We all dream of gaining media coverage that positively impacts our brand. It leads to increased exposure, builds authority, fosters trust, and often provides valuable backlinks.
However, the path to such coverage often seems shrouded in mystery for many of us. Some hold myths about needing to be top-of-the-industry to catch the media’s eye. But let me tell you, that’s not entirely accurate.
There’s also a belief that media coverage is a commodity that can simply be bought. While you might find contributors willing to feature you for a fee, this practice is against most outlet guidelines. Even if you momentarily land a feature, it’s not sustainable; once discovered, it leads to content removal and getting blacklisted.
So, how can you get featured? It starts with understanding the process and applying it consistently.
Develop Your Story
Each of us likely has a compelling story waiting to be discovered. For the media, content is a never-ending demand, and having a strong story is your ticket to being featured.
But let’s dig into what doesn’t make a compelling story. It isn’t enough to be the first, claim to be the best, or even aim to change the world.
The key lies in telling an actual story that resonates. Explain why the audience should care. Like how I rebuilt my success story using PR, our agency’s approach comes from personal experience, aiming to empower others similarly.
Remember, you don’t need a life-or-death struggle for a great story. Tap into a mission that engages people and gives them something to care about.
Craft Your Pitch
Even with the best story, crafting an effective pitch is vital. It must stand out amidst hundreds of emails journalists receive daily. Your pitch should succinctly communicate your story and compel a response.
Focus on connecting your story to current events. Remember, while it involves you, the story isn’t solely about you. Always prioritize what the audience wants.
Condense your story into a few engaging sentences and align a short, punchy subject line with your pitch to grab attention positively. A well-aligned subject line is crucial for getting your email opened and read.
Build Your Media List
PR isn’t a numbers game. The goal is to send the right pitch to the right people at the right moment. Identify media contacts who align with your story, which you can often do through search engines or social media.
Timing is partly chance, but with persistence, you can always improve your odds.
Send Your Pitch
The perfect time to send your pitch doesn’t exist—unless pressing news demands immediate attention. Avoid bombarding contacts with follow-ups; once a week is sufficient. After two or three attempts with no response, move on.
It’s not personal; given the volume of pitches received, a lack of reply isn’t uncommon. Patience and perseverance are essential.
Nurture Your Relationships
Most pitches won’t result in immediate media coverage, and many stop after initial rejection; I find this approach baffling.
I’ve faced many “no” responses before achieving a feature. The key is in fostering relationships; these media contacts were strangers at first. Investing in building real relationships has ensured that my emails get opened. Once you have a network of responsive press contacts, consistent pitching becomes much easier.
Where does my content lose its impact on AI systems? The answer lies in the five crucial stages: discovery, selection, crawling, rendering, and indexing.
The journey of my content doesn’t stop at creation. The DSCRI-ARGDW pipeline maps the ten gates my content must pass through before AI systems recommend it. Among these, the initial five infrastructure gates are discovery, selection, crawling, rendering, and indexing.
This infrastructure phase is critical—it determines whether my content is even visible to AI systems. As each stage passes, confidence in my content can degrade, leading to missed opportunities downstream.
If the content can’t be rendered, it might still get indexed, albeit with incorrect information. Thus, every competitive gate that follows relies on the surviving information.
When the core content is compromised, no competitive strategy can save it. This intricate process has been simplified into a checklist labeled “crawl and index,” but each step is an opportunity for optimization.
Even if you’re a seasoned technical SEO expert, don’t skip this. You might be missing out on crucial improvements that could ensure your content reaches indexing with maximum confidence.
The infrastructure gates are sequential—each gate’s success determines the next, and failure at any point can halt the entire process.
Starting with discovery ensures focus on the earliest failures. Tackling this first is more cost-effective than addressing later stages prematurely.
Discovery, selection, and crawling are well-known gates where content undergoes assessment, and understanding them is crucial for effective optimization.
Discovery is a signal-based process driven by XML sitemaps, IndexNow, and internal linking. Unfortunately, content that lacks entity association becomes an orphan in this system, waiting longer to be processed.
The process of selection is often ignored despite being a key determinant of the crawl budget. Less is more, a lesson from Microsoft Bing’s Fabrice Canel, highlights the importance of focusing on quality over quantity of pages.
