I’ve noticed that Google Search Query Reports are moving towards AI-driven interpretations, reflecting inferred intent rather than exact user searches.
What’s happening. Google has clarified that the search terms in Search Query Reports might not precisely match what users typed. Instead, the system displays the “closest approximation” due to the complexity of modern search behaviors.
What’s behind it. It’s fascinating how heavily AI now influences Google Ads’ matching systems. Rather than depending solely on specific keywords, Google increasingly interprets user intent, context, and behavioral signals to decide which ads to display.
Why we care. For those of us in advertising, Search Query Reports might become less of a mirror reflecting user language and more of a summarized representation of intent. This shift might complicate query analysis, decisions on negative keywords, and strategy around match types.
Discovered by. This update was brought to my attention by Adsquire founder, Anthony Higman, on an official Google help page discussing ad group and asset group prioritization in Google Ads.
The bottom line. Google Ads continues its evolution from keyword matching to AI-driven intent modeling, meaning we might have less insight into the exact searches that activate our ads.
Over the years, as Google continually tweaked its algorithms and transformed its search results pages, I’ve seen Condé Nast adjust its strategies considerably. Now, we’re designing our business around the notion that search traffic barely impacts us anymore.
In a recent conversation featured on TBPN—the tech media network that’s been likened to “technology’s daily show”—CEO Roger Lynch shared that we’ve stopped regarding Google search as a dependable traffic source.
Here’s what Lynch explained. While Google traffic isn’t expected to vanish completely, we’re intentionally planning as if it’s on the decline:
“Last year, I instructed our teams: plan as if there is no search—consider search as non-existent.”
“We’re not saying it will be gone entirely… but we anticipate it will comprise only single digits of our overall traffic—very minimal.”
The background. Throughout the past few years, Lynch has observed a recurring trend: Google’s adjustments consistently exceeded our expectations in reducing our visibility.
“For each of the last three years, we predicted some search traffic declines in our budgets, but it fell even more than anticipated,” he noted.
Why has our search traffic dwindled? Lynch attributes this decline not only to algorithm changes but also to AI Overviews and Google’s increasingly commercial-centric results.
“Seven or eight years ago, search results had a few ads, followed by ’10 blue links.’”
Currently, users first encounter AI Overviews, then a slew of commerce links, pushing organic results further down the page.
“It’s worked out well for Google,” Lynch commented.
A shifting landscape. The alterations made by Google have disrupted the model that other digital entities, like BuzzFeed, used to convert social media and search traffic into revenue.
“That era has ended,” he declared.
Lynch mentioned that brands in the intermediary stages are having the most trouble adapting to changes in AI and search frameworks.
“In today’s world, having a specified niche with a dedicated audience is crucial. Relying solely on advertising to support significant journalism investments is a challenging position,” he stated.
Shifting priorities at Condé Nast. We are now emphasizing brands that excel in these areas:
Dedicated direct audiences.
Potential for subscriptions.
Undeniable expertise in a given niche or category.
Lynch also hinted at a potential advantage for premium publishers against AI-generated content:
“Our audience expects and desires human-generated content. Creating AI-generated content doesn’t play to our strengths. Identifying and building on your competitive advantages is vital.”
Why this matters. Lynch emphasized that the practice of turning search and social media traffic into lucrative businesses is outdated. Publishers lacking a strong brand or dedicated readership might face challenges, as platforms can revise their methods at any moment.
The full interview. You can watch Lynch’s discussion, where he elaborates why human journalism remains crucial in the AI era, starting at 30:28 here.
As I delved into Google’s exclusive Discover profiles program, I discovered an intriguing behind-the-scenes look at what 54 publishers did with their newfound control.
Google Discover’s publisher profiles are housed at profile.google.com/cp/ and appear when a user interacts with a publisher name on a Discover card. While these profiles have been around since August 2025, it was only recently that Google secretly offered enhanced profile capabilities to a select few. This privilege includes customizable banner images, an optional link shelf, and the ability to pin posts for better content engagement.
While most of the over 47,000 monitored pages remain auto-generated with basic information and a label stating “Profile generated by Google,” the select few who’ve gained this access enjoy advanced control over their profiles.
Google’s approach appears highly selective; no public documentation or application process exists to apply for this feature. Throughout our monitoring, 54 U.S.-based, English-speaking publishers were identified as part of this exclusive cohort.
Our analysis of profile features is comprehensive, tracking 46,926 publishers across various languages. From this dataset, we narrowed down those displaying enhanced features, offering clues into Google’s intentions and priorities.
The skew toward local news and community publishers is evident, with nearly half of these publishers being regional newspapers and local TV stations. This focus is consistent with Google’s commitment to supporting local journalism.
