Tag: Visibility

New Google AI Opt-Out: A Smart Move or Risky Gamble?

Recently, I discovered that Google introduced an AI opt-out feature, and it got me thinking.

For as long as I can remember, we’ve been pushing Google for more insight into AI traffic and control over our content’s portrayal in AI settings.

Now, this week, Google answered us with new controls allowing site owners to opt out of AI-powered experiences, like AI Overviews and AI Mode, coupled with fresh AI reporting tools in Google Search Console. Although still in early beta, it signals progress.

Despite this being a step forward, it’s sparked a split. Some are excited about the reporting aspect, while others debate whether opting out is wise.

What intrigued me wasn’t the announcement itself, but how swiftly the conversation pivoted from seeking visibility to potentially forfeiting it.

Let’s clarify what Google really launched with their announcement. The new controls don’t hinder AI Overviews or user engagement with AI Mode, nor do they stall AI’s momentum. Users will continue to engage with AI for searching and queries.

Essentially, publishers have a newfound ability to determine whether their content appears in AI-powered experiences. Was it Google’s plan or a response to external pressure, such as the UK Competition and Markets Authority?

This isn’t a debate about AI itself disappearing. What changes is brand eligibility within AI interactions. If a site like Expedia opts out, people will still plan trips—they’ll just find someone else in the AI-generated responses.

The choice is not about AI’s success, but rather about whether your brand remains present when users turn to AI solutions.

I get it—the appeal to opt out stems from fears around lost traffic and how AI uses our content.

Yet, assuming that opting out changes user behavior is where I disagree. Users aren’t concerned about a brand’s participation; they’re using AI to get quick answers.

Opting out may seem like a decision to curb AI adoption, but it more so enhances your competitors’ visibility. They snag the spotlight and gain trust while yours potentially fades.

The goal isn’t just visibility reduction—it’s about evolving with search behavior changes to remain seen.

Google’s announcement didn’t just focus on opting out but also on the new AI data they’re offering. Though imperfect, it’s a step towards greater transparency in AI search interactions.

Despite demands for more comprehensive reports, reality shows SEO has long dealt with imperfect data. Some of SEO’s big wins came from leveraging imperfect data.

Hence, we shouldn’t be stuck waiting for flawless data. While not perfect, it’s more than what we had before and will likely evolve further.

In my approach, reporting must expand beyond traditional SEO metrics, encompassing a wider discovery landscape, including AI and interaction insights.

We need to assess brand mentions, citation frequency, and how they’re perceived across differing AI platforms. Visibility stretches beyond mere traffic metrics.

Ultimately, we must rethink our questioning. Instead of asking, ‘Should I opt out of AI?’, ask, ‘Can I afford to be absent where users find brands?’ They’re already in these spaces—why shouldn’t we be?

Google’s update isn’t just a feature but a strategic pivot. By choosing to opt out, you aren’t erasing AI; you’re simply amplifying someone else’s presence.

Are you ready to adapt, or will you stay behind, longing for Google’s ‘free clicks’?

Inspired by this post on Search Engine Land.

June 18, 2026
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.

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.

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.

June 8, 2026
Unlock Business Growth by Aligning SEO and Affiliate Strategies
SEO and affiliate teams often influence the same metrics, such as revenue, rankings, and visibility in the digital landscape. By aligning these teams, we can cut costs and significantly enhance brand performance.

In many businesses, SEO teams and affiliates—partners promoting our products for commissions—operate separately. While the SEO team focuses on rankings and organic traffic, the affiliate team is busy cultivating partner relationships and handling commissions. However, rarely do these teams collaborate, missing out on boosting their collective impact.

Cross-departmental cooperation is essential for business growth. Collaborating with other teams helps me understand their views on success, expands my perspective beyond SEO, and reveals new opportunities for leveraging initiatives for SEO advancements.

A harmonious relationship between SEO and affiliate teams is crucial. Let’s explore the importance of this alignment for brand protection, LLM visibility, and tool sharing, and how this synergy can enhance efficiency, save costs, and bolster business performance.

