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.
Starting in June, Google Ads will implement a policy that deletes any reporting data older than 37 months, unless we take action to export and preserve it.
As someone who heavily relies on historical data for reporting and forecasting, I recognize the urgency to revamp my data management strategies before access to older records is lost.
What’s Changing. From June 1st, only data from periods shorter than a month—such as hourly, daily, and weekly reports—will be accessible for 37 months. For longer spans like monthly, quarterly, and annual reports, we will enjoy access for up to 11 years.
Once those retention periods lapse, the data will no longer be available in the Google Ads interface or through APIs.
Nitty-gritty Details. Metrics that measure reach and frequency will have even shorter retention limits, staying available for just three years. These metrics include:
unique users,
average impression frequency per user,
7-day and 30-day average impression frequency,
and frequency distribution metrics.
The Larger Impact. The policy change means I need to export and securely store historical Google Ads data soon, or it’ll become permanently inaccessible.
I acknowledge that long-term trend analysis and benchmarking depend heavily on years of granular data, which may no longer be directly accessible in Google Ads.
Looking Ahead. If I rely on external BI tools or customized reporting systems, I need to set up automated data export pipelines to maintain continuity before the new retention limits take effect in 2026.
For More Information. Read more about Google’s data retention changes on their official support page.
I recently came across some exciting updates from Google that are designed to enhance the way we search for and interact with content. Google is introducing new features to its AI experiences, including AI Mode and AI Overviews, by incorporating preferred sources along with a perspectives carousel and highly cited labels.
Preferred Sources in AI Mode and AI Overviews. One of the updates brings preferred sources to AI search results. According to Duncan Osborn, Product Manager at Google Search, users will now be able to easily identify links in AI responses from sources they have selected. I find this particularly beneficial as it helps me quickly access content from sources I trust.
I saw Google testing this feature recently, and now we have the final version that’s rolling out. There will be a label highlighting preferred sources within AI results, making it noticeable to us. It’s fascinating how this is now available globally and in all languages. Google mentions that users have selected over 345,000 unique sources, and these sources receive double the click-through rate. For those interested in trying it out, you can find more details in Google’s documentation.
Perspectives Carousel. Another interesting addition is the perspectives carousel. Google will present a new carousel for certain searches, tailored to help us dive deeper into specific topics, especially when they’re rapidly evolving. The carousel will prominently feature our preferred sources, making recent articles more accessible across various search queries.
In addition to this, there’s also a carousel that shows helpful perspectives from online discussions, forums, and social media. This is a wonderful way for us to tap into diverse viewpoints, broadening our understanding of topics that interest us. These features are being rolled out in AI Mode and AI Overviews.
Highly Cited Label. Finally, Google is expanding the highly cited label to more web article links within search results. This feature makes it easier to find articles that many other stories refer to. It’s a fantastic tool for me to trace a story back to its primary reporting, ensuring that I am viewing the original source of information. This feature will be available across Google Search, beyond just AI-specific functions.
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.
As someone who’s always on the lookout for innovative marketing solutions, I’m thrilled to share that OpenAI is venturing deeper into the world of performance advertising. They’re gearing up to offer conversion-driven ads through ChatGPT, complete with tracking tools and a pay-for-success pricing model.
This shift brings OpenAI into the same competitive space as Google and Meta. By focusing on small to mid-sized businesses intent on generating leads, bookings, and sales, they are targeting a market that prioritizes tangible results over mere impressions.
What’s happening? From what I’ve gathered, OpenAI has been communicating with advertisers and ad tech companies about attracting smaller local businesses. This includes enterprises like dry cleaners, car washes, and those based on appointments.
Ad formats are being crafted to inspire direct actions such as:
Purchases,
Appointment bookings,
And contact form submissions.
Those who test these ad formats will only incur costs when the desired actions occur. This aligns ChatGPT advertising more closely with traditional performance marketing models.
Why this matters to us. OpenAI is escalating beyond experimental AI ads, building a performance-focused advertising ecosystem that rivals Google and Meta. By incorporating conversion-based pricing, pixels, and API tracking, ChatGPT is poised to become a dynamic player in lead generation, bookings, and e-commerce advertising.
The infrastructure behind it. OpenAI is also developing the necessary framework to validate ad performance.
Advertisers, in order to test their campaigns, will need to implement OpenAI’s ad pixel on their websites. This will help track user interactions following ad engagement. Furthermore, advertisers are urged to connect their internal systems through OpenAI’s API, enabling continuous conversion and customer action data flow.
Such a setup mirrors the established ad-tech environments long utilized by platforms like Google and Meta.
The bigger picture. In pushing towards conversion-centered advertising, OpenAI marks a significant shift of AI platforms from being mere informational tools to becoming transactional ecosystems.
Should this venture prove successful, ChatGPT could evolve into more than a discovery platform, transforming into a lead generation and commerce hub actively competing for performance ad budgets.
