Tag: SEO

  • Navigating SEO Careers in the AI Era

    Navigating SEO Careers in the AI Era

    I’m witnessing a fascinating shift in the search industry, something I hadn’t anticipated witnessing in my career.

    The supply of search expertise now outweighs the demand.

    We can point fingers at artificial intelligence, the economy, or the increasing commonality of checkbox SEO.

    Whatever the cause, the outcome remains unchanged.

    SEO job cuts are rising. Openings are dwindling. I’ve never seen the market as competitive in my 15+ years.

    The hard truth is many SEO skills that were once invaluable are becoming easier to automate or outsource.

    Grab a seat.

    I’d love to explore why this is occurring, which skills are now expected, and what SEO talent employers should really be seeking as we move towards 2026.

    View embedded content

    The notion that AI is directly targeting SEO jobs is widespread, but I disagree.

    Instead, AI is reshaping which SEO skills are most valued.

    Traditionally, SEO involved collecting data and crafting strategies — technical audits, content briefs, keywords, and more.

    These tasks still have importance today.

    However, they’re becoming much simpler to execute.

    With AI, crafting an audit or optimization suggestion can now take just moments.

    This doesn’t devalue the output, but it changes the landscape of value.

    For years, companies viewed recommendations as final products. The report was the result.

    ```json
{
  "alt": "Comparison of old and new models for achieving promotion with emphasis on SEO knowledge.",
  "caption": "From SEO Knowledge to Success: Discover how the new model combines multiple skills for effective promotion.",
  "description": "This image compares two models for achieving promotion. The old model relies solely on SEO knowledge, while the new model incorporates SEO knowledge, business acumen, communication & influence, and execution & testing, illustrating a more comprehensive approach to success. Symbols are used for each component, with promotion depicted as a trophy. Keywords: SEO, promotion, business acumen, communication, execution, testing."
}
```

    But recommendations aren’t goals on their own.

    They add value only if they lead to prioritized actions and deliver business results.

    AI solves the idea generation problem quite proficiently.

    However, it falls short in implementation.

    That’s why I foresee the first SEO roles AI might impact are those focused on crafting suggestions rather than driving outcomes.

    As producing recommendations becomes nearly costless, employers favor those who discern valuable suggestions and execute them.

    In essence, AI is streamlining SEO execution tasks.

    Yet, it isn’t undermining judgment.

    As AI enhances in recommendations, SEO talent shifts towards skills like prioritization, testing, and influence.

    These skills have always been crucial.

    Now, they’re rapidly becoming key differentiators.

    Most companies don’t lack ideas. They struggle with alignment and decision-making.

    Ultimately, judgment is essential.

    Recently, I disagreed with Gemini on a well-known topic. While the answer was polished, it was incorrect.

    As AI grows, recognizing when it’s confidently incorrect is a skill itself.

    The future SEO isn’t about generating numerous recommendations, but identifying which are truly impactful.

    ```json
{
  "alt": "SEO For Lunch Newsletter by Nick Leroy, featuring actionable SEO insights.",
  "caption": "Join Nick Leroy's SEO For Lunch: Your go-to source for actionable SEO insights served directly to your inbox.",
  "description": "This image promotes Nick Leroy's 'SEO For Lunch' newsletter, emphasizing actionable SEO insights. It features a smiling person against a dark blue background with the newsletter's branding, '#SEOFORLUNCH,' and website details. The design includes graphic elements like a fork and knife, alongside the tagline 'Not Your Average Table Talk.'"
}
```

    In the past, SEO career growth was straightforward: gain knowledge, get promoted.

    Yet now, as AI diminishes pure knowledge value, the layered skills atop expertise matter significantly more.

    Today’s most valuable SEOs understand search, AI, and business operations. They align people and resources towards common goals.

    Higher organizational roles rely less on identifying problems and more on solving them.

    While AI scales execution, people scale vision.

    If I were hiring an SEO in 2026, I would focus less on technical details and more on how candidates handle complex situations.

    I’d ask for a disagreement experience.

    For example, I suspected H1 tags didn’t significantly impact rankings. Initially, people laughed, and opinions varied until further confirmed by experts.

    I care more about their resolve than their correctness.

    I’d ask about a failed test.

    Experienced SEOs know projects often stall. The key is their follow-through post-failure.

