I’m adjusting how I refer to Google’s shopping platform now that Google has dropped “Next” from Merchant Center Next. Going forward, the product is simply called Google Merchant Center.
Google made the change official in a Merchant Center announcement, saying, “The platform you use today will simply be referred to as Google Merchant Center.” For anyone managing product feeds, shopping campaigns, or merchant accounts, this is mainly a naming update rather than a product change.
I remember when Google Merchant Center Next was introduced in 2023 as the newer version of the old Google Merchant Center. Over the past few years, more merchants, site owners, and advertisers moved into that updated experience.
At this point, it appears that Merchant Center Next has effectively become the standard experience. So Google is removing the “Next” branding and returning to the simpler name: Google Merchant Center.
Rows of illuminated data cabinets and paper files stretch into the distance, capturing the pressure on marketers to turn fragmented customer data into a smarter performance engine.
Google said users will start seeing the “Next” branding removed from Help Center articles, email communications, and the Merchant Center interface.
Google also clarified that no action is required and that the name change does not affect existing accounts. In other words, I do not need to update settings, migrate anything, or make account-level changes because of this rebrand.
Why does this matter? When I talk about Google’s merchant tools now, I can leave off “Next” and just call the platform Google Merchant Center. Honestly, that is what many of us were already calling it anyway.
I’m seeing Google expand merchant listing structured data with support for sale duration and the Product.category property. The update brings Google Search’s merchant listing structured data closer to the capabilities already available in Google Merchant Center feeds.
Sale duration. Google added a new Sale duration section to its Merchant listing structured data documentation. In that update, Google said the guidance explains how to use the validFrom, validThrough, and priceValidUntil schema.org properties to define the effective date range for sale prices.
I find this useful because Google’s guidance also covers best practices and examples for placing those properties on either Offer or PriceSpecification nodes. Google said the change aligns schema.org usage with the Merchant Center feed attribute sale_price_effective_date, giving merchants clearer instructions for handling sale price timing in structured data.
Google's sale duration guidance shows merchants how to define when a sale price starts and ends in structured data, including Offer and UnitPriceSpecification JSON-LD examples.
Here is the new sale duration section Google added:
Product category. Google also updated the same Merchant listing structured data documentation to include support for the Product.category property.
Google’s merchant listing guidance now shows how product categories can mix custom text labels with Google Product Category codes in structured data.
Google wrote that the documentation now explains how Product.category can be used with both Text and CategoryCode types. According to Google, this aligns with Google Merchant Center feed specifications for the product_type and google_product_category attributes.
From my perspective, this makes the structured data more practical for merchants because it lets them provide both merchant-defined and Google-defined category details directly in schema.org markup. Google said this can enhance product information for Google Search and Shopping.
A glowing Google search bar cuts through streams of digital data, capturing the fast-moving world of search, shopping visibility, and SEO innovation.
Here is what Google added for product category support:
Why I care. If I maintain merchant listing structured data for Google, these additions are worth reviewing. Product category support can help Google better understand the products being provided, which may improve how those products match relevant queries.
I also see sale duration support as a practical improvement for planning promotions. When I update merchant listing structured data, I can now define sale price timing more clearly and align that markup more closely with Google Merchant Center feed behavior.
I’m seeing an important shift for Standard Shopping campaigns: Google is bringing Maximize Conversion Value bidding to these campaigns without requiring a Target ROAS. That gives advertisers more room to pursue value-based optimization without immediately being locked into a specific return target.
What’s happening. Google is rolling out Maximize Conversion Value bidding for Standard Shopping campaigns, and advertisers no longer have to set a Target ROAS to use it.
Before this update, if I wanted to optimize around conversion value in Standard Shopping, I generally had to use a Target ROAS bidding strategy. Now, this new option lets campaigns focus on maximizing conversion value while giving Google’s bidding system more flexibility to find the highest-value opportunities.
Why I care. This matters because I can now use Google’s value-based bidding in Standard Shopping without being constrained by a Target ROAS goal. That gives me more flexibility while preserving the control and transparency that many advertisers still prefer in Standard Shopping campaigns.
It may also reduce the need to run feed-only Performance Max campaigns just to access Maximize Conversion Value bidding. For advertisers who prefer tighter campaign control, that is a meaningful change.
Between the lines. I know many advertisers have continued to favour Standard Shopping because it offers more visibility and control than Performance Max. But when they wanted flexible value-based bidding, they often created feed-only Performance Max campaigns as a workaround.
With this update, that workaround may no longer be necessary for some accounts.
Why advertisers should care. I can now combine the structure and transparency of Standard Shopping with a more flexible automated bidding strategy. In practical terms, this could simplify campaign setups, reduce unnecessary Performance Max usage, and make account management cleaner.
The bottom line. Google is narrowing one of the biggest feature gaps between Standard Shopping and Performance Max. For me, this gives advertisers another reason to keep using Standard Shopping while still benefiting from automated value-based bidding.
First spotted. Performance marketer Yash Mandlesha spotted the update and shared the option on LinkedIn.
Imagine scrolling through Google Search and effortlessly collecting items from various retailers into one convenient Universal Cart. That’s exactly what Google is offering now, a seamless shopping experience that allows me to keep all my desired products in one place and check them out with a single click using Google Wallet.
Recently announced by Vidhya Srinivasan, VP/GM Ads & Commerce, Google’s Shopping Graph has reached an impressive 60 billion product listings, a significant jump from the 50 billion earlier this year. This growth reflects Google’s commitment to enhancing our online shopping experiences.
Universal Cart. With Universal Cart, I can add items from multiple stores while browsing Google Search, or even when I’m on YouTube and Gmail. It’s so liberating not to jump from site to site!
Here’s how it works: as I shop, Google helps me find the best deals and in-stock availability across different retailers. Then I simply choose my preferred store for checkout, leaving no room for the hassles generally associated with online shopping.
Google’s Universal Cart is smart too! Imagine you’re assembling a custom PC—your cart will alert you if any parts are incompatible and suggest compatible alternatives. Built on Google Wallet, it even recognizes payment perks and loyalty offers, revealing savings opportunities I might otherwise overlook.
Merchants. Google has partnered with renowned merchants like Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, and Shopify sellers such as Fenty and Steve Madden. This wide array ensures I have plenty of shopping options!
Availability. This feature will roll out in the U.S. this summer, initially available on Google Search and the Gemini app, with plans to expand to YouTube and Gmail soon after.
UCP and AP2. Google is also extending the Universal Commerce Protocol to Canada and Australia soon, with plans for the U.K. The Agent Payments Protocol will support secure, accountable transactions by authorizing agents to shop on my behalf according to my specific criteria.
Moreover, Google’s innovative features are set to debut across Google products, starting with Gemini Spark. It’s an exciting time to be an online shopper!
When I search for products on Google, I’ve noticed significant changes to the results page. Now, product packs and scrollable carousels appear multiple times within a single results page, reshaping my shopping experience.
As part of my ongoing journey to boost ecommerce visibility, I constantly analyze data. Recently, I’ve tracked searches presenting up to 60 individual organic product listings on one page. These premium placements increasingly mark the beginning of the purchase journey for many users.
This transformation is gradual, and interestingly, I see many brands still adjusting their strategies. It’s crucial to revisit these changes because the opportunity for traffic through product packs is immense, with fierce competition. Today’s leading brands approach this differently.
Thanks to Nozzle, I’ve delved into data from over 63,000 merchants across a wide array of ecommerce keywords from January 2025 to January 2026. Here’s what I discovered that really caught my attention.
Defining Success: Appearances vs. Actual Traffic
I found that just appearing in product packs and actually capturing traffic are two distinct achievements, and the difference between them can be substantial as the data shows.
For instance, in this dataset:
eBay appears in product results for 874,621 keywords.
Home Depot has a similar presence, appearing for 831,699 keywords.
However, the estimated traffic paints a contrasting picture:
eBay garners about 3.2 million visits from these pack appearances.
Home Depot, meanwhile, generates nearly 28.8 million visits from a slightly smaller keyword range.
The secret? Quality position within the pack. Home Depot’s products consistently snag prime, visible, above-the-fold spots that attract shoppers’ clicks.
For eBay, many keywords involve long-tail marketplace terms that dilute overall impact. Understanding Google’s use of product packs to drive purchase decisions for common goods is crucial for brands aiming to compete effectively in this space.
For marketers: Dissecting product pack performance means wisely segmenting data, focusing on categories with significant search volumes to optimize visibility within the packs. That’s how to pinpoint where the genuine opportunities lie.
The Critical Gap: Distinguishing Product Pack Visibility
Product carousels scroll horizontally, increasing exposure for the first few slots, while listings tucked further back remain unseen. This distinction is crucial for assessing true reach.
Disparities among major retailers further illustrate this point:
REI has a massive catalog of 3.8 million products, yet 1.52 million of these require scrolling before they are visible.
Walmart finds itself in a similar spot, with 1.29 million of its 3.5 million unique products are relegated to non-visible placements.
Even industry titans often miss out on optimal visibility, skewing the perceived benefits of their presence. Analyzing visible versus non-visible appearances is essential for identifying where optimizing product data and feeds can yield substantial returns.
For CMOs: When using total product pack appearances as a metric, it’s wise to ask how many of those appearances are truly visible. Understanding this ratio better reflects the channel’s contribution to the business.
Does Discounting Drive Product Pack Visibility?
It’s a common belief that discounted items might secure better placement in Google’s product packs. However, data from the top 10 merchants doesn’t necessarily support this notion.
Amazon.com leads the pack with 49% of its catalog discounted, achieving a 72% visibility rate, placing it squarely mid-tier.
eBay, on the other hand, discounts only 8% of its products yet matches the highest visibility rate in the dataset at 81%.
Walmart Seller discounts 24% of its items, reaching 81% visibility, while Walmart itself discounts 27% but ranks lower at 62% visibility.
This irregularity indicates that discounting is just one of many factors. It doesn’t solely determine a product’s chance of securing a prominent spot. Feed quality, category relevance, reviews, and image standards wield greater influence.
For retail teams: If your strategy for product packs relies heavily on promotions, you might need to pivot. The current landscape favors strategies aligned with where purchasing decisions occur over sheer pricing tactics.
Specialist Brands Competing with Giants and Winning
A refreshing realization from this data is that product pack success isn’t exclusive to the retail giants. Specialist brands, leveraging focused expertise, compete exceptionally well against far larger competitors.
Camp Chef, for instance, appears in results for 155,299 keywords—just a small fraction of Walmart or eBay’s footprint—yet it pulls in an estimated 2.6 million visits, thanks to advantageous product placements.
Brands like Fellow, expanding into niches such as high-end coffee makers, find opportunities for growth through strong organic channels.
These brands achieve impressive product pack traffic against much larger rivals because they prioritize category relevance and high-quality product feeds over sheer scale.
For brands traditionally overshadowed in traditional SEO, product packs present a chance to compete on a more level field. Detailed product data, competitive prices, quality imagery, and favorable reviews can supersede a larger competitor for crucial category keywords.
For agencies: This channel awards dedication and quality over brute scale. Brands with depth in a category can translate that expertise into superior product pack performance, outpacing broader competitors.
Staying Informed on Product Pack Visibility Shifts
Examining the entire dataset, I noticed a consistent pattern: nearly all merchants experience shifts in product pack visibility throughout the year.
Brands holding strong positions during parts of the year sometimes see fluctuations as Google adjusts how it surfaces product results. Some grew steadily midyear only to recede in Q4, while others surged during promotions before reverting to previous levels.
This fluidity is typical of the channel. Google regularly updates its criteria for product pack placements, influenced by factors like feed quality, product availability, review counts, pricing, and images.
The brands thriving are those with sustained visibility into performance, staying agile and responsive to changes before they impact revenue.
With Google’s future announcements and AI integration like Gemini 3 looming, the foundational structure of product packs will shift, influenced by agentic commerce and the Universal Commerce Protocol.
As Google navigates balancing paid and organic visibility, a two-tiered search economy emerges. Securing AI Overview citations becomes vital for brand recognition, impacting both organic and paid product pack performances.
The Bigger Picture
Google’s product packs have morphed from merely supplementary to pivotal touchpoints in commercial searches.
The extensive Nozzle data analysis of over 63,000 merchants reveals that competition is already fierce in this domain. Leaders are distancing themselves, and the gap between attentive and indifferent brands manifests tangibly in traffic and revenue disparities.
The silver lining is that the essentials for success in this space are accessible to most brands: robust product data, strategic pricing, high-quality creative, and vigilant monitoring.
These require not a colossal budget but focus, the right tools, and asking the right strategic questions within the right organizational levels.
Recently, I’ve discovered that Google is stepping up its game in AI tools for advertisers and retailers.
They’re testing something quite futuristic called Merchant Advisor, an AI assistant integrated directly into the Merchant Center. This tool aims to simplify the process of setup, troubleshooting, and optimization for us all.
What’s happening. As someone who watches Google’s every move, I’ve noticed them testing Merchant Advisor, a cutting-edge AI-powered chatbot right within Google Merchant Center. Although in beta, its purpose is clear: to offer personalized recommendations and support, making my experience smoother than ever.
How it works. The Merchant Advisor acts like a proactive assistant, offering tasks and suggestions like setting up a returns policy or finalizing account setup steps. It feels like having an assistant who is always available to enhance my feed quality and account health.
The bigger trend. This development is part of Google’s strategy to weave AI assistants throughout its marketing products, reminding me of earlier launches like Google Ads Advisor and Analytics Advisor. The AI co-pilots are evidently becoming the norm for managing campaigns and analytics.
Between the lines. Let’s face it, Merchant Center can be a technical labyrinth, especially for smaller retailers juggling feeds, policies, and diagnostics. But now, with an embedded AI guide, I’m finding it less daunting to get onboarded quickly and spot optimization opportunities I might have overlooked.
Spotted by. This feature first caught the eye of Tamara Hellgren during a Google Ads Decoded podcast episode that focused on retail innovations.
The bottom line. It’s clear to me that Google is transforming the Merchant Center into a more intuitive, AI-assisted environment, which reflects a larger trend towards automation within its advertising landscape.
Having my Google Merchant Center account suspended felt like a gut punch. One moment, everything’s running smoothly, and the next, you’ve lost access to Google Shopping and your most lucrative sales channel is cut off. It’s daunting, but here’s how I managed to turn things around.
Initially, I needed to understand why my Merchant Center was flagged. It required a comprehensive audit of my site and feed to pinpoint and correct the issues before I could confidently request a review.
Google imposes strict policies for Google Shopping, stricter than its general advertising rules. Any perceived violation can lead straight to suspension. Let me walk you through my experience and offer some heartfelt guidance.
Here’s what I did to fix the suspension and bring my account back online. I learned it’s not just a matter of addressing one big issue; often, it’s a combination of smaller gaps that signal untrustworthiness to Google’s automated systems.
The first step was a complete compliance audit of my website and Merchant Center settings. I discovered that my Contact Us page needed a physical address and professional email. These are small details that Google flags for authenticity.
Next, I addressed policy pages like shipping, returns, and refund policies, ensuring they contained all the necessary details such as cancellation terms and payment methods.
Additionally, I ensured the functionality of my site was up to par. It was essential that Google could crawl my site without issue. I fixed URL structures and ensured product data matched across platforms.
Each change was meticulously documented and prioritized. Once everything was set, I requested a review from Google. It felt rewarding when Google approved the appeal and reinstated my account.
Key takeaway: It’s crucial to understand that reinstatement often requires addressing multiple aspects of your site and data feed. Google evaluates your entire ecosystem, not just isolated elements.
Most product feeds are traditionally geared towards paid media. But I’ve discovered aligning them with organic search behaviors significantly enhances visibility across Shopping and AI platforms.
When I ask most e-commerce brands who manages their product feed, the response is usually the same: the paid media team is in charge.
Often, a feed management tool is categorized under PPC. It might even be a relic created by the shopping team years ago, with titles that haven’t been updated since. SEO, unfortunately, rarely has its say in these strategies.
Whether you’re focused on AI-powered search or traditional clicks, excluding SEO from your product feed strategy means missing out on substantial opportunities.
AI Shopping Results Are Connected to Google Shopping Data
According to a recent Peec AI study, up to 83% of ChatGPT carousel products reflect Google’s organic Shopping results—and 60% of those are from Shopping positions 1-10.
Data shows how ChatGPT’s product carousel matches Google Shopping’s organic results, with Google dominating over Bing.
On Google’s side, their Shopping Graph includes over 50 billion product listings, directly feeding AI Overviews, AI Mode, and Gemini. AI Overviews now appear in about 14% of shopping inquiries, a leap from roughly 2% in late 2024. As I’ve seen, AI search results are still largely based on the traditional search engine result page (SERP).
SEO is vital for establishing brand authority. It opens up valuable opportunities to collaborate across channels for improved search visibility. It’s time for SEOs, commerce, and paid media teams to come together.
The Case for a Dedicated Organic Feed
Most brands run a single product feed aimed at Google paid shopping campaigns. The focus is often on optimizing titles for bid relevance and descriptions for Quality Score rather than for user search behaviors.
As user search habits evolve, aligning product data with search queries becomes increasingly important. A title with too many paid-friendly modifiers doesn’t necessarily match natural search queries.
When we tested this with a major ecommerce brand, our agency’s AI SEO team worked with the commerce team to create a dedicated product feed just for organic listings. Optimizing specifically for organic visibility made a world of difference.
After implementation, we saw the following results:
Organic listing CTR increased by 10% month over month and purchasing rates rose by 4%.
A product-level test revealed a 92% increase in revenue for free listings, with an 83% increase in visibility and a 14% rise in add-to-cart rates.
Organic optimizations alone generated 35,000 impressions with a 1.4% CTR—55% higher than paid CTR for the same period.
We recognized that our paid and organic strategies serve different needs, so they should be optimized independently. Organic feed titles should reflect how customers naturally search.
What to Prioritize in an Organic Feed Strategy
Not all feed attributes are equally important. Whether you’re setting up a dedicated organic feed or auditing an existing one, these elements are essential starting points.
Focus on Titles as the Key Lever
Google’s algorithm favors feed titles highly in matching products to queries. As Google documentation suggests, including significant attributes can lift performance. Consider what customers might conversationally say when searching for your product.
Google’s Merchant Center documentation emphasizes aligning your feed strategy with how customers shop, enhancing their search journey.
Don’t Neglect Global Trade Item Numbers (GTINs)
According to Google’s GTIN documentation, products with accurate GTINs gain significant visibility. Data shows well-matched products can attract up to 40% more clicks and are key in aggregating reviews.
Images Add Value
Images are often flagged in Merchant Center disapprovals. Products with both standard and lifestyle images engage more users. Google’s Product Studio can assist in editing, helping SEO and creative teams work together on feed assets.
Optimize Key Attributes: product_highlight and product_detail
product_highlight allows you to add concise benefit statements in Shopping views. Descriptions like “water-resistant for light rain commutes” are more beneficial than vague terms like “high-quality material.”
product_detail gives structured specs that influence Google’s filters in product grids.
The semantic optimization SEOs apply to product pages should guide feed attributes. Product and content teams’ insights are vital not just for PDPs but also for feeds.
Your Feed is Your Agentic Commerce Foundation
Investing in feed optimization for organic visibility will prepare your brand for the agentic commerce landscape.
Google’s Universal Commerce Protocol is essential for AI agents to complete transactions directly in AI Mode and Gemini. Feeds entering the Shopping Graph fuel AI responses to shopping requests.
Google added the native_commerce attribute for UCP-powered buy buttons across Google services. Several new conversational commerce attributes will soon be available, which means feed and on-page content must be in sync.
Building a Cross-Channel Strategy for AI Search
Product feed strategy is ideal for cross-team collaboration to test, execute, and measure brand visibility. A harmonized approach across all surfaces benefits both traditional and AI-driven search outcomes.
SEOs contribute keyword intelligence and semantic insights about AI system matching.
Commerce teams manage product data and retail relationships.
Paid teams have the infrastructure and expertise in feed health management.
These teams should collaborate to create a unified AI SEO strategy. Reviewing existing feeds and gathering all relevant stakeholders is essential to developing a comprehensive and effective product feed strategy.
As I delve into the world of e-commerce, I’m constantly amazed by how paid search can transform business growth. Platforms like Google Shopping and Amazon Ads are game-changers, offering high conversion rates and efficient spending when campaigns are crafted thoughtfully.
These platforms are adept at capturing high-intent demand, providing the crucial data to expand my campaigns. They connect search queries directly to revenue streams, letting me pinpoint which terms are boosting sales so I can allocate my budget wisely.
However, the true test lies in organizing campaigns to effectively leverage this data.
Why does paid search excel in e-commerce? It’s all about intent and data. Google and Amazon thrive on search-driven environments. When someone seeks a product, they’re clearly expressing their needs. I don’t need to make inferences; I’m delivering precisely what customers want.
Moreover, Google Shopping and Amazon Ads offer unparalleled keyword-level revenue data. This insight helps me understand conversion rates and costs better. Amazon, in particular, shines with its granular product and category level revenue visibility.
