Tag: AI Search

  • Boosting Brand Authority: The Key to Winning in AI Search

    Boosting Brand Authority: The Key to Winning in AI Search

    I’ve discovered a fascinating truth about search in the age of AI: brand authority often outshines topical authority. The landscape of search has shifted, and it’s time for us to adapt.

    While topical authority remains a beloved concept among SEO consultants pitching content, brand authority holds the reins in today’s AI-driven search landscape. Marketers have long discussed brand authority, though it was often dismissed or left to brand teams post-sitemap adjustments.

    AI’s emergence has upended the traditional approach, revealing underlying issues. Search is crucial for the global economy, and the industry’s marketing approach needs re-examination. More content doesn’t automatically confer authority. In fact, AI search champions brands gaining notable visibility, mentions, and real demand.

    Too many SEOs overlook the reasons people choose, trust, and remember brands. In this new world of AI search, such ignorance stands out even more. That’s why brand authority prevails—but not in the way our typical SEO tools might suggest.

    Previously, the meaning of topical authority was intended to highlight genuine expertise through useful work, citations from others, and a growing associated reputation. This builds your brand’s association with a topic, which in turn, creates authority and fosters brand development.

    However, the industry often marketed topical authority commercially, emphasizing volume over value. Technical SEO became a niche, links were outsourced or repackaged, but content was the consistent agency engine.

    Pre-AI, this made sense. Creating good content involved rigorous processes and offered substantial value, earning rankings and supporting commercial interests. In contrast, topical authority introduced the misguided idea that mere keyword coverage equated to expertise, diluting the concept’s original intent.

    Another intriguing aspect of authority is understanding what others say about you, rather than solely focusing on self-published content. Google’s Jun Wu highlighted the importance of ‘mention information’—how search engines discern topics, identify sources, and map relationships.

    Our modern term for this is brand co-occurrence. Being consistently mentioned by authoritative sites and communities solidifies your brand’s association with a topic, elevating market perception and authority.