Google operates under a two-tier profile system. Most publishers have standard profiles automatically generated, while the lucky few have claimed profiles with enhanced control over elements like social media links and content prioritization.
Through our investigation, we uncovered the actions of these privileged publishers, offering insights that could direct future adopters when Google decides to roll out this feature more broadly.
The use of professional banner images was a common thread, with participants investing in high-quality design to enhance their branding. From brand-patterns to local landmarks, each choice reflects deliberate design strategies to communicate their identity.
When exploring the links feature, local TV stations actively used this for site navigation, while national publishers were less engaged, suggesting differing strategic priorities.
Interestingly, many within the cohort failed to track profile link performance through UTM parameters, indicating an opportunity most have yet to seize.
Ultimately, this special program allows publishers to fine-tune their brand presence on a Google-owned platform, a tool for presence rather than ranking influence. The strategic implications for publishers are significant as they prepare for potential future rollout.
In considering methodology, insights were derived from the 1492.vision Profile Features Monitor, underscoring that the cohort’s composition reflects Google’s selection preferences rather than a random sample, highlighting important trends for those in the publishing industry to watch closely.
Have you recently noticed a decline in clicks and impressions around May 7th to May 8th? Don’t worry; it’s just a reporting glitch.
I discovered that Google has confirmed a bug affecting the Discover report in Google Search Console. It turns out there was a ‘logging’ error with the data, which has resulted in a drop in clicks and impressions during May 7th to May 8th, 2026.
Google assures us that this is merely a ‘data logging only’ issue, and it hasn’t impacted the actual positioning in Google Discover.
The issue: Google stated once again that a data logging error caused the discrepancies in the Discover report between May 7th and 8th, 2026.
As per Google’s post, this bug might have caused a ‘decrease in clicks and impressions in the Discover performance report.’
Why it matters: Numerous publishers, possibly including myself, saw a dip in performance metrics. It’s crucial to note that this is likely due to this bug.
Make sure to annotate your reports and inform your stakeholders that the Discover data from May 7th to May 8th is inaccurate and should be disregarded.
I recently discovered a fascinating development from OpenAI that has the potential to revolutionize e-commerce advertising. They’ve started transforming product catalogues into automated ads within ChatGPT, allowing retailers to seamlessly scale their campaigns.
Retailers now have the option to connect their product feeds directly to ChatGPT. This integration means that the platform can generate ads automatically, using product names, images, and other attributes. Gone are the days of manually crafting campaigns!
For users, these ads will still appear beneath responses and remain clearly labeled as sponsored content. There’s no change here in terms of user experience.
As someone interested in how e-commerce brands operate, I’m intrigued by this update. It significantly reduces the barriers that retailers with large inventories face when running scaled ads.
Brands have the flexibility to establish rules on which products are featured, allowing the system to efficiently generate ads. It reminds me of how shopping campaigns function on platforms like Google, leveraging structured feeds for both organic and paid visibility.
Previously, ChatGPT could use product data for answering queries but not for advertising purposes. Now, with this advancement, the same data supports both functions, bridging the gap between organic presence and paid campaigns.
This shift signals how OpenAI is looking to monetize shopping. Instead of taking a slice of transactions, they’re targeting ad budgets typically spent on platforms like Amazon and Meta.
Industry analyst Debra Aho Williamson calls this shift to feed-based automation a necessity, highlighting ChatGPT’s unique approach to serving ads based on conversational intent, a distinct advantage.
According to ad tech partners like StackAdapt, the integration with existing feeds is straightforward, easing the adoption process.
This latest move is part of a series of updates that focus on performance, including cost-per-click bidding and new conversion tracking tools. Cost-per-action models are reportedly in development, suggesting an even deeper focus on performance advertising.
I’m eager to see more retailers experimenting with ChatGPT as a performance channel. The ease of setup might make this an attractive option, but the real test will be if conversational intent can drive conversions as efficiently as traditional methods.
The bottom line is that OpenAI is effectively turning product feeds into ads, making ChatGPT a more potent, scalable channel for e-commerce advertising.
Starting June 10, I’ll enjoy seamless access to valuable YouTube engagement data through Google Ads, all thanks to an automated linking feature.
I received a notification from Google alerting me that my Google Ads accounts will soon be automatically linked to any associated YouTube channels. This change comes into effect on June 10, 2026, and eliminates the need for manual connections.
Now, without lifting a finger, I can access a world of video engagement data and targeting features directly through Google Ads.
Why it matters to me. By linking my YouTube channel, I can now dive into deeper insights and leverage more advanced targeting options that I might have otherwise overlooked.
With this automation, video data becomes a standard tool in my campaign optimization arsenal.