What to keep an eye on. Measurement accuracy might soon arise as the biggest hurdle for OpenAI’s advertising trajectory. Given the current vulnerability of pixels to browser restrictions and ad blockers, API-driven conversion tracking could gain prominence for advertisers aiming to validate ROI within AI-driven ad experiences.
First seen. The conversation around this development started when Digital Marketer Glenn Gabe shared insights from The Information article, available on X.
On a recent Thursday, I logged into Google Search Console expecting the usual link report, only to discover a significant issue—it had broken. For some, it displayed zero links, while others saw their reported links drop by nearly 90% from the previous week.
Google acknowledged the problem and decided to revert to older data temporarily as they worked on a fix. This means the link data you’re seeing might be weeks old.
Google’s Response: John Mueller of Google mentioned, “Thanks for the heads-up, Barry. We’ll take a look to see if there’s anything unexpected happening (given the long weekends, it might take a bit of time).”
By Saturday, the links seemed to reappear, but as Mueller explained, they had merely switched back to previous data as a temporary measure. “They’re working on resolving the actual issue and in the meantime switched back to the data from the week before.”
Old Data: If you check your link report now, it displays old information. This is crucial to keep in mind if you’re using this data for reports to clients or stakeholders.
The Bug’s Impact: Many folks noticed either zero links or a drastic drop exceeding 85%. Here’s a screenshot highlighting the problem:
OK, this takes the cake. Hahaha. Yeah, something is very off with the links reporting in GSC. pic.twitter.com/KIYmFPm1fX— Glenn Gabe (@glenngabe) May 21, 2026
Why It Matters: For those relying on this link data for generating reports, the inaccuracy can be problematic. Data pulled on that Thursday might not be reliable.
While Google is addressing the issue, be prepared to work with data that’s temporarily outdated.
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.
As I immerse myself in Google’s latest guidance on AI search optimization, it’s hard not to approach it with a healthy dose of skepticism.
Whenever Google releases a new Search Central document, our industry splits into two predictable groups. The first group eagerly screenshots the content to share on LinkedIn, captioning it with “SEE? IT’S JUST SEO” before returning to their usual practices. In contrast, the second camp underscores their posts with, “Here’s proof they’re deceiving us,” treating Google’s words as gospel as long as it supports their pre-existing beliefs.
Recently, Google updated its guide on optimizing websites for generative AI features. The “it’s just SEO” advocates had much to celebrate. Many emerging concepts were downplayed or outright dismissed by the guide, reinforcing their belief that not much has changed over the years.
Yet, I can’t help but recall the critical insight we gained a couple of years back from leaked internal documents. Those leaked papers revealed discrepancies between Google’s public messages and what their internal documentation actually detailed. Despite public denials, these documents showed certain signals were very much a part of Google’s algorithms. This reinforces the need for caution in taking Google’s public directions at face value.
I’m not suggesting everything in Google’s new guidance is misleading, but it’s important to note Google’s tendency to push the industry towards its own interests first, possibly benefitting the open web as an afterthought. Google’s narrative drives SEOs to maintain the web’s infrastructure rather than moving towards a more independent approach across diverse platforms.
In my previous discussions about chunking, I’ve highlighted how Google’s influence is waning, as competitive AI platforms redirect user attention. Google’s once-dominant definition of “good content” is now challenged, as evident in their increasingly protective language.
Meanwhile, over at Microsoft, Bing is taking a different approach, transparent about changes and offering publishers insights and tools to optimize their content’s performance in AI responses.
For instance, in their posts, Bing describes the transition towards Generative Engine Optimization and provides practical tools for users, something Google hasn’t quite matched.
So, let’s discuss Google’s claims point by point:
“Is SEO still relevant for generative AI search?”
The idea that “it’s just SEO” is overly simplistic. SEO encompasses more than a collection of tactics; it includes strategic thinking and organizational presence. SEO has been evolving beyond basic practices to influence broader content strategies, yet it is often still underestimated as a supportive task.
This pattern has persisted across various developments, from mobile and voice search to schema and AMP, all initially labeled as merely “SEO.” Each innovation triggers more work for SEO professionals without an equivalent increase in resources.
The skill set and audience have diversified. Traditional SEO targets machine and human users differently than AI Search, which also caters to systems that might bypass traditional site visits altogether.
New labels, like AEO and GEO, can prioritize budgets and attention towards such progressive approaches, unlike the catch-all label of SEO.
When AI Search is recognized distinctly within organizations, it can catalyze cross-functional collaboration and sponsorships that SEOs have long sought.
Despite the extra responsibility placed on practitioners, aligning AI Search under the SEO umbrella usually doesn’t come with new resources or authority, which limits growth and innovation.
Google’s approach, treating all work as “just SEO” rather than recognizing unique systems like AI Mode or AI Overviews, simplifies the real diversity within their technologies.
Non-commodity content is key. Creating valuable and unique content is universally acknowledged as a good practice.
llms.txt files are beneficial, even if Google doesn’t require them. They serve other systems and therefore should be considered in a broad strategy.
Ignoring the multi-platform dynamics leaves a business vulnerable to losing ground where other systems are gaining traction.
