalisation: fit match technology.

Unclear sizing and fit issues lead to a high rate of returns among US consumers, resulting in significant commercial impact. AI can play a role in addressing this problem. Ukrainian startup 3D Look, for example, uses AI to provide accurate virtual try-on experiences based on just two photographs of the customer. By recommending accurate sizes and showing realistic images of clothing on the customer's body, they aim to reduce returns.

AI-driven fit guidance technology and augmented reality can positively impact return rates, which have cost retailers billions of dollars globally. By using AI to analyse data on returns, such as reasons and user reviews, chatbots could provide better guidance on fit. AI can also assist in writing copy for marketing and product pages, as well as creating micro-targeted advertising through synthetic media.

Chatbots powered by conversational AI, like ChatGPT, have gained attention, to say the least, in recent times. Some brands are already experimenting with chatbots for customer service, while others are using them as styling solutions. The ability of AI chatbots to provide complex answers to questions will change the search experience, enabling more comprehensive and nuanced results. However, monetizing chatbots through advertising poses challenges, although Microsoft plans to experiment with integrating ads into Bing's chatbot answers.

Generative adversarial networks (GANs), commonly known as deep fake technology, are worth noting. These networks compete to identify faked images and produce convincing deep fakes. One notable example is TikTok's Bold Glamor filter, which went viral for its ability to remove imperfections from users' faces. While controversial, it showcases the targeted use of AI to revolutionise existing technology, such as social media filters. Text-to-video apps are also introducing powerful video software, but TikTok has gained an advantage with the technological advancements represented by Bold Glamor.

What are your thoughts on AI and technology applied to fashion brands? Let us know in the comments or shoot us an email at?[email protected]. Happy to chat!

Stay tuned for the next episodes of “Asking &why?” by hitting the button subscribe????