    I’d inquire about AI mishaps.

    I aim to find candidates who turn knowledge into tangible outcomes.

    The hard part has always been delivering results, not knowing what to do.

    AI won’t substitute SEOs, but those unwilling to adapt may face challenges.

    This article initially appeared on my personal site, shared here with permission.


    Inspired by this post on Search Engine Land.


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  • Google Enhances Local Real Estate Ads Nationwide

    Google Enhances Local Real Estate Ads Nationwide

    I’ve got some exciting news to share! Google is expanding its enhanced Local Services Ads (LSAs) for Home Listings all across the U.S., and it’s set to revolutionize the home-buying process.

    As someone who frequently turns to Google at the start of my own home-searching journey, I see this as a fantastic opportunity for connecting homebuyers like me with local agents earlier in the process.

    What’s New: With the updated LSA experience, I’m thrilled to see that ads now include detailed property information, such as pricing, photos, and key home features, right within the ad itself.

    This new functionality is made possible through a collaboration with HouseCanary, which provides the property data showcased in the ads.

    Why It’s Important: For me, having access to actual property listings, including visuals, pricing, and details directly through Google’s Local Services Ads, means I can better evaluate homes and reach out to agents without ever leaving the search page. This could very well boost lead quality and conversion rates.

    How It Works: If I’m in the market for a new home, I can contact agents directly from these ads, whether through a call, message, or by booking an appointment.

    Who Benefits: Existing LSA advertisers are automatically included in this enriched experience. Real estate professionals not yet using Local Services Ads have the chance to sign up and start receiving high-quality leads. Additionally, portal partners can sign up agents through Google’s managed partner program.

    The Bottom Line: Google’s strategy, combining rich listing information with direct agent connections, seems designed to make Search a more beneficial starting point for homebuyers like myself. It’s poised to become a valuable resource for agents looking for high-intent leads.


    Inspired by this post on Search Engine Land.


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  • Mastering SEO Fixes: Predict Traffic Impact with Confidence

    Mastering SEO Fixes: Predict Traffic Impact with Confidence

    Hey there! If you’re anything like me, your backlog is overflowing, your developer is eager to know what to tackle first, and your boss is questioning why months of SEO work haven’t shown results. I’ve been stuck defending my roadmap with gut feelings, and it’s tough.

    Without estimating the traffic impact of a fix before it’s live, it’s just a guess—and we both know guesses don’t cut it in budget meetings.

    Let me share a framework I use to transform messy data into reliable estimates. It’s not perfect, but it’s solid enough to prioritize with confidence and explain my strategy in any meeting.

    Why every recommendation can’t be high priority

    I’ve seen teams spend sprints on minor schema issues, ignoring a bigger problem—like a title tag bug affecting thousands of pages. Both were marked as “high priority,” but the traffic impact of one was negligible compared to the other.

    Traffic guides true priority. While we can’t neglect brand visibility or UX, traffic offers a universal measure to compare efforts. Without quantified impact, you’re letting the loudest voice, or the most tempting technical puzzle, dictate your roadmap instead of focusing on what truly drives business value.

    Plus, SERP landscapes have changed drastically. According to SparkToro, 68% of U.S. Google searches this year ended without a click, up significantly since just two years ago.

    With AI Overviews intercepting traffic, the impact of a ranking improvement can vary wildly by SERP layout. Jumping to position three on a commercial keyword might be gold, but on an informational query dominated by AI? Not necessarily.

    Your forecasts should account for these dynamics to avoid overpromising.

    Step 1: Define the scope

    Before making any estimates, I always define the scope. Is the adjustment sitewide, a template fix, or a single-page optimization? Each scenario changes the math.

    Sitewide technical fixes

    These encompass site speed, mobile usability, HTTPS migrations, and Core Web Vitals. They influence every page, but not uniformly. Address areas with pages on the borderline of failing tests first.

    Template-level changes

    Fixes like rewriting title tags can have a major impact, but it’s vital to focus where traffic truly exists. Product templates might garner the majority of clicks, while blogs might trail behind.

    Individual page optimizations

    Actions like updating meta descriptions can provide quick wins, but their small scale might not significantly impact the business. Focus on these without losing sight of larger opportunities.

