How Google AI Shopping Is Reinventing Shopping From Search to Purchase

Almost 30 years ago, Google turned the Internet on its head with a simple search text box. Today, they are galvanizing online retail with AI Mode.

Shopping comes with a lot of questions: How do I choose a pair of hiking boots? Will these pants look good on me? If I buy this today, will the price just drop tomorrow? Most shoppers waste hours comparing products, second-guessing purchases, and wondering if they'll find better prices tomorrow.

Google AI Shopping just solved the nightmare of online shopping decisions.

Google's AI can now virtually dress you, hunt for deals on your behalf, and complete purchases without you ever touching a checkout form.

Research shows that more than half of shoppers struggle to find specific clothing items they envision, and price anxiety keeps millions from pulling the trigger on purchases they actually want to make.

Google's new AI Mode shopping experience brings together Gemini capabilities with its Shopping Graph to help consumers browse for inspiration, think through considerations and narrow down products. The system handles the three biggest shopping headaches: product discovery, fit uncertainty and price timing.

Instead of spending hours researching and agonizing over decisions, you'll get personalized recommendations, see exactly how clothes look on your body, and let Google's AI buy items automatically when they hit your target price.

The Shopping Graph now has more than 50 billion product listings, from global retailers to local mom and pop shops, while every hour, more than 2 billion of those product listings are refreshed on Google to ensure you're getting current information.

Now let's explore exactly how these three transformative features work.

Understanding Google AI shopping features

Google is fundamentally reshaping the online shopping landscape with AI. They've designed a suite of tools that create a more personalized, interactive and seamless journey from product discovery to purchase.

AI Mode: conversational discovery reinvented.

Key among these innovations is the new AI Mode in Search that helps shoppers find what they want faster. It combines Gemini AI with the Shopping Graph for dynamic, image-rich search panels. This feature makes online shopping more interactive and personalized. It also supports complex, context-aware queries, using AI to show curated, relevant options directly within Google Search without the need to navigate multiple websites.

Virtual try-on with your own photo.

We've seen virtual fitting rooms before. Google AI Shopping brings the fitting room to your phone. Consumers no longer need to use generative AI for a facsimile but can now upload their own full-body photo to see the actual cut and fit for a customer's body type.

AI Mode is like an intuitive shopping assistant, offering a more sophisticated virtual try-on feature for apparel and even hair color and makeup. The goal is to increase shopper confidence and reduce the likelihood of returns, a common pain point in online fashion retail. According to an Ipsos poll [PDF], 59% of online shoppers were dissatisfied with their purchases because of unmet quality expectations.

Agentic checkout with price tracking.

The future of automated purchasing is known as agentic checkout. This upcoming functionality allows an AI agent to act on behalf of the consumer to complete a transaction. When users select a product, they can set preferences such as size, color, and target price. This "track price" feature then monitors the product across the web and notifies the customer if and when the price drops.

Once the user confirms acceptance of the price, the AI agent proceeds to "buy for me" and navigates to the retailer's website to complete the purchase. Google's AI-driven agents drive every step of the shopping process, completing the transactions using Google Pay.

While Google is leading the way for agentic checkout, Mastercard and Visa are pioneering shopping features and payment functionality to deliver personalized and secure shopping experiences as well.

Industry experts view this as a foundational shift in how people will discover and pay for items online, potentially making the traditional checkout page obsolete.

Shoppable visual inspiration. 

Google is introducing a fresh way to shop with its AI Mode, turning the search experience into something far more visual and hands-on. Instead of scrolling through endless options, you can see exactly how an item might work for you.

Try it by joining the "try on" experiment in Search Labs. When browsing clothes, simply tap the "try it on" icon, upload a full-body photo, and watch the shirt or top appear on you in seconds.

The experience doesn't stop there. Shopping often feels social, and Google weaves that into the process. After testing out a look virtually, you can easily share the image with a friend for feedback before deciding.

Even bigger possibilities are on the way. Soon, Google AI Mode will help with outfit ideas and room design layouts, matching your vision with items you can actually buy.

Why this matters for merchants

The shift from keyword searches to conversational, personalized shopping experiences fundamentally changes how people buy online.

Data now drives sales success. AI-powered shopping platforms need current, comprehensive product information to function effectively.

New features like price tracking and virtual try-ons keep shoppers within Google's platform longer, creating more selling opportunities. This increased engagement gives merchants a strong incentive to make their products easily discoverable.

Merchants who optimize their product feeds see three key benefits: increased visibility in search results, higher customer engagement, and shorter purchase journeys.

Action steps to get ready for Google AI shopping

Optimize your product feed.

Google's AI Mode prioritizes complete product details: full titles, high-quality images, and detailed attributes. Merchants already succeeding with Google Shopping have an advantage — their rich product feeds translate well to AI-driven discovery.

Real-time accuracy matters more than ever. Because Google updates billions of product listings hourly, outdated inventory or pricing immediately hurts your competitive position.

Elevate visual content.

Visual discovery is becoming dominant. High-quality product images paired with structured data now separate winning merchants from the rest. A variety of product views, from drape and fit for clothing to up-close mechanical details in an unboxing, help meet customer expectations.

Preparing for AI-first discovery.

Merchants should enrich product data beyond basic specifications. Include contextual details like "waterproof for rainy commutes" or "formal enough for job interviews" that match how people naturally describe their needs.

