Google virtual try on what retailers must do

The quick answer

To prepare for Google's virtual try-on tool and other shopping AI, retailers must complete these steps:

1. Optimize product data feeds for the Google Shopping Graph with accurate, complete information.
2. Invest in high-resolution product photography showing items from multiple, clear angles.
3. Implement product schema markup on your website so AI can easily understand your listings.
4. Monitor performance data in Google Merchant Center to track the impact on sales and returns.

What is Google's new virtual try-on tool?

Google has expanded its virtual try-on shopping feature. The AI tool now lets online shoppers see how both apparel and shoes look on their own bodies before they buy.

Users upload a full-length photo of themselves. They can then browse product listings and tap a "Try It On" button. Google's AI generates a realistic image showing the item fitted to their body, helping them make a better purchase decision.

Key features of the AI shopping update

This update is more than a simple feature. It represents a significant step in visual, AI-driven commerce. Here are the core details for your business.

• Footwear Included: The tool now works for sneakers and other shoes, rendering them at the correct scale and angle on a user's feet.
• Geographic Expansion: Previously only in the U.S., the feature is now available in more countries, including Canada, Australia, and Japan.
• Advanced AI: The model creates lifelike images by understanding complex factors like perspective, body shape, and even how a pant hem might cover a shoe.
• Massive Integration: It works with billions of products from major retailers like Walmart, Macy's, and Kohl's through Google's Shopping Graph.

Why virtual try-on matters for your business

This technology directly solves the biggest problem in online fashion retail: "How will this actually look on me?" Answering this question for your customers has immediate, tangible benefits for your bottom line.

When shoppers feel confident, they are more likely to complete a purchase. This tool removes major doubt from the buying process, turning browsers into buyers.

Increase shopper confidence and conversions

Uncertainty is the enemy of e-commerce conversions. Sizing charts and model photos help, but seeing an item on their own body is the ultimate confirmation for a shopper. By enabling this experience, you reduce purchase anxiety and increase the likelihood of a sale.

Philipp Schindler, Google’s chief business officer, noted that engagement has been "extremely positive, particularly with Gen Z users," highlighting its effectiveness with a key demographic.

Reduce expensive product returns

Product returns are a massive operational cost. They involve reverse logistics, inspection, restocking, and often result in unsellable inventory. A primary driver of returns is poor fit or a mismatch between expectation and reality.

Virtual try-on tackles this problem at the source. When customers can better visualize fit and style, they make more accurate choices. This leads to a direct reduction in your return rate, saving you money and protecting your margins.

How to prepare your store for Google's virtual try-on

You cannot simply "turn on" this feature. Your products become eligible when you provide Google with high-quality, structured data. Here is the process to get your products ready for AI-powered shopping features.

The foundation is Google's Shopping Graph, a real-time dataset with over 50 billion product listings. Your goal is to ensure your products are included and correctly understood within this ecosystem. A strong fully managed digital presence makes this process seamless.

Step 1: Master your product feed

Your product feed is the single most important element. This is the file you submit to Google Merchant Center containing all your product information. For AI features to work, this feed must be perfect.

Focus on these key attributes:

• High-Quality Images: Provide several `image_link` and `additional_image_link` URLs. The images must be clean, high-resolution, and show the product from different angles on a white background.
• Detailed Titles and Descriptions: Use clear, descriptive `title` attributes that include the brand, color, material, and product type. AI uses this text to understand context.
• Complete Product Identifiers: Accurately fill in GTIN, MPN, and Brand. These are non-negotiable for Google to correctly identify and categorize your products.

Step 2: Implement structured data

Structured data, or schema markup, is code you add to your website to help search engines understand your content. For e-commerce, `Product` schema is essential. It tells Google explicitly that a page is about a specific product and provides details like name, price, availability, and reviews.

You can use Schema.org's Product vocabulary to mark up your product pages. This helps Google correctly index your products and makes them eligible for rich results like virtual try-on. Modern e-commerce platforms often handle this automatically, but it's critical to verify it is implemented correctly.

Step 3: Invest in professional product photography

Google's AI is powerful, but it relies on good source material. Low-quality, inconsistent, or busy product photos will not work. Your photography is now an input for a machine learning model.

Your photo standards should include:

• Consistency: All photos should have the same lighting, background, and general positioning.
• Clarity: The product must be in sharp focus, with its colors and textures clearly visible.
• Multiple Angles: Provide images of the front, back, side, and detailed close-ups. This gives the AI more data to create a realistic rendering.

Measuring the impact of AI in your store

After you optimize your listings, you need to track performance. Measuring the impact shows you the ROI of your efforts and informs your future strategy. Rely on the data your business already generates.

Do not look for a single dashboard called "Virtual Try-On Performance." Instead, monitor key e-commerce metrics for products that are eligible for the feature.

Key performance indicators to watch

In your analytics platform, segment your sales data. Compare the performance of apparel and footwear categories against other product types. Look for changes after optimizing your product feeds.

• Conversion Rate: Are products with virtual try-on potential converting at a higher rate?
• Return Rate: Is your return rate for apparel and shoes decreasing over time? This is a primary goal.
• Add-to-Cart Rate: Are shoppers showing higher purchase intent for these items?

You can also find vital performance information directly inside Google Merchant Center. The platform provides insights on impressions, clicks, and performance for your free listings and ads. Monitor these metrics for eligible products to see if visibility increases.

The future is visual and automated

Google's move is part of a larger industry trend. Platforms like Pinterest and Snapchat have already invested heavily in AR-powered commerce. This is not a gimmick; it is the new standard for online shopping.

As noted in the initial report from TechCrunch, Google is also rolling out features for generative outfit inspiration. This means AI won't just help users try on one item, but will build entire looks using products from your catalog.

Preparing for this future does not require a crystal ball. It requires a commitment to a solid technical foundation. A fast, mobile-friendly website with clean code, structured data, and an optimized product feed is the best defense and offense. This is the core of an effective website to social, monthly marketing plan that ensures you are ready for whatever comes next.