Protect Your Brand and Search Terms

It’s crucial to maintain control over brand-related search terms and not let affiliates dominate them. With my clients, anything affecting organic performance falls under the SEO team’s domain.

Consider high-intent terms like:
- [brand] + discount code
- [brand] + promo code
- And many other variations
Allowing affiliates to rank for these terms can redirect your branded traffic and sales back to you, incurring unnecessary commissions. This costly situation can be easily avoided.

Dig deeper: The best affiliate networks by need and use case

How to Reclaim Your Rankings

Brands can lose their conversions to affiliates as well, like Trainline. The term “trainline promo code” garners 17,000 monthly searches in the UK, yet Trainline fails to optimize their promotional page for this term, losing traffic and conversions to affiliates.

The fix is simple: a focused adjustment of the meta title, H1, and main content to reflect these terms effectively.

By reclaiming control over these rankings, we:
- Increased organic revenue.
- Reduced affiliate expenses.
- Enhanced overall business profitability.
For instance, one brand we manage saw a boost in Share of Voice from 14% to 31% after a strategic content update, all overnight.

These victories benefit the entire business, not just SEO. This is the true purpose of SEO — driving business growth through insight and strategy.

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See terms.

How SEO and Affiliate Teams Can Work Together to Compound Returns

Affiliates generally produce content that enhances reputational signals like “Best of” and comparison articles. LLMs heavily weigh these signals, increasing our brand’s authority when mentioned in numerous reputable articles across our niche.

Educating affiliates on including our brand in such articles can provide:
- Increased affiliate visibility, leading to traffic and conversions from those placements.
- Enhanced LLM visibility, boosting reputational signals that inform AI models recommending our brand.
Technically, we need to manage affiliate tracking URLs correctly. No-indexing these URLs prevents them from being indexed in search results, avoiding potential indexing issues.

I monitor this with SEOTesting, which alerts me about newly indexed URLs, allowing us to swiftly address any tracking URLs that slip through.

Dig deeper: What incrementality really means in affiliate marketing

Collaborate with Affiliates Today

SEO and affiliate teams should not work in silos. Their synergy can save money and increase visibility. Affiliates can boost LLM visibility, while SEO data can empower affiliate decisions, driving business success together.

The closer these teams operate, the more beneficial the results for the business.

Inspired by this post on Search Engine Land.
June 3, 2026
Unlocking AI Visibility: The Key Role of Brand Depth

Have you ever wondered why some brands consistently show up in AI recommendations, while others don’t? I’ve discovered that building deep and consistent brand presence is the real game changer.

I’ve come to realize that simply getting cited isn’t enough. It’s the brands with a strong semantic footprint the AI systems love to retrieve and recommend.

For me, generative engine optimization (GEO) is like playing two games at once: creating both long-lasting brand influence within AI systems and crafting content that navigates modern data retrieval pipelines effortlessly.

During my deep dive into AI recommendations, I learned that brand depth significantly boosts your chances in both retrieval and synthesis processes.

Playing Two Games: The GEO Challenge

Every layer I explored influenced visibility differently.

Game 1: Building Parametric Weight

Brands are like coordinates in a language model’s embedding space, shaped by the density and consistency of signals. I’ve found that building this weight takes time, growing steadily over months, even years.

A brand with inconsistent messaging, as I’ve seen, ends up with a fuzzy vector, which hampers recall and confidence during AI retrieval.

Through my experiences, it’s clear that ignoring the foundational elements of a brand in favor of short-term citation strategies leads to missed opportunities in AI systems’ recognition.

Game 2: Survival of Retrieval

For me, the true test comes when systems like Google AI Mode or ChatGPT Search launch their retrieval pipelines. Will my content make it through? About 85% of brand mentions in AI systems stem from external domains, which says a lot about where I need to focus my efforts.

Different AI search systems have their unique methods, from Perplexity’s citation embedding to Google’s query fan-out, and each presents its own set of challenges and opportunities.

