Introduction
Online clothes shopping can feel like a gamble. You scroll through endless product pages, trying to guess how a static image on a model will translate to your own body. Questions about fit, drape, and style can lead to hesitation, abandoned carts, and frustrating returns. It’s a universal challenge in the e-commerce world: bridging the gap between seeing an outfit online and knowing how it will actually look on you.
Google is now stepping into this space with a potential solution: an experimental new AI app called Doppl. Positioned as a tool to help you explore your style and visualise outfits, it aims to take the guesswork out of online shopping. But Doppl is much more than a simple virtual try-on feature. It represents a bold, AI-first e-commerce strategy with several surprising features that could challenge the established order of online fashion retail.
It’s a Shopping Feed With No Human Influencers
Doppl introduces a “shoppable discovery feed” that provides personalised outfit recommendations. Users can scroll through this feed to discover new items, virtually try them on, and click direct links to purchase from merchants. The most counter-intuitive aspect of this feature is what’s missing: human influencers. The feed consists entirely of AI-generated videos showcasing real products.
This is a direct departure from the dominant e-commerce model popularised by platforms like TikTok and Instagram. Instead of human authenticity, Google is betting on a purely algorithmic approach. The app’s recommendations are based on a detailed profile of your style, analysing preferences you share, items you interact with, your virtual try-on history, and saved looks. This strategic pivot isn’t just a novelty; it’s a calculated business move. By replacing human content creators, Google is testing a model that offers immense cost efficiency by eliminating influencer fees and massive scalability, as AI can generate endless content variations tailored to each user.
You Can Try On an Outfit From Any Photo
The core functionality of Doppl begins when a user creates a virtual avatar. This can be done by uploading a full-body photo of themselves or, for those with privacy concerns or who just want to experiment, by selecting a pre-set AI model. From there, the app’s most surprising capability comes into play: users can use almost any image to generate a virtual try-on.
This isn’t limited to a pre-approved catalog of clothing. A user can snap a photo of an interesting outfit at a thrift store, use a picture of what a friend is wearing, or even take a screenshot of a look they see while scrolling through social media. Doppl’s AI then visualises that specific outfit on the user’s avatar. This feature is impactful because it breaks free from the walled garden of a single retailer’s inventory, effectively turning the entire visual world into a potential wardrobe to explore.
It Creates Videos, Not Just Static Pictures
While other virtual try-on tools generate a static image, Doppl’s AI takes it a step further. After creating an image of the user’s avatar in a new outfit, the app can convert that static picture into a dynamic, AI-generated video.
The purpose of this feature is to provide a much better sense of how an outfit would look and behave in the real world. The generated videos aim to show the clothing’s movement, drape, and overall fit in a way that a flat image simply cannot capture. This added layer of visualisation is designed to increase a shopper’s confidence before making a purchase, tackling one of the biggest hurdles in online fashion retail.
It’s an Experiment, and Google Admits It’s Not Perfect
Doppl is not a fully polished, final product. It is an experimental app from Google Labs, currently in its early stages of development. Its availability is limited to users 18 and older on iOS and Android within the U.S. Google has been transparent about the technology’s current limitations, including an explicit disclaimer in its communications about the app:
“As a Google Labs experiment, Doppl is in its early days and it might not always get things right. Fit, appearance and clothing details may not always be accurate.”
This candidness frames the app as a public test of a transformative technology. While Google openly admits to potential accuracy issues, the experiment also surfaces deeper industry challenges like authenticity concerns from users accustomed to human creators and critical privacy questions about the data required for deep personalisation. Doppl is a glimpse into the future of e-commerce, inviting users to participate in the evolution of AI-driven shopping, flaws and all.
An AI Stylist is part of the Future of Shopping
Ultimately, Google’s Doppl is more than just a virtual closet. It’s a new, AI-first approach to e-commerce that directly challenges discovery models from giants like Amazon and TikTok. By replacing human influencers with a scalable AI feed and allowing users to try on styles from anywhere, Google is testing a fundamentally different way for consumers to interact with fashion.
The implications could be far-reaching, potentially leading to a reduced reliance on the human influencer economy, creating new opportunities for smaller brands to be discovered via algorithms, and fundamentally changing how fashion trends emerge and spread. As AI becomes more deeply integrated into our shopping habits, it raises a thought-provoking question for the future of style. Will we begin to trust an algorithm’s personalised recommendations more than a human influencer’s? And what might that mean for the brands, creators, and shoppers of tomorrow?
