I’ve noticed that Google is currently investigating an issue with the Google Search Console. Specifically, this concerns the data logging and reporting of “Job listing” and “Job details” search appearance filters.
On April 16th, a bug began affecting how this data is logged, causing Google to report zero clicks and impressions for job-related reports. Although traffic is still being received, it’s not being recorded correctly.
What Google said. According to an update from Google, “A logging error is preventing Search Console from reporting impressions and clicks for ‘Job listing’ and ‘Job details’ Search appearance types from April 16, 2026 onward. We’re working to resolve this issue. This issue affects data logging only.”
Complaints. I’ve also seen numerous SEOs voicing their concerns on social media, as shared in a tweet by Max Peters. The bug seems to impact impressions and clicks, but the traffic still comes through other measurement methods like google_jobs_apply UTM.
Why we care. If you’ve noticed a decrease in search data for job listings, rest assured, it’s due to this bug on Google’s side. Your listings are likely still active and receiving traffic, although this isn’t reflected in Search Console at the moment.
I’ve recently come across a noteworthy update from Google, which now enhances the potential impact of our spam reports. Interestingly, these reports are no longer just documentation—they might trigger manual actions against the reported sites. In addition, whatever I write in my report could be shared verbatim with the site owner I’ve reported.
Here’s Google’s Announcement. Google clarified in a note that they may utilize our spam report submissions to undertake manual actions against policy violations. This update makes it clear that spam reports are more critical than ever in maintaining the integrity of Google’s search results.
The updated guidelines specify:
“Ranking manipulation techniques that attempt to compromise the quality of Google’s search results violate our spam policies and can negatively impact a site’s ranking. Google may use your report to take manual action against violations. If we issue a manual action, we send whatever you write in the submission report verbatim to the site owner to help them understand the context of the manual action. We don’t include any other identifying information when we notify the site owner; as long as you avoid including personal information in the open text field, the report remains anonymous.”
Spam Reports Fuel Manual Actions. It seems that Google aims to clarify their usage of spam reports. This is quite the shift from their previous communication, where spam reports didn’t directly lead to manual actions. To me, this feels like more than just a clarification—it’s a significant development in how reports are handled.
Direct Transmission of Spam Report Text. Also, Google stated that the exact text I use in my spam report might be sent to the site owner. They advise us not to include personal details, as my submission remains anonymous unless I disclose such information.
Google emphasizes the importance of keeping sensitive information out of the report to ensure my anonymity is maintained.
Why This Matters to Us. This change could significantly alter how we approach spam reporting on Google. If you’re someone who regularly submits these reports, like I do, it’s essential to understand the new implications and modify your reporting practices accordingly.
I was thrilled to learn that Google has rolled out its Google Search Live globally, expanding its reach to over 200 countries and territories where AI Mode is available. You can check which languages and regions are supported.
Google attributes this remarkable expansion to its cutting-edge audio and voice model, Gemini 3.1 Flash Live. This model offers more natural and intuitive conversations, and because it is bilingual, it allows individuals worldwide to engage with Search in their language of choice.
How it works. To get started with Search Live, I simply open the Google app on my Android or iOS device and tap the Live icon beneath the Search bar. From there, I can speak my question out loud and receive a helpful audio response. It’s seamless to continue the conversation with follow-up questions or delve deeper using the provided web links. When I need visual context, like figuring out how to install a new shelving unit, I just enable my camera, and it complements Search Live’s suggestions with relevant information from the web.
Moreover, if I’m already using Google Lens to capture an image, tapping on the Live option lets me have a real-time conversation about what I see, bringing what’s in front of me to life.
More. Back in September, Google made Search Live with video available in the U.S., appealing to those who enjoyed its earlier iterations. Initially, it was an opt-in beta, and before that, it featured a talk and listen mode, minus the video component.
Why we care. This development offers a fresh approach for users to interact with Google’s AI through conversation rather than text queries. While this might reduce traditional web traffic, since users get direct answers, the inclusion of citations and links might still benefit content creators and brands, even if users are less compelled to click through for more depth.
I recently stumbled upon a report about Clickout Media, a company that’s notoriously transforming reputable news sites into hubs of AI-driven gambling content. Google refers to this practice as ‘site reputation abuse’. Essentially, it involves using legacy news brands, adding fabricated bylines, embedding casino links, and eventually abandoning these sites after they incur penalties from Google.
According to PressGazette, Clickout Media has been buying sports, gaming, and tech sites only to pivot them from authentic editorial content to topics saturated with casinos and cryptocurrency. Former employees revealed that original reporting gets stripped and replaced with AI-generated articles that promote offshore gambling links.