    Step 2: Calculate your current traffic exposure

    To gauge traffic exposure, I turn to Google Search Console to pull essential data.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    Organic clicks serve as a baseline. By filtering affected URLs and reviewing trends, I assess urgency and context.

    Impressions and near-win rankings pinpoint real potential. Pages ranked 8-15 are ripe for improvements—push them higher for a CTR boost.

    SERP features can greatly influence CTR. Using Search Console’s AI Mode data, I check for AI Overview dominance and adjust expectations.

    Step 3: Estimate potential lift

    Now, it’s time for educated estimation.

    Your own history

    When I’ve optimized similar pages before, I use those outcomes as future baselines. Keeping track of past projects builds a valuable benchmarking library.

    Competitor benchmarks and SERP analysis

    Review competitors and pinpoint their advantages, whether it’s content depth, UX, or backlinks. Aiming to close these gaps can justify a ranking gain.

    AI-influenced CTR assumptions

    Forecasting can falter without updated CTR assumptions. Seer’s research shows drastic CTR changes due to AI integration. Staying aware of these shifts is essential.

    Step 4: Build three scenarios, not one number

    One definitive forecast can be deceptive. I prefer building three—conservative, expected, and aggressive—to provide a range that reflects real possibilities.

    In the conservative model, expect partial implementations and competition improvements. With the expected model, rely on solid historical benchmarks. The aggressive model accounts for perfect execution and fast indexing.

    This comprehensive view guides stakeholders through potential outcomes, ensuring transparency and credibility.

    Step 5: Use the forecast to build your roadmap

    After forecasting, I compare traffic impact predictions to effort levels using frameworks like RICE. This demonstrates which initiatives offer the most value for the effort and helps align priorities with business goals.

    A well-organized roadmap doesn’t just appeal to me but speaks clearly to everyone involved, highlighting efficiency and business impact.


    Inspired by this post on Search Engine Land.


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  • Doug Davis on Building Lasting Trust Through Community Validation

    Doug Davis on Building Lasting Trust Through Community Validation

    Chatting with Doug Davis, the visionary Founder of Voted Number One, offers a refreshing perspective on how genuine community trust can transform a business’s credibility. In a world where consumers face too many choices and are skeptical of self-promotion, Doug’s insights into local-level trust-building are invaluable. He explains why community backing signifies strong business credibility and how local companies can unwittingly harm trust despite providing high-quality work. Doug also delves into how a business’s reputation increasingly hinges on customer testimonials rather than self-advertisements.

    First Page Sage: Many businesses think visibility equals trust. Doug, can you shed light on where companies often get recognition and credibility wrong?

    Doug: A common mistake is equating attention with trust. A business might be well-known but still lack authentic trust within its community. Companies often focus excessively on advertising while neglecting the customer experiences that genuinely shape their long-term reputation.

    What truly counts is whether people are willing to recommend a business without any personal gain. That’s a very telling indication of trust. True community trust is developed through consistent, reliable interactions over time.

    First Page Sage: Voted Number One emphasizes community-driven recognition over internal rankings. Why does this matter now more than ever?

    Doug: People rely more on collective community experiences than on polished corporate assertions. Community-driven recognition showcases genuine, repeated positive interactions, not just catchy marketing phrases.

    Trust within communities grows cumulatively. When individuals repeatedly hear about the same business from close acquaintances, neighbors, or fellow professionals, natural confidence builds, which is hard to fabricate through artificial means.

    First Page Sage:: In competitive local markets, what factors actually guide consumer decisions when comparing providers?

    Doug: It boils down to clarity and evidence. Since most consumers aren’t industry experts, they look for signs that reduce uncertainty. They want assurance that a business has consistently delivered for others like them.

    Specificity makes a business stand out quickly. Clear communication regarding a company’s experience, processes, and results outshines vague promises. Consistent touchpoints build trust faster, while inconsistency can arouse consumer hesitance.

    First Page Sage:: With consumer decisions increasingly swayed by community recommendations and automated systems, how crucial is genuine customer advocacy?

    Doug: Genuine customer advocacy is now essential. Modern systems focus on patterns of trust rather than singular claims. Businesses that naturally generate customer support are more likely to sustain their visibility and credibility.

    Authentic advocacy often stems from operational excellence rather than marketing tricks. Communities back businesses that consistently deliver, solve problems effectively, and communicate transparently.

    First Page Sage:: What practical habits should local business owners adopt to build enduring reputations?

    Doug: Building a lasting reputation requires treating trust as a key operational target rather than a mere branding effort. This means ensuring consistency, responsiveness, and follow-through, even in busy times.

    Furthermore, documenting real customer experiences and outcomes, as well as community involvement, significantly enhances credibility. Avoiding complacency is vital as a strong reputation is never guaranteed; it requires continuous reinforcement through action.

    For more on Voted Number One’s recognition platform, visit votednumberone.com.


    Inspired by this post on First Page Sage Blog.


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  • Discover the Leading Pharmaceutical GEO Agencies of 2026

    In early 2026, I had the task of evaluating 42 pharmaceutical marketing agencies, aiming to spotlight those excelling in GEO services. My evaluation used specific criteria to make these selections.

    The agencies were assessed on several factors: the strength of their GEO offerings, their visibility in AI platforms like ChatGPT and Perplexity, leadership experience, client reviews, media references, notable clients, the year established, and their unique specialties.

    After meticulous evaluation, I curated a list of the top pharmaceutical GEO agencies, complete with an in-depth analysis and summarized client reviews.

    The Top Pharmaceutical GEO Agencies

    RankAgencyYear EstablishedGEO ScoreAI Visibility ScoreLeadership ScoreAvg Review ScoreMedia ReferencesNotable ClientsSpecialty
    1First Page Sage20095.04.94.84.9~810BIOVA, Tesseract Medical GEO-driven lead generation, SEO, and thought leadership 
    2Genevate20254.84.64.24.8~20PharmaEssentia, Eton PharmaceuticalsGEO and PR 
    3Signal Hill Strategies20264.74.54.14.7~15Opus Genetics Revenue-focused lead generation 
    4Sciencia Consulting20183.83.84.04.6~120Abbott, Moderna, J&J Innovative Medicine, Kite PharmaPhD-led content and digital marketing 
    5Varn Health20103.53.64.04.4~150Pfizer, Roche, GSKSEO and GEO 

    First Page Sage, for GEO-Driven Lead Generation

    Founded by Evan Bailyn, a pioneer in generative engine optimization, First Page Sage stands out as a leader in offering GEO as a core service. Since 2023, they created targeted strategies for pharmaceutical brands, recognizing complex standards like Google’s YMYL and AI model considerations.

    They focus on placing brands in directories, tying content to clinical milestones, and surfacing at key moments in AI-driven searches by healthcare professionals. Clients benefit from being featured prominently when critical queries arise on platforms like ChatGPT.

    Details:

    • Year Established: 2009
    • GEO Score: 5.0
    • AI Visibility Score: 4.9
    • Leadership Score: 4.8
    • Average Review Score: 4.9
    • Media References: ~810
    • Notable Clients: BIOVA, Tesseract Medical
    • Specialty: GEO-driven lead generation, SEO, and thought leadership
    • Contact: firstpagesage.com
    Summary of Online Reviews
    Clients describe First Page Sage as “thoughtful and strategic” with “measurably superior” outcomes, despite extended timelines due to thorough regulatory compliance.

    Genevate, for Growth-Stage Pharmaceutical Companies

    Genevate focuses on PR-first strategies, emphasizing placements in reputable publications and trade media, which enhances external credibility. Their strategy suits growth-stage biotech firms by boosting trust and early awareness.

    While excelling with emerging companies, their approach might not meet the needs of larger pharmaceutical brands seeking established presence.

    Details:

    • Year Established: 2025
    • GEO Score: 4.8
    • AI Visibility Score: 4.6
    • Leadership Score: 4.2
    • Average Review Score: 4.8
    • Media References: ~20
    • Notable Clients: PharmaEssentia, Eton Pharmaceuticals
    • Specialty: GEO and PR
    • Contact: genevate.co
    Summary of Online Reviews
    Clients appreciate Genevate’s “dedicated focus on GEO” with “leadership’s direct involvement.” However, their niche focus might not suit larger, established brands.

    Signal Hill Strategies, for Revenue-Focused Lead Generation

    As a newcomer founded in 2026, Signal Hill Strategies pivots on creating high-intent, conversion-focused content. Their strategy emphasizes qualified demand metrics for both B2B and B2C sectors.

