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Category: News

Enhance Forum Visibility: Google’s New Structured Data Update

I recently discovered that Google has enhanced its structured data support for forum and Q&A pages. This update introduces new properties that allow us to better signal reply threads, quoted content, and identify whether content is generated by AI or humans.

With these changes, which aim to boost Google’s accuracy in interpreting discussions and Q&A content, we can now ensure our content is represented more precisely.

What’s New. Google has updated its QAPage documentation to include commentCount and digitalSourceType. Moreover, the DiscussionForumPosting documentation now supports sharedContent alongside these new properties.

The Details. Using Q&A markup, I’m able to apply commentCount to questions, answers, and comments, showcasing the total number of comments even if they are not fully marked up. This total should align with answerCount + commentCount, representing all types of replies.

How It Works. The digitalSourceType property allows me to indicate whether content is produced by a model or simple automation. I can use TrainedAlgorithmicMediaDigitalSource for advanced outputs and AlgorithmicMediaDigitalSource for basic bots. If this property is left out, Google assumes the content is human-generated.

What’s New for Forums. The sharedContent property helps me to mark the primary item that’s being shared in a post. Google supports various content types like WebPage, ImageObject, and more, including quotes or reposts.

Why This Matters. This update provides me with greater control over how Google interprets community content, which is particularly important for sites rich in forums, support communities, UGC platforms, and Q&A sections. Google can now distinguish between answers and comments more effectively, tally partial threads across multiple pages, and recognize when a post primarily shares specific media types.

Documentation. The official documentation was updated on March 24, providing all the details I need to apply these new capabilities.

Inspired by this post on Search Engine Land.

March 26, 2026
Google Unveils Powerful March 2026 Spam Update Impacting All

Today, Google released its March 2026 spam update, making it the second announced algorithm change this year, following the February 2026 Discover core update.

This marks the first spam update of 2026. The previous one was rolled out in August 2025.

Timing. Google mentioned that this update might “take a few days to complete.” They reiterated on LinkedIn: “This is a normal spam update, and it will roll out for all languages and locations. The rollout may take a few days to complete.”

Why we care. Since this is the second major algorithm update of 2026, I need to stay alert for any changes in rankings or traffic on my sites. Google hasn’t specified what spam is being targeted, but shifts in performance could be related.

More on the spam update. Google’s documentation states: “While Google’s automated systems to detect search spam are constantly operating, we occasionally make notable improvements to how they work. When we do, we refer to this as a spam update and share when they happen on our list of Google Search ranking updates.”

Google’s AI-based spam-prevention system, SpamBrain, gets enhanced from time to time to better detect and manage new types of spam. If I notice changes after this update, reviewing and ensuring compliance with Google’s spam policies is essential for maintaining or improving rankings. Violations can lead to lower rankings or removal from search results entirely.

For link spam updates, improvements might not translate to immediate gains since any ranking boost from spammy links is nullified. Hence, reclaiming lost benefits isn’t possible.

Inspired by this post on Search Engine Land.

March 24, 2026
Identical Google Ads Metrics Spark Industry Concerns
I recently stumbled upon an intriguing issue with Google’s paid search ads. Imagine my surprise when I noticed multiple competing ads displaying identical web statistics! This strange occurrence immediately made me question whether it’s a bug or perhaps a deliberate change by Google.

What’s happening? I’ve seen several paid search ads showcasing the same website statistics simultaneously, despite these metrics usually being unique to each site. This uniformity makes the data appear dubious, leaving me uncertain if it’s a display glitch, an experimental test, or something more intentional.

Why we care. Trust signals in search ads play a crucial role in helping users like us make informed decisions. They boost click-through rates by instilling confidence in the results. If identical stats appear across competing ads, it risks undermining their credibility—potentially impacting the confidence and trust advertisers rely on.

What we don’t know.
- Whether Google is testing this actively or it’s an unintended bug
- How widespread the issue is across different search queries or markets
- Whether it’s affecting user click behavior or advertiser performance
No official word. So far, Google has not confirmed or commented on this behavior. Paid Media expert and Founder Anthony Higman was the first to notice and flag this anomaly, sharing his findings on LinkedIn.

