Tag: Product Data Management

  • Google UCP and SEO: How I’m Preparing for AI Commerce

    Google UCP and SEO: How I’m Preparing for AI Commerce

    Google's Universal Commerce Protocol changes the path from search to sale

    For as long as I’ve worked in search marketing, I’ve viewed the path to purchase as a simple sequence: search query → click → buy.

    I’ve approached SEO through much the same model, using organic traffic, impressions, and click-through rate (CTR) as the primary measures of success.

    Google’s Universal Commerce Protocol (UCP) tells me that this familiar path is changing. Google is evolving from a discovery engine into a transaction layer where searching and buying can happen inside the same experience.

    With the rise of “agentic commerce,” I’m seeing Google gain the ability to discover, evaluate, compare, and purchase products on a user’s behalf within AI-powered experiences such as AI Mode, Gemini, YouTube, and Gmail.

    I believe the SEO implications are substantial. Instead of optimizing only for clicks, I now need to think about optimizing for AI-assisted transactions. If a brand cannot communicate through UCP and the product data that supports it, it risks becoming invisible to the next generation of shoppers.

    Here’s how I understand UCP, why I think it will reshape digital marketing, and what I recommend doing now to prepare an SEO strategy for agentic commerce.

    UCP: The infrastructure behind AI transactions

    I think of UCP as an open-source, vendor-agnostic standard that supports the entire commerce lifecycle inside an AI interface. That lifecycle can extend from product discovery and cart creation through checkout, fulfillment, and post-purchase tracking.

    Google co-developed UCP with Shopify, Walmart, Target, Wayfair, Etsy, and other commerce leaders. From my perspective, it acts as a universal translator between AI shopping agents and the systems merchants use to operate their online stores.

    Google UCP - Pay with GPay

    The clearest analogy I can make is that UCP may become the ecommerce equivalent of HTTPS. HTTPS standardizes secure communication between browsers and servers; UCP standardizes how AI agents interact with online stores. Instead of building a custom one-to-one integration for every merchant, an AI agent can use a shared framework to browse inventory securely and complete purchases across many stores.

    How I see AI transactions flowing through UCP

    Imagine I ask AI Mode to “find and order a replacement water filter for a 2021 Samsung French-door fridge with the fastest shipping.” UCP can coordinate that transaction through a structured workflow.

    Capability publication

    First, I expect the merchant to publish the capabilities its store supports, including product search, live pricing, fulfillment options, and accepted payment methods. This gives the AI agent a clear picture of what it can request and complete.

    Three mobile screens show a Monos suitcase listing, Google Pay order review, and completed checkout through Google’s Universal Commerce Protocol.
    From product discovery to payment and confirmation, this mobile shopping sequence shows a Monos suitcase purchase completed with Google Pay through Google’s Universal Commerce Protocol.

    Handshake

    Next, the AI agent reads the merchant’s profile, compares those capabilities with its own, and establishes a secure path forward. I see this step as the point where the systems can align on details such as loyalty programs and supported digital wallets.

    Action execution

    Once the systems are aligned, the AI searches for the product, verifies real-time inventory, builds the cart, and uses the Agent Payments Protocol (AP2) to complete a secure, tokenized transaction.

    Human escalation

    If the transaction needs my input—perhaps to select a delivery window or confirm a shipping address—UCP can pause the process and prompt me. After I respond, control returns to the AI so it can finish the workflow.

    Dig deeper: How Google’s Universal Commerce Protocol could reshape search conversions


    Why I believe UCP matters for search and SEO

    I don’t see UCP as merely a technical update. I see it changing the way AI discovers, evaluates, and purchases products—and that makes it directly relevant to SEO.

    1. I’m shifting from click-throughs to buy-throughs

    In an agentic search environment, I can no longer treat website traffic as the only measure of business value. Features such as Universal Cart can let shoppers add products from multiple retailers to one Google cart and check out with Google Wallet, dramatically shortening the buying journey.

    A shopper may never visit my homepage, category page, or product detail page. That changes my SEO objective: I need to earn product selection within the AI recommendation layer so a search query can become a sale even when it generates no intermediate website visit.

    2. I’m planning for hyper-personalized queries

    I’m also rethinking keyword research. Shoppers are moving beyond broad searches such as “men’s running shoes” and using detailed, situational prompts like “Best running shoes for flat feet under $150 that can arrive by Friday.”

    To match a request that specific, I know a search engine needs more than polished on-page copy. It needs rich, structured, and queryable product attributes. UCP helps bridge that gap by giving AI agents a way to match merchant inventory with a shopper’s precise requirements.

