Creating Virtual Shopping Experiences

In retail, many chase the next big thing—a new style, a new way to reach consumers—triggering a frantic race to adopt. But most trends fade as fast as they appear. The real game-changers are curated habits that prove they can stand the test of time. I’ve championed social commerce as the future of retail for over a decade. In hindsight, that barely scratches the surface. It’s now a deeply ingrained consumer behavior. The imperative isn’t just to adopt it, but to evolve with it—constantly and intentionally. At HSN, social commerce was core to our strategy. We pioneered the blend of shopping and entertainment. That’s the essence: finding the sweet spot where entertainment, connection, and commerce converge. Soon after, platforms like Twitch began enabling users to both game and shop in real time, blending entertainment with commerce. Fanatics has successfully leaned into this model as well, immersing fans in live experiences while showcasing gear in action, often worn by their favorite athletes and community, turning fandom into a powerful trust signal. More recently, TikTok Shop collapsed the purchase funnel into a single scroll. It's no longer discover, then buy. Now, it’s see it, want it, buy it—seamlessly, in-platform. So, as we look ahead, how do I see this "social commerce habit" evolving? Here's what I expect: 🔹 Creator Integration is Non-Negotiable. For Gen Z, in particular, TikTok Shop has become a primary discovery engine. They trust their favorite creators to genuinely try products and offer honest feedback. The more brands lean into authentic partnerships with creators, the more trust they build in this integrated shopping experience. It’s about relationship-driven commerce. 🔹 Embrace a Zero-Click World. Speed and simplicity are paramount. Consumers need to be able to see, buy, and receive as fast as humanly possible. This means minimal clicks, minimal friction, and no moments for reconsideration. It's about instant gratification and removing all barriers between desire and ownership. 🔹 Elevate Live Shopping. This is a powerful return to the personal connection and real-time interaction that defined the best of traditional retail. Shoppable videos and live sessions transform social media into a personalized shopping aisle. Imagine experts demonstrating products, showing how they fit or can be styled, all in real-time, tailored to your interests. It brings humanity back to digital retail. 🔹 Unlock the Power of Virtual Try-Ons. A longstanding hurdle in e-commerce is "try before you buy." AI-enabled virtual try-on features solves that, making online shopping more immersive and convenient. This translates directly into higher conversion rates, deeper engagement, and customers spending more valuable time interacting with your brand digitally. It’s time to stop treating social commerce like a trend. This is commerce, full stop. It’s a fundamental consumer behavior that belongs at the center of every modern retail strategy.

𝐙𝐚𝐫𝐚’𝐬 𝐯𝐢𝐫𝐭𝐮𝐚𝐥 𝐭𝐫𝐲-𝐨𝐧: 𝐚 𝐪𝐮𝐢𝐞𝐭 𝐬𝐭𝐞𝐩 𝐟𝐨𝐫𝐰𝐚𝐫𝐝 ZARA has recently launched an AI-powered virtual try-on. This technology is not new and many brands are integrating it into their e-commerce. What I find especially interesting about Zara is how they are doing it: selectively in some markets (not yet in Spain btw), and without over-communicating it and the execution looks very accurate. Zara is testing, learning and iterating before scaling. This approach is consistent with how Inditex has historically adopted technology: pilots first, operational validation and scale once the value is proven. If we look back, Inditex has been experimenting with AR and VR for some years, especially in-store: ✳️ AR shop windows where garments appeared in motion, scanning them with your smartphone, in their store in Oxford Circus in London (if I remember correctly) ✳️ Smart fitting rooms with virtual try ons, but in a fun way as those in Bershka Barcelona, where technology was about engagement, experimentation and social sharing. ✳️ Digital collections with AR technologies, also with Bershka by FFFACE.ME, clearly designed for a younger audience, allowing users to interact with digital garments through AR layers and posting them in their socials, building brand relevance and viral moments. Zara’s website is, in my view, a real spectacle in consumer experience. It manages to be highly aspirational and extremely functional at the same time: 🔅 Editorial-level visuals and fashion films (as the last one, "The dinner", have you seen it? ) that reinforce brand desire. 🔅 High-resolution product imagery with an exceptional level of detail, allowing the customer to really “see” the garment. 🔅 Short videos embedded at product level, showing the piece in movement on the model, adding context, fit and attitude. 🔅An AI assistant (“How can I help you?”), only in some markets, still text-based but clearly designed to guide and support the purchase journey. And now we have the virtual try-on functionality: ✅ Realistic fit The solution is based on AI-generated avatars created from user-uploaded images (one selfie and one full body picture). By analysing the photos, the system builds a personalised digital representation of the user in 2 minutes, allowing garments to be overlaid and visualised in movement. This allows to see YOURSELF with a different combinations of looks, not on a 1,80 cm stunning model. And they can saved in the "My looks" section. ✅ Clear impact on returns and sustainability Early tests point to double-digit reductions in size-related returns. Fewer returns mean lower logistics costs and less reverse shipping. This could reduce the famous "bracketing"? It should. Looking ahead, why not integrate try-on technologies into platforms like Roblox? But let's leave this one for another post. #zara #virtualtryons #AR #consumerexperience

