Nov 28 2025
Google’s Mueller Says Sites In A ‘Bad State’ May Need To Start Over via @sejournal, @MattGSouthern

Google’s John Mueller says sites with low-quality AI content should rethink their purpose rather than manually rewrite pages. Starting fresh may be faster than recovering.

  • Manually rewriting AI content doesn’t automatically restore a site’s value or authenticity
  • Mueller recommends treating recovery as starting over with no content, not as a page-by-page editing task
  • Recovering from a “bad state” may take longer than launching on a new domain
Ecommerce MGMT 0 Comments
Nov 14 2025
Data: Translated Sites See 327% More Visibility in AI Overviews

This post was sponsored by Weglot. The opinions expressed in this article are the sponsor’s own.

When Google’s AI Overviews launched in 2024, dozens of questions quickly surfaced among SEO professionals, one being: if AI now curates and summarizes search results, how do websites earn visibility, especially across languages?

Weglot recently conducted a data-driven study, analyzing 1.3 million citations across Google AI Overviews and ChatGPT to determine if LLMs cite content in one language, would they also cite it in others?

The result: translated websites saw up to 327% more visibility in AI Overviews than untranslated ones, a clear signal that international SEO is becoming inseparable from AI search.

Read The Full Study

What’s more, websites with another language available were also more likely to be cited in AI Overviews, regardless of the language the search was made.

This shift is redefining the rules of visibility. AI Overviews and large language models (LLMs) now mediate how information is discovered. Instead of ranking pages, they “cite” sources in generated responses.

But with that shift comes a new risk: if your website isn’t available in the user’s search language, does AI simply overlook it, or worse, send users to Google Translate’s proxy page instead?

The risk with Google’s Translate proxy is that while it does the translation work for you, you have no control over the translations of your content. Worse still, you don’t get any of the traffic benefits, as users are not directed to your site.

The Study

Here’s how the research worked. To understand how translation affects AI visibility, Weglot focused the research on Spanish-language websites across two markets: Spain and Mexico.

The study was then split into two phases. Phase one focused on websites that weren’t translated, and therefore only displayed the language intended for their market, in this case, Spanish.

In that phase, Weglot looked at 153 websites without English translations: 98 from Spain and 55 from Mexico. Weglot deliberately selected high-traffic sites because they offered no English versions.

Phase two involved a comparison group of 83 Spanish and Mexican sites with versions in both Spanish and English. This allowed Weglot to directly compare the performance of translated versus untranslated content.

In total, this generated 22,854 queries in phase one and 12,138 in phase two. The methodology converted the top 50 non-branded keywords of each site into queries that users would likely search, and then these were translated between the Spanish and English versions.

In total, 1.3 million citations were analyzed.

The Key Results

Untranslated Sites Have Very Low AI Search Visibility

The findings show that untranslated websites experience a substantial drop in visibility for searches conducted in non-available languages, despite maintaining strong visibility in the current available language.

Diving deeper into this, untranslated sites essentially lose massive visibility. From the study, even when these Spanish websites performed well in Spanish searches, the sites virtually disappeared in English searches.

Looking at this data further within Google AI Overviews:

  • The sample size of 98 untranslated sites from Spain had 17,094 citations for Spanish queries vs 2,810 citations for the equivalent search in English, a 431% gap in visibility.
  • Taking a look at untranslated sites in Mexico, the study identified a similar pattern. 12,038 citations for Spanish queries vs 3,450 citations for English, showing 213% fewer citations when searching English.

Even ChatGPT, though slightly more balanced, still favored translated sites, with Spanish sites receiving 3.5% fewer citations in English and 4.9% fewer with Mexican sites.

Image created by Weglot, November 2025

Translated Sites Have 327% More AI Search Visibility

But what happens when you do translate your site?

Bringing in the comparison group of Spanish websites that also have an English version, we can see that translated sites dramatically close the visibility gap and that having a second language transformed visibility within Google AI Overviews.

Google AI Overviews:

  • Translated sites in Spain saw 10,046 citations vs 8,048 in English, showcasing only a 22% gap.
  • Translated sites in Mexico showed 5,527 citations for Spanish queries and 3,325 citations for English, and a difference of 59%.

Overall, translated sites achieved 327% more visibility than untranslated ones and earned 24% more total citations per query.

When looking at ChatGPT, the bias almost vanished. Translated sites saw near-equal citations in both languages.

Image created by Weglot, November 2025

Next Steps: Translate Your Site To Boost Global Visibility In AI SERPs

Translation does more than boost visibility, it multiplies it.

Not only does having multiple languages across your site ensure your site gets picked up for searches in multiple languages, but it also adds to the overall visibility of your site as a whole.

The study found that translated sites perform better across all metrics. The data shows that translated sites received 24% more citations per prompt than untranslated sites.

Looking at this by language, translation resulted in a 33% increase in English citations and a 16% increase in Spanish citations per query.

Weglot’s findings indicate that translation acts as a signal of authority and reliability for AIOs and ChatGPT, boosting citation performance across all languages, not only the ones content is translated.

Image created by Weglot, November 2025

AI Search Rewards Translated Content as a Visibility Signal

Traditional international SEO has long focused on hreflang tags and localized keywords. But in the age of AI search, translation itself becomes a visibility signal:

  1. Language alignment: AI engines prioritize content matching the query’s language.
  2. Authority building: Translated content attracts engagement across markets, improving perceived reliability.
  3. Traffic control: Proper translations prevent Google Translate proxies from intercepting clicks.
  4. Semantic reach: Multilingual content broadens your surface area for AI training and citation.

Put simply: If your content isn’t in the language of the question, it’s unlikely it will be in the answer either.

The Business Impact

The consequences aren’t theoretical. One case in Weglot’s dataset, a major Spanish book retailer selling English-language titles worldwide without an English version of its site, shows the impact.

When English speakers searched for relevant books:

  • The site appeared 64% less often in Google AI Overviews and ChatGPT.
  • In 36% of the cases where it did appear, the link pointed to Google Translate’s proxy, not the retailer’s own domain.

