With the global online fashion market worth $821 billion and expected to hit $1.2 trillion by 2027, it’s clear that consumers are more than comfortable buying clothes, footwear and accessories through digital screens. But physical retail is far from dead – it still captures 80% of consumer spend, however buyers are increasingly becoming hybrid shoppers, blending both digital and physical together in their purchase journeys.
To keep up with the likes of H&M, Zara and Shein, fashion retailers need to respond to consumer habits and preferences by bridging the phygital divide, and ultimately make shopping more human.
The store experience, at home
Shoppers return 15-40% of online apparel purchases, versus only 5-10% of items bought in store. It’s not surprising that clothing bought sight-unseen often disappoints – a garment’s construction and draping, color, and most importantly, fit is hard to determine through a 2-dimensional experience.
The best way to instill confidence to purchase and mitigate returns online is to provide the best and most true-to-life images, product information and fit finding support as possible.
Fit finding
Beyond static size charts, merchants are adding interactive, quiz-like fit finders that leverage data from across brands. Point solutions like TrueFit can be easily added to any composable commerce application.
Virtual try-on
A step above fit finders is virtual try-on technology. Using AR (augmented reality), shoppers can superimpose garments and accessories over their own photograph. Advanced try-on tools use real body scans to provide an accurate fit preview.
Digital Avatar
Alternatively, generative AI tools can create relevant images on-demand. For example, Google and Walmart have already employed virtual try on experiences that let shoppers choose a virtual model with their body type, or enter their measurements to generate a realistic, 360-degree preview on their personal avatar.
Live Commerce
Live events make “home shopping” style videos interactive. Retailers like JC Penney, Aldo and Nordstrom are among the first adopters of livestreaming commerce. Participants can watch live try-ons on real humans, ask questions of the hosts and product experts, and buy directly from the stream. According to Coresight Research, return rates are 50% lower for livestream purchases.
Conversational commerce
The release of the ChatGPT API has unleashed new capabilities for headless commerce integrations. Notably, bringing the large language model (LLM) and natural language processing (NLP) to retail chatbots. While still a nascent feature, with the right training, generative AI can come very close to the personalized care you’d receive from a knowledgeable sales associate in-store.
Visual search and discovery
The ability to upload photos to search, explore visually similar items with one-click from a category or product page, or hone in on hotspots from an embedded social media post is a trending use case in fashion, especially fast fashion brands like Fashion Nova where catalogs are large and SKUs move quickly.
The digital experience, in-store
The in-store experience solves the issue of “will this fit,” but the brick-and-mortar world lacks digital features that customers love, like product descriptions, customer reviews and photos, details about the brand and manufacturing process, and comparison pricing and promotions.
According to Google, 56% of customers in-store use their mobile devices to help them shop, often to access this missing content. Because most customers always carry a mobile device, in-store digital like large screens, kiosks, tablets and AR/VR stations are not must-have installations but can still enhance the customer experience.
More important is access supporting digital in-store use cases, regardless of what screen they’re accessed from. For instance:
More adventurous brands are also exploring more immersive ways to turn their retail shops into “retail-tainment” destinations, with AR/VR experiences, gamification, video, and digital events. The key is to connect these in-store experiences back to the digital commerce platform, and not to launch siloed projects. This ensures experiences are consistent across touchpoints, and valuable customer data is persisted to their individual profiles to better personalize online experiences, email offers, loyalty rewards and to better measure ROI.
Revamping retail with technology
Innovation in retail hinges on continuous digital transformation. And to support this evolution, the organization needs the right tech enablement. Legacy systems built for the brick-and-mortar era, or an early foray into ecommerce are rapidly becoming obsolete – they simply cannot support today’s hyper-connected world.
Moving to MACH-X
MACH-based commerce platforms (Microservices, API-first, Cloud-native and Headless) have grown in popularity because of their integrate-with-anything properties, ability to scale and rapidly speed up new feature delivery, and their flexibility.
Today, approximately half of large enterprises have either partially or fully moved away from heavily customized legacy monoliths to API architecture. Those still working with rigid enterprise systems struggle to connect experiences across channels and rarely innovate or keep pace with competitors.
But MACH itself is still not the most flexible option for fashion and apparel merchants. MACH-X (MACH + eXtensibility) provides companies with an open stack that enables the development of custom microservices, and the customization of existing commerce APIs to fit any unique requirement.
MACH-X architecture supports composable commerce – the ability to integrate with third party applications and critical enterprise systems through an API layer. But the commerce services delivered as APIs must be used “as is.” Retailers that want to innovate often find themselves building their own microservices to supplement them, many times using a different tech stack, without documentation.
MACH-X lets you modify the core set of standard commerce APIs to add or tweak functionality (while keeping customizations separate from the core) and use the same stack to build custom APIs. Developers benefit from a “standard” stack, and organizations benefit from cost savings – it’s easier and more cost effective to find resources to work with open-source languages than proprietary code.
Get in touch with us at contactus@infosysequinox.com to learn more about how headless microservices can support digital commerce transformation for your retail brand.
Learn how a women’s casual apparel retailer migrated from their legacy ecommerce monolith to our MACH-X based composable commerce architecture to better support omnichannel experiences and operations, while significantly lowering their total cost of ownership by 30%.