Citations: Just the Surface

In my findings, citations only signal output presence, not the underlying retrieval and synthesis processes. Focusing solely on citations can be misleading. It’s important to delve deeper into the factors that lead to citation in the first place.

Brand Depth: The Familiar Route for AI and Humans

As I looked into it, I realized that human brains and LLMs share a common strategy: defaulting to the familiar through dense information frameworks.

Predictive processing theory helped me understand why both prioritize densely established information, highlighting the similarities between human decision-making and AI functions.

Getting Technical with Brand Depth

Diving into the technical aspects, I learned that Google and AI models focus on entity salience, coherence, and relational density to determine a brand’s visibility and reliability.

Entity Salience

I discovered that high entity salience increases the likelihood of being cited and recognized in AI systems.

Low salience restricts visibility to exact branded queries, whereas high salience ensures my brand surfaces even when just the topic is discussed.

Entity Coherence

I’ve realized the importance of maintaining a consistent brand identity to avoid low confidence representations in AI models, which otherwise leads to brand drift over time.

Inter-entity Relationship Density

Building strong connections with authoritative entities enhances the chances of my brand being retrieved and recognized during AI reasoning processes.

The RAG Layer: Where Site Quality Shines

I’ve learned from Mark Williams-Cook that a site’s quality score can determine its eligibility for retrieval, emphasizing the need for strong brand infrastructure for consistent visibility.

Why AI Systems Highlight Clinique’s Black Honey

Clinique’s “Black Honey” lipstick is a fantastic case. Its impressive entity depth frequently registers it in AI responses. I aspire for such widespread recognition for my endeavors.

From its cultural anchors to competitive benchmarking, the layers of meaning around “Black Honey” continually rack up its mentions and trustworthiness in AI systems.

Crafting Content for AI Retrieval Success

In my approach, focusing on rich, unique content is crucial. High-quality content naturally finds its way through the retrieval funnel, while generic content falls by the wayside.

By crafting detailed, data-rich narratives, I ensure that my work stands out as essential, enhancing chances of being cited and referenced by AI tools.

Inspired by this post on Search Engine Land.

May 28, 2026
Mastering Pre-Search Visibility: The SEO Pyramid Guide

I’ve come to realize that my buyers often have a shortlist in mind even before hitting Google. It’s fascinating how these pre-search decisions form. Here’s my take on how I influence those vital conversations that put my brand on that list.

The customer journey used to kick off with a simple search, but it’s evolved beyond that point. By the time potential buyers type a query into Google, they usually have some brands in mind. They’ve watched Instagram Reels featuring a product repeatedly, read threads on Reddit with unanimous recommendations, and seen similar endorsements in Facebook groups.

Google is now more of a confirmation tool than a starting point. When someone searches, they’re looking to confirm their assumptions, not to browse aimlessly.

The key question is, did my brand make it onto their mental shortlist before they began searching? In most cases, being visible on comparison platforms is crucial for this.

So, where is this shortlist actually built? Peer-driven decisions are made in various industry-specific environments

By the time these interactions prompt a Google search, choices are often boiled down to specific comparisons like “brand X review” or “brand X vs. brand Y.” Being mentioned in those off-SERP discussions is usually more influential than ranking for a head term.

It’s worth noting that platforms like Reddit won’t hold the spotlight forever as visibility there is inherently temporary. Yet the basic behavior remains constant: people ask their peers before consulting search engines. My strategy focuses more on participating in these conversations rather than just chasing trending platforms.

Dig deeper into strategies to ensure pre-search visibility and why your brand might not be included in AI recommendation sets.

The two objectives of search everywhere optimization, or SEvO, form the backbone of my campaigns:

Direct visibility ensures my brand appears where buyers are narrowing options, measurable by direct search traffic and specific branded queries. Engine comprehension, on the other hand, leverages each brand mention next to relevant problems or solutions to enhance AI system recommendations.

Steve Jobs famously said, “You can’t connect the dots looking forward; you can only connect them looking backward.” I can’t see how these efforts gel until they start appearing in AI responses and the buyer conversations.