Understanding that Google’s public guidance is tailored to its interests rather than offering generalized best practices across all platforms is crucial for developing a robust SEO strategy in this new era.
Google’s recommendations are one perspective in a rapidly evolving landscape where multiple opinions and infrastructures are emerging.
Stay informed, apply what’s relevant, but don’t take any single source as absolute truth. We’re navigating a new world requiring attention to diverse strategies to succeed across platforms.
First published on the iPullRank blog, republished here with permission.
Attending Google I/O 2026 for the first time felt like stepping into a realm of boundless energy and optimism, almost as thrilling as witnessing a crowning ceremony.
The initiatives launched last year have transformed into robust pillars of growth. Ask Maps, for instance, has become the blueprint for introducing Ask YouTube. Gemini 3.5 Flash fuels Antigravity, akin to Claude Code but under Google’s banner, and Googlers are already harnessing it to construct the exciting features shown on stage.
The pace of innovation was breathtaking, everything rolled out swiftly and assuredly.
Every announcement seemed to cater to a diverse audience.
Gemini Omni was likened to Nano Banana but designed for video content (see this strange proof).
Smart glasses are making a much-discussed return.
There are video game-like experiences that can be instantly prompted and played.
The capability for Workspace to bring documents to life with mere conversations.
A feature allowing the transformation of Google Maps images into surreal dreams seems more like a solution waiting for a problem, perhaps for Hollywood studios looking to bypass on-location shoots?
I even have Gemma on my phone, enabling in-flight conversations with a smaller model. (Thanks to American Airlines’ free Wi-Fi, I’m all set.)
And yet, the most intriguing element remains to be addressed.
Gemini and Search: Converging Evolution
Gemini is beginning to resemble Search, while Search is adopting features of Gemini.
Both platforms now include features that satisfy similar needs: keeping tabs on the web and alerting users when something of interest arises.
In Search, these are known as information agents. In Gemini, they go by Spark or Daily Brief. The connection is unmistakable.
I asked a product manager about their approach to long-term feature management and overlapping utilities. Their response was simple: “Right now, it’s all about velocity.”
Shipping fast is the mantra shared by three other product managers, all behind key I/O features initiated and deployed within this whirlwind year, 2026. It’s astounding.
The product manager elaborated, “Velocity is achieved through reduced managerial overhead.”
This implies jumping on board quickly and figuring out the finer details later.
Once You See It, You Can’t Unsee It
Armed with this understanding, the rest of the day wore a new perspective. The demos were impressive, yet I pondered: what’s the next step with these innovations?
Though I now have Gemma on my phone, one developer couldn’t provide a tangible day-to-day use case. I witnessed AI Mode’s monitoring prowess by prompting it to “keep me updated.” Despite seeing the connection of components, my questions about managing these alerts as they age went unanswered, indicating it’s still an early-stage demo.
Many features appear not to address their second-order effects thoroughly. It seems engineers are using these systems at a command line level rather than considering user interfaces.
A notable point is my current inability to delete old Gemini chats in a web browser, a functionality available in the Mac app.
Universal Cart Sparks Discussions
A frequently mentioned feature during I/O was Universal Cart, Google’s new cross-platform shopping protocol.
My opinion? If you’re Google, it’s an exciting development because, upon adoption, it further solidifies their control over the complete shopping experience. Conversely, for others, this development might be a cause for concern.
Despite these concerns, the group I conversed with didn’t seem troubled, feeling distanced from the growing anti-AI sentiment in the U.S.
Speaking with an SEO expert at a major ecommerce brand implementing Universal Cart, they related the velocity comment to their own implementation experience, describing it as feeling rushed.
Just four days before I/O, Google’s Search quality team advised publishers to “write for humans, not AI.” Shortly thereafter, the AI agent team demonstrated capabilities where Google’s own agents browse, interpret, transact, and create web content.
As Google shifts towards AI handling more tasks, the advice given to publishers starts to sound less sincere.
Impact on the Web Ecosystem
I don’t wish to undermine the engineers’ efforts. I communicated my respect for their work directly to them. Building products for search and clients myself, I can relate to frequent criticisms over compliments.
Still, the potential downside of overlapping features, difficulty in managing or reconciling data could lead to significant technical challenges later. The current AI strategy appears to be: prioritize feature utilization first, reconcile later.
Nevertheless, I admire Google’s rapid progress and look forward to future developments. Leveraging substantial resources, they can experiment comprehensively to identify successes.
Regrettably, my enlightening conversation with the product manager was abruptly concluded as we were asked to vacate the premises.
Spotting the Bright Spots
Google reports unprecedented high search query volumes. They are enhancing authentication and provenance through SynthID’s expansion into Search and Chrome, welcoming new partners like OpenAI, and integrating C2PA content credential verification.
These are indeed significant accomplishments.
However, the relentless pace might lead to unforeseen challenges. My hope is that the quest for speed doesn’t further destabilize the already-fragile web ecosystem.
In conclusion, it’s undeniably an exhilarating era for search technology.
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.