The approach leverages existing domain authority to manipulate Google rankings. Initially, legitimate content is maintained to preserve the site’s credibility. However, as time passes, gambling content takes over, with human writers being replaced by AI-generated articles and fake author profiles. The revenue stream mainly comes from affiliate deals with casino operators, often linked to player losses.
It’s disheartening to see the impact—several previously active publications are now deindexed, with repercussions including layoffs and closures. Alarmingly, even charity websites have been repurposed to host gambling content.
In Google’s view, publishing content at such a scale purely to manipulate rankings is a breach of their policies, labeled ‘site reputation abuse.’ This can result in manual actions and the removal of these sites from Google’s search index.
As someone who cares about the integrity of SEO, it’s clear this isn’t search engine optimization in any authentic sense. It’s a blatant manipulation of reputation to deceive and gain at scale.
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.
When I think about how ChatGPT retrieves information, I find it fascinating that most sources it pulls in don’t make it to the final answers. According to a report by AirOps, a whopping 85% of the sources identified by ChatGPT never appear in its final response.
Why this matters to me. If I’m aiming to have my content mentioned in AI-generated answers, it’s clear that simply being discovered by the AI isn’t sufficient. Most pages that get retrieved ultimately don’t get the exposure I’m hoping for.
Key insight. It’s interesting to note that just because a page ranks and is retrieved doesn’t mean it gets cited. My content has to align closely with the prompt or the context it supports to be chosen.
Per the report: the focus shifts to how well I can optimize my content for selection in the AI synthesis process, beyond just showing up in the search results.
By the numbers:
82,108 citations appeared in final responses, but only 15% of the retrieved pages were mentioned. That means 85% of the pages that surfaced during research didn’t make it into the answers.
Citation rates also varied based on query type:
18.3% for product discovery queries, 16.9% for how-to queries, and 11.3% for validation searches.
Fan-out queries. I noticed that when ChatGPT generates an answer, it often triggers additional internal searches, resulting in a “second citation surface.” This stood out in the dataset findings:
89.6% of prompts prompted two or more follow-up searches. Fan-out searches expanded 15,000 prompts into 43,233 queries. Interestingly, 32.9% of the cited pages were results from these fan-outs and not the original prompt.
95% of fan-out queries had zero traditional search volume.
Google ranking correlation. I’ve learned that high rankings in Google significantly improve chances of citation:
55.8% of cited pages ranked within Google’s top 20. Pages in Position 1 were cited 3.5 times more often than those outside the top 20.
About the data. AirOps examined 548,534 pages from 15,000 prompts to understand how ChatGPT expands queries and selects which citations to include.
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.
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.
I recently discovered a new help document from Google that explains how their web crawlers operate. This document aims to offer basic educational information about crawling, highlighting key resources available to site owners.
There are currently nine essential insights listed in the document, and they’re pretty enlightening!
Frequent crawling is a good sign! It indicates that your site’s pages contain fresh or highly relevant content that attracts attention. Google specifically mentions, “If we’re crawling your site a lot, it’s an indication your pages have fresh or highly relevant content that people want to find, and that our systems are recognizing that demand. Online shopping is a great example: we crawl ecommerce sites often so that our results will display retailers’ most up-to-date prices, promotions, and inventory status.”
What’s included in the guide? Here’s a quick overview, though I’d definitely recommend diving into the document for a detailed read. It’s not new information, but it serves as a beneficial refresher:
What is crawling? In short, crawling is how Google “sees” the web.
Google uses numerous crawlers, each tasked with different jobs.
Repeat crawls help provide the freshest search results by catching the latest updates.
Frequent crawling remains a positive indicator!
With the increased complexity of pages over time, Google’s crawling has evolved.
Crawling is automatically optimized.
Google doesn’t access paywall or subscription content without consent.
Site owners have control over what gets crawled and how.
Respect for robots.txt and other instructions is a standard for Google’s crawlers.
Why does this matter? The art of crawling is a cornerstone of SEO, essential for being visible in Google Search and other platforms. This new help document can serve as a guide to enhance the crawlability of your site.
I’ve noticed a shift in SEO from the traditional “rank, click, and convert” strategy towards a new model that emphasizes being scraped, summarized, and recommended. This change marks the beginning of the dark SEO funnel era, transforming how we measure success in search engine optimization.
Today, up to 84% of B2B buyers use AI tools to discover vendors, and an astounding 68% initiate their search journey with AI rather than Google, according to recent data from Wynter. It’s clear that tools like ChatGPT influence initial decisions, with Google merely acting as a verifier.
If, like me, you’re still considering SEO success through traffic, you’re likely focusing on an outdated model. Here’s what we need to prepare for.
Marketing professionals are already acquainted with the concept of dark social, where sharing happens away from trackable channels. Dark SEO is its algorithmic counterpart, where AI, rather than peers, offers brand recommendations, followed by a Google search for validation.