To measure effectively, I keep tabs on things like brand mention volume and trends in branded searches. These indicators suggest that pre-click visibility is working.

When it comes to Search Everywhere Optimization, the strategy I use is all about getting discovered where my buyers spend time, even before they think to search for brands like mine.

The Search Everywhere Optimization Pyramid organizes my efforts:

The groundwork is Audience Platform Research, guiding me to where my customers are likely making their decisions.

Setting up effective alert systems is key to knowing when relevant topics surface, helping me know when my brand should join the conversation.

Next up comes credibility through industry publications, earning my brand recognition in places potential buyers trust.

Then I focus on distribution, ensuring my content reaches my audiences effectively and keeps them engaged.

Finally, I create and refine my own content to support everything from below, nudging my brand into view when buyers are in that crucial decision-making phase.

Understanding that conversation is ongoing helps me navigate future shifts, even as specific platforms rise and fall in popularity.

If my goal is making it to the buyer’s shortlist, I need to ensure visibility not just on SERPs but across all the web spaces they engage with. Through consistent and deliberate steps, the pyramid ensures that my brand is more than just a search result — it’s part of the discussion.

Inspired by this post on Search Engine Land.

May 21, 2026
Boost Your Brand’s AI Recommendations with Clarity and Relevance

Over the past few years, I’ve been inundated with advice on generative engine optimization (GEO) – everything from AI citation checklists to technical guides for structuring content for large language models.

Most GEO guidance revolves around a key premise: To be visible in AI-generated answers, your content must be structured, authoritative, and easy to extract.

In my view, this advice, while valuable, falls short if your brand isn’t yet eligible for consideration in AI-generated results.

The underlying assumption is that ticking those boxes makes your brand eligible for AI-generated answers. However, many brands overlook the fact that they aren’t even being considered.

To get past this hurdle, we need to address an underappreciated factor that many GEO enthusiasts miss.

Traditional SEO has taught us to seek visibility through rankings, believing that higher rankings translate into more clicks and better outcomes. Many have now adapted this mindset to AI, aiming for citations or inclusions in AI-generated answers.

However, AI systems don’t just rank; they filter and select entities based on signals, determining eligibility before weighing options.

Without eligibility, many brands risk being excluded from the AI recommendation set right from the start.

Brands often misprioritize, focusing on extractability before establishing clarity, which results in missed opportunities.

It’s critical to understand the difference between qualification (being eligible to join the candidate set) and selection (being chosen from that set).

AI-driven search changes the game. While traditional SEO ranks pages, AI selects entities, such as branded products and concepts, interconnected in a web of knowledge.

This shift means we must prioritize entities over pages. An entity might excel in traditional search yet remain ambiguous in AI-generated answers.

Common issues lie in clarity and relevance. AI systems ask: Can I identify and associate this entity accurately?

If definitions are inconsistent across platforms or names vary, brands struggle to pass this threshold.

Clarity is the cornerstone. When AI or search engines see your brand, clarity allows them to understand exactly who you are.

For example, when I noticed my common name, Mariana Franco, was causing confusion, I changed it to “Maryanna.” This helped ensure that my identity was distinct and recognizable to AI systems.

By consistently using this unique name variant across all my online assets, I reduced ambiguity within a week, making it easier for systems to recognize me as an entity.

Relevance is another crucial factor. Does the web associate your brand with relevant topics consistently and strongly?

This involves appearing alongside related entities, demonstrating expertise through in-depth content, and being referenced by well-known entities in your field.

Once qualified, a brand becomes part of the candidate pool, applying GEO strategies to increase the chance of selection.

Credibility becomes vital at this stage. You need corroboration from reputable sources to enhance your credibility.

Multiple credible mentions and appearances in media, reports, and podcasts bolster your visibility and reliability.

Extractability, or how easily an AI can generate answers from your content, is crucial once in the candidate set.

To ensure extractability, organize your content clearly, prioritizing concise, context-independent answers.

Testing your brand’s appearance in AI tools can reveal whether you’re recognized or recommended. A search using ‘best [your category]’ illuminates inclusion gaps.

