- Google Doppl incorporates a discovery feed with shoppable products and direct links to stores.
- The app uses generative AI and computer vision to create a user avatar and virtually try on clothes.
- The new feed consists solely of AI-generated videos, following the format of social media reels.
- For now, the feature is launching on iOS and Android in the United States for users over 18 years of age, with potential impact on European e-commerce.
The battle to transform how we buy clothes online adds a new chapter with Doppl, the Google's experimental app that combines artificial intelligence, short video, and personalized recommendations for fashion products.Although for now the novelty It is being tested in the United StatesThe movement points to a change that, sooner or later, could reach the major e-commerce markets in Europe and Spain.
With Doppl, Google is trying to fit into an environment where purchases are increasingly decided in TikTok or Instagram type video feedsBut turning the concept on its headInstead of real influencers, it is AI that generates both the content and the viewing experience. of how each garment would look on the user.
What is Doppl and how does this Google app work?
In essence, Doppl is a "virtual fitting room" app which relies on computer vision models and on generative AI for create a realistic avatar of each userTo start using it, the person uploads a Full body photo And from there, the application generates a digital version that will serve as a personal mannequin.
Regarding that avatar, Doppl can overlay clothing items taken from almost any digital sourceImages from online stores, screenshots, photos saved on your phone, or looks seen on social media. The system doesn't just place the garment like a sticker; the AI adjusts the fabric to the body, simulates drape and movement, and creates a animated video of the outfit so that the effect is closer to reality.
This initial photo combination, three-dimensional user model And video generation allows the experience to go beyond the typical static photos of virtual fitting rooms. The user sees how the sleeves move, how a dress drapes when walking, or how pants fit—key to reducing doubts before buying and potentially lowering the price. volume of returns in e-commerce.
A fully shoppable fashion discovery feed
The big new feature that Google is incorporating into Doppl is a shopping discovery feedA feed of visual content where each piece is practically a purchase suggestion. In this feed, most of the items that appear are... Real products with direct links to storesso that the leap between inspiration and payment is reduced to a few taps.
The feed is not a simple static catalog: it shows AI-generated videos of clothingThe images are presented in motion so the user can better appreciate the fit, drape, and overall style of the look. Each recommendation functions as a short piece of video content, very much in line with the consumption patterns that have become normalized on social media platforms.
Google's intention is for this space to act as a A direct bridge between discovering new outfits and buying themThis prevents the user from having to jump between different apps, websites, and intermediate processes. In Doppl, the logical path would be: watch the video, view the outfit on the avatar, choose the size, and from there, follow the link to the store selling the garment.
Personalized recommendations based on style and interaction
To make that feed useful and not just a generic showcase, Doppl builds a style profile of each user. This profile is formed from two main sources: the preferences declared when setting up the account and, above all, the behavior within the app itself.
The application analyzes the garments with which the user interactsIt tracks which products the user saves, which videos they watch the longest, which looks they try on their avatar, and which they quickly discard. Using this data, the AI refines which cuts, colors, or brands best suit the individual, thus generating a personalized product profile. more refined recommendations as the tool is used.
This approach follows the same logic as recommendation algorithms video platforms and social mediaBut adapted to the context of fashion and shopping. For the European user, accustomed to Netflix, TikTok, or Spotify increasingly accurately predicting what they show, it wouldn't be surprising if a clothing app did something similar with outfits.
An AI-only feed versus human influencers
One of the most striking aspects of Doppl is that All the content in the new feed is generated by artificial intelligenceUnlike what happens on TikTok or Instagram, where they are content creators, brands or influencers Those who present the products; here, it is AI that builds the video and the context of each garment.
This change presents a clear contrast to the dominant trend in social media, which revolves around the human prescription and the figure of the influencerIn Doppl there is no famous face recommending a jacket, but a synthetic model showing how it looks, complemented by the user's own personalized avatar.
Google is aware that a feed made up entirely of synthetic content This may generate some resistance among a segment of the public, accustomed to evaluating the credibility of those showcasing the product. However, the tech giant argues that the format is the same one millions of people have already grown accustomed to—short video, infinite scrolling, and direct purchase—only with AI taking center stage instead of traditional creators.
Potential impact on e-commerce in Spain and Europe
Although the initial implementation of Doppl's discovery feed is limited to users over 18 years of age in the United StatesThe strategy fits with a scenario that could easily be replicated in markets like Spain or Europe if the tests are positive. Europe is one of the main focuses of growth of fashion e-commerce, with consumers very accustomed to online shopping but also sensitive to issues such as privacy and data use.
For European retailers and marketplaces, a tool of this kind could open the door to specific integrations with local catalogsThis applies to both large chains and niche brands. The possibility of reducing returns through a more realistic try-on process is especially relevant in the region, where the logistical costs and environmental impact of fashion returns are increasingly prominent issues.
However, its arrival in markets like Spain would inevitably involve assess regulatory and cultural fitFrom the processing of body photos uploaded by users to compliance with European data protection regulations. Added to this is the social perception of... hyperrealistic avatars and purely synthetic contentwhich can vary considerably between countries.
Opportunities and challenges for startups and retailers
Beyond Google's move, the technology behind Doppl opens up a range of possibilities opportunities for startups and retailers specializing in fashion, beauty, footwear, or accessories in Europe. The central idea—using AI to create virtual fitting room videos—is applicable to glasses, handbags, jewelry, makeup and even to sectors such as furniture or sports, where digital testing makes more and more sense.
For tech entrepreneurs, Doppl becomes a Practical case study of AI + user experience integrationshowing how a highly visual and direct flow can accelerate conversion without exactly replicating the traditional social media model. At the same time, it would serve as a reference for developing solutions designed from the ground up for local markets, European languages and specific regulations.
The challenge, for both startups and established brands, will be to find a balance between the commercial effectiveness of personalization and transparency in the use of personal data. The key may lie in offering users clear control over what information they share, how their avatar is generated, and how their interactions are used to refine the recommendation algorithm.
Context: the expansion of AI-generated video
The launch of Doppl's discovery feed fits into a broader trend: the rise of AI-generated video-based platforms and featuresDuring the last few months, proposals have emerged focusing on synthetic clips, both in experimental social networks and in intelligent assistants that integrate summaries or video content produced by generative models.
In this context, Google seeks to strengthen its position in e-commerce against giants like Amazon and the rise of social networks that have transformed short videos into a direct sales channel. By investing in an app specializing in fashion and a virtual fitting room, the goal is to occupy a space where the product visualization on the body Make a difference compared to a simple list of results.
For European consumers, accustomed to browsing between different online stores and comparison sites, a solution of this type could become a complementary tool to the usual purchasing channelsprovided that the availability of products, sizes, and links to stores in the region is extensive and well integrated.
Overall, Doppl presents itself as a Google's lab to explore the intersection of generative AI, short video, and fashionThis tests the extent to which users accept having an algorithm—rather than an influencer—choose and display outfits. Its evolution and eventual arrival in Europe will be key to gauging whether this type of experience becomes the industry standard or remains just another experiment in the long list of digital commerce ventures.
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