Crawling, while vital, has become commonplace due to advancements in server response optimizations. However, rendering fidelity continues to be a significant challenge where much of the core content could be lost.
JavaScript can pose a challenge in this stage. Not all systems invest in executing it, leading to potential loss of vital content for bots.
To bypass JavaScript issues, consider alternatives like server-side rendering or new pathways through WebMCP, Markdown for Agents, or Cloudflare’s markup.
The conversion fidelity stage transforms the content once it passes rendering, but here it might face new challenges in preserving the integrity of information.
The indexing stage could fail if the system can’t determine which parts of a page are essential, making proper semantic markup crucial.
As I navigate these stages, from an absolute to a competitive test, structured data emerges as a powerful tool but only when used correctly.
Skipping stages such as rendering and maximizing confidence before competition gives my content a significant edge. Employ methods like WebMCP or IndexNow to innovate past existing stages.
In conclusion, paying attention to these infrastructure gates helps me preserve confidence in my content and leverage structured data effectively. This ensures that my competitive strategy in SEO starts on a strong foundation, prepared to face the ARGDW phases to come.
As a marketing professional, I’ve experienced various identity crises in my journey. Initially, I was just a channel expert, then an integrated marketer, and eventually evolved into roles like growth and performance marketing. And then, AI became a buzzword that sneakily entered everyone’s job description.
Now, I find myself stepping into the era of the full-stack marketer, especially as a media leader. It’s strikingly similar to adopting a product management mindset.
Don’t worry, this doesn’t mean writing Jira tickets for fun (though some of us might enjoy it). It actually signifies that the most successful media leaders will not just focus on campaign optimization. They’ll take ownership of outcomes, foster cross-team connections, and holistically enhance the entire user experience, from first contact to final conversion and beyond.
In the sectors I’ve engaged with, especially those with extensive consideration cycles and rising acquisition costs, the link between marketing performance and the user experience is evident.
Let’s explore what spurs the rise of the full-stack marketer, what it truly means to “think like a product manager,” and why this mindset is essential for media leaders today.
What is a full-stack marketer, anyway?
From my perspective, a full-stack marketer knows the importance of how various elements mesh together, rather than trying to juggle everything solo, which inevitably leads to burnout.
Reflecting on my career, truly impactful media decisions are never born from expertise in a single channel. Instead, they stem from a broad fluency, inclusive of:
Media and channels: Understanding paid search, paid social, SEO, email, SMS, and staying abreast of upcoming trends and platforms.
Creative and messaging: Grasping what resonates, where, and why.
Data and analytics: Diving beyond dashboards by asking insightful questions.
UX and CRO: Identifying friction, intent, and behavior patterns.
Technology and platforms: Utilizing CRMs, CMSs, automation tools.
The full-stack marketer’s goal isn’t to become an all-knowing expert in every facet. Instead, we aim to gather sufficient knowledge to connect insights and make informed decisions by consistently zooming out and then zooming in whenever necessary.
Why media leaders are evolving into product thinkers
As I reflect on my earlier career, media leadership often revolved around meeting CPA targets and efficiently allocating budgets. These metrics mattered, and they still do.
Yet now, the landscape demands tackling larger, more complex questions like declining conversion rates or mysterious pipeline drop-offs, which oftentimes are product questions by nature.
Product managers focus heavily on the comprehensive experience — the user journey, friction points, trade-offs, and ultimate outcomes. Adopting this mindset encourages media leaders to view campaigns as part of a larger ecosystem, influencing our decision-making significantly.
Media doesn’t live in a vacuum
Marketing performance isn’t isolated. In many sectors, particularly those with extended decision cycles, a click represents merely the beginning of an intricate journey.
Industries such as financial services, healthcare, and education involve buyers moving through nonlinear paths, impacted by numerous interactions. This scenario is where the full-stack mindset becomes crucial.
Example 1: When media isn’t the problem, the experience is
I’ve frequently heard the claim “The platform is getting more expensive” when performance metrics drop. But as a product-minded media leader, I delve deeper into possible reasons, asking:
Has the conversion path recently changed?
Were additional steps or fields introduced?
Is mobile traffic directed to a non-responsive desktop?
In numerous instances, I’ve observed promising intent followed by a sharp decline at the conversion breather, a sign of a flawed product experience rather than a media issue.