If AI recognizes your brand but doesn’t recommend it, focus on building selection signals — credibility and extractability.

For comprehensive visibility, prioritize clarity and relevance to ensure eligibility, then focus on credibility and extractability to strengthen your standing.

Start by ensuring name consistency and clarity — the foundation of being recognized as a distinct entity.

Your About page should explicitly define your brand, utilizing schema to integrate into AI systems.

In AI’s expanding landscape, qualified entities will thrive, making consistent clarity and corroboration more critical than ever.

Inspired by this post on Search Engine Land.

May 13, 2026
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.

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.

May 4, 2026
Boost Visibility: Build Trust for Lasting Impact

Every day, I notice how our attention becomes more fragmented as new information platforms emerge.

With entrants like AI search and proprietary spaces on social networks, we’re bombarded by noise from every direction.

In this deluge of information, trust is slipping, even in previously reliable sources like search engines and social media.

In times of uncertainty, we revert to the most timeless source of trust: other people. To be visible, I must appear across multiple platforms, especially those led by people.

Search is a trust experience

Rachel Botsman, a trust expert, defines trust as “a confident relationship with the unknown.” It’s the element we rely on when facing uncertainty.

As humans, I search for information when uncertain, relying on three layers of trust: self-trust, platform trust, and source trust.

The entire search process hinges on trust, and the most effective support comes from other humans.

An example of my own search journey to find a trusted answer

Recently, I decided to buy new shoes. My search began with AI tools, where I conducted low-trust research using ChatGPT and Claude.

Seeking high trust in pricing and delivery, I turned to Amazon for reviews and pricing, then to Google for deeper insights from Reddit and YouTube.

Bombarded by low-trust social media ads, I finalised my decision with high-trust recommendations from friends and a local running shop.

Search journeys now span dozens of platforms and sources

Research by Yext found that 75% of consumers use more platforms now than a year ago, but only 10% trust the first result. Reflecting on my 65-source journey, most were people-led, matching a trend in professional decision-making.

The 2026 Edelman Trust Barometer reinforces that amidst rising uncertainty, people seek advice from those they trust most.

So how do you turn trust into visibility?

To influence someone’s search journey, I aim to appear on all information-searching platforms and in as many people-led sources as possible.

Start by earning mentions in people-led spaces and build genuine trust. This naturally leads to visibility on major platforms.

For instance, Adidas Terrex was visible at every touchpoint in my journey, reflecting its active engagement and trust-building with consumers.

Through events and community initiatives, Adidas fosters engagement, enhancing visibility through hashtags and social platform mentions.

Where to go to earn people’s trust
Building relationships lays the foundation for trust. I start by engaging in communities, events, social media, and forums where genuine conversations occur.

Select places with active, two-way communication where you can authentically connect and build a trustworthy presence.

How to engage in trust-building spaces

The priority is helping, not selling. I listen first to understand what people need, then engage meaningfully to build trust.

Start by listening, not talking

Before jumping in, I learn what ‘helpful’ means in the specific space and identify how I can support the community’s needs.

Engage to build trust

Building trust takes time and involves personalized interactions and consistent presence as a genuine individual, not as a brand representative.

Turn conversations into scalable trust

Using insights from personal interactions, I create scalable assets that support people’s aspirations, reinforcing trust on a larger scale.

For example, a guest-posting program for professionals looking to amplify their personal brand can be a powerful tool for fostering trust.

What does this actually look like in action?

In my journey from marketing to community building, I experienced firsthand how focusing on helping rather than selling leads to building trust and achieving visibility.

By listening and engaging with genuine support, an SEO SaaS partner grew visibility in our community, resulting in substantial business impact.

Building trust is a long-term visibility bet

Trust persists as a critical factor in information seeking. By embedding trust-building into my business strategies, I ensure lasting visibility across current and future platforms.

Remember, prioritizing trust preserves visibility beyond algorithms, creating enduring presence in an ever-evolving digital landscape.

Inspired by this post on Search Engine Land.

