🔥 The SEOs Diners Club - Issue #169 - Weekly SEO Tips & News

In our industry, what worked yesterday might not work tomorrow. Today, however, we have a rare glimpse into what works at Google thanks to some extraordinary leaked documents. Plus, compelling data on how AI Overviews are reshaping user behaviour, and fresh insights from my recent presentation at WORLDEF Istanbul.

Google's Ranking Secrets Leaked: Quality, Clicks, Popularity, and LLM Support

The antitrust lawsuit filed by the U.S. Department of Justice against Google has revealed fascinating insights into how the search giant ranks websites. Court documents, including testimony from a Google engineer, have unveiled algorithmic details that SEO professionals have been curious about for years. These documents provide valuable information about Google's quality scoring, click behaviours, popularity signals, and AI integration.

Google's Data Flow and Indexing Process

Google's search results generation process begins with data collection. According to court documents, Google feeds on two main data sources:

1. Structured Data: Information from third-party feeds, organised in a specific format.

2. Unstructured Data: Raw content collected through web crawling (GoogleBot).

This data is collected and processed through a system called "Multiverse." The collected data undergoes cleaning and normalisation processes to prepare for the main index. Structured information is forwarded to systems like Knowledge Graph to provide rich results and semantic contributions.

When a user performs a search, components like Query Understanding Service (QUS) and Superroot come into play. These systems analyze user queries and match them with appropriate content. In the final stage, Google Web Server (GWS) delivers the results and applies personalisation. Throughout this process, Logging Stack monitors user interactions and records them to optimise the system.

Google's ABC Signals

One of the most interesting revelations in the court documents is Google's core ranking factors, called "ABC Signals." These signals include:

• A — Anchors: Pages linking to the target page, i.e., backlinks.

• B — Body: The presence of search query terms in the document content.

• C — Clicks: The time users spend on a page before returning to search results.

These ABC signals form a page's "topicality" score. According to the Google engineer's testimony, the ranking development process (especially topicality) involves solving complex mathematical problems, and a team is continuously working on these problems.

Hand-Crafted Signals and Machine Learning

Another noteworthy point in the documents is Google's continued use of "hand-crafted signals." This indicates that the algorithm is not entirely automatic or AI-based but consists of scalable algorithms fine-tuned by search engineers.

The Google engineer compares their approach with Microsoft's completely automated approach used in Bing and says: "The reason the vast majority of signals are hand-crafted is so that when something breaks, Google knows what to fix. Google wants their signals to be completely transparent so they can troubleshoot and improve."

This approach offers an important insight for SEO professionals: Google's algorithm consists of understandable and predictable components. This means SEO strategies can still be effective.

The Relationship Between Page Quality and Relevance

Another important point revealed in the court documents is the relationship between page quality and query relevance. According to the Google engineer, page quality is generally a static value independent of queries. In other words, if a page is evaluated as high-quality and reliable, it is accepted as such for all relevant queries.

However, in some cases, the quality signal may include information from the query in addition to the static signal. For example, if a site is high-quality but contains general information, a query seeking very narrow/technical information can be used to direct to a high-quality site that is more technical.

The Google engineer emphasises that the page quality measure called "Q*" (Q-star) (the concept of reliability) is "incredibly important." The quality score remains of great importance even today, and page quality is what people complain about the most.

AI and Quality Issues

The Google engineer notes that AI is making quality issues worse: "People still complain about quality today, and AI is making it even worse."

This statement serves as an important warning for SEO professionals. As AI content production becomes more widespread, maintaining quality standards and meeting Google's quality assessment criteria becomes even more important.

LLM-Based Ranking Signals

The documents also provide hints about how Google uses LLM (Large Language Models) based ranking signals. The Google engineer mentions a system called "eDeepRank." This is an LLM system that uses language models like BERT.

The engineer says, "eDeepRank tries to take LLM-based signals and break them down into components to make them more transparent." This shows Google's effort to make LLM-based ranking signals more understandable. This parsing process is done so that search engineers can understand why the LLM ranked something.