For example, in higher education, potential students exhibiting strong intent may encounter roadblocks due to lengthy or unclear application processes. This often has less to do with the marketing campaign and more with the experience provided.
Here, the role of a full-stack marketer is to highlight these challenges, bring data insights to the table, and work cross-functionally to tackle and resolve these issues.
Example 2: Different audiences, different ‘products’
One vital product lesson is that not every user is the same, and thus, shouldn’t be lumped together.
Different audiences possess distinct motivations, risk profiles, and decision timelines. Viewing them as a homogenous group often leads to mediocrity.
I’ve discovered industries like healthcare — where patients, caregivers, and referring providers require individualized approaches — are perfect examples. Similarly, in financial services, decisions vary greatly depending on the individual’s life stage and goals.
A full-stack marketer tailors their media strategy, from messaging to channel selection, understanding that product-market fit is key, not just audience targeting.
Example 3: What happens after the conversion
A common blind spot in media strategies is post-conversion tracking. Product thinkers probe into the depths of:
How prompt and personalized the follow-up is.
Whether the messaging aligns with campaign promises.
I’ve witnessed enhanced performance with simple changes like improving lead response times or ensuring follow-up messages match campaign intentions.
Healthcare stands out in illustrating these principles, showing how vital immediate follow-up and aligned customer experiences can be across workflows.
Thinking in roadmaps
Roadmap thinking — prioritizing initiatives by impact — is another core aspect of product management. Similarly, full-stack media leaders prioritize marketing efforts accordingly.
Instead of pursuing every new shiny channel, we focus on sustainable progress, often by mapping out phases, such as:
Product managers don’t merely view metrics at face value; they challenge them. Being similar in nature, media leaders should mirror this approach, asking:
“Which segments convert faster?”
“How does performance vary across regions or stages?”
“Are engagement signals reflecting readiness or curiosity?”
In higher education, for example, dissecting performance by program or brand intent helps sharpen our strategies, turning data into actionable insights.
Collaboration is the new superpower
Full-stack marketers are naturally collaborative. In education, achieving success requires coordination across various departments including admissions and IT. In this role, we don’t just fulfill requests; we help partners navigate choices and establish shared objectives.
Translating data into actionable narratives becomes part of our collaborative toolbox and is essential in breaking down silos.
So, what does this mean for tomorrow’s media leaders?
The rise of the full-stack marketer doesn’t mark the end of specialization. It’s about seeing the broader structure rather than just optimizing single elements.
In my view, tomorrow’s media leaders should:
Understand the business driving their campaigns.
Think beyond their specific channels.
Advocate sincerely for user experiences.
Use data thoughtfully for influence.
Embrace change and unpredictability.
In industries where trust, timing, and transformation are integral, this mindset is vital. Marketing is about more than just campaigns — it’s about guiding pivotal life choices. If you feel like your media leadership role is expanding, that’s because it is — and rightfully so!
Almost two years ago, when the Digital Markets Act (DMA) came into effect, I was hopeful. But today, it’s clear that the user experience has worsened, business metrics have plummeted, and Google’s monopoly is as strong as ever.
As an SEO professional, I’ve joined countless others in agreeing that Google has long abused its dominant position in search to favor its own services over others. The DMA was supposed to be the solution—a regulation promising to level the playing fields in the digital world.
The European Union was hailed for finally taking steps against tech giants with the 2022 passage of the DMA, which came into force in March 2024, aiming to balance competition. Headlines were optimistic, signaling a fair and promising digital era.
Back in 2024, my perspective was captured in an article where I wrote about this legislation being a ‘much-needed piece.’ Fast forward two years, the DMA is doing more harm than good and this is not just speculation—it’s supported by concrete evidence.
The DMA was born from understandable frustration over Google’s well-documented abuses, where it would promote its own services like Google Shopping, often at the cost of others with better offerings.
Years of watching Google rank its own products first while burying competitors ignited the creation of this act, attempting to enforce fairness by having tech giants, the gatekeepers, treat all services equally.
For those like me, who have seen clients lose traffic to Google’s products despite providing superior content, the promise of algorithmic neutrality and fairness was nothing short of intoxicating.
But, as a comprehensive assessment reveals, the reality is different. Findings from a recent survey of 5,000 European consumers indicate that users find the online experience more cumbersome since the DMA was enacted.