    3. I expect less checkout friction

    I continue to see cart abandonment as a major ecommerce challenge, especially when shoppers encounter long forms, broken checkout flows, or unexpected shipping costs. Because UCP can work with secure digital wallets and automatically pass verified user data, I expect it to eliminate many of those friction points.

    Glowing blue streams of people converge on a search bar and digital portal, symbolizing SEO traffic, AI visibility, and customer acquisition.
    As AI reshapes search, every glowing path to discovery carries commercial value—turning SEO investment into a conversation about pipeline, risk, and customer acquisition costs.

    For high-intent, urgent, or repeat purchases, I believe merchants that support UCP may capture more conversions than competitors that send every shopper to a separate checkout experience.

    4. I can retain brand control and customer ownership

    One detail I consider especially important is that the merchant remains the Merchant of Record when a transaction takes place through UCP. I can still control pricing, fulfillment, and return policies while retaining the customer relationship and first-party data. UCP provides the transactional infrastructure without replacing the merchant’s role.

    Dig deeper: Winning the AI decision layer: From AI discovery to agentic commerce

    How I recommend preparing a brand for UCP

    If I limit an SEO strategy to blog articles and meta descriptions, I overlook the technical infrastructure that powers AI commerce. To make products eligible for UCP-powered experiences, I recommend focusing on the following priorities.

    I would optimize the Merchant Center feed

    I no longer view Google Merchant Center (GMC) as a tool used only for Shopping ads. I see it becoming a primary source of product information for AI discovery, which makes feed quality central to both visibility and transaction eligibility.

    • Enable the native_commerce attribute: To opt into UCP-powered checkouts, I would add the native_commerce attribute to the product feed. Google recommends using supplemental feeds to apply it at the product level without changing the primary feed.
    • Map product identifiers: I would make sure every product ID in the GMC feed maps one-to-one with the corresponding ID in the internal checkout API. If the identifiers differ, I would use the merchant_item_id attribute to align them.
    • Complete policy data: I would keep returns, shipping, and customer-support information complete and current. Clear policy data gives an AI agent the details it needs to evaluate a merchant confidently.

    I would align structured data with the product feed

    Because AI search depends on consistent information, I would keep the Product, Offer, and Review schema on the website synchronized with the Merchant Center feed. If the price, availability, identifiers, or other details conflict, validation problems could make a product ineligible for AI-powered checkout.

    I would prepare for conversational attributes

    As Google introduces semantic attributes designed for conversational AI search, I would prepare inventory and product-information systems to supply richer answers. In particular, I would prioritize:

    • Real-time inventory availability.
    • Direct answers to product FAQs, such as “Is this jacket machine washable?”
    • Detailed compatibility information, including accessory pairings, sizing guides, and model-specific replacements.

    I would treat these details as more than feed enhancements. They are the signals that help an AI agent decide whether a product satisfies a nuanced request involving price, fit, compatibility, delivery speed, or another real-world constraint.

    Beyond clicks: The next SEO opportunity I see

    To me, the Universal Commerce Protocol reflects a broader transformation in search. It expands the role of SEO beyond generating traffic and brings product data, inventory systems, checkout infrastructure, and conversion readiness into the search conversation.

    By prioritizing structured product data, reliable commerce information, and readiness for agentic transactions, I can position a brand to capture demand at the exact moment a shopper expresses intent.

    I don’t believe the future of search will be only about getting found. Increasingly, it will be about making sure the products I represent can be evaluated, selected, and bought.


    Inspired by this post on Search Engine Land.


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  • How I’d Get Products Cited Higher in ChatGPT Shopping

    How I’d Get Products Cited Higher in ChatGPT Shopping

    I’m seeing product feeds become far more important in ChatGPT Shopping, especially as AI systems look for clean, structured product information they can trust and cite.

    Product detail pages still matter, but I no longer think brands can rely on PDPs alone when ChatGPT searches for product information. The signals that power AI shopping results appear to come from a broader mix of feeds, product data, availability, pricing, and clear brand-owned content.

    After looking at what more than 1 million ChatGPT shopping offers revealed, I’d treat product feeds as a core visibility asset, not just a backend ecommerce requirement. If my feed data is incomplete, inconsistent, or hard to match to the product page, I’m making it harder for AI shopping systems to understand and recommend my products.

    For brands, the takeaway is clear: I need to strengthen both my product feeds and my PDPs. The better my product data is structured, aligned, and easy to verify, the better chance I have of being cited higher in AI Shopping experiences like ChatGPT.