The bottom line. If trust signals can’t be trusted, they fail to serve their purpose. As someone invested in digital advertising, I’m keenly watching whether this pattern gains momentum or fades away. Observing these developments is critical for both advertisers and users.

Inspired by this post on Search Engine Land.
March 23, 2026
Why Walmart’s ChatGPT Checkout Fell Short: Key Insights

When I first heard about Walmart’s experiment with ChatGPT’s Instant Checkout, I was intrigued. But after testing 200,000 items, Walmart discovered that conversions through this method were three times lower compared to their website.

Why This Matters: This experiment highlights an important point: traditional shopping environments still hold the crown when it comes to conversions. Even in a world dominated by AI, guiding users to owned environments proves more effective.

The Experiment Details: Starting last November, Walmart introduced around 200,000 products available for purchase directly inside ChatGPT through OpenAI’s Instant Checkout. The goal was to let users buy items without ever leaving ChatGPT.

Daniel Danker, Walmart’s EVP of Product and Design, revealed that these purchases had a conversion rate one-third lower than similar transactions on their website. He described the experience as “unsatisfying,” which prompted Walmart to reconsider their approach.

Farewell to Instant Checkout: Originally, Instant Checkout aimed to complete transactions within ChatGPT. However, OpenAI recently confirmed plans to phase it out, leaning towards merchant-handled app checkouts.

Changes on the Horizon: Walmart plans to integrate its own chatbot, Sparky, within ChatGPT. This will allow users to log into Walmart’s system, sync their carts across platforms, and finalize purchases seamlessly.

A similar integration with Google Gemini is expected next month, broadening Walmart’s technological reach.

The WIRED Report: For those interested in the comprehensive story, WIRED provides further insights into how Walmart and OpenAI are revolutionizing agentic shopping (subscription required).

Inspired by this post on Search Engine Land.

March 19, 2026
Unlock More Creative Control with Google Ads Editor Update

The latest update of Google Ads Editor has really opened up a world of possibilities for me as an advertiser. Now, I’m enjoying enhanced creative flexibility and budget control, which are crucial in today’s fast-paced AI-driven advertising landscape.

Google has significantly expanded its capabilities in the Ads Editor, providing us with better tools to manage creativity, automation, and budget precision. This is particularly handy as AI-driven campaign types continuously evolve.

What’s new. With the 2.12 release, I’m excited to explore the updates across Performance Max, Demand Gen, and video campaigns. The focus here is on scaling creative assets and enhancing workflow efficiency.

Creative expansion. I’m now able to include up to 15 videos per asset group in Performance Max campaigns. This is a game-changer, allowing me to offer more variations for Google’s AI to test. Additionally, the introduction of 9:16 vertical images caters to the growing demand for mobile-first formats.

Campaign upgrades. Demand Gen campaigns have seen several exciting enhancements. New customer acquisition goals, brand guideline controls, and hotel feed integrations are just a few updates. The new minimum daily budget and streamlined campaign build flow are set to improve campaign stability and setup.

Video & AI control. I’m appreciating the updates to non-skippable video formats and real-time bid guidance. They offer greater control over performance, and with new text and brand guidelines, I can ensure my AI-generated assets stay true to my brand.

Budgeting shift. The new total campaign budget feature is ideal for setting fixed spends over defined periods, like promotions or seasonal bursts. It’s great to see Google automatically pacing the delivery, ensuring every dollar counts.

Workflow improvements. With improvements like account-level tracking templates, better visibility into Final URL expansion performance, and clearer campaign status filters, my campaign management has become much more efficient.

Why I care. These updates provide me with enhanced creative flexibility and control over AI-driven campaigns, particularly in Performance Max and Demand Gen. Features like increased video limits and total campaign budgets empower me to test more, scale faster, and manage spend efficiently.

Moreover, the improvements in workflows and brand safeguards make it easier for me to guide automation while ensuring consistency and performance across Google Ads.

Between the lines. This update is part of a broader trend where, as automation rises, Google provides more ways to guide AI instead of manually controlling every aspect.

The bottom line. Google Ads Editor 2.12 isn’t about one standout feature. It’s about incremental improvements across creative assets, automation, and control, helping me refine my approach to increasingly AI-driven campaigns.