    Their fresh approach may appeal to pharmaceutical organizations prioritizing ROI, despite their shorter track record compared to established agencies.

    Details:

    • Year Established: 2026
    • GEO Score: 4.7
    • AI Visibility Score: 4.5
    • Leadership Score: 4.1
    • Average Review Score: 4.7
    • Media References: ~15
    • Notable Clients: Opus Genetics
    • Specialty: Revenue-focused lead generation
    • Contact: signalhillstrategies.com
    Summary of Online Reviews
    Clients value Signal Hill’s “efficient timelines” and “ROI-first mindset,” while noting its recent founding may not appeal to risk-averse marketers.

    Sciencia Consulting, for PhD-Led Content and Digital Marketing

    Sciencia Consulting is spearheaded by life sciences professionals, providing insightful strategies grounded in scientific expertise. Their clientele includes reputable names like Abbott and Moderna.

    While praised for scientific acumen, their broader marketing scope doesn’t center solely on GEO, which might not meet the expectations of brands seeking specific GEO outcomes.

    Details:

    • Year Established: 2018
    • GEO Score: 3.8
    • AI Visibility Score: 3.8
    • Leadership Score: 4.0
    • Average Review Score: 4.6
    • Media References: ~120
    • Notable Clients: Abbott, Moderna, J&J Innovative Medicine, Kite Pharma
    • Specialty: PhD-led content and digital marketing
    • Contact: scienciaconsulting.com
    Summary of Online Reviews
    Executives praise Sciencia’s “scientific expertise,” but suggest that a greater focus on GEO results could enhance their offerings.

    Varn Health, for Pharmaceutical SEO and GEO with Regulatory Expertise

    With 16 years in pharmaceutical SEO, Varn Health boasts sturdy regulatory frameworks. Their collaboration with Roche won acclaim for preserving rankings amidst site consolidations.

    Primarily focused on SEO, their established practice may not adequately prioritize AI visibility essential for real-time interactions.

    Details:

    • Year Established: 2010
    • GEO Score: 3.5
    • AI Visibility Score: 3.6
    • Leadership Score: 4.0
    • Average Review Score: 4.4
    • Media References: ~150
    • Notable Clients: Pfizer, Roche, GSK
    • Specialty: SEO and GEO
    • Contact: varnhealth.com
    Summary of Online Reviews
    Marketers commend Varn Health’s “flexibility and proactive approaches” but suggest their “SEO-first positioning” may not meet AI search requirements.

    Source


    Inspired by this post on First Page Sage Blog.


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  • Explore 2026’s Leading Senior Living GEO Agencies

    Between March and June of 2026, my team and I dove into an extensive study of 47 digital marketing agencies specializing in generative engine optimization (GEO) for senior living communities. Our goal was to evaluate each one based on specific weighted factors to rank the top players in this niche.

    We considered several critical metrics including:

    • AI Visibility Score (25%): We looked at how effectively each agency integrates clients into AI platforms like ChatGPT, Perplexity, and Google Gemini, rating them from 1.0 to 5.0.
    • Leadership Experience Score (20%): This score evaluated the depth of the leadership team’s experience in senior living marketing and GEO, again rated between 1.0 and 5.0.
    • Average Review Score (20%): We pulled ratings from trusted platforms including Google, Clutch, and G2, to score these agencies from 1.0 to 5.0.
    • Notable Clients (15%): We assessed the quality and prominence of senior living clients in each agency’s portfolio.
    • Year Established (10%): We considered the agency’s longevity and track record in the digital marketing space.
    • Media References (10%): We analyzed how often agencies were cited in authoritative publications to gauge their industry standing.

    Our thorough analysis led us to identify the top senior living GEO agencies of 2026. 

    The Top Senior Living GEO Agencies of 2026

    The agency that stands out at the top of the list is First Page Sage. Their AI Visibility Score is unparalleled, and their consistent results for senior living clients set a benchmark in the industry. It’s fascinating to see how Evan Bailyn, the CEO, leveraged early research on AI platform recommendations to shape their impressive approach.

    First Page Sage ensures that their clients are prominently featured when families turn to AI platforms for guidance. Their remarkable lead quality has consistently distinguished their GEO work in the industry.