Together, this data forms a powerful feedback loop. By analyzing which terms tie back to revenue, I can strategically shift my spending and enhance my return on ad spend (ROAS) over time. On Amazon, higher conversion rates even boost organic rankings, reducing future acquisition costs.
My success in search campaigns hinges on creating multi-funnel structures. While the concept remains consistent, execution varies based on campaign types, settings, and bidding strategies.
I implement campaign architectures that utilize wide-net, low-cost discovery initiatives to explore the search landscape. High-intent converters funnel into dedicated performance campaigns with strategic bidding. This approach not only strengthens ROAS but also enhances rankings and fosters scalable growth.
Embarking on Google Shopping, the priority sculpting method, inspired by Martin Roettgerding, is invaluable. Utilizing a three-layer campaign structure, I route keywords into distinct campaigns based on their performance.
This strategy optimizes spending on discovery keywords and directs investment toward high-performing, high-intent terms. The Google Shopping priority settings are pivotal; high-priority campaigns initially serve at lower bids.
Layer 1 focuses on capturing branded search traffic through a Performance Max campaign, maintaining an assetless format to focus on shopping inventory and avoid bleeding into other channels.
Layer 2, the catch-all, casts a wide net, experimenting with search terms to gather conversion data, while Layer 3 dedicates budget to best-performing terms, aligning with high-ROAS strategies.
Amazon’s multi-tier campaign structure offers its own set of advantages, like higher conversion rates and the intricate connection between ad spend and organic rankings. Campaigns are organized at the SKU level, employing research, ranking, and performance tiers.
Each tier serves a unique purpose, managed by differing advertising cost of sales (ACOS) targets, tailored for profitability. The research tier explores broad keyword possibilities, performance tiers maximize returns on proven converters, and ranking tiers drive organic positions aggressively.
Both Google Shopping and Amazon Ads offer unique opportunities in the e-commerce landscape. Whether aiming for short-term gains on Amazon or long-term brand building via Google, using these platforms synergistically can propel a business to new heights.
When I learned about Google’s latest protocol, I realized how significant this new development could be for those of us in ecommerce. Google’s Universal Commerce Protocol (UCP) is here to revolutionize how purchases are made within the Gemini and AI search environments. It allows users to make purchases without ever leaving Google’s interfaces, which changes the game for search conversions.
As Google introduces AI Overviews, AI Mode in Search, and the Gemini ecosystem, a new challenge presents itself: how do users get answers and complete purchases seamlessly within Google’s spaces? That’s where UCP comes in, currently in its beta phase.
UCP is a tool designed to help brands reach customers directly within the Gemini or Language Learning Model (LLM) environments. It allows consumers to finalize transactions, earning reward points, and completing checkouts, all within the LLM. Imagine telling Gemini, “Find me a highly rated, waterproof hiking boot in size 10 under $200 and buy it,” and watching as UCP makes that transaction happen smoothly.
At its heart, UCP standardizes the communication between consumer AI interfaces and merchant checkout systems. Although Google’s developer documentation might mention terms like “Model Context Protocol (MCP)” and “Agent2Agent (A2A) interoperability,” the process is actually user-friendly:
UCP leverages your existing Google Merchant Center shopping feeds. It ensures you remain the merchant of record, thus preserving your customer relationships and data. Plus, by integrating checkout within Google’s AI ecosystem, it minimizes cart abandonment and boosts conversions.
Implementing UCP involves enhancing your shopping feed management and staying updated on best practices. Google’s guidelines suggest focusing on feed data hygiene, conveying trust signals, and upgrading your technical infrastructure.
To excel in this new system, it’s crucial to detail your product listings accurately and ensure comprehensive descriptions. Trust and convenience become paramount as AI-driven decisions heighten consumer’s purchasing confidence. Providing data on free shipping, return policies, and reliable pricing can make a difference.
Finally, preparing for UCP means keeping pace with technological updates and future tools. Venture into Google’s pilot programs and explore features like Business Agents or Direct Offers to stay ahead in this evolving landscape.
The evolution of search into a transactional engine within LLMs is undeniable. UCP offers a clearer path from search discovery to purchase conversion, and it’s up to us to adapt and thrive in this shift by ensuring our product data is impeccable.