Despite offering exactly what English users wanted, the business lost visibility, traffic, and ultimately, sales.

The Bigger Picture: AI Search Is Redefining SEO and Translation Is Now a Growth Strategy

The implications reach far beyond Spain or Mexico, or even the Spanish language.

As AI search evolves, the SEO playbook is expanding. Ranking isn’t just about “position one” anymore; it’s about being cited, summarized, and surfaced by machines trained on multilingual web content.

Weglot’s findings point to a future where translation is both an SEO and an AI strategy and not a localization afterthought.

With Google AIOs now live in multiple languages and ChatGPT integrating real-time web data, multilingual visibility has become an equity issue: sites optimized for one language risk being invisible in another.

Image created by Weglot, November 2025

Final Takeaway: Untranslated Sites Are Invisible in AI Search

The evidence is clear: Untranslated = unseen. Website translation is high up there for AIO visibility.

As AI continues to shape how search engines understand relevance, translation isn’t just about accessibility; it’s how your brand gets recognized by algorithms and audiences alike.

For the easiest way to translate a website, start your free trial now!

Plus, enjoy a 15% discount for 12 months on public plans by using the promo code SEARCH15 on a paid plan purchase.

Read The Full Study

Image Credits

Featured Image: Image by Weglot. Used with permission.

In-Post Images: Image by Weglot. Used with permission.

Ecommerce MGMT 0 Comments
Nov 10 2025
A Step-By-Step AEO Guide For Growing AI Citations & Visibility via @sejournal, @fthead9

This post was sponsored by TAC Marketing. The opinions expressed in this article are the sponsor’s own.

After years of trying to understand the black box that is Google search, SEO professionals have a seemingly even more opaque challenge these days – how to earn AI citations.

While at first glance inclusion in AI answers seems even more of a mystery than traditional SEO, there is good news. Once you know how to look for them, the AI engines do provide clues to what they consider valuable content.

This article will give you a step-by-step guide to discovering the content that AI engines value and provide a blueprint for optimizing your website for AI citations.

Take A Systematic Approach To AI Engine Optimization

The key to building an effective AI search optimization strategy begins with understanding the behavior of AI crawlers. By analyzing how these bots interact with your site, you can identify what content resonates with AI systems and develop a data-driven approach to optimization.

While Google remains dominant, AI-powered search engines like ChatGPT, Perplexity, and Claude are increasingly becoming go-to resources for users seeking quick, authoritative answers. These platforms don’t just generate responses from thin air – they rely on crawled web content to train their models and provide real-time information.

This presents both an opportunity and a challenge. The opportunity lies in positioning your content to be discovered and referenced by these AI systems. The challenge is understanding how to optimize for algorithms that operate differently from traditional search engines.

The Answer Is A Systematic Approach

  • Discover what content AI engines value based on their crawler behavior.
    • Traditional log file analysis.
    • SEO Bulk Admin AI Crawler monitoring.
  • Reverse engineer prompting.
    • Content analysis.
    • Technical analysis.
  • Building the blueprint.

What Are AI Crawlers & How To Use Them To Your Advantage

AI crawlers are automated bots deployed by AI companies to systematically browse and ingest web content. Unlike traditional search engine crawlers that primarily focus on ranking signals, AI crawlers gather content to train language models and populate knowledge bases.

Major AI crawlers include:

  • GPTBot (OpenAI’s ChatGPT).
  • PerplexityBot (Perplexity AI).
  • ClaudeBot (Anthropic’s Claude).
  • Googlebot crawlers (Google AI).

These crawlers impact your content strategy in two critical ways:

  1. Training data collection.
  2. Real-time information retrieval.

Training Data Collection

AI models are trained on vast datasets of web content. Pages that are crawled frequently may have a higher representation in training data, potentially increasing the likelihood of your content being referenced in AI responses.

Real-Time Information Retrieval

Some AI systems crawl websites in real-time to provide current information in their responses. This means fresh, crawlable content can directly influence AI-generated answers.

When ChatGPT responds to a query, for instance, it’s synthesizing information gathered by its underlying AI crawlers. Similarly, Perplexity AI, known for its ability to cite sources, actively crawls and processes web content to provide its answers. Claude also relies on extensive data collection to generate its intelligent responses.

The presence and activity of these AI crawlers on your site directly impact your visibility within these new AI ecosystems. They determine whether your content is considered a source, if it’s used to answer user questions, and ultimately, if you gain attribution or traffic from AI-driven search experiences.

Understanding which pages AI crawlers visit most frequently gives you insight into what content AI systems find valuable. This data becomes the foundation for optimizing your entire content strategy.

How To Track AI Crawler Activity: Find & Use Log File Analysis

The Easy Way: We use SEO Bulk Admin to analyze server log files for us.

However, there’s a manual way to do it, as well.

Server log analysis remains the standard for understanding crawler behavior. Your server logs contain detailed records of every bot visit, including AI crawlers that may not appear in traditional analytics platforms, which focus on user visits.

Essential Tools For Log File Analysis

Several enterprise-level tools can help you parse and analyze log files:

  • Screaming Frog Log File Analyser: Excellent for technical SEOs comfortable with data manipulation.
  • Botify: Enterprise solution with robust crawler analysis features.
  • Semrush: Offers log file analysis within its broader SEO suite.
Screenshot from Screaming Frog Log File AnalyserScreenshot from Screaming Frog Log File Analyser, October 2025

The Complexity Challenge With Log File Analysis

The most granular way to understand which bots are visiting your site, what they’re accessing, and how frequently, is through server log file analysis.

Your web server automatically records every request made to your site, including those from crawlers. By parsing these logs, you can identify specific user-agents associated with AI crawlers.