    ```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."
}
```

    Many might pitch the concept of topical authority as building a comprehensive keyword strategy, but actual authority requires originating valuable data and sharing insights that engage audiences and capture media attention.

    The changing economic landscape of AI means that traditional advertising methods through content must evolve. With AI offering direct answers, the value of certain traditional SEO practices is diminishing. Users, like my AI-liking father, prefer quick, synthesized information over cumbersome web browsing.

    The rise of AI citations in search metrics has become a focus, but they differ from authentic human endorsements. Real influence is reflected through human testimonies, where your brand is discussed, cited, and recommended.

    If measuring brand authority, brand searches present a clearer indicator of growth. If more people search specifically for your brand, it signals rising demand and market presence—a more accurate reflection of impact than solely relying on AI citations.

    Traditional SEO still plays a role, ensuring you’re found where it matters—be it in search rankings or marketplaces. Yet, brand authority distinctly drives recommendations, and AI search is starting to favor consolidated options, often mentioning specific brands and solutions.

    The future echoes the demand for meaningful engagement and widespread brand visibility. Though SEO isn’t dead, a simplistic keyword-centric approach is fading. A holistic approach integrating positioning, PR, reviews, and content as interconnected elements is pivotal.

    In an era where fitness and visibility are equal determinants of success, brands must excel in products and services while ensuring their market presence is robust and omnipresent. After all, brand authority is what truly wins, confirming that mediocrity no longer warrants attention.


    Inspired by this post on Search Engine Land.


    crushpress.ai community screenshot
  • Discover the Power of AI with Ask Profound: Your Data’s New Best Friend

    Discover the Power of AI with Ask Profound: Your Data’s New Best Friend

    I’m thrilled to introduce Ask Profound, an exciting feature for Profound customers. Now, you can engage directly with your AI Search data, transforming how you interact with your information.

    Imagine having a dynamic conversation with your data, receiving insights and answers more efficiently than ever. This innovative tool is designed to enhance your data experience, making it more intuitive and personal.

    Whether you’re a data analyst, business strategist, or just someone who values data-driven decisions, Ask Profound is here to make your life easier by turning complex data into clear and actionable insights.

    Join me in exploring this new era of data interaction where AI bridges the gap between information and understanding. Dive into a smarter way of managing your data with Ask Profound!


    Inspired by this post on Try Profound Blog.


    crushpress.ai community screenshot
  • Why AI Searches Differ: Insights from ChatGPT and Beyond

    Why AI Searches Differ: Insights from ChatGPT and Beyond

    Whenever I type a question into an AI engine, I’ve noticed that the engine doesn’t just search for the exact words I typed. Instead, it explores a broader spectrum of possibilities. This behavior intrigues me.

    Recently, I came across a fascinating study by Profound. They monitored 10,000 prompts across various AI platforms like ChatGPT, Copilot, and Perplexity over two weeks. The findings highlighted remarkable differences in how these AI engines search and process queries.


    Inspired by this post on Try Profound Blog.


    crushpress.ai community screenshot
  • Can A Fictional Brand Outsmart AI? Our Surprising Experiment!

    Can A Fictional Brand Outsmart AI? Our Surprising Experiment!

    In late 2024, I embarked on an eye-opening 16-month journey with SE Ranking’s research team to test the performance of AI-generated content in organic search. We launched 20 diverse websites, eagerly tracking their progress.

    But my curiosity didn’t end there. I was driven to comprehend how AI systems find, process, and use information. This inspired me to expand our project and delve deeper into AI search and LLM visibility experiments.

    In our next phase, we boldly created a fictional brand and inserted it into a real, competitive niche. Our aim? To see how fast AI would catch on and if our make-believe brand could stand toe-to-toe with industry giants and governmental sources.

    After just one month, enlightening patterns began to emerge.

    Methodology behind the experiment

    I crafted a fictional brand and dispersed content across various platforms:

    • A fresh website exclusively for the brand, registered specifically for this daring experiment.
    • 11 seasoned domains, each over a year old with a solid history and existing rankings.

    I experimented with seven different content formats:

    • Comprehensive guides.
    • “Alternatives” listicles.
    • “Best of” listicles.
    • Review articles.
    • Comparative (“vs”) pages.
    • How-to/tutorial content.
    • Clickbait-style articles.

    Kicking off in March 2026, I monitored five AI systems: ChatGPT, Google’s AI Overviews, Google’s AI Mode, Perplexity, and Gemini, tracking 825 prompts and generating 15,835 AI answers during the initial month.

    For every prompt, I considered:

    • Our brand’s appearance in AI responses.
    • Its recognition as a source.
    • Frequency of being the main cited source (position 1).

    This ongoing experiment was initially designed to observe AI systems’ reactions to freshly created, fictitiously branded information.

    Key experiment insights

    • 96% of our brand’s AI visibility stemmed from branded searches. Even in a low-competition niche, a new domain struggled to compete on non-branded topics.
    • For niche-specific queries, our brand outshined well-established competitors by up to 32 times, achieving dominant visibility in under 30 days.
    • Despite lacking authority, clearly articulated identity pages, like “[Brand Name] Complete Guide” and “About Us”, became frequently cited, highlighting the importance of brand positioning in AI.
    • Perplexity surfaced new content swiftly, often citing additional domains over the main site.
    • Google’s AI Mode offered stability on branded queries.