It’s disconcerting when users, who previously received services for free, express willingness to pay to regain their prior experiences.
In professional circles, we have to acknowledge a truth: many users favored the integrated Google experience that we spent years criticizing. Now, users must jump through more hoops—and they aren’t pleased with this supposed ‘fair’ competition landscape.
The business implications have also been damaging. Metrics reveal declines in click-through rates and a drop in direct bookings, highlighting a disconnect between DMA’s objectives and real-world outcomes.
The issue of enforcement is daunting. Without addressing the core monopoly, any attempts to fine or regulate Google amounts to levying cost of doing business fees for them, rather than ushering in real change.
Long term, it raises a pivotal question for regulators: is it time to consider breaking monopolies to genuinely foster competition? Or continue to enforce rules that fail to address the underlying problem?
We need to create conditions that truly allow emerging companies to compete, not just manage monopoly symptoms with ineffective regulations. The DMA had the right intent, but it’s the wrong solution to this complex problem.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
This feature is undocumented because, as John put it, “Given how big of a hammer it is, I don’t know if it’s something we should really suggest in the docs.” Essentially, you can block all links from a specific TLD, a top-level-domain, using a special syntax.
Let me break down how it works. You simply add “domain:abc” to your disavow file if you’re certain that you need to block an entire TLD. John shared this insight on his Bluesky post, and it’s a fascinating possibility if you’re often dealing with spammy domains.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
This feature is undocumented because, as John put it, “Given how big of a hammer it is, I don’t know if it’s something we should really suggest in the docs.” Essentially, you can block all links from a specific TLD, a top-level-domain, using a special syntax.
Let me break down how it works. You simply add “domain:abc” to your disavow file if you’re certain that you need to block an entire TLD. John shared this insight on his Bluesky post, and it’s a fascinating possibility if you’re often dealing with spammy domains.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
This feature is undocumented because, as John put it, “Given how big of a hammer it is, I don’t know if it’s something we should really suggest in the docs.” Essentially, you can block all links from a specific TLD, a top-level-domain, using a special syntax.
Let me break down how it works. You simply add “domain:abc” to your disavow file if you’re certain that you need to block an entire TLD. John shared this insight on his Bluesky post, and it’s a fascinating possibility if you’re often dealing with spammy domains.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
As I was exploring Google’s lesser-known features, I came across an intriguing method to disavow an entire TLD using their link disavow tool. John Mueller from Google mentioned this capability, though it’s not officially documented.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
This feature is undocumented because, as John put it, “Given how big of a hammer it is, I don’t know if it’s something we should really suggest in the docs.” Essentially, you can block all links from a specific TLD, a top-level-domain, using a special syntax.
Let me break down how it works. You simply add “domain:abc” to your disavow file if you’re certain that you need to block an entire TLD. John shared this insight on his Bluesky post, and it’s a fascinating possibility if you’re often dealing with spammy domains.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
This feature is undocumented because, as John put it, “Given how big of a hammer it is, I don’t know if it’s something we should really suggest in the docs.” Essentially, you can block all links from a specific TLD, a top-level-domain, using a special syntax.
Let me break down how it works. You simply add “domain:abc” to your disavow file if you’re certain that you need to block an entire TLD. John shared this insight on his Bluesky post, and it’s a fascinating possibility if you’re often dealing with spammy domains.
He did caution, “If you’re sure that it’s what you want to do, you can use ‘domain:abc’ in the disavow file. Keep in mind that you can’t carve out specific domains if you like some, but if you find the TLD is almost only annoying spammers, it’ll save you time.”
However, he also advised, “I’m sure all TLDs have some good sites.” This method is powerful but should be used judiciously. It’s a big decision—like using a sledgehammer when sometimes a chisel might do.
Why should you care about this? If you find a TLD that’s causing issues or is full of low-quality spammy backlinks, disavowing it might just be the clean-up you need. But be cautious—it’s often better to carefully choose which links to disavow and avoid blanket decisions.
For those interested in exploring the disavow tool further, there’s a helpful document available here.
With Google referrals declining and LLM usage on the rise, I’ve discovered that successful discoverability now hinges on metrics, structure, and authority—not just rankings.