Here’s how you can approach it:

  1. Access Your Server Logs: Typically, these are found in your hosting control panel or directly on your server via SSH/FTP (e.g., Apache access logs, Nginx access logs).
  2. Identify AI User-Agents: You’ll need to know the specific user-agent strings used by AI crawlers. While these can change, common ones include:
  • OpenAI (for ChatGPT, e.g., `ChatGPT-User` or variations)
  • Perplexity AI (e.g., `PerplexityBot`)
  • Anthropic (for Claude, though often less distinct or may use a general cloud provider UAs)
  • Other LLM-related bots (e.g., “GoogleBot” and `Google-Extended` for Google’s AI initiatives, potentially `Vercelbot` or other cloud infrastructure bots that LLMs might use for data fetching).
  1. Parse and Analyze: This is where the previously mentioned log analyzer tools come into play. Upload your raw log files into the analyzer and start filtering the results to identify AI crawler and search bot activity. Alternatively, for those with technical expertise, Python scripts or tools like Splunk or Elasticsearch can be configured to parse logs, identify specific user-agents, and visualize the data.

While log file analysis provides the most comprehensive data, it comes with significant barriers for many SEOs:

  • Technical Depth: Requires server access, understanding of log formats, and data parsing skills.
  • Resource Intensive: Large sites generate massive log files that can be challenging to process.
  • Time Investment: Setting up proper analysis workflows takes considerable upfront effort.
  • Parsing Challenges: Distinguishing between different AI crawlers requires detailed user-agent knowledge.

For teams without dedicated technical resources, these barriers can make log file analysis impractical despite its value.

An Easier Way To Monitor AI Visits: SEO Bulk Admin

While log file analysis provides granular detail, its complexity can be a significant barrier for all but the most highly technical users. Fortunately, tools like SEO Bulk Admin can offer a streamlined alternative.

The SEO Bulk Admin WordPress plugin automatically tracks and reports AI crawler activity without requiring server log access or complex setup procedures. The tool provides:

  • Automated Detection: Recognizes major AI crawlers, including GPTBot, PerplexityBot, and ClaudeBot, without manual configuration.
  • User-Friendly Dashboard: Presents crawler data in an intuitive interface accessible to SEOs at all technical levels.
  • Real-Time Monitoring: Tracks AI bot visits as they happen, providing immediate insights into crawler behavior.
  • Page-Level Analysis: Shows which specific pages AI crawlers visit most frequently, enabling targeted optimization efforts.
Screenshot of SEO Bulk Admin AI/Bots ActivityScreenshot of SEO Bulk Admin AI/Bots Activity, October 2025

This gives SEOs instant visibility into which pages are being accessed by AI engines – without needing to parse server logs or write scripts.

Comparing SEO Bulk Admin Vs. Log File Analysis

Feature Log File Analysis SEO Bulk Admin
Data Source Raw server logs WordPress dashboard
Technical Setup High Low
Bot Identification Manual Automatic
Crawl Tracking Detailed Automated
Best For Enterprise SEO teams Content-focused SEOs & marketers

For teams without direct access to server logs, SEO Bulk Admin offers a practical, real-time way to track AI bot activity and make data-informed optimization decisions.

Screenshot of SEO Bulk Admin Page Level Crawler ActivityScreenshot of SEO Bulk Admin Page Level Crawler Activity, October 2025

Using AI Crawler Data To Improve Content Strategy

Once you’re tracking AI crawler activity, the real optimization work begins. AI crawler data reveals patterns that can transform your content strategy from guesswork into data-driven decision-making.

Here’s how to harness those insights:

1. Identify AI-Favored Content

  • High-frequency pages: Look for pages that AI crawlers visit most frequently. These are the pieces of content that these bots are consistently accessing, likely because they find them relevant, authoritative, or frequently updated on topics their users inquire about.
  • Specific content types: Are your “how-to” guides, definition pages, research summaries, or FAQ sections getting disproportionate AI crawler attention? This can reveal the type of information AI models are most hungry for.

2. Spot LLM-Favored Content Patterns

  • Structured data relevance: Are the highly-crawled pages also rich in structured data (Schema markup)? It’s an open debate, but some speculate that AI models often leverage structured data to extract information more efficiently and accurately.
  • Clarity and conciseness: AI models excel at processing clear, unambiguous language. Content that performs well with AI crawlers often features direct answers, brief paragraphs, and strong topic segmentation.
  • Authority and citations: Content that AI models deem reliable may be heavily cited or backed by credible sources. Track if your more authoritative pages are also attracting more AI bot visits.

3. Create A Blueprint From High-Performing Content

  • Reverse engineer success: For your top AI-crawled content, document its characteristics.
  • Content structure: Headings, subheadings, bullet points, numbered lists.
  • Content format: Text-heavy, mixed media, interactive elements.
  • Topical depth: Comprehensive vs. niche.
  • Keywords/Entities: Specific terms and entities frequently mentioned.
  • Structured data implementation: What schema types are used?
  • Internal linking patterns: How is this content connected to other relevant pages?
  • Upgrade underperformers: Apply these successful attributes to content that currently receives less AI crawler attention.
  • Refine content structure: Break down dense paragraphs, add more headings, and use bullet points for lists.
  • Inject structured data: Implement relevant Schema markup (e.g., `Q&A`, `HowTo`, `Article`, `FactCheck`) on pages lacking it.
  • Enhance clarity: Rewrite sections to achieve conciseness and directness, focusing on clearly answering potential user questions.
  • Expand Authority: Add references, link to authoritative sources, or update content with the latest insights.
  • Improve Internal Linking: Ensure that relevant underperforming pages are linked from your AI-favored content and vice versa, signaling topical clusters.

This short video walks you through the process of discovering what pages are crawled most often by AI crawlers and how to use that information to start your optimization strategy.

Here is the prompt used in the video:

You are an expert in AI-driven SEO and search engine crawling behavior analysis.

TASK: Analyze and explain why the URL [https://fioney.com/paying-taxes-with-a-credit-card-pros-cons-and-considerations/] was crawled 5 times in the last 30 days by the oai-searchbot(at)openai.com crawler, while [https://fioney.com/discover-bank-review/] was only crawled twice.

GOALS:

– Diagnose technical SEO factors that could increase crawl frequency (e.g., internal linking, freshness signals, sitemap priority, structured data, etc.)

– Compare content-level signals such as topical authority, link magnet potential, or alignment with LLM citation needs

– Evaluate how each page performs as a potential citation source (e.g., specificity, factual utility, unique insights)

– Identify which ranking and visibility signals may influence crawl prioritization by AI indexing engines like OpenAI’s

CONSTRAINTS:

– Do not guess user behavior; focus on algorithmic and content signals only

– Use bullet points or comparison table format

– No generic SEO advice; tailor output specifically to the URLs provided

– Consider recent LLM citation trends and helpful content system priorities

FORMAT:

– Part 1: Technical SEO comparison

– Part 2: Content-level comparison for AI citation worthiness

– Part 3: Actionable insights to increase crawl rate and citation potential for the less-visited URL

Output only the analysis, no commentary or summary.

Note: You can find more prompts for AI-focused optimization in this article: 4 Prompts to Boost AI Citations.

By taking this data-driven approach, you move beyond guesswork and build an AI content strategy grounded in actual machine behavior on your site.

This iterative process of tracking, analyzing, and optimizing will ensure your content remains a valuable and discoverable resource for the evolving AI search landscape.

Final Thoughts On AI Optimization

Tracking and analyzing AI crawler behavior is no longer optional for SEOs seeking to remain competitive in the AI-driven search era.

By using log file analysis tools – or simplifying the process with SEO Bulk Admin – you can build a data-driven strategy that ensures your content is favored by AI engines.

Take a proactive approach by identifying trends in AI crawler activity, optimizing high-performing content, and applying best practices to underperforming pages.

With AI at the forefront of search evolution, it’s time to adapt and capitalize on new traffic opportunities from conversational search engines.

Leverage AI Insights

Image Credits

Featured Image: Image by TAC Marketing. Used with permission.

In-Post Images: Image by TAC Marketing. Used with permission. 

Ecommerce MGMT 0 Comments
Nov 6 2025
Why AI Content All Sounds the Same & How SEO Pros Can Fix It via @sejournal, @mktbrew

This post was sponsored by Market Brew. The opinions expressed in this article are the sponsor’s own.

If your AI-generated articles don’t rank but sound fine, you’re not alone.

AI has made it effortless to produce content, but not to stand out in SERPs.

Across nearly every industry, brands are using generative AI tools like ChatGPT, Perplexity, Claude, and more to scale content production, only to discover that, to search engines, everything sounds the same.

But this guide will help you build E-E-A-T-friendly & AI-Overview-worthy content that boosts your AI Overview visibility, while giving you more control over your rankings.

Why Does All AI-Generated Content Sound The Same?

Most generative AI models write from the same training data, producing statistically “average” answers to predictable prompts.

The result is fluent, on-topic copy that is seen as interchangeable from one brand to the next.

To most readers, it may feel novel.

To search engines, your AI content may look redundant.

Algorithms can now detect when pages express the same ideas with minor wording differences. Those pages compete for the same meaning, and only one tends to win.

The challenge for SEOs isn’t writing faster, it’s writing differently.

That starts with understanding why search engines can tell the difference even when humans can’t.

How Do Search Engines & Answer Engines See My Content?

Here’s what Google actually sees when it looks at your page:

  • Search engines no longer evaluate content by surface keywords.
  • They map meaning.

Modern ranking systems translate your content into embeddings.

When two pages share nearly identical embeddings, the algorithm treats them as duplicates of meaning, similar to duplicate content.

That’s why AI-generated content blends together. The vocabulary may change, but the structure and message remain the same.

What Do Answer Engines Look For On Web Pages?

Beyond words, engines analyze the entire ecosystem of a page:

These structural cues help determine whether content is contextually distinct or just another derivative variant.

To stand out, SEOs have to shape the context that guides the model before it writes.

That’s where the Inspiration Stage comes in.

How To Teach AI To Write Like Your Brand, Not The Internet

Before you generate another article, feed the AI your brand’s DNA.

Language models can complete sentences, but can’t represent your brand, structure, or positioning unless you teach them.

Advanced teams solve this through context engineering, defining who the AI is writing for and how that content should behave in search.

The Inspiration Stage should combine three elements that together create brand-unique outputs.

Step 1 – Create A Brand Bible: Define Who You Are

The first step is identity.

A Brand Bible translates your company’s tone, values, and vocabulary into structured guidance the AI can reference. It tells the model how to express authority, empathy, or playfulness. And just as important, what NOT to say.

Without it, every post sounds like a tech press release.

With it, you get language that feels recognizably yours, even when produced at scale.

“The Brand Bible isn’t decoration: it’s a defensive wall against generic AI sameness.”

A great example: Market Brew’s Brand Bible Wizard

Step 2 – Create A Template URL: Structure How You Write

Great writing still needs great scaffolding.

By supplying a Template URL, a page whose structure already performs well, you give the model a layout to emulate: heading hierarchy, schema markup, internal link positions, and content rhythm.

Adding a Template Influence parameter can help the AI decide how closely to follow that structure. Lower settings would encourage creative variation; higher settings would preserve proven formatting for consistency across hundreds of pages.

Templates essentially become repeatable frameworks for ranking success.

An example of how to apply a template URL

Step 3 – Reverse-Engineer Your Competitor Fan-Out Prompts: Know the Landscape

Context also means competition. When you are creating AI content, it needs to be optimized for a series of keywords and prompts.

Fan-out prompts are a concept that maps the broader semantic territory around a keyword or topic. These are a network of related questions, entities, and themes that appear across the SERP.

In addition, fan-out prompts should be reverse-engineered from top competitors in that SERP.

Feeding this intelligence into the AI ensures your content strategically expands its coverage; something that the LLM search engines are hungry for.

“It’s not copying competitors, it’s reverse-engineering the structure of authority.”