Write product descriptions using conversational language that mirrors AI search queries. Instead of "Men's Athletic Footwear," use "comfortable running shoes for daily workouts."

Focus on complete attribute data: materials, sizing guides, care instructions, and use cases. AI systems rely on this structured information to match products with specific customer requests.

Update inventory and pricing in real-time to maintain search visibility.

How BigCommerce and Feedonomics help merchants with Google AI shopping

In partnership with Google, BigCommerce and Feedonomics have launched a closed beta program to optimize catalog product data for the AI era. Participation is free for customers during the beta, offering a streamlined approach to scalable, global-ready content without manual effort.

AI-optimized product feeds.

Feedonomics enriches product data so listings are accurate, detailed, and easy for machines to read. With Google Cloud and Gemini AI, attributes fill in automatically, while titles and descriptions stay consistent with your brand. Strong data management connects search queries with the right items, aligning with shopper needs and purchase intent. Well-structured details give every product the best chance to be discovered.

Integration with Google Merchant Center.

BigCommerce stores link with Google Merchant Center through Feedonomics, keeping product details in sync without extra steps — any change to pricing, stock or descriptions updates right away. Shoppers see accurate information across Google Shopping and AI Mode results, reducing errors and keeping listings consistent.

The final word

Google AI Shopping represents a state-of-the-art transformation in ecommerce, fundamentally changing how consumers discover and purchase products online. This artificial intelligence-powered platform combines advanced AI models with Google's massive Shopping Graph to solve the three significant shopping problems: finding the right products, knowing how they'll fit, and timing purchases for the best prices.

The platform's revolutionary try-on experience lets shoppers upload their own photos to see how clothing actually fits, while AI tools automate price tracking and can complete purchases when items hit target prices.

Unlike traditional ecommerce experiences that require endless scrolling through Amazon-style product pages, Google's conversational AI assistant understands natural language queries and provides personalized recommendations through visual, interactive panels.

For merchants, this means optimizing product feeds with rich, descriptive content that AI can parse effectively — moving beyond keyword matching to contextual discovery.

Success requires high-quality image generation, comprehensive product attributes, and real-time inventory updates. The platform's visual discovery features keep shoppers engaged longer than traditional shopping tools, creating more selling opportunities.

Google's AI Mode essentially functions as an advanced SEO system that prioritizes complete product data over keyword matching. Merchants who adapt their content strategy for AI-first discovery — using descriptive language instead of generic terms gain a competitive advantage.

This shift represents the future of retail, where AI assistants handle everything from research to automated purchasing, creating more efficient shopping experiences while potentially making traditional checkout processes obsolete.

FAQs about Google AI shopping

How does Google AI Mode decide which products to feature in search results?

Behind the scenes, Google's AI Mode uses something called "query fan-out" — breaking down your question into multiple searches that run at the same time. Rather than depending on one algorithm, this approach combines several powerful tools working together. The system pairs billions of product listings to create shopping experiences that feel personal and helpful.

Understanding what you actually want matters more than matching keywords exactly. When you tell AI Mode you're looking for a "cute travel bag," it recognizes you need visual inspiration. It shows you browsable images tailored to your preferences. This specificity creates conversations around shopping instead of simple searches.

Personalization happens through context-aware recommendations that adapt as you browse. Dynamic panels update with relevant products and images in real-time, helping you discover new brands while pinpointing exactly what you need.

What attributes in my product feed have the most significant impact on AI Shopping visibility?

The most significant attributes are those that provide the raw text for Google's large language models to analyze. These fields are your primary way to "talk" to the AI.

• Product title [title]. The title remains the most critical factor for search visibility. A well-optimized title should be descriptive and mirror a user's search intent, including crucial attributes like brand, product type, color, and size. For AI, a title like "Men's Waterproof Gore-Tex Hiking Jacket" is more relevant than just "Men's Jacket."

• Product description [description]. This attribute has gained immense value. While titles are concise, the description allows for up to 5,000 characters of rich, keyword-heavy text. Google's AI will parse this to understand nuanced features, use cases, and technical specifications that answer complex shopper questions. It's crucial to front-load the most important information and keywords within the first 150-180 characters.

• Structured title [structured_title] and structured description [structured_description]. If you use generative AI to create your titles or descriptions, Google now requires you to use these specific attributes. To ensure transparency, Google wants to know how you created the content. While Google prioritizes the standard title and description attributes, if you provide both, compliance with these new attributes is necessary for AI-generated content.

Can AI Shopping features like virtual try-on increase conversion rates for apparel merchants?

Virtual try-on (VTO) can increase conversion rates for apparel and cosmetic merchants by addressing one of the biggest hurdles in online fashion retail: purchase uncertainty.

By allowing shoppers to visualize how clothes or makeup will look on their own bodies and faces, VTO builds confidence, enhances the shopping experience, and directly impacts sales.

Virtual try-ons can boost sales by up to 30%. The cosmetics brand Avon, for example, reported a staggering 320% increase in conversions with its virtual try-on tool.

The post-purchase is just as crucial to your bottom line. The cost of a return can be anywhere between 20 and 70 per cent of the original selling price, according to Hannah Bravo, Loop's COO. (Loop is a returns and exchanges management platform.)

How often should merchants refresh product images and descriptions for optimal AI performance?

Product images are your primary visual handshake with both the customer and the AI. Specific events and strategic goals should trigger refreshes.

Here is a recommended cadence: