I’m excited to share that Google has introduced a new feature designed to streamline the ad approval process called Real-Time Policy Reviews. During the creation of campaigns, this system offers instant feedback, making it faster and easier to get ads up and running.
The feature is currently tailored for Responsive Search Ads, but Google has plans to expand it to other campaign types within the year. This means as I create ads within Google Ads, I receive immediate policy feedback, eliminating the need to wait in a post-submission review queue.
The real magic happens in two phases. First, as I draft my ad, the system flags any editorial issues instantly, like typos or errors with destination links, allowing me to correct these before finalizing my ad.
Once I’ve saved the ad, Google provides a policy decision immediately. Ads that pass without any issues can go live almost instantly, whereas those with more complicated violations are redirected to a post-save review page, detailing the problem and outlining possible solutions.
I find this update crucial because it reduces campaign launch delays, especially during promotions or product launches that demand immediate action and can’t afford postponements.
Google has segmented policy issues into two main categories: ‘editable,’ which are simple problems I can fix on the spot like formatting errors, and ‘complex,’ which need further certifications or appeals.
This aligns with Google’s ongoing mission to make campaign management smoother by integrating it into our day-to-day tasks, especially essential for those rapid-response campaigns.
As Real-Time Policy Reviews become available across more campaign types, I anticipate a faster transition from creation to delivery. However, it also emphasizes the importance of addressing compliance throughout my creative process.
I’ve recently discovered that Google is reshaping our approach to Display Ads by integrating them into Demand Gen campaigns, providing us with wider reach and innovative AI-driven features.
What’s happening? Now, I can effortlessly manage my placements on the Google Display Network (GDN) through Demand Gen campaigns. Interestingly, I still have the option to keep my ads running exclusively on GDN if that’s more suitable for my needs.
Through Demand Gen campaigns, I’m able to extend my ad reach across YouTube, Discover, Gmail, Maps, and a vast array of Display Network sites, all within a more centralized system.
Why do I care? This strategic shift by Google is crucial because it centralizes more inventory, harnesses automation, and leverages AI for enhanced campaign optimization. It’s become an essential factor for my performance and discovery ad strategies.
As a Display advertiser, these adjustments mean I gain access to advanced AI features, greater cross-platform reach, and potentially increased efficiency. I see this as a shift towards less reliance on traditional standalone Display management over time.
The bigger picture. Google is steering Demand Gen to be the go-to campaign type for visual discovery advertising, merging creative social-style distribution with its powerful AI targeting capabilities.
Google claims an average ROI increase of 9.5% for those who’ve added GDN inventory to their Demand Gen campaigns, and I’m intrigued by the potential benefits.
Between the lines. These changes provide me with access to the latest Demand Gen features announced at Google Marketing Live, including enhanced channel controls and forward-looking AI campaign tools.
What to watch. With Google’s ongoing journey towards consolidating campaign management under AI-led products, I find myself reevaluating my strategies for upper-funnel discovery, Display, and performance-centric media purchasing.
I recently followed an intriguing conversation with Google’s CEO, Sundar Pichai, where he explored the transformative journey that awaits Google’s AI, Search, and digital tools. The path forward envisions these elements coalescing into a unified powerhouse capable of executing tasks seamlessly.
In a detailed exchange with Nilay Patel from The Verge, Pichai addressed concerns about an evolving Search landscape. He firmly reiterated Google’s commitment to connecting users with the open web, assuaging publisher concerns about potential traffic declines.
Pichai assured, “Through it all, we are very committed to both meeting user expectations and also connecting them to what’s out on the web.” Yet, it’s clear why some fears persist as Google steers towards an AI-driven future where Search evolves to include conversational agents and task-oriented tools, reducing the need for traditional clicks.
Why we care. It’s important to recognize the emerging landscape, one where Google’s Search, Gemini, and agent technologies blend into a singular AI layer. This shift points toward a revamped approach to discovering information, creating content, and handling tasks.
Agents are the future. These AI agents are poised to drive the next evolution on the web. According to Pichai, “I look at agents, and that is the next evolution of the web. I think it will evolve the web pretty profoundly.”
In the background, Google’s efforts in developing agentic tools across Search, Gemini, Spark, and Antigravity aim to bring these innovations together for a more cohesive user experience. Acknowledging this unified trajectory, Pichai envisions Google’s ecosystem as evolving into an ‘agent manager’ model.
One product. When asked if Google’s suite of AI search and app-building tools might eventually merge into one, Pichai affirmed, “It will.” This convergence means Google agents will quietly assist users in planning and executing tasks, a vision for which Google is diligently assembling essential building blocks.
Pichai elaborated, “We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work.”
Dig deeper. Explore perspectives on how Google’s Search and Gemini might converge or continue to diverge in the discussion led by Google’s Liz Reid.
Google rejects Google Zero. In the face of concerns about Google’s evolving role in web traffic, Pichai illustrated his view of an expansive information ecosystem, far broader than Google alone.
Addressing Condé Nast’s apprehension about declining search traffic, he highlighted the dynamism of the current landscape, where publishers adapt continually to shifts in user behaviors and new digital formats.
“It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world,” he observed.
Google says some clicks are going away. While Pichai refrained from advising publishers on business planning, he emphasized that as technology improves, low-quality clicks naturally dwindle, alongside metrics reflecting a decline in bounce clicks.
Google points to subscriptions. By highlighting Google’s adjustments to support subscription models, Pichai acknowledged this as a key adaptation amid evolving publisher strategies.
“We are adapting to the fact that publishers are increasingly turning to subscription offerings, too,” he stated, promoting Google’s efforts to highlight subscribed content as preferred sources for users.
It’s worth noting that the drive towards subscriptions was, in part, a response to diminishing reliance on search traffic.
Search had to move faster. The decision to reorganize Google Search was a strategic move to enhance agility in the rapidly advancing AI era, positioning the platform for rapid decision-making and innovation under new leadership.
For more insights into Sundar Pichai’s thoughts on AI, search, and the future of the web, consider listening to the full interview here.
When I think about the future of AI in search engines, I’m reminded of a statement by Nick Fox, Google’s senior vice president of Knowledge & Information. He believes that as AI begins handling simpler search queries, we need to focus on crafting content that’s richer with human perspectives—something AI summaries simply cannot replicate.
As I ponder how our content can remain relevant in the age of AI, I remember Fox’s advice shared during the Google Marketing Live 2026 interview with Ben Smith of Semafor. Here, he emphasized that quality content must transcend surface-level answers to truly shine.
Consistency is key. Fox noted that our approach to ranking in AI search remains similar to traditional methods. It’s all about crafting exceptional content.
“The way to optimize for AI search is the same way to optimize for search. Create great content.”
He advised, though, that moving beyond basic summaries is crucial.
“The additional piece of advice we give is go beyond the surface level.”
According to Fox, while AI summaries might address initial queries, the content that truly excels goes further, answering deeper layers of questions.
“If you assume that the AI will provide sort of a first-level response, high-level framing, the best content that will do the best within AI is one that goes one level deeper, two levels deeper, and is really helpful there.”
It got me thinking—how does Google distinguish “deeper” content from just longer pages?
The human touch AI can’t duplicate. I find it intriguing that Google’s new AI search guidelines emphasize the value of content AI can’t easily reproduce. These guidelines caution against creating “commodity” content that merely echoes others or is readily generated by AI models.
Producing content that offers little in unique insight is discouraged, whereas content rich with expert or personal experience goes far beyond the ordinary, and that stays with me during content creation.
During the interview, Fox highlighted the web’s future role, emphasizing the need for human perspective in AI-driven search results.
“If you’re looking to buy something, you don’t just want to hear what the AI says. You want to hear from someone who’s used it. What did they think? What did they experience? What was amazing about it? That kind of rich human content is invaluable.”
“As humans, we want to hear from other humans. We crave human perspectives and experiences.”
Addressing traffic concerns. I’m aware that Google’s focus on human experience underscores the web’s value, even as AI summaries cut down on organic search traffic clicks that traditionally supported such enriching content.
Unfortunately, the interview didn’t touch upon how AI summaries might shrink organic search traffic or counteract these drops.
Changing search habits. Observing people has shown me that search behavior is evolving, influenced by conversational AI tools. As Fox pointed out, queries are becoming more intricate and detailed.
“The questions that people are asking now are these two-, three-, four-sentence queries.”
He highlighted how natural-language searches now include more context, offering intricate prompts rather than short keyword phrases. Google didn’t accompany this with specific data, but I’ve noticed the change in my own search habits.
Why this matters to us. In our pursuit of creating content that stands out, AI-generated responses with basic summaries mean we must offer original reporting, share firsthand experiences, or deliver valuable analyses not available in generic AI answers.
The interview. For those interested, you can watch the complete interview with Nick Fox on the future of AI and search.
Today, I’m excited to discuss the latest development in the world of search engines: Google has just rolled out the May 2026 core update. This follows the previous update we saw in March.
I learned that the announcement was made by Google through their official status page. It’s a significant moment as it marks the second core update of the year after March’s update and the earlier Discover update in February.
What Google is sharing. According to Google’s updated Search Status Dashboard, the rollout might take up to two weeks to complete. They also made a LinkedIn post explaining the aim is to enhance the visibility of relevant content.
Core updates like these occur several times yearly. They bring broad, impactful changes to Google’s algorithms, and though they often aren’t announced, this one is attracted due attention.
If you’ve noticed changes. Experiencing shifts in your site’s rankings? Google typically suggests focusing on producing quality content. Even if hit, it may not indicate problems with your pages.
Reflection on past updates. Looking back, we’ve seen similar significant updates like the March 2026 and December 2025 rollouts, each influencing search result dynamics differently. Will this update continue that trend? Only time will tell.
Why this matters for us. Core updates can shake up the search engine landscape, causing noticeable volatility. It’s an opportunity for improved site visibility or a call to action to tweak your strategies if rankings dip. May this update bolster your SEO efforts, rewarding your dedication with increased organic traffic.
Today, I discovered some exciting news about Google’s expansion of Demand Gen with fresh YouTube creator tools. It’s all about enhancing performance advertising and was recently highlighted at Google Marketing Live 2026.
Here’s the scoop. Google has unveiled new updates for Demand Gen with a focus on partnerships with creators, innovative product discovery methods, and improved cross-platform campaign optimization.
As an advertiser, I soon will be able to:
Create engaging videos using the multimodal capabilities of Asset Studio.
Seamlessly integrate creator partnership videos during campaign setup.
Dynamically share Merchant Center product videos directly from campaign structures.
Include Demand Gen campaigns in Google Maps for increased outreach.
Google’s also pushing checkout links into more markets and expanding product feed support to new verticals, such as automotive. They mentioned that advertisers with vast product options tend to experience a 33% boost in conversions with product feeds.
Additional improvements in measurement include:
Campaign Type Attribution to understand source impact.
Uplift Experiments for deeper insights.
Enhanced third-party integrations with partners like TransUnion.
I also learned about Google introducing AI-assisted Demand Gen campaign creation, which uses existing campaign settings, like those from Performance Max, to simplify setup processes.
Understanding the mechanism. Demand Gen harnesses AI signals across YouTube, Discover, Maps, and Shopping to smartly allocate creative and product feeds amidst Google’s platforms. Advertisers, like myself, can leverage creator videos and Merchant Center product assets for more tailored campaigns responsive to user interest and engagement techniques.
The reason it’s noteworthy. Google’s tactic to pitch YouTube and Demand Gen as comprehensive performance channels shows a shift from just creating awareness. The merge of creator content, Maps inventory, and dynamic product experiences epitomizes the evolving intersection of discovery and commerce within Google’s ecosystem.
For us, the advertisers, these updates are a golden opportunity to marry creator-driven content with tangible conversion metrics.
What’s ahead. Google’s ongoing focus on creator tools and Demand Gen sets the stage for YouTube’s larger involvement in performance advertising plans. It’s essential to keep tabs on how Maps inventory and creator-led commerce campaigns may influence conversion performances.
When can we expect it? Many of these Demand Gen updates are globally expanding in open beta.
Want more insights? Check out more from Google Marketing Live 2026:
Today, I’m excited to share that Google is making Analytics 360 even more powerful by integrating the Meridian marketing mix modeling platform. They’ve also introduced a new predictive conversion metric that promises to enhance media mix decisions for advertisers.
I learned about these updates during the Google Marketing Live 2026 event, where Google unveiled several enhancements aimed at expanding measurement capabilities. The integration of Meridian, Google’s open-source marketing mix modeling tool, directly into Analytics 360 is a significant step forward.
Driving the news. With this integration, I’m able to unify first-party and cross-channel data, measure incremental performance, forecast campaign outcomes, and optimize media mix investments with greater ease.
Moreover, Google is rolling out Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini. QFCs link current ad activity to future sales signals like branded search behavior, providing insights that were previously harder to visualize.
How it works. From my perspective, Meridian combines first-party data, media signals, and cross-channel performance metrics in Analytics 360. This helps to model incremental impact while Qualified Future Conversions use Gemini’s predictive signals to understand potential future purchasing behaviors.
In the long run, Google aims to integrate QFC insights into Meridian for more accurate predictive modeling. This is part of their broader effort to simplify measurement and refine ROI forecasting in today’s complex media landscape.
Why we care. As I’ve observed, measurement and attribution are becoming increasingly challenging with evolving customer journeys and the emphasis on privacy. These latest updates highlight Google’s commitment to helping advertisers like us better understand and plan for long-term performance.
The combination of Meridian and QFCs can empower marketers to make better budgeting decisions by accurately linking current campaign activity to future outcomes. It’s a tool we should all keep an eye on.
What to watch. Predictive measurement is becoming crucial. I’m looking forward to testing whether Meridian and QFCs can offer more actionable forecasting compared to existing solutions.
Availability. I found out that Meridian integrations are rolling out globally in Google Analytics 360, supporting all languages. QFCs are in a restricted global pilot phase, with wider beta access anticipated later this year.
Dig deeper. If you’re interested, there’s more news from Google Marketing Live 2026, including tests of new conversational ad formats and AI-powered tools in the Merchant Center, as well as expansions across various Google services.
I’ve recently discovered that Google has introduced a new feature in Chrome Lighthouse to check for llms.txt files. Though Google mentions that llms.txt isn’t necessary for AI search visibility, Lighthouse has started flagging sites based on their presence.
Google’s latest Lighthouse audits, under the “Agentic Browsing” category, now focus on a site’s usability for machine interaction. I find this interesting as it aligns with Google’s push towards better machine readability.
The new audits are part of Chrome’s evolving “Agentic Browsing” features, which analyze if sites are prepared for automated interaction. This concept came soon after Google issued guidance on AI search optimization, debunking the necessity of llms.txt files in their new guide on generative AI features.
What Lighthouse Evaluates Now. Lighthouse’s Agentic Browsing tests focus on how well my site is built for machine interactions, incorporating various deterministic audits as per Google’s documentation. These checks include:
– WebMCP integration.
– Accessibility tree integrity.
– Layout stability through CLS.
– Presence of an llms.txt file.
These audits help ensure that there’s a machine-readable summary at the site’s domain root. Google explains that without llms.txt, agents might take longer to understand a site’s main structure.
The impact of these audits doesn’t translate into a traditional Lighthouse score but into a fractional pass ratio related to agentic readiness signals.
The Tension. Interestingly, while these audits don’t directly affect SEO rankings, their mention in Google’s readiness checks could make SEOs reconsider their stance on llms.txt files.
Agentic Engine Optimization. Google’s approach aligns with insights shared by Addy Osmani from Google Cloud AI about Agentic Engine Optimization. Osmani emphasizes creating web content that is semantically structured, token-efficient, and easy for AI to process.
SEO vs. llms.txt. According to Google, creating llms.txt or similar files isn’t necessary for AI search success, as outlined in the guide on Mythbusting generative AI search. The AI systems can discover, crawl, and index a variety of file types encountered on the internet.
John Mueller from Google responded to concerns about the role of llms.txt in a discussion with Lily Ray on Bluesky, stating that the use of these files is more for functionality and not directly linked to search engine optimization.
Google’s Take on AI Agents. Besides llms.txt, Google’s Lighthouse guidelines place strong emphasis on accessibility and interface stability. The insight I gained is that AI agents heavily rely on the accessibility tree as their core data model, focusing on integrity and proper layout.
Ultimately, while Google indicates llms.txt isn’t needed for search, including such files might be beneficial for adapting to Google’s evolving tools that prioritize machine readability.
Today, I want to share some exciting news. Google has unveiled its most significant change to the search box in 25 years. This new feature, known as the “Intelligent Search Box,” is designed to provide us with an easier way to access AI search capabilities.
This innovation is powered by the latest technology, the Gemini 3.5 Flash.
Here’s How It Looks. Google completely redesigned the search box to give us more space for longer and deeper queries. As I type my search, the box will expand, supported by an AI-powered suggestion tool that goes beyond simple autocomplete, according to Google’s Head of Search, Liz Reid.
What’s even more impressive is the ability to search with text, images, files, videos, and even my Chrome tabs. It’s truly versatile!
Let me show you what this looks like:
This innovation puts Google’s most powerful AI tools right at our fingertips, enabling us to ask questions more easily, as explained by Liz Reid from Google.
Seamless Transition to AI Mode. Google also made it easier to switch to AI Mode with their new AI Overviews feature, which is now available globally on both desktop and mobile. Initially launched to many in January, it’s now fully operational.
Here’s how it works:
Why It Matters to Us. The transformation of the Google Search Box impacts how we search and potentially changes the type of traffic Google sends our way. It may encourage more users like me to switch to AI Mode for deeper answers, possibly leading to fewer direct clicks on our websites.
While change can be challenging, it’s also inevitable. Google’s CEO Sundar Pichai emphasized how our expectations from Google Search evolve—from individual queries to ongoing conversations and now to agentic workflows. As the world’s most-used product, Google is determined to stay ahead of our needs.
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.