Together, these three inputs create a contextual blueprint that transforms AI from a text generator into a brand and industry-aware author.

Market Brew’s implementation of reverse engineering fan-out prompts

How To Incorporate Human-Touch Into AI Content

If your AI tool spits out finished drafts with no checkpoints, you’ve lost control of what high-quality content is.

That’s a problem for teams who need to verify accuracy, tone, or compliance.

Breaking generation into transparent stages solves this.

Incorporate checkpoints where humans can review, edit, or re-queue the content at each stage:

  • Research.
  • Outline.
  • Draft.
  • Refinement.

Metrics for readability, link balance, and brand tone become visible in real time.

This “human-in-the-loop” design keeps creative control where it belongs.

Instead of replacing editors, AI becomes their analytical assistant: showing how each change affects the structure beneath the words.

“The best AI systems don’t replace editors, they give them x-ray vision into every step of the process.”

How To Build Content The Way Search Engines Read It

Modern SEO focuses on predictive quality signals: indicators that content is likely to perform before it ever ranks.

These include:

  • Semantic alignment: how closely the page’s embeddings match target intent clusters.
  • Structural integrity: whether headings, schema, and links follow proven ranking frameworks.
  • Brand consistency and clarity: tone and terminology that match the brand bible without losing readability.

Tracking these signals during creation turns optimization into a real-time discipline.

Teams can refine strategy based on measurable structure, not just traffic graphs weeks later.

That’s the essence of predictive SEO: understanding success before the SERP reflects it.

The Easy Way To Create High-Visibility Content For Modern SERPs

Top SEO teams are already using the Content Booster approach.

Market Brew’s Content Booster is one such example.

It embeds AI writing directly within a search engine simulation, using the same mechanics that evaluate pages to guide creation.

Writers begin by loading their Brand Bible, selecting a Template URL, and enabling reverse-engineered fan-out prompts.

Next, the internal and external linking strategy is defined, which uses a search engine model’s link scoring system, plus its entity-based text classifier as a guide to place the most valuable links possible.

This is bolstered by a “friends/foes” section that allows writers to define quoting / linking opportunities to friendly sites, and “foe” sites where external linking should be avoided.

The Content Booster then produces and evaluates a 7-stage content pipeline, each driven by thousands of AI agents.

Stage Function What You Get
0. Brand Bible Upload your brand assets and site; Market Brew learns your tone, voice, and banned terms. Every piece written in your unique brand style.
1. Opportunity & Strategy Define your target keyword or prompt, tone, audience, and linking strategy. A strategic blueprint tied to real search intent.
2. Brief & Structure Creates an SEO-optimized outline using semantic clusters and entity graphs. Perfectly structured brief ready for generation.
3. Draft Generation AI produces content constrained by embeddings and brand parameters. A first draft aligned with ranking behavior, not just text patterns.
4. Optimization & Alignment Uses cosine similarity and Market Brew’s ranking model to score each section. Data-driven tuning for maximum topical alignment.
5. Internal Linking & Entity Enrichment Adds schema markup, entity tags, and smart internal links. Optimized crawl flow and contextual authority.
6. Quality & Compliance Checks grammar, plagiarism, accessibility, and brand voice. Ready-to-publish content that meets editorial and SEO standards.

Editors can inspect or refine content at any stage, ensuring human direction without losing automation.

Instead of waiting months to measure results, teams see predictive metrics: like fan-out coverage, audience/persona compliance, semantic similarity, link distribution, embedding clusters and more. The moment a draft is generated.

This isn’t about outsourcing creativity.

It’s about giving SEO professionals the same visibility and control that search engineers already have.

Your Next Steps

If you teach your AI to think like your best strategist, sameness stops being a problem.

Every brand now has access to the same linguistic engine; the only differentiator is context.

The future of SEO belongs to those who blend human creativity with algorithmic understanding, who teach their models to think like search engines while sounding unmistakably human.

By anchoring AI in brand, structure, and competition, and by measuring predictive quality instead of reactive outcomes, SEOs can finally close the gap between what we publish and what algorithms reward.

“The era of AI sameness is already here. The brands that thrive will be the ones that teach their AI to sound human and think like a search engine.”

Ready to see how predictive SEO works in action?

Explore the free trial of Market Brew’s Light Brew system — where you can model how search engines interpret your content and test AI writing workflows before publishing.

Get Started Here

Image Credits

Featured Image: Image by Market Brew. Used with permission.

Ecommerce MGMT 0 Comments
Sep 30 2025
Google’s Spam Updates, Explained

Google completed its August 2025 algorithm update a few days ago. The update coincided with Google’s cancellation of the &num=100 query parameter, which lowered impression counts in Search Console.

Thus assessing the impact of the update in Search Console is confusing as the two events occurred more or less concurrently.

Google stated the update focused on spammy web pages. To gauge the impact on your site, view the “Clicks” metric in Search Console’s “Performance” report.

Traffic declines from spam updates are typically drastic. In this case, affected sites would have experienced a steep drop in clicks from August 26 through September 22.

Google’s spam updates:

  • Are automated, with no penalty message in Search Console, even if impacted.
  • Can only affect sites negatively. Traffic increases result from competitor declines.
  • Are usually recoverable after fixing the cause(s). The recovery may take months, although it does not depend on another core update.
  • Focus on sites violating its spam policies, and likely pertains only to on-site content. When it targets external backlinks, Google usually includes “link” in the update name. Otherwise, spam updates don’t include backlink signals.

Google’s Spam Policies

Google’s Search Central portal contains the company’s spam policies. Here are my explanations of the key components.

Cloaking or sneaky redirects. When a page (i) shows different content to search engines and users or (ii) redirects for users, but not search engines.

Doorway abuse. When a site has pages targeting similar keywords — a common reason to be hit by a spam update. To recover, cluster keywords by intent and restructure the site to target those groups instead of each word or phrase.

Expired domain abuse. When you buy an expired domain and leverage its authority for elevated rankings. There’s no easy recovery short of moving to a fresh domain. I have not seen declines in sites hosted on expired domains. Perhaps Google now detects that activity and does not rank expired-domain pages to begin with.