    • Gemini struggled with brand identification, resulting in 60% of responses without our brand’s citation for uniquely branded queries.
    • Deep guides, review articles, and comparison pages gained the most citations, while generic content saw minimal impact.
    • A hub page with 10 supporting articles yielded no citations, whereas shorter, repetitive pages garnered over 1,800 citations, emphasizing the power of high-volume content publishing.

    A new site struggles to compete broadly initially. However, our fictional brand quickly gained traction through branded queries, largely because these were the focus points.

    Of all AI answers, a staggering 96% came from branded searches alone, reiterating the crucial role of brand-specific queries in early visibility.

    This mirrors traditional SEO patterns where new brands must first build trust and recognition.

    My key takeaway for marketers was clear: AI systems are inclined to use your site as a primary information source during your brand’s formative years.

    This insight was reinforced as pages consolidating brand information, such as the “Complete Guide” and “About Us”, became the primary sources cited from our main domain.

    Therefore, shaping the brand narrative early on AI platforms is crucial, even for emerging brands.

    Insight 2: AI engines behave very differently

    Our experiment shed light on the unique behaviors of five AI systems in indexing and presenting our fictional brand.

    Google’s AI Mode: The most stable for branded visibility

    Google’s AI Mode proved to be a reliable ally, consistently putting our brand at the top for around 90% of branded queries.

    It was the bastion of predictable brand visibility in our experiment.

    Google’s AI Overviews: High visibility, lower consistency

    Though less consistent, Google’s AI Overviews provided notable brand visibility. Yet, fluctuations and temporary drops were observed during our test period.

    Whenever links were absent, visibility suffered, highlighting the need for sustained link presence.

    Perplexity: The fastest to pick up new content, but not always brand-first

    Perplexity swiftly indexed new content, quickly boosting early visibility.

    However, its affinity for additional domains over the main brand site complicated content attribution in AI responses.

    ChatGPT: Slower to react, stronger over time

    ChatGPT gradually improved recognition of our brand, with a notable increase in visibility over March.

    Notable growth occurred in unique claims and comparisons (“vs”), showcasing ChatGPT’s potential for longer-term brand assimilation.

    Gemini: Weakest performance and most inconsistent behavior

    Gemini presented challenges with niche recognition, improving only when framing prompts appropriately.

    Despite effort, results remained inconsistent, with significant citation gaps on brand-specific queries.

    Insight 3: Content format matters, but so does the volume

    Through diverse content experimentation, we found in-depth articles earn the most AI citations.

    Comprehensive guides, reviews, and comparisons outperformed simpler formats, reinforcing the power of detailed content presentation.

    The volume of content also played a role. Although the individual performance was low, 30 shorter pages collectively generated impressive AI visibility.

    This doesn’t diminish the value of quality but indicates a large amount of content can boost overall reach.

    Insight 4: Topical clustering alone doesn’t produce AI visibility

    Our structural tests revealed that topical clustering, without substantial content, didn’t boost AI visibility.

    It challenges the notion that clustering inherently strengthens authority, stressing the importance of standalone content value.

    Though structured linking offers insight into site understanding, AI systems prioritize the need for direct and valuable information retrieval.

    So, do AI engines reward entity coherence more than truth verification?

    Our first month’s results point to a significant insight: AI systems value availability and consistency over strict truth verification.

    Though not all-reaching, well-structured, repeated, and available content can be surfed with surprising ease.

    This phenomenon was observed during manual checks where even a fictional brand received favorable recommendations due to consistent narratives.

    It’s not simply LLMs favoring new brands, but where gaps exist, even limited information may be built up positively.

    Final thoughts

    The true revelation isn’t the visibility of a fictional brand. Rather, it’s how visibility aligns with brand-centric inputs like unique claims and varied content.

    This leads to pivotal conclusions:

    • AI search isn’t arbitrary. It responds to discernible and influenceable signals.
    • AI remains vulnerable to manipulation. Without inherent truth-checking, strategies used by legitimate brands can simulate credibility.

    Illuminating the need for active narrative shaping, our experiment urges businesses not to rely on AI systems to innately capture accurate brand representation.

    We’re committed to expanding and monitoring these insights over time, as we collect ongoing data.


    Inspired by this post on Search Engine Land.


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  • Navigating SEO in the Age of AI: A Personal Guide

    Navigating SEO in the Age of AI: A Personal Guide

    SEO is evolving, but it’s certainly not disappearing. In my journey through the changing landscape, I’ve found that blending traditional SEO techniques with emerging AI search practices is crucial for staying ahead.

    SEO is at a fascinating juncture. On one side, there’s a push to optimize for AI and large language models (LLMs), while on the other, some want to stick to the tried-and-true methods. I’ve found a middle path — merging core SEO principles with an awareness of LLMs and their operations.

    Embracing this approach means holding onto effective strategies like on-page SEO and quality backlinks while also exploring new avenues such as optimizing for query fan-out and new prompt intents. Since the rise of tools like ChatGPT, my research has focused on how AI engines present search results and the future direction of SEO.

    ```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."
}
```