If your organic traffic is decreasing while impressions rise, AI might be citing your content without generating clicks. If both metrics are down, it’s likely your content is being overlooked. Either way, the conventional search behavior that shaped your marketing strategy has transformed, and merely waiting for traffic to rebound is not a viable strategy.
The year 2026 presents a new reality. According to KEO Marketing, 73% of B2B websites faced significant traffic declines between 2024 and 2025, averaging a 34% year-over-year drop.
These drops aren’t uniform. Websites with predominantly informational content have been more adversely affected, experiencing declines between 15% and 64% since AI Overviews emerged.
News publishers, in particular, have been vulnerable, with Google referrals decreasing globally by 33% in the year leading up to November 2025.
These aren’t typical fluctuations; they signify a fundamental shift in how information is discovered online, posing a threat to business models reliant on site traffic.
Organic clicks are diminishing due to two intersecting reasons, each necessitating a different approach:
Google has fostered zero-click behavior through features like featured snippets and knowledge panels. These provide answers directly on the search results page, often eliminating the need to click on search results. While 25% of searches concluded without clicks ten years ago, today it’s over 65%. This trend has rapidly accelerated with AI Overviews, now found in about 16% of desktop searches and 41% of mobile searches.
On top of that, a growing number of users are bypassing traditional searches entirely. Nearly 52% of U.S. adults now frequently use AI tools, and approximately 28% of employed Americans incorporate AI at work. When they seek answers from ChatGPT or other LLMs, they often get responses without visiting any websites. While your content might contribute to that answer, it doesn’t translate to traffic or attribution.
Traditional metrics such as impressions, clicks, and page views no longer accurately reflect discoverability. They measure site behavior without informing how your brand performs in AI-mediated interactions, impacting upstream traffic.
Here are the five key metrics for AI visibility:
Citations in AI responses indicate how often your content is directly referenced when an LLM responds to a query. A citation suggests your content is valuable, well-structured for AI parsing, and authoritative.
Brand mentions differ from citations. LLMs may mention your brand without citing your content, often pulling data from review sites, forums, and third-party articles. A mention absent a citation implies your brand is recognized but not sourced from your content, guiding where to focus investments.
Share of voice measures your frequency of citations and mentions relative to competitors within specific categories.
Brand sentiment evaluates whether AI-generated responses portray your brand positively, neutrally, or negatively.
AI-influenced traffic gauges the proportion of traffic generated from LLM referrals. Initial data indicates this traffic has a conversion rate 3-5 times higher than other sources, making it valuable to track even if minor in volume.
Modern tools can track these metrics at scale, eliminating the necessity for manual LLM prompts. However, even conducting basic benchmarks by querying major LLMs with your target questions and tracking mentions is advantageous over not measuring at all.
Achieving visibility in AI-driven search doesn’t involve rewriting your content strategy but instead requires shedding ineffective practices and pivoting towards lasting principles.
Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) continue to form the foundation of content credibility. LLMs give precedence to sources that demonstrate real expertise and are trusted by authoritative figures.
By earning citations from reputable sites, producing content authored by subject matter experts, and delving into topics thoroughly, you can outshine content that fails to meet these criteria, regardless of optimization efforts for other factors.
Structure and clarity are essential because LLMs extract content by pinpointing passages that effectively answer questions. Structuring content around clear questions and answers, utilizing bullet point summaries, and avoiding dense paragraphs enhance retrievability over embedding answers in narrative prose.
Your information architecture should be comprehensible to both human readers and LLM systems. Introducing a Q&A section or reorganizing posts around clear question-and-answer pairs provides significant improvements.
Human-written, human-led content has a distinct advantage. After Google’s recent core update, AI-generated content saw an 87% drop in rankings and citation frequency, with keyword-optimized content seeing a 63% fall. LLMs are becoming adept at detecting AI-created content and rank it lower.
The 2025 demand for AI-produced content has highlighted a quality issue now evident in performance data. Prioritizing quality over quantity is essential. Use AI for drafting and editing, but not for generating final content. Implement a review process to catch generic phrasing or a synthetic tone, either through AI-detection tools or human editors.
Recency is crucial for AI citations. AI systems consider both the publication and update dates when selecting sources. A high-quality piece from 2022 can be dismissed for a newer version from 2025.
Audit your high-traffic pages and key assets for outdated data, refreshing them with recent examples and data. It’s a quick yet often overlooked strategy.