Hidden text and link abuse. When you hide words or links from users behind images and font-background color matching, such as white fonts on white backgrounds. I haven’t seen these tactics for years.

Keyword stuffing. When you fill a page with keywords or numbers to manipulate rankings. The policy is subjective, making it difficult to detect. (How many keywords are too many?) In my experience, however, actual keyword stuffing is obvious and rare.

Machine-generated traffic; scaled content abuse. When you deploy artificial intelligence or other automated methods to generate content at scale.

Scraping. When you use automated methods to steal and publish content from other sites.

Site reputation abuse. When you publish irrelevant content (usually whole sections) to benefit from your site’s authority, Google used to target this tactic separately, but may now include it in generic spam updates.

Thin affiliation. When you create an affiliate site by duplicating external product descriptions without adding anything unique or useful.

Misleading functionality. When a page promises one functionality, such as a PDF download, but instead executes something else, such as an ad click.

User-generated spam. When a site’s comments and other user-generated info include excessive promotional or offensive language or links.

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Sep 11 2025
Google Expands YMYL Guidelines To Cover Election & Civic Content via @sejournal, @MattGSouthern

Google published a new edition of its Search Quality Evaluator Guidelines.

The update clarifies that the Your Money Your Life (YMYL) category now covers election and voting information, along with other government and civics topics that affect people’s lives.

What’s New

The YMYL framework now uses the label “YMYL Government, Civics & Society,” with the definition calling out “election and voting information” and other informational topics about government and civics.

That takes the YMYL definition beyond the broader societal-impact wording you may remember from earlier editions.

Google’s changelog for this release lists three items: updated YMYL definitions, additional examples for clarity, and minor textual fixes.

A Quick Refresher On YMYL

YMYL topics are subjects where misinformation could significantly affect health, finances, safety, or the welfare of society. Pages on YMYL topics require the most scrutiny for Page Quality ratings.

The guidelines group YMYL into four buckets: Health or Safety, Financial Security, Government/Civics & Society, and Other.

Reminder: Quality raters follow these guidelines to evaluate search results, but their ratings don’t directly affect how any individual page ranks. Google uses the ratings to check whether its systems are producing helpful results and to guide improvements over time.

Why This Matters

If you cover elections, voting procedures, candidate information, or local civic processes, your pages are now treated as YMYL.

That raises the bar for accuracy, sourcing, and author credentials. The guidelines also stress reputation signals from experts in the field when evaluating YMYL topics.

What To Do Next

Take some time to review your current civic and government pages to ensure they’re accurate and thorough. Highlight the author’s experience so visitors can trust the content, and be sure to cite primary sources when possible.

For information that can change quickly, such as registration deadlines or polling places, consider setting up a maintenance plan and keeping update logs.

When it comes to reputational signals on YMYL pages, it’s helpful to link to expert references and independent coverage instead of relying solely on traffic snapshots or general popularity.

Looking ahead

This edition runs 182 pages and is the first major update to these guidelines since January.

By aligning your civic content with these standards, you’ll be better positioned to meet user expectations and adapt to any changes Google makes in the future.

Expect continued revisions as Google refines examples and rating guidance.

Featured Image: Mameraman/Shutterstock

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Sep 10 2025
Quick SEO: 6 Key Elements, 3 Free Tools

A page’s visibility on search engines and generative AI platforms depends on six key elements:

  • Title,
  • Meta tags,
  • HTML headings,
  • Links, internal and external,
  • Images,
  • Structured data.

When optimizing a page, I rely on three free browser extensions to quickly reveal those components: Devaka Tools, Site Inspector, and SEO Meta in 1 Click.

What follows is my explanation of the six elements, followed by a side-by-side table comparing the three extensions.

Title of page

The title tag is the most important on-page optimization element because search engines use it to understand the page’s purpose. Descriptive and keyword-focused page titles improve and diversify organic rankings.

The title tag appears in the browser tab and is not necessarily visible on the page.

Meta tags

Two types of meta tags are key for search engine optimization:

  • A meta description does not directly impact rankings, but it may appear in search snippets and thus affect click-throughs.

HTML headings

HTML headings such as H1, H2, and H3 organize on-page content. This article includes HTML headings: “Title of page,” “Meta tags,” “HTML headings,” et cetera. The headings, while optional, help readers digest the content and assist crawlers in identifying relevant info for searchers’ queries. Using keywords in HTML headings serves both purposes.

Links, internal and external

Internal links signal to search engines the importance of a page: the more internal links pointing to a page, the higher its significance.

Internal links also help search engines understand the linked page. The link’s anchor text is the strongest signal, although its surrounding words also send relevancy signals, per Google. Improving internal linking structure is often a quick way to streamline crawlability and increase organic search visibility.

External links to authoritative sites add credibility to the page, especially in “Your Money Your Life” niches.

Images

Images enhance visitor engagement, a Google ranking factor, and improve visibility in image search results.

Image alt tags are essential for both visually-impaired visitors and search engines. Compressing images enhances page speed and thus Core Web Vitals, another ranking factor.

Structured data

Structured data helps search engines and AI platforms understand a site, its pages, and the owner. Schema.org’s “vocabulary” of structured data is the most popular. Google and Bing recognize it as well as other methods.

Browser Extensions

You can quickly see all of these elements using one or more of the following browser extensions:

Feature Devaka Tools Site Inspector SEO Meta
Browser Many Chrome Chrome
Title of page Yes Yes Yes
Meta tags Yes Yes Yes
HTML headings Yes Yes Yes
Links: internal, external Yes Yes Yes (plus highlighting nofollow links)
Images Yes Yes Yes
Structured data Yes Yes Yes
Excel export Yes Yes Yes
Notes Can highlight keywords, show image alt text, reveal hidden text. Provides links to tools such as Schema.org validator and Search Console. Can keep sidebar open to automatically load data. Provides a page summary with word count, headings, images. Can export a page’s copy. Includes a page preview and Schema.org validator.