Take a closer look. I’ll have instant access to organic video metrics like view counts right within Google Ads.
I’m also able to create audience segments based on user interactions with my YouTube content, such as video views and channel engagement.
Extra benefits. This integration means I can track ‘earned actions’ like subscriptions or additional views spurred by my ads, making these interactions valuable conversion signals.
Such insights offer a clearer picture of how my video campaigns impact user behavior beyond mere clicks.
What I’m watching for. It’ll be fascinating to see how my measurement strategies evolve with the integration of organic and paid video data, and whether this encourages a broader adoption of engagement-based conversion tracking.
The bottom line. Google is making it impossible to ignore YouTube insights, turning automatic linking into a necessary step for honing targeting, measurement, and performance.
First spotted. Multiple advertisers, including myself, were informed by Google. Notable mentions are Menachem Ani, Hana Kobzová, and Arpan Banerjee.
Adthena has unveiled an exciting new platform that offers advertisers a clearer view of the ChatGPT ad landscape. This development gives me unprecedented insight into my competitors and ad performance within the ChatGPT ecosystem.
As a digital marketer, I find Adthena’s ChatGPT Intelligence Platform fascinating because it’s the first tool of its kind offering whole-market visibility into ChatGPT Ads, similar to the comprehensive insights I already get from Google Ads.
Tracking over 300,000 daily prompts, Adthena allows me to see which brands are advertising, the locations of these ads, and the messaging strategies employed. It’s a powerful way to stay ahead in a competitive field.
The current native tools in ChatGPT provide a limited, self-centric view of my ad performance. Now, Adthena bridges that gap, enabling me to understand my competitors’ positions, share of voice, and specific prompt activity in an often unclear channel.
What I find particularly useful is how Adthena offers a comprehensive view of ad appearances across ChatGPT conversations, complete with competitive intelligence on advertising bids and creative types used.
The platform also provides real-time recommendations to optimize my campaigns—it’s about taking action based on insights rather than just watching things happen.
Furthermore, I can evaluate ad copy effectiveness, monitor my brand’s presence, and track share of voice—all from one dashboard that integrates both ChatGPT and Google Ads data, helping me make informed budget decisions as search behaviors evolve.
The introduction of this tool follows Adthena’s earlier AdBridge tool, which helps in the seamless transition of Google Ads campaigns into ChatGPT’s Ads Manager, indicating a burgeoning AI-driven search advertising ecosystem.
Ashley Fletcher, CMO, emphasizes that early adopters like me have the potential to influence the competitive terrain, with the platform clearly indicating the best strategies to employ.
Looking ahead, I anticipate more third-party tools emerging as advertisers like myself desire greater transparency in AI-driven ad environments. The pace at which brands recognize ChatGPT Ads as a vital performance channel will likely drive this adoption, possibly urging platforms like ChatGPT to enhance their native reporting capabilities.
The bottom line is that Adthena is positioning itself as the go-to visibility layer for ChatGPT Ads, offering me a clearer understanding of this rapidly growing but still enigmatic channel.
I’m excited to share that Google has rolled out its Merchant Center for Agencies worldwide! This powerful tool now lets agencies like mine manage and optimize product data for all clients in one convenient location.
After initially launching in the U.S. and Canada, Google’s Merchant Center for Agencies is now available to agency users globally. This represents a significant step forward for us, as product data’s role in shopping and discovery experiences continues to grow in importance.
For those of us managing multiple client accounts, this tool is a game-changer. It centralizes essential tasks like diagnosing issues and spotting growth opportunities, streamlining the process dramatically.
The days of fragmented and time-consuming product feed management are finally behind us. With this update, agencies can now efficiently monitor account health, address problems swiftly, and optimize product data more effectively.
The platform’s unified dashboard offers a comprehensive view of all client accounts. It allows agencies to see onboarding statuses and receive critical alerts, helping us stay on top of everything.
The portfolio-wide diagnostics feature enables us to identify issues across accounts quickly, filter them by market or campaign type, and prioritize solutions based on their potential impact.
Additionally, we can now monitor store quality metrics and inventory health within the platform, keeping a close eye on out-of-stock products and managing promotions directly.
On the performance front, new insights reveal high-potential products that currently have low visibility. We can tag and prioritize these products for ad campaigns to boost their visibility.
As agencies integrate this tool into existing workflows, I’ll be watching to see if it reduces our reliance on third-party feed management tools and whether more advanced optimization features become available.
Ultimately, Google is providing us with a scalable solution for managing product data. Merchant Center is becoming much more than a mere feed repository; it’s transforming into a strategic performance tool.