In this new phase, traditional analytics fail to capture the path from ingestion to recommendation to verification—all obscured within the dark SEO funnel. This gives direct or branded search undue credit, even though the groundwork was laid by SEO.
In this evolving dynamic, Google’s role is changing. A surveyed CMO mentioned using Google only when they know exactly which software or product they want. AI is for evaluation, Google is for verifying—a fundamental shift in our understanding of search behavior.
To succeed, we must understand two visibility types: brand mentions and LLM citations. In traditional SEO, the aim was to get clicks from links. In AI-driven search, it’s about visibility. An LLM could highlight your brand when relevant, impacting how users perceive and search for it.
Brand mentions occur when an LLM explicitly names your brand as a preferred solution—something influenced by your brand’s presence in relevant conversations and media. On the other hand, URL citations represent instances where AI uses your data as a credible source, an opportunity driven by unique data and information gain.
Emphasizing on relevant platforms like review sites and communities helps establish authority. As AI algorithms recognize your brand’s consistent presence, it can become an authoritative recommendation source.
When direct traffic is no longer a primary metric, leadership desires proof that SEO remains effective. This involves measuring more than just clicks. We should pivot to metrics like LLM recommendations visibility, branded traffic, product page visits, and conversion rates.
Ultimately, we’re heading towards a state where brand visibility is the triumph, and traffic is its byproduct. Adapting to this dark funnel era means we need to prioritize inclusion, recommendation, and intent over traditional traffic metrics. By focusing on high-intent queries and third-party visibility, you ensure the strategic progression of your brand in this new SEO landscape.
I’ve been asked numerous times about how to track prompts effectively, especially by those using tools like Profound, Athena, and Peec. The big question on everyone’s mind is, “Which prompts are worth tracking?” In this ever-evolving landscape, it’s challenging to determine what buyers are querying about my company when they use LLMs.
Currently, there isn’t a reliable data source that puts my mind at ease. Unlike traditional search with publicly available Keyword Planner data, it’s unlikely that OpenAI or Google will fully release this kind of data for analysis. Though there have been recent proposals by the UK CMA about Google and data transparency, I’m not holding my breath for significant change.
Long story short, LLM tracking feels like navigating a black box. So, are there any alternative data sources we can use to track which prompts? Perhaps.
Back in November, Jason Packer published an interesting report highlighting how ChatGPT searches accidentally leaked into Google Search Console reports, featuring PII. When this was confirmed by Ars Technica, OpenAI stated the problem affected only a small number of queries.
This confirmed, for me, that ChatGPT queries do appear in some Search Console profiles. While privacy implications are significant and beyond this article’s scope, it shows that LLM queries are not impossible to capture.
Additionally, Barry Schwartz has reported that AI Mode data is available in Search Console. This supports the idea that Search Console can track how users interact with LLMs.
Based on my analysis, it seems that AI data appears to come from this area. By applying specific filters, I’ve noted steady increases in impressions over recent months, coinciding with Google’s roll-out of AI Mode features.
So, how can I access user prompt data in Search Console? The key is focusing on longer queries. Using regex, we can filter queries with 10 or more words, unveiling prompt-like behavior:
1. Navigate to Search Console Performance > Search Queries
2. Select Add Filter > Query
3. Choose Custom Regex
4. Input: ^(?:S+s+){9,}S+$
This method revealed understandable, prompt-styled queries when applied to various properties. Though the actual data cannot be shared, examples such as “Map out a full day in Glacier National Park…” highlight the trend.
Mind you, there’s no direct evidence these queries originate from ChatGPT or similar AI platforms. It’s possible they reflect new user behavior patterns within Google.
Regardless, analyzing these conversational query patterns provides invaluable insight into how customers search using longer strings.
Will Critchlow wisely said, “we’re doing business, not science.” In our shift toward less attributed, zero-click data collection, the choice to leverage this available data is up to us.
Currently, my preferred tool for prompt analysis is Claude. Its results are reliably robust, and its visualizations are effective. Integrating Claude into existing frameworks streamlines the process.
After export, uploading prompt lists to Claude lets it perform behavioral analysis, identifying data themes and trends for better prompt tracking.
Posing specific questions to Claude about customer behavior opens a treasure trove of insights. Analyzing this data reveals learning opportunities I would not have anticipated.
For instance, I discovered searches probing a PR issue from over three years ago are still frequent and that searches often use one company as a benchmark against its competitors.
Finally, leveraging Claude to suggest new prompt-tracking methods, based on this data, offers an informed way to continually hone tracking efforts.
While there’s no definitive system for selecting which prompts to track, incorporating Search Console data provides a clearer direction. The insights derived can help unearth unique user prompts and discern scalable themes for ongoing data tracking.