Static pictures as manipulations will not cut it anymore. If we want meaningful manipulations, Virtual Reality belongs in our methods toolbox. I do not mean another “cool demo.” I mean controlled, reproducible environments that feel real enough to study behavior with rigor. What changes in practice? ◾Whole environments, not single images. In consumer research, a virtual supermarket lets me vary layout, prices, shelf space, or crowding and isolate effects without touching a real store. Presence and product involvement can be tested directly in that setting. Great work by Sandra Loureiro and colleagues, see here: https://lnkd.in/eJchQvr3 ◾Ethics and safety for high-stakes questions. VR eyewitness and perpetrator scenes allowed Lilian Kloft-Heller and colleagues to show that THC acutely increases false-memory proneness in a double-blind, randomized, placebo-controlled trial. Try doing that with a few pictures on a screen, or hiring expensive actors. VR offers opportunities: https://lnkd.in/eQQFzxvH ◾ Scripted social interactions. Virtual confederates let researchers control gaze, timing, and emotion precisely, while keeping the scene identical for every participant. This balances realism with experimental control, which classic lab set-ups rarely achieve. See this article: https://lnkd.in/e676gNrB Is VR a field study? Not yet. But it is a big step toward the contexts we actually care about, with data quality we need for causality. If you are still running picture-based manipulations, try one VR pilot this semester. Small step. Big upgrade. #VR #ResearchMethods #Psychology #Marketing #ResearchMatters #Academia #PhDLife #DEXLab #Innovation #DigitalTransformation

Conjoint analysis has long been a powerhouse for understanding how users make trade-offs - but the field has evolved far beyond the traditional models most UX teams still use. Classic methods like Full-Profile, Adaptive, and Choice-Based Conjoint taught us how to quantify preference and predict demand. They remain powerful for testing early concepts, subscription options, or pricing tiers. Yet, as digital products became more complex - configurable SaaS dashboards, adaptive apps, or multimodal experiences - these methods began to show their limits. Modern conjoint frameworks now bridge behavioral realism with computational sophistication. Hierarchical Bayesian (HB) models reduce survey fatigue by inferring individual preferences from minimal data - perfect for agile UX cycles where speed matters. Hybrid conjoint designs (like HIT-CBC) combine ratings and choices to capture nuanced trade-offs without overwhelming respondents. Menu-Based Conjoint (MBC) takes things further by mirroring the way users actually interact with digital products: they build their own bundle. This method captures real configuration behavior seen in subscriptions, feature toggles, and personalization flows - while managing cognitive load through progressive disclosure. Dynamic Choice Modeling introduces a time dimension. It tracks how preferences evolve with feedback or experience, making it ideal for studying onboarding journeys or adaptive recommendations where past actions influence the next choice. Virtual and Immersive Conjoint (VR/AR) place participants in simulated environments - digital storefronts, 3D layouts, or interface prototypes - to measure how spatial design and aesthetics shape real decisions.