Additionally, signals called "RankEmbed," derived from Google's main LLM model, are also used in the ranking process.

PageRank and Distance Ranking Algorithms

PageRank, Google's original ranking innovation, has been updated since then. According to court documents, PageRank is still an important signal that provides input to the quality score.

The Google engineer defines PageRank as: "PageRank is a single signal about distance from a known good source and is used as an input to the Quality score."

This shows that link distance algorithms are still important. These algorithms calculate the distance from authoritative websites for a specific topic (called seed sites) to other websites. The algorithms start with a set of authoritative sites for a specific topic, and sites that are farther from the relevant seed site are determined to be less reliable. Sites closer to the seed sets tend to be more authoritative and reliable.

Chrome-Based Mysterious Popularity Signal

The court documents mention a popularity signal that is redacted but uses Chrome data. This suggests that Google may use data collected from the Chrome browser as a ranking factor.

This information provides a new perspective for SEO professionals. The claim that the Chrome API leak is related to real ranking factors seems reasonable, but many SEO experts believe that these APIs are developer-focused tools used to display performance metrics like Core Web Vitals in the Chrome Dev Tools interface.

Navboost: System Measuring Click Behaviours

The documents also mention a system called "Navboost." This system measures how often users click on a document for a particular query and uses data from the last 13 months.

According to Dr. Eric Lehman's testimony, "Navboost is not a machine learning system. It's just a big table. For this document — sorry, for this search query, this document got two clicks. For this query, this document got three clicks, and so on. And it's aggregated, there's some extra data. But you can just think of it as a giant table."

This information confirms the role user behaviors play in Google ranking and emphasizes the importance of SEO professionals focusing on click-through rate optimization.

Google's AI Overviews: Is Being Visible and Reliable Enough?

According to a new UX study, users neither read Google's AI Overviews completely nor click on the links within them. This UX research conducted by Kevin Indig and Eric van Buskirk provides the first concrete data on the real effects of the AI Overviews experience. Although the study covers a small group of users, it offers important clues to observe trends.

Highlights

• Reading depth is quite low: Only 30% of users were observed to scroll down in AI Overviews content. Meaning the content is mostly consumed only with its top part.

• Click-through rates are decreasing: Only 19% of users on mobile devices and only 7.4% on desktop click on links within the AI Overview.

• Visibility exists, but interaction doesn't: AI answers increase visibility but actual visitor attraction decreases.

• Trend toward Reddit and forums: After AI answers, 30% of users move on to Reddit, YouTube, or other forums.

Google AI Overviews Research: Clicks Decreased by 30%, But Why?

BrightEdge's 2025 data indicates a paradigm shift in the SEO world: While Google search impressions increased by 49%, click-through rates decreased by 30%.

The reason for this dramatic decrease is Google AI Overviews, which was introduced exactly one year ago and now appears in many queries.

Highlights

• Google AI Overviews provides users with the answer directly in the SERP for many queries. This eliminates the need for users to click on the site.

• Long-tail queries (7% increase) and searches containing technical terms (48% increase) have started to appear more frequently in AI Overviews.

• Citations are now mostly made from content outside ranks 1-30. In fact, 89% of citations come from outside the top 100 rankings.

• B2B technology and insurance sectors have seen a dramatic increase in AI Overviews coverage. E-commerce is declining.

An Experience at the Intersection of E-Commerce and AI at WORLDEF

On Thursday, May 15, at WORLDEF Istanbul 2025, I presented "The AI Revolution in E-Commerce" on the Search 'n Stuff Case Study stage, connecting with a highly engaged audience.

Learning together, sharing, and growing... This is precisely the essence of the SEO world. The atmosphere on stage once again demonstrated that synergy beyond individual efforts is possible.

Today, AI has become a necessity for e-commerce, not just an option. Transformation is accelerating in areas like ChatGPT-supported shopping experiences, smart chatbots, content production processes, and Google's AI overviews.