    Here’s what I’ve learned and how you can adjust your strategy to consider human behavior at the forefront of SEO innovations.

    The Red Queen evolutionary model suggests that we must constantly adapt to maintain our position; if we don’t evolve, we risk falling behind. This is exactly the case in the world of AI and SEO — stand still, and you’ll be left behind.

    ```json
{
  "alt": "Recommended anti-aging products list with descriptions and ratings.",
  "caption": "Explore top-rated anti-aging skincare products curated for their efficacy. See expert picks to keep your skin youthful and glowing.",
  "description": "This image presents a recommended list of anti-aging skincare products with detailed descriptions, prices, and ratings from various beauty retailers. Featured items include SkinCeuticals C E Ferulic, CeraVe Resurfacing Retinol Serum, Estee Lauder Advanced Night Repair Overnight Treatment, and Clarins Double Serum. Each product is accompanied by user reviews and star ratings, providing insights into their popularity and effectiveness. Keywords: anti-aging, skincare, product recommendations, beauty reviews."
}
```

    As you and your competitors adapt, you must maintain your competitive edge. In SEO, failing to adapt means losing visibility and influence.

    How to apply the Red Queen principle to your AI SEO strategy

    The evolution of AI search is a continuation of developments over the past decade. With concepts like RankBrain since 2015, familiar SEO tactics remain relevant. This isn’t about a complete overhaul but rather a series of adaptations and improvements.

    ```json
{
  "alt": "Screenshot discussing February 2026 as a favorable time for home buyers due to low mortgage rates and rising inventory.",
  "caption": "Considering buying a house? February 2026 is predicted to be ideal for buyers with low mortgage rates, a surplus of sellers, and increased inventory!",
  "description": "This image highlights a favorable housing market forecast for February 2026, emphasizing low 30-year fixed mortgage rates averaging 5.87% to 5.98%. With 44% more sellers than buyers, the market provides strong negotiating leverage. An increase in listings by over 10% year-over-year reduces bidding wars, and stable home prices (0.9% to 1.2% growth) prevent significant spikes. Relevant sources include Redfin and Freddie Mac."
}
```

    Core elements like retrieval-based search engines, content quality, speed, and intent matching are as important as ever. By focusing on these, alongside optimizing for AI retrieval and third-party visibility, you position yourself favorably.

    One effective way I’ve discovered to engage with AI search is by understanding its limitations, particularly their reliance on retrieval-augmented generation (RAG) systems. RAG helps fill the gaps in LLM databases without constant updates, ensuring relevant answers are provided.

    ```json
{
  "alt": "February 2026 snapshot of the U.S. housing market trends and forecasts.",
  "caption": "Explore the latest trends in the U.S. housing market for February 2026, including mortgage rates and buyer-seller dynamics.",
  "description": "This image presents a February 2026 overview of the U.S. housing market. It features articles from the Financial Times, Reuters, and New York Post detailing recent mortgage rate changes, construction trends, and market dynamics. Key highlights include mortgage rates hitting the lowest since 2022 and a notable gap with more home sellers than buyers. This image serves as a guide for potential homebuyers evaluating current market conditions."
}
```

    In practice, this involves seeing how AI tools like Google AI Mode and ChatGPT respond to prompts and identifying where they draw their information. Using this insight, you can ensure your content is part of the external sources AI assists rely upon.

    Understanding how your content interacts with AI engines’ limitations is critical. AI does its own searching and then provides answers, sometimes without showcasing external sources. Therefore, becoming a trusted source for LLMs is the key to SEO in the AI era.

    ```json
{
  "alt": "Makeup products for Gen Z, including Rare Beauty blush, Morphe face trio, and NYX lip oil.",
  "caption": "Discover trending makeup gifts perfect for Gen Z! Featuring Rare Beauty's blush, Morphe's face trio, and NYX's vibrant lip oil.",
  "description": "This image showcases top makeup and beauty gift ideas ideal for Gen Z, featuring three products: Rare Beauty Soft Pinch Liquid Blush ($25.00), Morphe Cheek Thrills Multi-Finish Face Trio ($19.00), and NYX Professional Makeup Fat Oil Lip Drip ($10.00). These products, highlighted for their trendy appeal and versatility, are available at Ulta Beauty and other retailers. The selection emphasizes lightweight, buildable, and vibrant aesthetics that appeal to modern Gen Z preferences."
}
```

    It’s essential to analyze AI answers, understand their behavior, and continuously evaluate their preferences. By feeding these systems with quality data, we can ensure we’re among the go-to trusted sources AI assistants reference.

    The long-term future of SEO relies on human behavior

    Long-term SEO strategies should remain focused on understanding human behavior. This involves pinpointing search intent and analyzing how AI-generated queries align with different user needs and intents.