Condé Nast and SEPHORA recently joined a growing number of major brands and retailers that are betting big on 𝐜𝐫𝐞𝐚𝐭𝐨𝐫-𝐜𝐮𝐫𝐚𝐭𝐞𝐝 𝐬𝐡𝐨𝐩𝐩𝐢𝐧𝐠 𝐝𝐞𝐬𝐭𝐢𝐧𝐚𝐭𝐢𝐨𝐧𝐬. I think it's going to be the new normal for social commerce and the de facto way an increasing number of shoppers will interact with the URLs of major brands and retailers. Sephora unveiled 𝘔𝘺 𝘚𝘦𝘱𝘩𝘰𝘳𝘢, a new platform allowing creators and influencers to curate their own beauty product storefronts directly on Sephora's website. "Whether it's the app, desktop or mobile, they can just go on, they create it and it's shoppable," Sephora President and CEO Artemis Patrick explained at the Fast Company Innovation Festival. "It's a very seamless experience, and it's very, very authentic for both the creator and the consumer." Meanwhile, Condé Nast announced 𝘝𝘦𝘵𝘵𝘦, an app launching in early 2026 that will give editors and influencers the tools to set up boutique e-commerce destinations. Condé Nast's SVP of Commerce Lisa Aiken described Vette as "a new route to market" that can drive sales without requiring foot traffic, direct-to-consumer infrastructure, or traditional affiliate marketing links. They're not alone. Best Buy and DICK'S Sporting Goods have also launched creator storefront programs, joining a growing crowd of traditional retailers trying to harness the power of the creator economy. To be clear, this idea of creator storefronts is nothing new. Amazon has had influencer storefronts for years. ShopMy has facilitated more than $500 million in sales since its inception with a mix of affiliate links, social shopping, and storefronts. LTK is generating $5 billion annually through the same channels. There's certainly a lot for all parties involved to like about creator storefronts with established retailers: 📦 Seamless fulfillment and distribution. 🚚 No third-party platforms, no shipping headaches. 💵 The same checkout experience customers already trust, curated by creators they follow. But will it work? 100%. There's a core marketing principle that the single greatest conversion variable on a landing page is often whether the messaging matches what sent users there. If consumers are going to land on these storefronts from the social posts of the creators that curate them, they're ideally going to see a familiar, trusted face throughout the shopping experience. That's a very powerful messaging match that's sure to influence consumers. I think the brands that succeed here the most will be the ones that incorporate creators' likenesses as much as possible, making the destination storefront into something that feels less like it was the creator who stocked the shelves, and more like the creator is your personal shopper. Expect to see a 𝘭𝘰𝘵 more of these announcements. And soon.

🚀 The Future of Shopping: Generative AI in Retail | Bernard Marr 🛍️✨ Bernard Marr dives into the transformative impact of Generative AI on the retail industry, showcasing how this advanced technology is revolutionizing both online and in-store shopping experiences. From virtual try-ons to AI shopping assistants, discover the seven ground breaking ways generative AI is enhancing retail. 🔗 https://lnkd.in/e7T4Spyi In This Episode, Explore: 🤖🛒 AI Shopping Assistants: Experience the convenience of virtual assistants like eBay's ShopBot, making shopping more intuitive through text, voice, or photo queries. 👗👓 Virtual Try-On Features: See how Google's generative AI offers a realistic and inclusive virtual try-on experience, changing the way we shop for clothes online. 📝💬 AI-Generated Customer Review Summaries: Quickly understand products through AI-condensed review summaries, simplifying your shopping decisions. 🎮👟 Metaverse Stores: Enter the world of immersive shopping with Nike's Nikeland in Roblox, where generative AI crafts personalized virtual stores. 🎁🛍️ Personalized Customer Journeys: Discover how AI tailors shopping experiences, from custom promotions to loyalty programs, catering uniquely to each shopper. 🎨👕 Personalized Products: Unleash your creativity with platforms like Space Runners' Ablo, allowing you to design custom fashion pieces using simple text prompts. 🪞🏬 Enhanced Physical In-Store Experience: Witness how smart mirrors and responsive displays merge digital convenience with the physical shopping realm. #GenerativeAI #RetailInnovation #FutureOfShopping #TechTrends #AIinRetail #DigitalTransformation

