Innovation has placed itself firmly in the fashion industry. Be it the IoT-enabled sewing machine or AI-enabled fashion e-commerce, the fashion industry as a whole has grown tremendously well in last couple of decades and it seems a forward-looking approach has already been adopted by the US $ 2.20 trillion worth of industry in the post-pandemic era which means the use of technology will grow at a much faster pace now than ever.
The recent implementations – from robots that sew and cut fabric, to AI algorithms that predict style trends, to VR mirrors in dressing rooms – clearly indicate that technology is automating, personalising and speeding up every aspect of fashion reshaping designing, manufacturing, distribution and marketing.
Changing ‘Product Design’ Landscape with the use of AI and ML…
Outside of fashion sector, the manufacturers have already been using AI and high-end automation to generate innovative prototypes for products ranging from aircraft parts to golf equipment. Now fashion brands of all sizes and specialties are embracing (or starting to embrace) technology in their product development process to understand customers better than ever before. As those data collection efforts grow more sophisticated, artificial intelligence (AI) will reshape brands’ approach to product design and development, with a focus on predicting what customers will want to wear next. According to CB Insights’ Industry Analyst Consensus, generative design software is expected to be a US $ 44.50 billion market by 2030.
Now it’s imperative to talk about the brands which have tested technologies and reached to a point where they can claim the generated outcomes are as per what they planned for.
- The list must start with Google which has already tested the waters of user-driven AI fashion design with Project Muze, an experiment it deployed in partnership with Germany-based fashion platform Zalando in 2016. The project trained a neural network to understand colours, textures, style preferences and other ‘aesthetic parameters’, derived from Google’s Fashion Trends Report as well as design and trend data sourced by Zalando. From there, Project Muze used an algorithm to create designs based on users’ interests and aligned with the style preferences recognised by the network.
- Next in line is Amazon – an e-commerce juggernaut – which is also innovating the product development area in its fashion segment. One Amazon project, led by Israel-based researchers, would use machine learning to assess whether an item is ‘stylish’ or not. Another, out of Amazon’s Lab126 R&D arm in California, would use images to learn about a particular fashion style and create similar images from scratch. If that sounds like ‘fast fashion by Amazon’, that’s because it probably is! In 2017, the e-commerce giant patented a manufacturing system to enable on-demand apparel-making. The tech could be used to support its Amazon Essentials line or the suppliers in Amazon’s logistics network.
- In April 2019, an AI designer called DeepVogueplaced second overall and won the People’s Choice Award at China’s International Fashion Design Innovation competition. The system, designed by China-based technology firm Shenlan Technology, uses deep learning to produce original designs drawn from images, themes and keywords imported by human designers.
- Who can forget Tommy Hilfiger’s project which it announced in 2018 in partnership with IBM and the Fashion Institute of Technology! The project, known as ‘Reimagine Retail’, used IBM AI tools to decipher: real-time fashion industry trends; customer sentiment around Tommy Hilfiger products and runway images; and resurfacing themes in trending patterns, silhouettes, colours and styles.
- Stitch Fixis already at the forefront of AI-driven fashion with its ‘Hybrid Design’ garments. These are created by algorithms that identify trends and styles missing from the Stitch Fix inventory and suggest new designs — based on combinations of consumers’ favorite colours, patterns and textiles — for human designers’ approval. Stitch Fix has developed over 30 pieces of apparel using the Hybrid Design methodology. The company has said that the AI-designed pieces perform comparably in ‘keeper’ sales to the garments from its fashion brand suppliers. That’s likely because Stitch Fix has such vast troves of customer data informing its AI, thanks to its subscription-based, feedback-focused business model.
Design isn’t the only area where Stitch Fix is putting AI and machine learning initiatives to work. The company employs a team of more than 85 data scientists to oversee machine learning algorithms that are used to inform everything from client styling to logistics to inventory management. According to Colson, the company is already seeing ROI from its AI investments, including increased revenue, decreased costs and improved customer satisfaction.
Manufacturing gets a supporting hand with evolution of online marketplaces…
The cost of starting a fashion brand has gone down significantly over the years, thanks to technology and e-commerce. Manufacturing marketplaces can leverage AI to give feedback on whether designs are feasible and provide estimates on cost and production time, potentially eliminating months of back-and-forth with suppliers.
Further, the dawn of the Etsy and Shopify online marketplaces made it easy for anyone to start an online shop and build a following. Now, decreased production costs make it feasible for small or emerging brands to manufacture small runs of products at reasonable margins and build up online audiences from there. In past years, fashion labels would have to manufacture hundreds or thousands of items in order to produce them at a reasonable price.
Now, startups like Maker’s Row make it simple for small labels to find small-batch manufacturing partners that can meet their needs at scale, with transparent standards around pricing and sourcing. Emerging brands can weave small-batch runs (and transparent production standards) into their marketing. NYC-based menswear line Noah, for example, produces ultrasmall batch clothing lines — rumoured to sometimes comprise as few as 12 or 24 items — and often sell out of these items quickly. The launches include detailed blog posts about the items’ sourcing and purpose.