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Sep 5 2025
Google: Your Login Pages May Be Hurting Your SEO Performance via @sejournal, @MattGSouthern

Google’s Search Relations team says generic login pages can confuse indexing and hurt rankings.

When many private URLs all show the same bare login form, Google may treat them as duplicates and show the login page in search.

In a recent “Search Off the Record” episode, John Mueller and Martin Splitt explained how this happens and what to do about it.

Why It Happens

If different private URLs all load the same login screen, Google sees those URLs as the same page.

Mueller said on the podcast:

“If you have a very generic login page, we will see all of these URLs that show that login page that redirect to that login page as being duplicates… We’ll fold them together as duplicates and we’ll focus on indexing the login page because that’s kind of what you give us to index.”

That means people searching for your brand may land on a login page instead of helpful information.

“We regularly see Google services getting this wrong,” Mueller admitted, noting that with many teams, “you invariably run across situations like that.”

Search Console fixed this by sending logged-out visitors to a marketing page with a clear sign-in link, which gave Google indexable context.

Don’t Rely On robots.txt To Hide Private URLs

Blocking sensitive areas in robots.txt can still let those URLs appear in search with no snippet. That’s risky if the URLs expose usernames or email addresses.

Mueller warned:

“If someone does something like a site query for your site… Google and other search engines might be like, oh, I know about all of these URLs. I don’t have any information on what’s on there, but feel free to try them out essentially.”

If it’s private, avoid leaking details in the URL, and use noindex or a login redirect instead of robots.txt.

What To Do Instead

If content must stay private, serve a noindex on private endpoints or redirect requests to a dedicated login or marketing page.

Don’t load private text into the page and then hide it with JavaScript. Screen readers and crawlers may still access it.

If you want restricted pages indexed, use the paywall structured data. It allows Google to fetch the full content while understanding that regular visitors will hit an access wall.

Paywall structured data isn’t only for paid content, Mueller explains:

“It doesn’t have to be something that’s behind like a clear payment thing. It can just be something like a login or some other mechanism that basically limits the visibility of the content.”

Lastly, add context to login experiences. Include a short description of the product or the section someone is trying to reach.

As Mueller advised:

“Put some information about what your service is on that login page.”

A Quick Test

Open an incognito window. While logged out, search for your brand or service and click the top results.

If you land on bare login pages with no context, you likely need updates. You can also search for known URL patterns from account areas to see what shows up.

Looking Ahead

As more businesses use subscriptions and gated experiences, access design affects SEO.

Use clear patterns (noindex, proper redirects, and paywalled markup where needed) and make sure public entry points provide enough context to rank for the right queries.

Small changes to login pages and redirects can prevent duplicate grouping and improve how your site appears in search.

Featured Image: Roman Samborskyi/Shutterstock

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Aug 8 2025
Google: Unique Image Landing Pages Can Help Boost Search Visibility via @sejournal, @MattGSouthern

Google’s John Mueller says giving each image its own landing page can help it appear in image search, while gallery setups may limit visibility.

  • Google recommends unique landing pages for important images instead of JavaScript-only galleries or URL fragments.
  • Responsive images and modern formats improve user experience but aren’t direct ranking factors.
  • Auditing your site’s image URLs could reveal search visibility gains you’re currently missing.
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Jun 17 2025
See What AI Sees: AI Mode Killed the Old SEO Playbook — Here’s the New One via @sejournal, @mktbrew

This post was sponsored by MarketBrew. The opinions expressed in this article are the sponsor’s own.

Is Google using AI to censor thousands of independent websites?

Wondering why your traffic has suddenly dropped, even though you’re doing SEO properly?

Between letters to the FTC describing a systematic dismantling of the open web by Google to SEO professionals who may be unaware that their strategies no longer make an impact, these changes represent a definite re-architecting of the web’s entire incentive structure.

It’s time to adapt.

While some were warning about AI passage retrieval and vector scoring, the industry largely stuck to legacy thinking. SEOs continued to focus on E-E-A-T, backlinks, and content refresh cycles, assuming that if they simply improved quality, recovery would come.

But the rules had changed.

Google’s Silent Pivot: From Keywords to Embedding Vectors

In late 2023 and early 2024, Google began rolling out what it now refers to as AI Mode.

What Is Google’s AI Mode?

AI Mode breaks content into passages, embeds those passages into a multi-dimensional vector space, and compares them directly to queries using cosine similarity.

In this new model, relevance is determined geometrically rather than lexically. Instead of ranking entire pages, Google evaluates individual passages. The most relevant passages are then surfaced in a ChatGPT-like interface, often without any need for users to click through to the source.

Beneath this visible change is a deeper shift: content scoring has become embedding-first.

What Are Embedding Vectors?

Embedding vectors are mathematical representations of meaning. When Google processes a passage of content, it converts that passage into a vector, a list of numbers that captures the semantic context of the text. These vectors exist in a multi-dimensional space where the distance between vectors reflects how similar the meanings are.

Instead of relying on exact keywords or matching phrases, Google compares the embedding vector of a search query to the embedding vectors of individual passages. This allows it to identify relevance based on deeper context, implied meaning, and overall intent.

Traditional SEO practices like keyword targeting and topical coverage do not carry the same weight in this system. A passage does not need to use specific words to be considered relevant. What matters is whether its vector lands close to the query vector in this semantic space.

How Are Embedding Vectors Different From Keywords?

Keywords focus on exact matches. Embedding vectors focus on meaning.

Traditional SEO relied on placing target terms throughout a page. But Google’s AI Mode now compares the semantic meaning of a query and a passage using embedding vectors. A passage can rank well even if it doesn’t use the same words, as long as its meaning aligns closely with the query.

This shift has made many SEO strategies outdated. Pages may be well-written and keyword-rich, yet still underperform if their embedded meaning doesn’t match search intent.