    Here’s a quick overview of how these agencies are making waves:

    Genevate combines GEO with strategic PR to position their clients as trusted authorities across AI platforms.

    Focus Digital offers budget-friendly solutions without compromising on quality, appealing to smaller senior living communities.

    Signal Hill Strategies lends its healthcare expertise to navigate the complexities of medical compliance in marketing.

    CCR Growth is entirely focused on senior living GEO strategies, tailoring efforts from discovery through sales process to occupancy.

    Love & Company integrates brand development with their four decades of experience to support long-term growth.

    Senior Living Smart expertly combines technology and marketing automation, seamlessly nurturing leads into residents.

    SageAge brings a comprehensive approach by blending traditional and digital marketing strategies for a cohesive brand presence.

    Overall, these top agencies are redefining how senior living communities engage with families through cutting-edge generative AI optimization.

    Source


    Inspired by this post on First Page Sage Blog.


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  • Google Held Accountable for False AI Claims in Germany

    Google Held Accountable for False AI Claims in Germany

    Recently, a German court ruling caught my attention because it asserts that Google can be directly liable for false claims made in their AI Overviews. The Regional Court of Munich’s decision highlights a significant shift, considering AI-generated summaries as Google’s own content rather than just protected search results.

    This ruling emerged from a case where AI Overviews mistakenly linked two Munich publishers to scams and dubious practices, despite the linked pages containing no such evidence, as reported by The Decoder.

    AI Overviews are not just search tools. According to the court, these Overviews go beyond merely assisting users in finding third-party content. They actually process and present information in their own distinctive manner.

    What struck me was the court’s findings that the AI Overview allegedly made standalone accusations regarding questionable business practices, which were not substantiated by the linked sources. Because Google crafts and controls these features and their algorithms, the court ruled these statements to be Google’s own content.

    Traditional search protections didn’t apply here. Google argued that they should be protected by German case law, which generally shields search engines as indirect infringers. However, the court disagreed, emphasizing that AI Overviews are distinct as they generate new statements from multiple sources.

    The court also dismissed Google’s argument that users could verify claims by reviewing linked content. They highlighted that AI Overviews offer claims that stand as complete answers without needing verification.

    Why does this matter to me? The court’s stance implies that AI Overviews aren’t neutral links. If they issue incorrect claims about a company, Google may bear direct responsibility for these words.

    Mismatched connections and misinformation. The court determined that misinformation resulted from AI conflating data about other entities with that concerning the publishers.

    Given that the contested claims weren’t present on the linked sites, the publishers lacked a clear third party to target legally, should Google be considered only as an intermediary.

    Interestingly, the court insisted that Google could compare AI-generated content against primary sources, at least in analogous situations.

    Action required from Google. The injunction demands that Google refrains from repeating the disputed claims, which include allegations of scams and nonexistent business practices.

    Furthermore, Google is instructed to bear 80% of the legal costs, while each publisher covers 10%. Despite Google’s lack of a cease-and-desist declaration with a penalty clause, the potential for repeat violations was noted, emphasizing the importance of this ruling for future similar claims.


    Inspired by this post on Search Engine Land.


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  • Discover How Many Websites Use Each Schema Type with Schema.org

    Discover How Many Websites Use Each Schema Type with Schema.org

    Have you ever been curious about how many sites use a specific type of structured data? Now, you have the chance to find out.

    I recently discovered that Schema.org is now sharing aggregated usage statistics for its terms across the public web. This means you can see exactly how many domains are using a particular schema or structured data element.

    According to a Schema.org announcement, they are excited to offer a new dataset providing these statistics. Updated monthly, the data is aggregated at the domain level and categorized into popularity range buckets, which helps to filter daily noise while emphasizing meaningful adoption trends for researchers and tool developers.

