How well are your products represented online? According to Google, 59% of shoppers still feel dissatisfied with their online purchases because they didn’t look as expected. Digital try-ons offer innovative ways to minimize this risk. After decades of experimentation, the tech may have finally left its awkward teenage phase behind – and come far enough to become mainstream. Here’s how it evolved from tech curiosity to shopping necessity, and where they’re heading next.

The Bumpy Road: How Digital Try-Ons Started – And Struggled

The eCommerce industry has been chasing the virtual try-on dream for decades. Long before TikTok filters made virtual makeup trials mainstream, beauty brands experimented with clunky webcam overlays. Clothing retailers weren’t far behind, launching waves of experimental technologies throughout the early 2010s.

Companies like Zugara and FittingBox pioneered basic AR mirrors that projected clothing onto webcam feeds. The catch? These early systems demanded studio-perfect lighting and produced results that looked more like digital stickers slapped onto bodies than actual garments.

The industry then pivoted toward 3D avatar-based solutions, where customers would input basic measurements to generate digital representations. The avatars were often blocky and unrealistic, with clothing that draped unnaturally and moved stiffly. 

Learn how Fielmann brought their in-store experience online with SCAYLE using digital try-ons.

Digital Try-Ons Are Finally Getting Good: How AI Is Solving the Biggest Problems

Early digital try-on technology for eCommerce faced three major hurdles: poor body representation, unrealistic fabric simulation, and privacy concerns. Here’s how today’s solutions tackle each challenge:

Inclusive Representation Finally Arrived

Google’s current technology shows clothes on models ranging from XXS-4XL, representing different skin tones using the Monk Skin Tone Scale, various body shapes, ethnicities, and hair types. But the real game-changer? You can now upload your own photo and see clothes on a digital version of yourself, not some generic avatar.

Fabric Physics Got Real

Modern AI models understand clothing behavior – how cotton clings differently than silk, how denim stretches compared to leather, how different cuts affect drape and movement. This isn’t just visual trickery; it’s physics-based simulation that helps predict actual fit and comfort.

Privacy Became Non-Negotiable

Zalando’s privacy-first approach sets the gold standard: Photos never leave your device, images are automatically deleted, and you control all data-sharing preferences. No creepy data collection, just helpful technology that respects boundaries.

Want to know where retail is heading? Get the data from industry leaders in our global shopper survey.

Plot Twist: They Actually Work Now (And Brands Are Loving It)

The numbers speak volumes about practical impact. Let’s examine how leading brands are leveraging these new tools:

Google’s Doppl: The Style Experiment

Launched in June 2025, Doppl takes a different approach entirely. Instead of shopping-focused try-ons, it’s about style exploration. Users upload photos of any outfit, spotted on friends, in thrift shops, or across social media, and watch their digital avatar model it in motion.The app creates AI-generated videos that show how clothes move and flow, turning inspiration into instant visualization.

Zalando’s Size Intelligence

While others focus on visual appeal, Zalando built a measurement ecosystem. Their approach combines fitting models, machine learning, and computer vision to predict sizing issues before they become problems. The technology from Swiss acquisition Fision analyzes two photos to estimate 15+ body measurements, creating size recommendations that feel almost psychic in their accuracy.

Perplexity’s Search-First Vision

Perplexity AI’s upcoming try-on feature represents yet another approach: search-driven styling. Users will be able to ask questions like “show me this sƒƒweater on someone my size” and get instant, personalized visualizations. It’s less about browsing and more about answering specific fit questions through AI conversation.

What’s Coming Next in Try-On Tech?

The next frontier is about creating a complete virtual shopping ecosystem. Here’s what’s on the horizon:

  • Visual Fabric Detail Enhancement: AI will render ultra-realistic close-ups showing fabric weave, texture patterns, and how materials catch light, helping shoppers understand quality before buying, even if they can’t physically touch it yet.
  • Predictive Lifestyle Matching: AI will analyze your calendar, weather patterns, and lifestyle data to suggest not just what fits, but what you’ll actually wear. The technology will understand that you work from home three days a week, prefer natural fabrics, and need versatile pieces that transition from meetings to school pickup.
  • Real-Time Collaborative Shopping: Future composable commerce platforms will enable shared virtual fitting rooms where friends can join styling sessions remotely, offering real-time feedback on potential purchases through synchronized avatars and virtual environments.
  • Sustainability Integration: Digital try-on technology will factor in garment lifespan, care requirements, and environmental impact. AI will suggest pieces that complement existing wardrobe items, reducing overconsumption while maximizing style versatility.

Your Next Move in the Try-On Revolution

Digital try-ons are on the way to become a necessity. Brands that embrace AI and personalization are already seeing reduced return rates, increased customer satisfaction, and stronger brand loyalty.

The question is whether your platform is ready to integrate these technologies as they continue evolving. The future of shopping is personal, visual, and powered by AI that understands both fashion and human behavior.

Ready to transform your retail strategy? Learn how mastering AI in retail can revolutionize your customer experience and slash return rates.