April 22, 2026
Evading AI’s ‘Bland Tax’: How to Maintain Brand Visibility
When I think about brand visibility today, it’s clear that being chosen by AI systems is crucial. Authority, unique insights, and consistent signals now determine if my brand makes the cut.

I’ve realized that AI isn’t just reshaping search; it’s deciding which brands are seen and which are ignored.

I learned from Andrew Warden, CMO of Semrush, at the Adobe Summit that visibility is evolving fundamentally, and our brands risk being systematically filtered out by AI systems.

“The idea of standing out is no longer optional. There’s a real risk of sameness,” he pointed out.

With AI systems deciding what to highlight and what to ignore, I know I must compete more fiercely for visibility in AI-generated answers.

AI is Changing How Discovery Works

The change is evident in the data: 60% of Google searches now end without a click to a website. People are still seeking information but aren’t always visiting websites. They’re getting their answers directly from AI systems like Google AI Overviews and ChatGPT.

These AI systems have become, as Warden described, the “new gatekeepers.”

This shift ushers us into the agentic era, where AI systems act as intermediaries, guiding users from inquiry to decision in one seamless interface.

Meanwhile, user behavior is evolving. People engage more in conversational environments, posing follow-up questions, refining queries, and surveying options within the interface, all resulting in fewer clicks but often attracting higher-intent users.

Warden noted that consumers using LLMs convert at least four times higher than those relying solely on search.

SEO is the Foundation

Despite some claims that AI could replace search, Warden reassured us that SEO is not dead.

SEO has become more foundational than ever. It’s essential to ensure my brand exists in the data layer AI systems rely on.

Warden emphasized, “SEO isn’t just for humans anymore. This is a training manual for AI right now.”

This involves ensuring:
- Crawlability
- Indexability
- Structured data
- Authority signals
Without these, my brand won’t appear at all.

Research backs this up: 94% of Google AI Overviews cite at least one top organic result, reaffirming that traditional search signals still support AI outcomes.

The Rise of the ‘Bland Tax’

One striking concept from the session was what Warden dubbed the “bland tax.”

AI conditions itself to overlook blandness, causing generic or repetitive content to vanish.

If I’m generic, Warden warned I’m perceived as average, and if I’m bland, I’m effectively invisible.

AI systems don’t reward sameness. Rather than highlighting my brand, they often condense similar content into a single, attribution-lacking response.

“This is an invisible penalty,” Warden noted.

The consequences manifest in several ways:
- My brand identity gets erased in AI-generated summaries
- My content is filtered out as low-value
- My work becomes training data for AI without offering visibility to my brand
“You also become a free training ground for LLMs,” he said.

What Visibility Depends On

Warden redefined brand visibility as a blend of:
- Discoverability: Can LLMs easily find me?
- Authority: Do they trust my brand enough to include it?
“You absolutely need both,” Warden asserted.

SEO ensures I’m discoverable. Authority determines whether my brand shows up in AI-generated responses.

Without authority, I risk turning into a “commodity that isn’t worth being mentioned.”

How to Win: Three Key Signals

Warden outlined three crucial areas determining whether my brand appears or gets filtered out:

1. Entity Authority

AI systems map entities and relationships, and they must recognize my brand as an authority on a topic.

One key signal is brand demand. If people aren’t seeking out my brand, neither will AI.

Strong brands emphasize their authority across various platforms—owned content, media exposure, and community discussions—demonstrating their niche.

2. Information Density and Originality

AI systems prioritize content that offers new insights. It’s vital to not just publish content but contribute something meaningful.

They emphasize new facts with proprietary data, original research, unique perspectives, and expert insights.

According to Warden, original insights can enhance visibility by 30 to 40%.

3. Signal Alignment

AI evaluates not just what I convey but also what others say about my brand.

This includes reviews, discussions on platforms like Reddit and YouTube, media mentions, and customer conversations.

Warden warned that conflicting signals could prompt AI to flag my brand as unreliable.

Consistency across these channels creates what he called a “consensus signal” that AI systems can trust.

Why Most Organizations Aren’t Ready

One of our biggest challenges is organizational, as visibility isn’t just a channel issue; it’s an organizational one.