    ```json
{
  "alt": "Search results for best makeup gifts for Gen Z, highlighting viral products from Rare Beauty, Rhode, and Fenty Beauty.",
  "caption": "Explore the top makeup gifts for Gen Z! Featuring viral products from Rare Beauty, Rhode, and Fenty Beauty, these selections promise high performance and trendy appeal.",
  "description": "The image displays search results for the best makeup gifts for Gen Z. It highlights popular products like the Rhode Peptide Lip Tint and Rare Beauty Soft Pinch Liquid Blush. Brands such as Rare Beauty, Rhode, and Fenty Beauty are emphasized for their appeal to Gen Z, focusing on high-performance formulas and 'glass skin' effects. The section also mentions TikTok's influence on beauty trends. Keywords: makeup gifts, Gen Z, Rare Beauty, Rhode, Fenty Beauty, TikTok trends."
}
```

    Being successful means considering both traditional search intents and new AI-induced intents to provide valuable content that resonates with user needs. It’s about dynamically adapting approaches based on observed behavior and striving to stay ahead in this ever-evolving field.


    Inspired by this post on Search Engine Land.


    crushpress.ai community screenshot
  • Mastering AI Search Visibility: Key Signals You Need to Know

    Mastering AI Search Visibility: Key Signals You Need to Know

    I’ve discovered that rankings alone no longer guarantee visibility in AI search. In today’s digital landscape, four key signals dictate whether a brand appears in AI-generated responses and how they’re portrayed.

    Ranking and visibility have diverged. For years, SEO was all about securing that sweet spot on the SERPs, boosting visibility, clicks, and traffic. This connection is unraveling.

    Earlier this year, Ahrefs reported that only 38% of pages featured in Google AI Overviews also ranked in the traditional top 10. Compare this to eight months prior when it was 76%, and you’ll see the shift.

    The message is clear: a high rank doesn’t necessarily mean visibility.

    Visibility in AI-generated responses hinges on inclusion and the portrayal of your brand upon inclusion, determined by a unique set of signals.

    So, how exactly does visibility work within the realm of AI search? There are four critical signals I need to focus on:

    ```json
{
  "alt": "Search result page highlighting best CRMs for startups including HubSpot, Pipedrive, and Attio.",
  "caption": "Explore the top CRM platforms for startups, featuring HubSpot, Pipedrive, and Attio, known for their scalability, ease of use, and affordability. Is your brand or resource listed?",
  "description": "This image showcases a Google search results page for 'what’s the best CRM for a new startup.' Featured CRMs include HubSpot, Pipedrive, and Attio, recommended for their functionality and cost-effectiveness. The page emphasizes considerations like affordability and ease of use, while highlighting resources from Reddit. Keywords: CRM, startup, HubSpot, Pipedrive, Attio, Google search."
}
```
    • Mention order.
    • Depth of explanation.
    • Authority signals.
    • Comparative positioning.

    Let me dive deeper into them, starting with mention order.

    The order in which AI models list options is crucial. According to a study by Growth Memo and Citation Labs, a whopping 74% of users tend to go with the AI’s top suggestion.

    Yet, 26% of users overturn the AI’s order if they recognize a brand they trust. This is quite a change from traditional search behavior. In AI Mode, most users accept the AI’s shortlist without further checks.

    However, the mention order is unstable. SE Ranking’s research shows AI Mode only overlaps with itself 9.2% of the time when running the same query thrice, indicating variable sources and order.

    Lesson learned: While mention order gives an edge, it’s not a sure thing. Brand recognition can surpass position.

    ```json
{
  "alt": "Four quadrants describing content relevance factors: Mention Order, Depth of Explanation, Authority Signals, Comparative Positioning.",
  "caption": "Boost your content's relevance! Explore how Mention Order, Depth of Explanation, Authority Signals, and Comparative Positioning enhance credibility and value.",
  "description": "This image is divided into four quadrants, each illustrating a factor that enhances the relevance of content. Mention Order notes that earlier mentions carry more weight. Depth of Explanation emphasizes comprehensive coverage for greater relevance. Authority Signals focus on citations and trust markers for credibility. Comparative Positioning underlines the importance of context and value clarification. These insights collectively aim at improving content strategy."
}
```

    Next, let’s explore the depth of explanation.

    Not every mention is equal. Some brands earn only a sentence, while others get full paragraphs detailing their strengths and uniqueness.

    This comes down to how much citation-worthy information AI systems have gathered about you.

    When Semrush launched its AI Visibility Awards in December 2025, it reviewed over 2,500 prompts using ChatGPT and Google AI Mode. Category leaders like Samsung in consumer electronics didn’t just show up more—they received more in-depth mentions.

    Challenger brands, like Logitech in gaming accessories, appeared too, but typically with shorter, focused mentions highlighting a single differentiator.

    ```json
{
  "alt": "Bar chart showing 74% of participants chose rank 1 items, compared to 10% for rank 3+ in AI mode.",
  "caption": "In a compelling AI study, the first choice dominated with 74% preference, leaving rank 3+ far behind at just 10%.",
  "description": "This image depicts a bar chart comparing choice rates in AI mode, where 74% of participants favored the first-ranked item, while only 10% selected items ranked third or lower. This visualization highlights the significant preference for top-ranked options in AI-derived responses. Source: Growth Memo / Citation Labs AI Mode Study."
}
```