🔵 Walmart launches virtual fashion collection on ZEPETO 👇 Retail giant Walmart has expanded its digital presence by introducing a virtual collection of its No Boundaries (NoBo) apparel brand on metaverse platform ZEPETO. 👚 The launch includes 10 virtual twins (digital versions) of real-world NoBo items from the fall collection and 3 limited-edition items created in collab with ZEPETO creator Xexi. Users can purchase the virtual items using ZEMs, the platform's digital currency. 🇰🇷 ZEPETO was launched in 2018 by South Korean tech company NAVER Z (ZEPETO) and has quickly become a popular platform. With +20 million monthly active users (of which 70% Gen Z), this 'metaverse' offers brands a unique way to connect with younger audiences through creative, interactive experiences. Comparable to Roblox, the platform combines avatar customization, virtual worlds, and social interaction, becoming a space for self-expression. It grew from an avatar maker to a full metaverse, including events, branded collaborations and virtual stores the last years. 📊 Roblox remains much bigger in terms of engagement (200 million MAU's) and revenue from digital goods ($2.8 billion in 2023 vs ZEPETO's estimated $40.5 mio), however ZEPETO's becoming an important niche platform with a specific Gen Z focus. 🛍 Walmart has been investing consistently in similar experiences, including Walmart Discovered on Roblox and Walmart Realm with Emperia. The strategy aligns with current market research on Gen Z consumer behavior: ‣ 56% of Gen Z report improved brand perception after visiting virtual experiences ‣ 97% use social media as their primary source of shopping inspiration ‣ 42% utilize virtual avatars to test potential real-life fashion purchases 👖 No Boundaries is Walmart's young adult apparel brand, generating approximately $2 billion in annual sales. The refreshed NoBo line features trendy items such as baggy fit jeans, drop shoulder tops, and cropped tees, with 80% of products priced under $15. Walmart already announced a second virtual NoBo drop scheduled for November 22, indicating ongoing commitment to its digital fashion strategy. ➡️ A clear example of a continually growing trend of bridging the gap between physical & digital shopping experiences, and overall a VERY smart move by Walmart to engage with younger consumers. #innovation #retail #walmart #zepeto #roblox #phygital #virtualretail #metaverse

Virtual try-ons and 360° product views are becoming table stakes for e-commerce brands. Returns are killing e-commerce profitability. In fact, the average return rate for online purchases is 20-30%. For fashion and apparel, it's closer to 40%. Simply because customers can't touch, feel, or try products before buying. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁'𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄: 𝟭. 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝘁𝗿𝘆-𝗼𝗻𝘀 𝗳𝗼𝗿 𝗳𝗮𝘀𝗵𝗶𝗼𝗻 𝗮𝗻𝗱 𝗮𝗰𝗰𝗲𝘀𝘀𝗼𝗿𝗶𝗲𝘀 Customers can see how sunglasses look on their face, how a watch fits their wrist, or how a jacket fits their body, all from their phone. 𝟮. 𝟯𝟲𝟬° 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝘃𝗶𝗲𝘄𝘀 Instead of static images, customers can rotate, zoom, and inspect products from every angle. 𝟯. 𝗔𝗥 𝗿𝗼𝗼𝗺 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Customers can place furniture, decor, or appliances in their actual space using their phone camera. 𝟰. 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝘀𝗵𝗼𝘄𝗿𝗼𝗼𝗺𝘀 Full VR experiences where customers can "walk through" a store, browse products, and interact with items as if they were physically there. Five years ago, AR/VR required expensive custom development. Today, platforms like Shopify, WooCommerce, and BigCommerce have plug-and-play AR integrations. You don't need a massive budget or a dev team. You just need to prioritize it.

The #Future of #Shopping: The "#Phygital" #Retail #Revolution The retail #landscape of 2026 is defined by the "phygital" #experience—a #seamless #blend of #physical touch and #digital intelligence. As #brands compete for #consumer #attention, three #breakthrough #display methods have moved from novelty to necessity. Immersive Display Technologies - #3D #Holograms: #Retailers are replacing static #mannequins with #3D holographic #fans that project #high_definition, floating #images. These displays draw 35% more foot #traffic by allowing shoppers to view intricate product details—like the texture of a watch strap or the grip of a sneaker—from every angle without the item being #physically present. - #Smart #Mirrors: Located in #fitting #rooms, interactive mirrors use RFID technology to recognize the clothes a customer is holding. They allow shoppers to adjust room lighting, request new #sizes via #touchscreen, or see "#virtual overlays" of #accessories, transforming the #dressing room into a #high_tech #styling suite. - #Virtual #Simulations: Using #AR and #VR, customers can now "#test drive" products in their intended #environment. Whether it is #visualizing how a new sofa #fits in a #digital twin of their living room or #simulating a hike to test camping gear, these #simulations remove the guesswork from #shopping. Why It Matters for the #Future? These #technologies offer more than just a "wow" #factor; they solve #critical business #challenges. By using #digital #displays, stores can offer an "#infinite #aisle"—showcasing thousands of #products within a #small physical #footprint. Furthermore, these #tools provide #retailers with #real_time #data on which items are being #engaged with most, while #virtual try-ons significantly #reduce return rates by ensuring customers are confident in their purchases. Ultimately, the #future of #retail lies in creating a "#destination" experience that offers #sensory depth that a #smartphone #screen cannot match.

Zara has introduced out a new “virtual try-on” feature in their mobile app, so I decided to test it and screen-record the full process. First impressions: the setup is genuinely simple. You only need two images: 📸 one selfie 📸 one full-body photo That kind of ease matters. If virtual try-on is ever going to reduce returns at scale, it has to be accessible to everyday shoppers, not just people who love tech. However, wearing my 3D technical designer hat, this is where the value currently splits into two very different things: visualisation versus fit. What I think it does well: ☑️ Fast setup for the user: two photos and you’re in. ☑️ Helps with styling decisions: you can quickly see proportion, colour, and overall outfit balance on a body-shaped avatar. ☑️ Potential to reduce returns (eventually): if brands combine this with better body data and product measurement logic, it could become a meaningful decision-making tool rather than a novelty. Where it currently falls short (in my view) ❎ Fit accuracy is still the big question. ❎ I can see how something looks on “me”, but without body measurements, garment measurements, fabric behaviour, and ease built into the logic, it’s not telling me whether it will actually fit like that. ❎ It feels more like a visual tool than a fit tool. Useful for “do I like this look?” but not yet reliable for “will this work in real life?” ❎ Time cost vs reward: it took around 10 minutes to generate the turnaround, which is too slow if the goal is quick browsing and outfit testing. ❎ Body representation limitations: the side profile wasn’t an accurate match for me, which makes the result feel less trustworthy overall. My takeaway: we’re moving in the right direction, but right now it’s closer to a digital mirror than a fit solution. If brands want this to genuinely reduce returns, the next step is integrating measurement-led fit logic and material behaviour, not just appearance. Have you tried it yet, and did it feel accurate to you?