Promotional language will not get cited. If your writing appears too commercial—emphasizing product claims and brand-forward language—answer engines may deprioritize it over more neutral sources.
This doesn’t mean you should avoid mentioning your product; rather, write about it like an impartial party by acknowledging trade-offs, providing context, and letting facts speak for themselves. Listicles and comparison articles excel here.
LLMs respond best to organized, objective comparisons—even when one option is clearly preferred.
If my presence is limited to my own blog, I’m at a disadvantage against a brand with less expressive assets but more robust third-party coverage.
That is why cultivating an external content ecosystem is critical. Reviews on sites like G2, Capterra, and Google are frequently used in AI curation. User-generated content on forums like Reddit is heavily indexed. Third-party articles, tutorial videos, and newsletter mentions build the multi-source consensus essential for AI citations.
Content partnerships also deserve focused effort. Sponsoring articles or placing newsletters in relevant publications not only drives referral traffic but also earns trusted, external citations that elevate AI visibility. With a growing readership, newsletters — offering curated, human-authored content — are vital, with YouTube citations becoming increasingly influential. ChatGPT favors authoritative video creators for citations.
The goal isn’t to merely generate mentions but to consistently express your brand’s narrative through credible external sources so LLMs consistently recognize that narrative. Consistency across partners, review platforms, and third-party content strengthens your AI share of voice.
With organic traffic plummeting by 30% or more, the visitors arriving at your site are more deliberate and valuable than before, making conversion optimization on landing pages crucial.
Focus on simplicity: one offer, one message, minimal text.
Each landing page should focus on a single call to action and a singular argument. If there are multiple conversion goals, develop separate landing pages rather than a single page attempting everything.
Ensure the header conveys the full value proposition succinctly, with supporting points kept brief. Visitors should instantly grasp the offer and know how to act without needing to scroll.
This approach contrasts with blog and thought leadership content, which should be detailed, well-sourced, and designed for LLM retrieval. Each serves different objectives and requires varied standards. Conversion-centric landing pages are not the place for nuance or elaborate prose.
The decline in traffic isn’t a temporary issue that will resolve itself. Users increasingly get answers directly from AI, bypassing websites, and this trend will only intensify. A strategy focused solely on ranking for clicks is now insufficient.
The new strategy involves a dual focus: optimizing for citations by AI answer engines and cultivating an external brand presence that offers LLMs compelling reasons to consistently mention you. These objectives align with longstanding best practices: crafting clear, authoritative content grounded in expertise.
AI-driven discovery favors brands excelling in the fundamentals: building real credibility, securing trusted external mentions, and writing for audiences rather than algorithms.
This approach was always the best, and now AI search makes it essential.
It’s fascinating to see the evolution of Google’s AI Mode and how it increasingly cites Google itself. In fact, almost one out of every five sources in its AI-generated answers now originates from Google, often guiding users back to more Google searches.
Why does this matter to us? As someone deeply involved in the world of digital content and SEO, I’m aware that AI search should highlight the best online sources. If Google prioritizes its own content, there’s a risk that we might encounter fewer direct links and see a reduction in traffic as users remain within Google’s ecosystem.
So let’s delve into the details. Research by SE Ranking reveals that Google.com is the most cited source within AI Mode responses, making up 17.42% of all references. This makes Google more mentioned than even the combined total of the next six well-known platforms: YouTube, Facebook, Reddit, Amazon, Indeed, and Zillow.
In an accelerated trend, back in June 2025, Google referenced itself in only 5.7% of AI-generated answers, but now that figure has tripled.
Almost one out of five AI citations is from Google. When considering YouTube, Google-owned properties account for about 20% of all sources.
This self-referencing is quite pronounced, with AI Overviews linking heavily to Google properties such as Maps, Images, and YouTube. AI Mode expands on this by further embedding users within the Google environment, often through presenting additional search results rather than directing them to external sites.
This strategy keeps users engaged with Google platforms where monetized content such as ads and reviews can be found.
What’s changed? Previous research showed that Google was mostly citing Google Business Profiles. However, this trend has shifted:
Travel: 53.18% of citations
Entertainment & hobbies: 48.74% of citations
Real estate: 30.54% of citations
Interestingly, the one area where Google is not the top source is Careers and Jobs, where Indeed appears more than three times as often as Google.