    Pages that are comprehensive, answering “what is it,” “who uses it,” and “how to choose” in one place, rose to the top in AI citations.

    Lesson learned: If AI systems only find sparse data on your brand, expect sparse mentions.

    Third on the list: authority signals.

    AI systems not only cite but also characterize sources by tone, indicating how much confidence they place in a brand’s authority.

    HubSpot’s AEO Grader classifies brands as leaders, challengers, or niche players, labels influencing how AI conveys their authority.

    ```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."
}
```

    Semrush’s data shows that brands identified as leaders exhibit less than 20% monthly volatility in AI share of voice, maintaining consistent authority.

    Leaders are described using strong terms like “the industry standard,” while challengers are termed “gaining traction.”

    Lesson learned: AI doesn’t just name-drop; it frames your reputation.

    Finally, comparative positioning is akin to traditional rankings in AI answers—how you’re positioned among multiple brands.

    Amsive’s research demonstrates clear positioning hierarchies within sectors.

    ```json
{
  "alt": "Line graph comparing visibility scores of banks and credit unions, including Bank of America, SoFi, and JPMorgan Chase, dated June 2025.",
  "caption": "Explore the visibility scores of top banking institutions like Bank of America and JPMorgan Chase over a week in June 2025. See which financial giants are leading the digital arena!",
  "description": "This image displays a line graph titled 'Visibility Score Comparisons' by Profound, illustrating the visibility scores of banks and credit unions as of June 2025. The data compares entities like Bank of America, SoFi, LightStream, Capital One, and others, showing subtle fluctuations over several days. Bank of America leads with a score of 32.2%, while Upstart is at the lower end with 11.1%. The graph provides insights into the digital presence and performance of these financial institutions."
}
```
    • In banking, Bank of America leads, followed by SoFi and LightStream.
    • In healthcare, Mayo Clinic stands out significantly.

    Kevin Indig’s research highlights how users self-select based on AI’s framing, regardless of actual capabilities.

    Lesson learned: It’s not about being number one; it’s about owning a niche in AI’s mental map.

    Traditional rankings’ correlation with AI visibility is minimal. The concept of query fan-out explains why visibility dropped so swiftly.

    During an AI Overview, Google processes not just the top pages for a query but various sub-queries to synthesize a complete response.

    This means your page might rank first for one query but may be overlooked if AI finds more relevant passages elsewhere.