Inspired by this post on Search Engine Land.

March 17, 2026
Mastering Google Ads: Avoid Costly Pitfalls & Optimize Performance

I recently had an enlightening chat with Chloe Varnfield, a seasoned digital marketer from Atelier Studios with nearly eight years of PPC experience. She shared invaluable insights on avoiding hidden Google Ads settings, steering clear of Friday mishaps, and the dangers of following Google rep advice blindly. These hard-learned lessons resonated with me deeply.

One of Chloe’s early eye-openers involved Google’s elusive account-level automated assets setting. It’s tucked away so deeply that I didn’t even realize it existed until I got an unexpected client message questioning a bizarre headline in their ad. It turns out Google had generated it automatically. This experience taught me the importance of auditing account-level settings and being proactive about Google updates.

Another lesson Chloe swears by is to never implement significant changes on a Friday. Once, she adjusted a campaign’s geographic targeting mid-conversation, only to accidentally exclude the UK. Recovery took three bewildering days. The rule I learned? Avoid major changes on a Friday and promptly audit your campaigns when things go awry.

Chloe’s most costly mistake unfolded when she followed a Google rep’s suggestion to switch bid strategies. What seemed like solid advice plummeted her campaign’s performance. It was a stark reminder of the high stakes involved in altering bid strategies, especially for businesses not hitting conversion volume thresholds. Patience and trusting my judgment emerged as crucial takeaways.

While auditing inherited accounts, Chloe often finds recurring issues like broken conversion tracking and brand-broad match campaigns—challenges that skew performance data and waste precious budget. These insights made me acutely aware of consistently vigilant account management.

Transparency in client relationships plays a pivotal role in Chloe’s success. Honest communication—explaining issues, solutions, and next steps—has shielded her from losing client trust. Her advice? Stay calm, be kind to yourself, and remember every problem offers a chance for growth.

Lastly, Chloe emphatically warns against over-relying on AI for generating ad copy without thorough review. AI should be a tool to enhance speed, not replace meaningful human oversight. It reinforced my commitment to always infuse my unique voice and critical review into AI outputs.

Inspired by this post on Search Engine Land.

March 13, 2026
Master Google Ads Audits: Navigate the Changes in 2026

I recently tuned into an episode of Google’s Ads Decoded podcast where Brandon Ervin, Director of Product Management for Google Search Ads, shared insights on campaign consolidation, AI Max, and the future of advertiser control as we approach 2026. It was enlightening to hear a product team so in tune with advertiser concerns.

However, I felt the podcast left some gaps. There’s a significant disconnect between Google’s narrative and what advertisers truly experience on the ground. While Ervin’s team is making strides, the fast-evolving platform presents new challenges, shifting performance measurement onto economic standards. This change fundamentally alters how we should approach search ad audits.

As I reflect on recent improvements, it’s clear that enhancements like brand exclusions in Performance Max and Demand Gen, exclusion of site visitors in PMax campaigns, and improved search term visibility are crucial. These are responses to issues caused by bundling and aggressive automation. It’s worth noting that these controls arrived after advertisers were already knee-deep in implementation.

In an era where Google’s product team pushes for advancement, it’s vital for us to audit whether these new tools genuinely expand control or simply restore baseline transparency lost with earlier automation efforts.

In building the foundation for a 2026 search audit, we need to start with the basics, ensuring full ad extensions, strategic automated bidding, and maintaining negative keyword lists, among others. These are undeniable essentials that set the stage for deeper audits.

Focusing on the intricacies of signal architecture, I realize that while traditional controls like exact match and manual bids gave us direct oversight, the new controls shift focus to data quality, density, and selectivity. These influence the algorithm, which ultimately makes the decisions.

An effective audit in this context addresses three core aspects: the quality of the data imported, the density of high-quality data available for modeling, and the selectivity of the data shared with Google. These elements are pivotal in shaping campaign success.

Being mindful of incrementality is another key consideration. Google optimizes towards reported conversions, often encompassing brand search and retargeting signals that may not truly reflect incremental gains.

It’s critical to analyze marginal returns as Google’s system operates on a blended cost-per-action model. Without understanding the incremental cost at each spend tier, advertisers risk overspending without realizing diminishing returns.