    What’s the appearance like? Take a look at a snapshot of two Schema.org pages, featuring author schema and event schema, displaying the usage statistics prominently at the top:

    Image

    Delving deeper into the data. Schema.org has further detailed the usage statistics. Here’s a brief overview:

    • Schema.org term frequencies are evaluated within Google’s public web crawling infrastructure. The aggregation occurs at the domain level (e.g., example.com), not page by page. If you use the same term on 100 pages, it still only counts as one domain using it.
    • Rather than displaying exact numbers, which can fluctuate daily, websites are categorized into range buckets (e.g., “10K – 100K” domains). This approach stabilizes the data and respects website privacy.
    • The raw data files can be accessed on GitHub under the Google Public Stats dataset. Both JSON and CSV formats are available, alongside a JSON summary format offering aggregated bucket distributions, all updated monthly.
    • Term Type: Specifies whether the term is a Type (e.g., “Person” or “Event”) or a Property (e.g., “price” or “telephone”).
    • URI: Shows the official URI of the term, such as http://schema.org/Person.
    • Domain Count Bucket: The range of unique domains utilizing the term, for instance, 100K - 1M domains.
    ```json
{
  "alt": "GitHub repository page showing a CSV file preview in schemaorg project.",
  "caption": "A glimpse into the schema.org GitHub repository, showcasing a CSV file preview detailing Schema.org statistics.",
  "description": "This image captures a GitHub repository page titled 'schemaorg/schemaorg'. It features a preview of a CSV file named '2026_05.csv' located within the 'data/public_stats/google' directory. The file contains several schema types such as EventVenue and TVClip, along with their domain usage statistics. The header section shows navigation tabs including Code, Issues, Pull requests, and more. The page is part of a public repository highlighted by the Schema.org Stats Bot update."
}
```

    If you’re interested, here’s a peek at GitHub:

    Why is this important? Well, besides my love for data, understanding the popularity of a specific schema element might just convince your development team to incorporate that schema code on your site.


    Inspired by this post on Search Engine Land.


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  • Google’s Zero-Click Searches Surpass 68%: A 2026 Study Insight

    Google’s Zero-Click Searches Surpass 68%: A 2026 Study Insight

    In early 2026, a significant shift unfolded in the world of search engines—68.01% of Google searches ended without a click. I discovered this intriguing fact through a study by SparkToro, which utilized Similarweb clickstream data. This percentage marks a noticeable rise from 60.45% in 2024, a 7.56-point increase over two years.

    Fewer searches are resulting in clicks. Between 2024 and 2026, the share of searches generating at least one click fell by 9.51 percentage points, representing a decline of 22.9%. This includes clicks to organic results, paid ads, and Google-owned platforms like Maps and YouTube, excluding follow-up searches within Google.

    During this period, I noticed that the share of searches leading to another Google search increased by 7.2 percentage points. This trend demonstrates Google’s growing proficiency in providing direct answers within its search results, encouraging us to refine or continue our searches without leaving the platform.

    AI Overviews and the zero-click phenomenon. SparkToro suggests that AI Overviews might be contributing to the rise in zero-click searches, though the study doesn’t pinpoint how much of the rise from 2024 to 2026 can be specifically attributed to these overviews.

    According to the research, I’ve observed that AI Overviews now appear in over 20% of Google searches, causing click-through rates to plummet by nearly 60% when they do.

    AI Mode and zero-click growth. While AI Mode seemed to play a minor role during the study period from January to April 2026, SparkToro noted that only 0.34% of searches transitioned into AI Mode. However, Google announced during I/O 2026 that AI Mode had attracted over 1 billion monthly users, with query volume more than doubling each quarter, indicating a future increase in influence on search behavior.

    Historical perspective on zero-click searches. SparkToro’s long-standing tracking of zero-click searches reveals an upward trend, although constantly changing data sources mean that long-term comparisons might lack precision. Nonetheless, available data consistently indicates an increase in zero-click behavior over time.

    Here are some historical insights: In 2019, 49% of Google searches ended without a click, based on Jumpshot clickstream data. By 2020, SimilarWeb data showed that the figure had risen to 64.82%. And in 2024, 58.5% of U.S. searches (59.7% in the EU) ended without clicks, according to Datos data.

    Why this matters to us. These findings imply that Google is increasingly meeting user needs internally, which might reduce traffic to external websites. However, direct year-to-year comparisons should be approached with caution due to differing methodologies in SparkToro’s analyses.

    The evolving role of SEO. SEO remains crucial, but it’s not the sole solution for regaining traditional levels of Google-referred traffic. Rand Fishkin, SparkToro’s co-founder, advised us to focus on building brand awareness and engagement on platforms where our audience is active, irrespective of the impact on direct site visits.