    Inspired by this post on Try Profound Blog.


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  • Discover Microsoft’s Product Explorer for Enhanced Ad Performance

    Discover Microsoft’s Product Explorer for Enhanced Ad Performance

    I’m excited to share Microsoft Ads’ latest tool—Product Explorer. It’s a remarkable addition that helps advertisers like us quickly spot catalog issues that might be hindering ad performance.

    The introduction of Product Explorer represents Microsoft’s effort to create a central hub where advertisers can effortlessly monitor product catalog health and performance. Navah Hopkins, the Microsoft Product Liaison, highlighted its potential to revolutionize how we handle large product feeds.

    Managing these expansive feeds often means struggling to pinpoint which items are ready to serve, which are capturing impressions, or which are missing vital data. Product Explorer steps in to make this task significantly more manageable.

    What’s new? Now, I can explore my entire product catalog through a searchable interface. This tool allows for filtering by SKU, title, GTIN, and product ID, helping to quickly identify active products that are delivering performance results.

    What it does. Product Explorer is designed to highlight eligibility issues and metadata gaps, along with other elements that might prevent products from serving. Plus, it offers recommended actions and the option to export filtered product lists for deeper analysis.

    ```json
{
  "alt": "Product listing page in Microsoft Advertising showing product details like ID, image, title, status, price, and impressions.",
  "caption": "Explore the Microsoft Advertising product listing page, showcasing various home and kitchen items with detailed status and pricing information.",
  "description": "This image displays a product listing page from Microsoft Advertising, featuring items such as kitchen towels and coffee makers. The table includes columns for product ID, image thumbnails, titles, statuses (accepted, pending, rejected), prices, and impressions. The interface allows for filtering, editing columns, and downloading data, ideal for online retail management. Keywords: Microsoft Advertising, product listing, home and kitchen, pricing, status, impressions."
}
```

    Why we care. As advertisers, having diagnostics and performance reporting combined in one interface means we can move more products into a servable state while identifying underperforming inventory more efficiently.

    From searchable catalog reporting to gaining product-level performance insights covering the last 30 days, this tool offers issue detection and actionable recommendations to enhance feed quality.

    The big picture. As retail advertising becomes more automated, focusing on feed quality is increasingly essential. Accurate visibility into catalog issues can significantly impact the reach and performance of our campaigns.

    Availability. According to Navah Hopkins, the tool is live and ready for use in our accounts.


    Inspired by this post on Search Engine Land.


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  • Google Ads Unveils Robust Merchant API Before Content API Exit

    Google Ads Unveils Robust Merchant API Before Content API Exit

    I recently discovered some exciting news that Google Ads has introduced a more robust Merchant API. This new API is crafted to offer advertisers scalable and feature-rich tools for handling product data, especially as we prepare for the shutdown of the Content API for Shopping.

    Google is steering us toward a more modern, scalable infrastructure for Shopping integrations. This shift brings cutting-edge capabilities, including AI tools, directly into our scripting workflows.

    What’s happening: Starting April 22nd, Google Ads scripts will support the Merchant API. This change comes as we approach the August 18th retirement of the Content API for Shopping. This new API will be available as an Advanced API within the scripts editor while we can still use the Content API until its official sunset.

    What’s new: The Merchant API introduces a modular architecture, breaking down functionality into sub-APIs for quicker updates, easier maintenance, and fewer disruptions. This setup enhances capabilities with features like the Google Product Studio API for generative AI, APIs dedicated to product and store reviews, and a Notifications API for real-time updates.

    Additionally, we now have more control over data management. This includes handling supplemental product data, managing local and regional inventories, and running promotions—all within an omnichannel system while still supporting our legacy setups.

    Why it matters: The Merchant API provides a more flexible approach to managing product data at scale. It’s especially beneficial for complex or omnichannel setups and introduces new capabilities like AI-driven content tools that can boost feed quality and performance. With the imminent retirement of the Content API, transitioning to this new system is crucial to avoid disruptions and maintain competitiveness.

    Yes, but: Switching to the new API requires adjustments, particularly for those of us with custom scripts or complex feed setups tied to the legacy API.

    Bottom line: For those of us using scripts, this is our chance to upgrade to a more powerful and scalable integration, enabling new features while future-proofing our Shopping workflows before the cutoff date.

    Dig deeper: Merchant API is coming to Google Ads scripts starting April 22, 2026


    Inspired by this post on Search Engine Land.


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