Furthermore, as Ervin acknowledged, AI-driven campaigns sometimes misalign with intended targets. Query mapping has deteriorated over time, and AI Max exacerbates irrelevant matches, underlining the need to rigorously classify queries by intent to maintain high-value engagements.

Lastly, the economics of network performance in bundled campaigns like Performance Max and Demand Gen need thorough examination as they obscure valuable insight into actual network-driven outcomes.

By focusing on value redistribution through audits, we can ensure that the surplus value generated by high-intent searches isn’t misallocated into Google’s weaker inventory, thereby optimizing ad spend efficiency and accountability.

Inspired by this post on Search Engine Land.

March 13, 2026
OpenAI Enhances Privacy with New ChatGPT Ad Features

I’ve been following the latest updates from OpenAI, and they recently made some significant changes to their privacy policy, especially with the introduction of ads in ChatGPT. These updates are designed to allow advertisers to run personalized ads while ensuring that our chats remain private and secure.

OpenAI shared these updates with ChatGPT users, detailing how ads will function within the platform and clarifying what data is accessible to advertisers. It’s a refreshing assurance that our personal interactions remain confidential.

Why this matters to me. Privacy is paramount, and OpenAI emphasizes that personal chats and histories remain shielded from advertisers. They utilize anonymized engagement signals for ad personalization, ensuring advertisers can target relevant users without accessing sensitive information.

This method allows advertisers to evaluate the performance of their ads within a privacy-first framework, fostering user trust.

Ads in ChatGPT For users like me on Free and Go plans, ads might start appearing, but if you opt for paid tiers like Plus, Pro, Enterprise, Business, and Education, you can enjoy an ad-free experience. OpenAI promises clear labeling and separation of ads from chatbot responses.

Importantly, the content generated by ChatGPT remains unbiased and unaffected by these advertisements.

How ad targeting is handled. OpenAI uses in-platform signals such as ad interactions to personalize ads, but advertisers do not get access to our conversations, chat histories, or personal information.

Advertisers receive only aggregated metrics like total views or clicks, ensuring our personal data stays protected.

Additional privacy updates A new feature allows for optional contact syncing, helping us connect with friends who also use OpenAI services. It’s up to us whether to enable this feature.

They also provided more transparency on data storage durations, processing methods, and user control options, helping us understand our data management better.

Safety and product enhancements. The update encompasses new safety tools and age prediction systems aimed at ensuring a safer environment for teenagers. Documentation for new features like Atlas, Sora 2, and parental controls for teen accounts has also been included.

The bottom line. With the expansion of advertising in ChatGPT, OpenAI is committed to maintaining strict boundaries concerning user privacy, offering advertisers valuable insights without infringing on personal conversations or data.

This update was first spotted by Paid Media expert Arpan Banerjee, who shared insights on LinkedIn. It’s a promising move towards privacy-centric advertising in AI-powered platforms.

Inspired by this post on Search Engine Land.

March 9, 2026
AI Assistants Dominate 56% of Global Search: New Study Unveils

I recently came across an intriguing study that shows AI tools are now responsible for generating 45 billion monthly sessions globally. This accounts for an impressive 56% of all search engine activity, according to Graphite.io CEO Ethan Smith.

The analysis combines web and mobile app usage across leading AI platforms and suggests that AI activity matches 56% of global search use and 34% in the U.S.

The surge is particularly evident in mobile applications like ChatGPT, Gemini, Perplexity, Grok, and Claude.

Why it matters: AI is broadening the horizons of discovery, rather than limiting the demand for search. Since 2023, combined usage across search engines and AI assistants has increased by 26% globally. It’s clear that having visibility in both LLMs and traditional rankings is crucial.

Key insights: The report dives into the performance of the top five LLM products—ChatGPT, Gemini, Perplexity, Grok, and Claude—and compares them to the biggest search engines. Here are some standout insights:

AI platforms generate 45 billion monthly sessions worldwide.

Within the U.S., AI accounts for roughly 5.4 billion monthly sessions.

An astounding 83% of global AI usage takes place within mobile apps (75% in the U.S.).

ChatGPT is leading the charge, representing 89% of AI sessions globally.