What SEO Got Wrong & What Comes Next

The story isn’t just about Google changing the game, it’s also about how the SEO industry failed to notice the rules had already shifted.

Don’t: Misread the Signals

As rankings dropped, many teams assumed they’d been hit by a quality update or core algorithm tweak. They doubled down on familiar tactics: improving E-E-A-T signals, updating titles, and refreshing content. They pruned thin pages, boosted internal links, and ran audits.

But these efforts were based on outdated models. They treated the symptom, visibility loss, not the cause: semantic drift.

Semantic drift happens when your content’s vector no longer aligns with the evolving vector of search intent. It’s invisible to traditional SEO tools because it occurs in latent space, not your HTML.

No amount of backlinks or content tweaks can fix that.

This wasn’t just platform abuse. It was also a strategic oversight.

SEO teams:

Many believed that doing what Google said, improving helpfulness, pruning content, and writing for humans, would be enough.

That promise collapsed under AI scrutiny.

But we’re not powerless.

Don’t: Fall Into The Trap of Compliance

Google told the industry to “focus on helpful content,” and SEOs listened, through a lexical lens. They optimized for tone, readability, and FAQs.

But “helpfulness” was being determined mathematically by whether your vectors aligned with the AI’s interpretation of the query.

Thousands of reworked sites still dropped in visibility. Why? Because while polishing copy, they never asked: Does this content geometrically align with search intent?

Do: Optimize For Data, Not Keywords

The new SEO playbook begins with a simple truth: you are optimizing for math, not words.

The New SEO Playbook: How To Optimize For AI-Powered SERPs

Here’s what we now know:

  1. AI Mode is real and measurable.
    ✅You can calculate embedding similarity.
    ✅You can test passages against queries.
    ✅You can visualize how Google ranks.
  2. Content must align semantically, not just topically.
    ✅Two pages about “best hiking trails” may be lexically similar, but if one focuses on family hikes and the other on extreme terrain, their vectors diverge.
  3. Authority still matters, but only after similarity.
    ✅The AI Mode fan-out selects relevant passages first. Authority reranking comes later.
    ✅If you don’t pass the similarity threshold, your authority won’t matter.
  4. Passage-level optimization is the new frontier.
    ✅Optimizing entire pages isn’t enough. Each chunk of content must pull semantic weight.

How Do I Track Google AI Mode Data To Improve SERP Visibility?

It depends on your goals; for success in SERPs, you need to focus on tools that not only show you visibility data, but also how to get there.

Profound was one of the first tools to measure whether content appeared inside large language models, essentially offering a visibility check for LLM inclusion. It gave SEOs early signals that AI systems were beginning to treat search results differently, sometimes surfacing pages that never ranked traditionally. Profound made it clear: LLMs were not relying on the same scoring systems that SEOs had spent decades trying to influence.

But Profound stopped short of offering explanations. It told you if your content was chosen, but not why. It didn’t simulate the algorithmic behavior of AI Mode or reveal what changes would lead to better inclusion.

That’s where simulation-based platforms came in.

Market Brew approached the challenge differently. Instead of auditing what was visible inside an AI system, they reconstructed the inner logic of those systems, building search engine models that mirrored Google’s evolution toward embeddings and vector-based scoring. These platforms didn’t just observe the effects of AI Mode, they recreated its mechanisms.

As early as 2023, Market Brew had already implemented:

  • Passage segmentation that divides page content into consistent ~700-character blocks.
  • Embedding generation using Sentence-BERT to capture the semantic fingerprint of each passage.
  • Cosine similarity calculations to simulate how queries match specific blocks of content, not just the page as a whole.
  • Thematic clustering algorithms, like Top Cluster Similarity, to determine which groupings of passages best aligned with a search intent.

🔍 Market Brew Tutorial: Mastering the Top Cluster Similarity Ranking Factor | First Principles SEO

This meant users could test a set of prompts against their content and watch the algorithm think, block by block, similarity score by score.

Where Profound offered visibility, Market Brew offered agency.

Instead of asking “Did I show up in an AI overview?”, simulation tools helped SEOs ask, “Why didn’t I?” and more importantly, “What can I change to improve my chances?”

By visualizing AI Mode behavior before Google ever acknowledged it publicly, these platforms gave early adopters a critical edge. The SEOs using them didn’t wait for traffic to drop before acting, they were already optimizing for vector alignment and semantic coverage long before most of the industry knew it mattered.

And in an era where rankings hinge on how well your embeddings match a user’s intent, that head start has made all the difference.

Visualize AI Mode Coverage. For Free.

SEO didn’t die. It transformed, from art into applied geometry.

AI Mode Visualizer Tutorial

To help SEOs adapt to this AI-driven landscape, Market Brew has just announced the AI Mode Visualizer, a free tool that simulates how Google’s AI Overviews evaluate your content:

  • Enter a page URL.
  • Input up to 10 search prompts or generate them automatically from a single master query using LLM-style prompt expansion.
  • See a cosine similarity matrix showing how each content chunk (700 characters) for your page aligns with each intent.
  • Click any score to view exactly which passage matched, and why.

🔗 Try the AI Mode Visualizer

This is the only tool that lets you watch AI Mode think.

Two Truths, One Future

Nate Hake is right: Google restructured the game. The data reflects an industry still catching up to the new playbook.

Because two things can be true:

  • Google may be clearing space for its own services, ad products, and AI monopolies.
  • And many SEOs are still chasing ghosts in a world governed by geometry.

It’s time to move beyond guesses.

If AI Mode is the new architecture of search, we need tools that expose how it works, not just theories about what changed.

We were bringing you this story back in early 2024, before AI Overviews had a name, explaining how embeddings and vector scoring would reshape SEO.

Tools like the AI Mode Visualizer offer a rare chance to see behind the curtain.

Use it. Test your assumptions. Map the space between your content and modern relevance.

Search didn’t end.

But the way forward demands new eyes.

Book Your AI Mode Strategy Session

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Image Credits

Featured Image: Image by MarketBrew. Used with permission.

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