Large high-end brands are also evolving their approach to production to better compete with fast fashion retailers. Tommy Hilfiger makes the fashions in its TommyNow line available instantly — all around the world, in-store and online — as soon as they sashay down the runway. That means TommyNow items hit stores 3 times faster than traditional collections, with just a 6-month window between product ideation/design and release.
Many other brands aim to follow TommyNow’s example, but this is no easy feat. Shortening an 18-month production window into just 6 months required the Tommy Hilfiger brand to overhaul its entire design, manufacturing and distribution ecosystems. And, the problem can be tackled with the plenty of technologies that are emerging to make scalable, sustainable production more feasible, at a faster pace.
Upgrade in Retail and Emergence of Visual Merchandising…
Large as well as small fashion retail spaces are closing around the globe. But physical retail isn’t going away – its purpose is just evolving. As fashions brands continue to tailor their lines to smaller, more targeted customer audiences (and use D2C strategies to reach them), they no longer need to stock vast lineups of inventory in standalone shops or large department stores.
What many brands do need are stores that help build or strengthen a connection between the customer and the label, creating a sense of excitement or urgency. AR/VR is redefining the online and in-store experience and several startups are helping brands enter a new era of experiential shopping.
Obsess, for example, helps labels use AR or VR in 3 key areas: e-commerce wherein it increases conversion by letting online/mobile shoppers see products in 3D in context in front of them; Physical retail wherein it enables brands use AR in-store to let shoppers access digital media on in-stock merchandise; and Marketing to create virtual or augmented experiences that ‘delight consumers’ — like an AR pop-up, interactive catalogue or VR recreation of a store or boutique.
As part of Walmart’s Innov8 VR competition, Obsess created a photorealistic CG virtual store for Rebecca Minkoff. The experience included the ability to shop racks or runway using a headset and complete the checkout process in VR. In 2019, the company worked with Tommy Hilfiger to create a virtual version of a pop-up store for the brand’s collaboration with actress and singer Zendaya.
“What we’re trying to show here is that shopping in the future will be a combination of some elements of what physical stores have today, like visual merchandising and curated pieces, but then they have all of these other things that are not possible in physical stores,” commented Neha Singh, Founder and CEO, Obsess.
TopShop uses in-store AR mirrors, so customers don’t need to get physically undressed to try on clothes, while Uniqlo‘s Magic Mirrors let customers see how apparel they try on in-store looks in different colour options. Neiman Marcus has introduced similar technology in some of its stores, partnering with MemoMi Labs to install 58 of the company’s Digital Mirrors in 37 locations.
Neiman Marcus has also expanded the technology footprint in its stores. In 2019, the company unveiled its first Manhattan location in Hudson Yards, and with it a vision of what a tech-enabled retail experience of the future might look like. Technological innovations featured in the 188,000-square-foot location included – Over 60 screens that broadcast promotional messages and real-time content across the store; Memory Makeover mirrors that let shoppers record beauty demonstrations and makeup tutorials to be texted or emailed to them for future reference; A smart fitting room experience powered by AlertTech that allows customers to customise their lighting, communicate with store associates and check out directly from the fitting room; and a voice-controlled customer service platform by Theatro that uses artificial intelligence to help optimise associates’ time on the floor.
Synergy between Brands and Consumers is intensifying, all thanks to social media…
There is no more ‘fashion season’ era. The rise of fast fashion is decimating the biannual seasonality that has long structured the fashion industry. In order to keep up, traditional apparel brands are now debuting around 11 seasons a year. Fast fashion brands, on the other hand, may issue as many as 52 weekly micro-seasons per year.
Topshop, for example, introduces around 500 styles per week on its website. Zara is producing 20,000 new styles in a year and the social media is accelerating this cycle. Influencer marketing and other social media strategies help new trends travel fast, creating rapid consumer demand for hyper-cheap fashions. Shoppers act on that demand instantly, thanks to “See Now, Buy Now” tools on platforms like Instagram and Pinterest. Adept social media strategies on TikTok have translated to strong sales for companies like Fashion Nova, PrettyLittleThing and Shein.
Fashion Nova is one example of a fast fashion e-commerce brand that has successfully leveraged social media to build its customer base and its brand. The company has more than 19 million followers on Instagram, as well as more than 3,000 influencers, known as #NovaBabes, promoting its clothes. It, reportedly, spent US $ 40 million in 2019 on influencer marketing alone. Fast fashion brand Boohoo has seen significant results by investing in influencer marketing, saying that its profits doubled after paying celebrities to promote its products on Instagram to 16- to 24-year-old fans.
Yet the fact can’t be denied that fast fashion has a dark side. Many fast fashion brands manufacture low-cost, low-quality apparel in factories with questionable working conditions, relying on workers who receive low pay. The inexpensive materials used to create cheap garments are also laden with chemicals. These are some of the areas which are yet to be worked upon by the fast fashion brands in order to make fast fashion industry more sustainable in the growing landscape.