When looking at search-like prompts, AI usage constitutes 28% of the global search and 17% within the U.S.

The report leaves out prompts in the “doing” or “expressing” categories. According to OpenAI, around 52% of prompts focus on seeking information, akin to traditional search queries.

Reading between the lines: Most forecasts comparing AI and search focus only on website traffic, often just Google.com and ChatGPT site visits. This approach overlooks much of AI’s impact.

The research suggests these comparisons undervalue AI activity by a factor of 4-5 times because a significant chunk occurs on mobile apps.

The analysis takes into account various LLMs and search engines, rather than only comparing Google and ChatGPT.

What to keep an eye on: Google remains a dominant force in discovery, but the report estimates its share of search-related activity has declined from 89% in 2023 to 71% by the fourth quarter of 2025.

While global AI usage seems stabilized since July 2025, the U.S. usage is still on a rapid climb—up about 300% year over year by December 2025.

The full report. For more depth, you can read the analysis titled AI Is Much Bigger Than You Think.

Inspired by this post on Search Engine Land.

March 9, 2026
Inside Google AI: Why It’s Citing Itself More Than Ever
It’s fascinating to see the evolution of Google’s AI Mode and how it increasingly cites Google itself. In fact, almost one out of every five sources in its AI-generated answers now originates from Google, often guiding users back to more Google searches.

Why does this matter to us? As someone deeply involved in the world of digital content and SEO, I’m aware that AI search should highlight the best online sources. If Google prioritizes its own content, there’s a risk that we might encounter fewer direct links and see a reduction in traffic as users remain within Google’s ecosystem.

So let’s delve into the details. Research by SE Ranking reveals that Google.com is the most cited source within AI Mode responses, making up 17.42% of all references. This makes Google more mentioned than even the combined total of the next six well-known platforms: YouTube, Facebook, Reddit, Amazon, Indeed, and Zillow.

In an accelerated trend, back in June 2025, Google referenced itself in only 5.7% of AI-generated answers, but now that figure has tripled.

Almost one out of five AI citations is from Google. When considering YouTube, Google-owned properties account for about 20% of all sources.

This self-referencing is quite pronounced, with AI Overviews linking heavily to Google properties such as Maps, Images, and YouTube. AI Mode expands on this by further embedding users within the Google environment, often through presenting additional search results rather than directing them to external sites.

This strategy keeps users engaged with Google platforms where monetized content such as ads and reviews can be found.

What’s changed? Previous research showed that Google was mostly citing Google Business Profiles. However, this trend has shifted:
- Travel: 53.18% of citations
- Entertainment & hobbies: 48.74% of citations
- Real estate: 30.54% of citations
Interestingly, the one area where Google is not the top source is Careers and Jobs, where Indeed appears more than three times as often as Google.

The data supporting these findings were gathered by SE Ranking, who analyzed 68,313 keywords across 20 industries, reviewing over 1.3 million AI Mode citations to determine how frequently Google.com was referenced.

If you’re interested, I recommend checking out the full report titled “Is Google stealing your clicks in AI Mode? (1.3M+ citations analyzed)” for an in-depth exploration.

Inspired by this post on Search Engine Land.
- 59% of citations now direct to conventional Google search results.
- 36.1% still reference Google Business Profiles.
- A smaller portion links to Google Support (1.7%), Google Flights (0.1%), and other Google services.
- Often, these AI citations are accompanied by a mini search results panel beside the answer, effectively creating a new search opportunity.
Industry differences are also evident. Google dominates citations across several topics, but some sectors show a stronger dependency on Google:
- Travel: 53.18% of citations
- Entertainment & hobbies: 48.74% of citations
- Real estate: 30.54% of citations
Interestingly, the one area where Google is not the top source is Careers and Jobs, where Indeed appears more than three times as often as Google.

The data supporting these findings were gathered by SE Ranking, who analyzed 68,313 keywords across 20 industries, reviewing over 1.3 million AI Mode citations to determine how frequently Google.com was referenced.

If you’re interested, I recommend checking out the full report titled “Is Google stealing your clicks in AI Mode? (1.3M+ citations analyzed)” for an in-depth exploration.

Inspired by this post on Search Engine Land.
March 6, 2026

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