Currently, responsibilities are fragmented. SEO teams focus solely on rankings, PR and brand teams manage messaging, and growth teams conduct experiments. This leaves no one clearly owning AI visibility.

This fragmentation leads to inconsistent signals and missed opportunities for us.

To truly compete, we need alignment across teams, working on a shared strategy about how my brand appears wherever LLMs gather data.

The Measurement Problem

Meanwhile, traditional performance metrics are unraveling.

Many marketers, including myself, notice a gap where rankings hold steady, but traffic declines. Meanwhile, leads might increase, yet attribution remains murky.

Warden explained that demand remains, but traffic no longer serves as its proxy. Our content is utilized, but not in ways directing users back to us.

This creates a growing disparity between impact and the ability to measure that impact accurately.

From Rankings to Relevance

The nature of competition has evolved. I’m no longer vying for a mere position; instead, I’m competing to be featured in a synthesized AI answer.

Authority, once easier to influence, now hinges on external validation—emphasizing what others say over what I publish.

Algorithms have shifted from being my allies to arbiters of meaning, marking a significant change in search dynamics since Google itself emerged.

The New Rules of Brand Visibility

AI has not altered what makes a brand strong but has transformed how that strength is measured and rewarded. The brands that win today will build real authority in a focused niche, publish original and high-value content, and ensure consistent messaging across every platform.

The need for consistent third-party validation across an ecosystem is paramount.

As Warden urged, I must make it impossible for LLMs to ignore my brand.

Inspired by this post on Search Engine Land.
April 21, 2026
Mastering AI Search: Elevate Your News Content Beyond Clicks

As someone deeply immersed in the world of SEO and content creation, I’ve seen firsthand how the landscape has shifted in 2026. It’s no longer just about racking up page views and clicks; brand awareness has become the star of the show. The game has evolved with the rise of multimodal search, and I’m excited to share how we can adapt to meet audiences wherever they are.

AI platforms are now a crucial traffic source that publishers like us must embrace. If we’re to stay relevant, we must engage with Google’s AI Overviews, chatbots, and other emerging technologies. Thankfully, utility news content still plays an essential role in connecting with audience needs.

So, what exactly is utility news content? It’s service journalism designed to provide simple, straightforward answers to top-line questions. Answer engine optimization (AEO) is a similar concept that’s gainign traction, encouraging readers to reflect on what a topic means and how it applies to their lives.

We must remember, simplicity is not stupidity. It’s about listening to the audience and crafting content that resonates. Gone are the days of setting evergreen content and forgetting it. Today’s strategies require more engagement.

To harness the full potential of utility news content, it’s vital to plan for evergreen targets with trend forecasting, track news closely, refresh explainers, create new content where gaps exist, and recirculate resources appropriately. Tracking performance and consolidating articles into libraries for review is also key.

Examples of traditional utility news content include checklists, FAQs, and “Everything to know about” guides. These formats prove that simple, straightforward content serves readers well by addressing their needs during critical windows.

During my time as SEO Director at ESPN, I led initiatives that put fan-forward queries at the forefront. This taught me valuable lessons in making utility content shine in a newsroom environment.

Lee Corso's impressive College GameDay record stands at 286-144, highlighting his expertise in game predictions since 1996.

In today’s world of zero-click search, some worry that service journalism may not seem as valuable. However, it’s not just about traffic—our responsibility is to provide accurate, credible information.

Performance metrics have shifted to emphasize overall brand visibility alongside page views and clicks. In 2026, search strategists need to focus on AI Overview placements, featured snippets, and other forms of visibility to ensure success.

Personalization features are becoming more prominent, and they offer publishers an opportunity to strengthen brand loyalty. By guiding readers to select your brand as a preferred source, you can enhance your visibility and engagement.

In summary, utility news content still wins by prioritizing audience needs and evolving in step with technological advancements. Let’s stay committed to delivering accurate and engaging information as the future unfolds.

Inspired by this post on Search Engine Land.

April 20, 2026