    ```json
{
  "alt": "Line graph showing Google's share of ChatGPT referral traffic from October 2024 to February 2026, displaying upward trend.",
  "caption": "Google's influence grows as its share of ChatGPT referral traffic rises steadily over time, peaking in early 2026.",
  "description": "This graph illustrates Google's share of total ChatGPT referral traffic, derived from Semrush US clickstream data between October 2024 and February 2026. The line graph, highlighted in purple, shows a general upward trend starting around mid-2025, reaching its highest point in early 2026. The chart provides insights into Google's impact on ChatGPT referral traffic over this period. Keywords: Google, ChatGPT, referral traffic, Semrush, clickstream data."
}
```

    Research shows Google’s Gemini 3 update altered approximately 42% of cited domains, making traditional rank positions less predictive.

    Where does AI traffic land? Interestingly, a substantial portion of ChatGPT traffic eventually ends up on Google. Users seek answers from ChatGPT, then confirm their findings on Google.

    Most prompts to ChatGPT are too specific for traditional keywords, intensifying the shift.

    So, how can I measure visibility in AI answers?

    • Track citation frequency to gauge how often your brand appears in AI answers.
    • Measure brand mention rate for category penetration.
    • Focus on recommendation rates, especially in B2B and high-consideration sectors.
    • Analyze sentiment and context of mentions to evaluate impact.
    • Citation position provides an edge, even if it’s not organic rank.

    The 2026 measurement model demands dual tracking—traditional and AI-focused metrics for accurate visibility insights.

    New tools have emerged for this purpose, complementing but not replacing traditional SEO tools.

    For citation tracking, platforms like Profound and Peec AI keep tabs on cited URLs across AI responses.

    For brand analysis, tools like Semrush’s AI Visibility Toolkit check mention frequency, portrayal, and recommendations.

    For competitive positioning, Bluefish and HubSpot’s AEO Grader assess your brand’s AI categorization against competitors.

    Traditional rank obsession persists, but visibility in AI requires a broader view with a distinct measurement model.


    Inspired by this post on Search Engine Land.


    crushpress.ai community screenshot
  • Explore YouTube’s New ‘Ask YouTube’ Conversational Search

    Explore YouTube’s New ‘Ask YouTube’ Conversational Search

    I’ve recently learned that YouTube is testing an innovative search feature called “Ask YouTube”. This aims to make searching on YouTube more conversational and interactive, just like Dave from YouTube explained. It deepens our interaction with content, allowing us to explore topics with more depth.

    What it looks like. I had the chance to see it in action through a captivating GIF:

    How can I try it? If, like me, you’re curious to test this feature, visit youtube.com/new. There, you can opt-in to experience this new way of interacting with YouTube.

    Currently, this experiment is only open to Premium users in the US who are 18 and older. However, Google has plans to expand access soon, which is promising for non-Premium users.

    ```json
{
  "alt": "Blank white image with no discernible features.",
  "caption": "A completely blank canvas—pure white and open to endless possibilities.",
  "description": "This image is entirely white, devoid of any visible features or markings. The blank nature of the image provides a neutral backdrop suitable for various uses. Ideal for design mockups, as a clean slate for digital artwork, or to be used as a minimalist element in creative projects. Keywords: blank, white, empty, neutral."
}
```

    What it does. Here’s an example shared by Dave from YouTube:

    “If you’re in the experiment, you can try it out by selecting “Ask YouTube” in the search bar. For instance, you might ask for help planning a 3-day road trip from San Francisco to Santa Barbara. Instead of just a list of videos, you’d receive a detailed, step-by-step itinerary. The response incorporates a mix of long-form videos, Shorts, and informative text, featuring local tips and must-see stops. You can even ask follow-up questions, like “where can I find good coffee?” to discover local gems along your journey. This approach surfaces various videos and video segments, complete with titles and channel details, making it easier to find new creators and content that matches your search.”

    Why we care. The integration of AI search is becoming prevalent in all Google platforms, and YouTube is joining this transformation. We should anticipate more AI-enhanced search experiences across various Google services as they evolve over time.

    For more insights and updates, you can check out detailed coverage on Techmeme.


    Inspired by this post on Search Engine Land.


    crushpress.ai community screenshot
  • Top AI Search Citations: Uncover the Dominant Domains

    Top AI Search Citations: Uncover the Dominant Domains

    Have you ever wondered which domains lead the way in the world of AI citations, specifically with giants like ChatGPT and Gemini? I’ve delved into a staggering 58.6 million AI citations to uncover the patterns and top-performing sites dominating this space. Join me as I share insights into these trends and explore strategies to boost your own citation share.

    The AI industry is bustling with innovation and adaptation. Identifying which domains stand out can give us valuable insights into the digital landscape’s future. Let me walk you through the journey of how these insights can be leveraged for growth and visibility in this ever-evolving domain.


    Inspired by this post on HiGoodie Blog.


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  • How Agile Competitors Outshine with AI Search Visibility

    How Agile Competitors Outshine with AI Search Visibility

    I’ve often faced the challenge of watching enormous digital budgets return less and less, while more nimble competitors seem to pull ahead effortlessly. It’s frustrating knowing the potential is there, yet being unable to act swiftly enough.

    Examining how AI Overviews and responses from tools like ChatGPT and Claude cite sources, I’ve noticed an unsettling trend: smaller, more agile companies are capturing the most valuable, bottom-of-funnel commercial queries.

