How luxury labels are fashioning the future
Keeping their finger on the pulse, traditional fashion brands and innovative creators alike are setting a new kind of trend.
The fashion industry is always looking ahead, in search of what’s next and what’s new. That same forward-thinking applies to its technological trends. Now intensified by the flow-on effects of covid-19, digital strategies from CGI models to AI modelling are ‘in’.
In recent years, CGI models (well, their creators) have worked with some of the biggest names in fashion. Shudu landed on the scene in 2018 as the world’s first digital supermodel and has gone on to grace the covers of international fashion magazines and to ‘attend’ the BAFTA awards dripping in Swarovski crystals. Superimposed Instagram influencer Lil Miquela has 2.5 million followers and has worked with Prada, Gucci and Calvin Klein. Over lockdown, the usefulness of virtual VIPs offered a glimpse into fashion shoots of the future as industry publication Business of Fashion reported an increase in demand for CGI and 3D rendering artists. Even Kendall Jenner had an avatar made in her image for a Burberry summer capsule campaign.
In playing out in real-time, live stream shopping events create a sense of urgency akin to a shop assistant telling a customer there is only one pair of pants left in their size. It’s an exciting way to shop when we’re stuck at home, or not feeling safe enough to try on clothes in-store. A solid technological foundation is essential to ensure retailers can run live stream events smoothly. Partnering with influencers can create trust, and keeping the session entertaining and informative, including answering viewer questions, will improve product discovery. Facebook and Instagram are reportedly piloting their own versions of successful Chinese applications with built-in e-commerce. Examples include Alibaba’s Tmall, which predicts over 500 million users to make purchases via live stream in 2020. Already, Australian-based Hawkeye Vintage, which has held pop-up retail events in New Zealand in the past, has held marathon shopping events – up to 8 hours – with one-off pieces presented on Instagram Live.
At the end of Fashion Month in Milan, Italy, concerns about catching covid-19 replaced the usual front-row rumours. Show-goers are no strangers to the persistency of the ‘fashion week flu’, which catches on when rundown attendees sit shoulder-to-shoulder at the change of season. If fashion weeks and months are to continue, designers need to have a few different tricks up their sleeves to impress industry decision-makers from a safe distance. An early success story was Hanifa, which launched a new collection via mesmerising 3D modelling showing every curve of the designs without a human presence. “It actually requires an even greater amount of attention-to-detail for the clothes to fit and look just right,” the designer told Teen Vogue after the live show. “The biggest challenge is making sure that the beauty we display in real life is well represented on the screen.” Acknowledging that digital shows need to be just as exciting as the real deal, Helsinki Fashion Week matched designers with tech firms to encourage out-of-the-box presentations. While New Zealand Fashion Week is postponed to early 2021, concerns for a second wave of covid-19 suggests local designers could learn from such collaborations.
Virtual showroom invites
Wholesale customers have been slower to migrate to digital than the end consumer. Now, out of necessity with covid-19, industry showrooms are adopting live streaming and 3D rendering techniques. The benefits of closing the distance with digital should not be lost on New Zealand showrooms, which can overcome our geographical distance by riding this new wave of industry interaction. In Auckland, Showroom 22 has introduced La Bella Figura, a weekly series inviting models to visit the showroom and photograph themselves in its clients’ new wares to pique interest. It’s also an opportunity for emerging designers, who can save themselves prohibitive up-front costs of creating multiple samples for multiple locations or signing onto an international showroom.
Big Data & AI
Big data and AI capabilities are perfectly positioned to enhance personalised luxury services. Early adopters, including Burberry and Dior, use machine learning to control complex communication channels and create relevant recommendations in real-time. For a premium service, it’s important to think of it as a tailored, not targeted, approach – it’s not polite to follow the customer too closely around any kind of retail set-up. For chatbots, Natural Language Processing (NLP) is more natural, and Dior has even included emojis and GIFs for a more modern connection. It’s a move that has paid off as many businesses face covid-19 concerns. “Many multi-channel businesses have had their first glimpse of what it takes to be truly digital-first, and this step-change in consumer adoption is likely to stick when we emerge from the crisis,” notes a recent McKinsey & Company report. “Since digital channels can be less profitable than physical retail, players need to establish a balanced model that prioritises digital growth in an integrated way with cutting-edge customer experience.”
Data, AI, BI & ML
Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”