However, it's important to remember: AI is a tool, not the goal. Without strategy, human touch, and original content, this tool alone is not sufficient.

I extend my sincere thanks to Search N Stuff founder Yağmur Şimşek who contributed by creating this platform, and to Can Mutioglu, Sevgi Ufaker, Onur Eroğlu, and Özgün Can Iltumur with whom I shared the stage.

As the SEO community strengthens, we all become stronger. I believe that when AI and human vision combine, our digital future will have more solid foundations.

This Week in the AI World: Tools, Services, and Tips

AI is driving innovations in digital marketing. Let's look at the latest developments and applications accelerating its impact on marketing!

• OpenAI announced GPT-4.1, GPT-4.1 mini, and nano models. These new models outperform GPT-4o and GPT-4o mini in all tests. They show significant improvements especially in coding (54.6% success), instruction following (38.3%), and long context understanding (72%). GPT-4.1 provides context support up to 1 million tokens, delivering more accurate results in long texts. It contains current information with a June 2024 knowledge cutoff. With these improvements, GPT-4.1 becomes the industry leader particularly in software development and complex instruction processing.

• The new PDF export feature added to ChatGPT offers an important workflow improvement for digital content professionals. You can now export all your research, tables, visuals, sources, and quotes in a single professional format. This feature will enable more effective sharing of SEO analyses and content strategies we provide to our corporate clients. Currently accessible to Plus, Team, and Pro users, this feature will soon be available to Enterprise and educational institutions.

• ChatGPT's "Deep Research" feature now also supports SharePoint integration (currently available as beta to Plus, Pro, and Team users); this allows ChatGPT to pull data from multiple SharePoint sites and combine content to provide referenced and contextually relevant answers based on corporate information — especially for SEO and content teams, this means eliminating knowledge silos and achieving significant time savings and productivity increases in content production, strategy development, and documentation processes.

SEO Implications & Action Items

With Google's internal ranking mechanisms now partially revealed, here's how you should update your SEO strategies for different content types:

For Blog Posts:

• Create comprehensive, in-depth content to strengthen quality and reliability signals.

• Focus on ABC signals to increase your content's topicality: acquire quality backlinks, naturally use keywords in content, and improve user experience to increase time spent on page.

• Pay attention to semantic relationships and topic coherence to help LLMs better understand your content.

For Product Descriptions:

• Make your product descriptions original and detailed; avoid AI-generated content.

• Strengthen the Navboost signal by improving user experience: provide clear product images, easy navigation, and fast page loading times.

• Optimize your internal linking strategy to increase the authority of your product pages.

For E-commerce Category Pages:

• Strengthen your category pages with rich, informative content.

• Make UX improvements that will positively affect user behaviors.

• Focus on technical SEO optimizations to increase page quality: speed, mobile compatibility, structured data markups.

For B2B Service Pages:

• Create in-depth content that emphasizes your expertise and reliability.

• Acquire backlinks from authoritative sources in your industry to strengthen the PageRank signal.

• Implement call-to-action buttons and form optimizations that will increase user interaction.

The Bottom Line

This leaked information about Google's ranking algorithm clarifies many topics that have been discussed in the SEO world for a long time. The documents show that Google still relies on traditional ranking factors (keywords, links, etc.) but supports them with AI and machine learning.

In light of this new information, it's critically important to review your SEO strategies and align them with current algorithmic dynamics. By striking the right balance between quality, relevance, user experience, and technical optimization, you can gain a competitive advantage in Google's complex ranking system.

Concurrently, we must adapt to the reality that Google AI Overviews is fundamentally changing user behavior patterns. The dramatic drop in click-through rates means we need to rethink how we measure success in SEO. Visibility alone is no longer enough - we need to create content so compelling that it breaks through the "answer without clicking" pattern that Google is establishing.

As always, I remain convinced that high-quality, expert content created with genuine human insight will maintain its value - even as the mechanisms for delivering that content continue to evolve.

Until next week,

Mert Erkal
Founder, Stradiji
SEO Strategist & Conversion Optimisation Expert

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