I recently sat down with Veronika Höller for an enlightening discussion on PPC campaigns in an episode of PPC Live The Podcast. We delved into a scenario where a seemingly flawless campaign was secretly underperforming, uncovering the real issue beneath the surface.
From “perfect” campaigns to zero revenue
Initially, Veronika encountered an impeccably organized account. It had all the right elements: a clean structure, compelling creatives, and well-allocated budgets with conversions rolling in. But there was one glaring omission—it wasn’t generating any revenue.
This discrepancy prompted us to investigate further, revealing that while surface metrics such as impressions, clicks, and conversions appeared promising, the true business impact was lacking. The unraveling began here.
The real issue: nothing stood out
The breakthrough came not from within the account but by stepping outside it. During competitor research, Veronika noticed that the brand’s messaging was indistinguishable from its competitors. There was no compelling reason for users to choose their products over others.
From a user’s perspective, the ads weren’t incorrect; they were simply forgettable. In a saturated market, being simply “good” wasn’t enough. The revelation was not about performance but positioning.
Starting again — from scratch
Veronika boldly decided to reconstruct everything from the ground up. This involved crafting new messaging, developing fresh creatives, and establishing a comprehensive strategic blueprint. A pivotal change was identifying not only the ideal customer but also defining who they were not targeting, utilizing anti-ICPs to refine the messaging.
This reset also incorporated enhanced localization, creating tailored landing pages for different markets, and formulating platform-specific strategies instead of simply recycling campaigns across channels. It was much more than optimization—it was a complete overhaul, and it succeeded.
The mistake that nearly broke everything
Looking back at earlier times in her career, Veronika recalled a major misstep that will resonate with many PPC professionals. She had implemented a recommended target CPA but failed to adjust the budget accordingly.
This oversight led to a halt in campaign delivery and a significant drop in performance, all of which went unnoticed over the weekend. By Monday, the damage was done, and the client was understandably upset.
Owning the mistake — and fixing it fast
Veronika didn’t shy away from the situation. She promptly admitted her mistake, provided an explanation, and took full responsibility. This transparency shifted the client’s initial frustration into collaboration, as there was no defensiveness, only a structured plan for resolution.
The takeaway was invaluable: one must never apply recommendations blindly and should always consider the entire context before implementing changes.
Why failure is part of getting good
For Veronika, mistakes aren’t something to avoid—they’re a stepping stone to mastery. “You can only be good if you fail,” she asserted.
This philosophy now influences her work approach and mentorship style. Mistakes signal progress, experimentation, and improvement.
Furthermore, sharing these experiences helps others steer clear of similar pitfalls.
The biggest issue she still sees today
Despite evolving PPC landscapes, tracking remains a persistent issue. Many setups suffer from flawed implementations, reliance on micro conversions, and misconfigurations in tools like Google Tag Manager.
In a world dominated by smart bidding and automation, inaccurate data not only constrains performance but leads it astray. Even the most stellar campaigns can falter without precise tracking.
AI won’t fix average marketing
Veronika emphasized that AI isn’t a magic bullet for improving outcomes. Feeding it mediocre data yields mediocre results.
Many marketers erroneously rely on AI tools for account analysis without a proper understanding of the necessary enhancements. AI can’t create uniqueness; it can only optimize existing inputs. Distinctive strategies still demand human ingenuity.
The mindset that matters now
The most significant takeaway isn’t about tactics; it’s about mentality.
Perfection isn’t the goal. Avoid following recommendations blindly, and don’t assume tools will think for you. Instead, rely on your instincts, experiment, and accept that mistakes are a valuable part of the journey.
In performance marketing, the real hazard isn’t failure but becoming invisible by playing it safe.
I recently came across some important news from Google that I felt compelled to share with you. As of May 7, 2026, Google will no longer support FAQ rich results. This change means that these helpful snippets will no longer appear in Google Search results.
Additionally, Google Search Console will cease reporting on FAQ structured data, impacting how we track and analyze our content’s performance in search engines.
What Google said: Google has posted a notice on the FAQ structured data developer documentation. They state: FAQ rich results are no longer appearing in Google Search. By June 2026, Google plans to fully drop the search appearance, rich result report, and support in the Rich results test. To provide some adjustment time, support for the FAQ rich result in the Search Console API will be removed by August 2026.
Remove code: You might be wondering what to do with your existing FAQ structured data. The choice is yours—you can remove it from your code, but leaving it might still benefit you if other search engines use it for their own purposes.
Why we care: For me and many others, rich results have been instrumental in increasing web pages’ click-through rates and attracting additional traffic. The discontinuation of FAQ rich results could impact this dynamic.
To gauge the effect on your website, monitor pages with FAQ structured data closely and pay attention to any shifts in your traffic from Google.