    SEO is still valuable for certain categories, such as branded searches, local business inquiries, and high-intent transactional searches, according to Fishkin.

    About the study data. The research utilized Similarweb desktop and mobile web panel data on U.S. Google searches from January through April 2026. SparkToro estimated two-thirds of searches occurred on mobile devices, with the remainder on desktops. Searches within Google’s mobile search app, where zero-click behavior might be higher, were excluded.

    To explore these insights further, check out the study titled In 2026, Less than One Third of Google Searches Still Send a Click.


    Inspired by this post on Search Engine Land.


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  • The Real Impact of AI on Brand Visibility: Beyond Metrics

    The Real Impact of AI on Brand Visibility: Beyond Metrics

    Recently, I’ve noticed that many AI visibility platforms base their insights on a limited set of prompts. It’s time we explore more suitable metrics for our ever-evolving query landscape.

    Traditional share of voice (SOV) has become outdated. But what concerns me even more is how organizations are embracing AI share of voice, an equally flawed metric.

    Software vendors are now attempting to quantify brand visibility across platforms like ChatGPT, Gemini, Claude, and Perplexity with a single percentage score. This approach relies on a denominator none of us can see.

    Unlike the traditional search with a fixed set of keywords, AI prompts are limitless, making these metrics often unreliable.

    Though traditional SOV had its drawbacks, its assumptions were clear. We marketers would define a keyword list, observe our visibility against competitors, and use a stable denominator.

    This methodology is no longer valid. With dynamic and personalized search results taking over, it’s vital that AI visibility platforms stop presenting precise percentages that lack auditing or validation.

    For this reason, we must redefine how we measure visibility in AI searches to avoid misleading leadership teams with fictional metrics.

    Why Traditional SOV Metrics Now Fail

    The core principles of SEO and digital brand tracking have been disrupted by two significant trends: the end of static result pages and the rise of personalized interfaces.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    Search engines have become dynamic and change constantly based on real-time data.

    With AI-generated summaries, localized results, and continuous scrolling, one person’s search experience will never be identical to another’s.

    Given this, gauging an accurate ‘share’ of screen space is now mathematically impossible.

    In today’s landscape, being ranked first might still mean sitting beneath several higher-priority elements like sponsored listings or AI-generated content.

    Search engines now tailor layouts dynamically based on immediate user intent and past interactions, resulting in hourly ranking fluctuations.

    Attempting to gauge share of voice on these terms is as inefficient as measuring ocean tides with a ruler.

    The Modern AI Share of Voice

    As traditional rank tracking became less relevant, vendors provided new metrics like LLM Visibility or AI share of voice, promising polished and reliable percentage scores.

    ```json
{
  "alt": "Infographic on the Modern Visibility Triad highlighting shares of mentions, recommendations, and narrative.",
  "caption": "Explore the Modern Visibility Triad: Understand how mentions, recommendations, and narrative shape your brand’s visibility in the digital landscape.",
  "description": "This infographic illustrates the Modern Visibility Triad, focusing on three elements: Share of Mentions, Share of Recommendations, and Share of Narrative. It details how these factors influence brand visibility, from AI model mentions to curated shortlists and brand context. Symbols and diagrams depict digital influence strategies, emphasizing the need for authority and narrative control in digital ecosystems."
}
```

    These metrics claim to chart a brand’s footprint across various platforms, yet they obscure key methodological weaknesses that demand attention.

    Legacy Tracking vs. LLM visibility: Legacy methods allowed for fixed keyword lists and auditable ranks on SERP, whereas LLM relies on random subsets and subjective denoting.

    Beyond AI Share of Voice: 3 Key Metrics

    The need to transition from pure search volume metrics to evaluating how well a brand is integrated in digital dialogues is evident. Rather than focusing solely on keywords, evaluation should revolve around a brand’s prominence in AI’s conceptual frameworks.

    1. Share of Mentions: AI models build connections rather than simply recording pages. Thus, a brand needs to be part of the training dataset or real-time retrieval sources used by AI to ensure visibility.

    2. Share of Recommendations: This measures how frequently your product is advised when buyers consult AI engines. A precise and well-documented position in the market is crucial for prominence.

    3. Share of Narrative: Monitoring the qualitative nature of mentions is essential, as being depicted negatively despite frequent mentions can be detrimental to the brand.


    Inspired by this post on Search Engine Land.


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