    This reality is a call to action, challenging the notion that simply having a well-known brand name can protect my market share. Agility is increasingly becoming more important than relying solely on brand heritage.

    To stay relevant, AI models require quick, machine-readable data to form a credible consensus. The bureaucracy I’ve encountered, which I call the “bureaucracy tax,” often hinders established companies like ours from deploying such knowledge quickly.

    Unintentionally, as my business expanded, the structures built for stability began to stifle our agility.

    In my experience, when deployment lags, it’s often marketing teams pointing fingers at legal, risk, or compliance departments. Yet, in sectors where regulation is strict, compliance is a necessity.

    The operational shortcoming isn’t with the legal department but with what we’re providing them. Winning in the AI search space requires that we separate factual data from marketing narratives.

    The truth is, legal teams debate adjectives—not APIs. They take months to scrutinize creative marketing copy. Conversely, they can review static data tables or product specifications in days.

    I recall how a global payments company struggled with this. A proposed 2,000-word marketing article was a compliance nightmare. However, when the same data was presented as a structured table, approval came within 24 hours.

    When a CFO asks Perplexity to “compare enterprise payment gateway fees,” it skips over blocked competitor blogs and cites your factual table as the authoritative source.

    Dig deeper: Why most SEO failures are organizational, not technical

    How Much Does the Bureaucracy Tax Actually Cost?

    From my perspective, the bureaucracy tax is a tangible and damaging effect on profit and loss statements. For a new initiative, the deployment cycle can take up to 180 days from idea to execution, hampering responsiveness to market shifts.

    Imagine being a global shipping company. While awaiting IT staging, your competitors publish a straightforward “Current freight delay and tariff matrix,” seizing AI consensus and lucrative leads before you can react.

    ```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."
}
```

    An analysis of AI citations across platforms revealed that disruptors deploying data within 14 days achieve a significantly higher share of AI voice compared to legacy companies that take much longer. The cost of delay is persistent, demanding both time and financial resources to recapture lost ground.

    Dig deeper: How to build an enterprise SEO strategy that gets buy-in

    The Technical Bypass: The Schema-Locked GEO Template

    I’ve come to understand that the loss in this race is partly due to outdated technology. Many of us are stuck on heavyweight, legacy CMS platforms.

    Generative Engine Optimization (GEO) demands a quick rollout of JSON-LD schema and data tables. If an IT ticket is required merely to update author info, the advantage is lost to faster disruptors.

    The remedy isn’t to circumvent systems insecurely. We must advocate for schema-locked GEO templates. This requires IT to create a non-modifiable template designed specifically for data, ensuring rapid deployment without risking architecture.

    From Compliance to Consideration in Record Time

    Workflows must balance keeping risk officers satisfied while drastically speeding up market delivery. These strategic frameworks are critical to protecting your AI consensus.

    If legal bottlenecks your progress, shift your strategy to use pre-approved, factual tables. If developing resources are scarce, implement a “schema-locked GEO template.” If your analytics indicate stability but pipeline velocity drops, audit your LLM visibility immediately.

    Agility is the New Authority

    It’s clear to me that digital acquisition rules have shifted. Winning isn’t just about budget size anymore; it’s about being the fastest to establish a machine-readable agreement.

    Legacy systems and poorly aligned compliance procedures can’t continue to define our market share. The bureaucracy tax siphons resources needlessly, hurting our bottom line.

    I urge you to audit your deployment processes promptly. Treat GEO as a high-speed data operation, not just a marketing campaign. Remove the barriers, and empower your teams to be the definitive resource consumers and machines turn to.


    Inspired by this post on Search Engine Land.


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  • How Query Language Transforms AI Citations Globally

    How Query Language Transforms AI Citations Globally

    As I dive deeper into the world of AI, I’ve come across something truly fascinating about how query language is changing the landscape of AI citations. In our analysis, Profound looked at an astounding 3.25 billion citations spread across seven AI models and fourteen countries. What the data revealed was mind-blowing: the language used in queries is the main catalyst reshaping citation rates across different AI platforms.

    Interestingly, I noted that AI tools like Google AI Overviews and ChatGPT handle non-English prompts in uniquely distinct manners. This variation has far-reaching consequences for brand visibility on a global scale, especially within the realms of AI search. The differences in response patterns not only highlight the power of language but also impact how brands are perceived worldwide.


    Inspired by this post on Try Profound Blog.


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