The data supporting these findings were gathered by SE Ranking, who analyzed 68,313 keywords across 20 industries, reviewing over 1.3 million AI Mode citations to determine how frequently Google.com was referenced.
59% of citations now direct to conventional Google search results.
36.1% still reference Google Business Profiles.
A smaller portion links to Google Support (1.7%), Google Flights (0.1%), and other Google services.
Often, these AI citations are accompanied by a mini search results panel beside the answer, effectively creating a new search opportunity.
Industry differences are also evident. Google dominates citations across several topics, but some sectors show a stronger dependency on Google:
Travel: 53.18% of citations
Entertainment & hobbies: 48.74% of citations
Real estate: 30.54% of citations
Interestingly, the one area where Google is not the top source is Careers and Jobs, where Indeed appears more than three times as often as Google.
The data supporting these findings were gathered by SE Ranking, who analyzed 68,313 keywords across 20 industries, reviewing over 1.3 million AI Mode citations to determine how frequently Google.com was referenced.
As someone passionate about video advertising, I’ve noticed how easily videos can now be distributed across platforms like YouTube, paid social media, and connected TV. It’s an immense opportunity for exposure.
However, I often find myself questioning the real effectiveness of these videos. Campaigns sometimes show impressive metrics, but lack in tangible business impact due to strategic missteps.
The issue isn’t so much about targeting or budget; it’s about focusing more on outputs—views, impressions—rather than crucial outcomes like attention and persuasion. That’s where most video strategies falter.
Misunderstanding Attention: A Common Pitfall in Video Ads
Many video ads operate under the assumption that they’re just like TV commercials, but that’s a misunderstanding of how attention works today.
In past meetings, we’ve defined success by views and impressions, not realizing these metrics don’t always translate to engagement or conversion.
True success lies in transforming impressions into meaningful actions, and that requires a drastic shift in strategy.
I’ve learned that the opening seconds of a video ad are critical. Initially, I assumed upfront branding mattered most, but ads that opened with engagement hooks performed better.
View-through rates don’t equate to persuasion. Real impact happens before the viewer can skip the ad.
An effective hook makes all the difference, whether it’s striking visuals or compelling questions. That initial grab of attention sets the stage for success.
Scrappy Ads Often Outperform Polished Productions
It’s surprising how often simple videos outperform higher quality productions. Authenticity resonates more with audiences than polished, overtly professional content.
Audiences and algorithms favor content that feels genuine over what looks like an ad. It’s about fitting in with the platform’s native content style.
Through experience, I’ve realized that the optimal length for an ad depends on the message itself. Sometimes a longer duration with a well-crafted story outperforms shorter clips.
A well-paced narrative keeps viewers engaged, making them more receptive to the brand’s message, regardless of duration.
Understanding Metrics: Decoding Signals, Not Outcomes
The abundance of data can be misleading, with metrics often misinterpreted as outcomes. I’ve seen campaigns with high completion rates fail to drive any business impact.
The true measure of success is how video metrics correlate with real-world actions and conversions.
Aligning Briefs with Creative Outcomes
A common issue is poorly defined briefs leading to lackluster creative. Clear objectives and a deep understanding of the target audience guide more effective video strategies.
Knowing precisely who you’re speaking to and what action you desire them to take results in more intentional and impactful creative.
Creative and Distribution: An Inseparable Duo
Strategically planning how and where ads are distributed is just as crucial as content creation. I’ve witnessed great ideas fall flat due to mismatched platform contexts.
Designing ads tailored for specific platforms ensures they resonate and are effective in their intended environment.
Insight-Driven Testing: Beyond Mere Variance Generation
Effective testing focuses on key elements that engage audiences. Hypothesis-driven testing yields insights far more valuable than superficial variant testing.
Ultimately, I’m looking for tools that prove reliable in predicting real-world outcomes, enhancing creative confidence well before any campaign goes live.
Despite evolving platforms and algorithms, I’m convinced that the core elements of attention, curiosity, and trust remain constantly human.
The most successful video ads I’ve been part of focused on relevance, respecting viewers’ time, and delivering valuable content. That’s what truly captivates audiences.
Success in video advertising comes from understanding people—not just appealing to platform metrics.
For two decades, I’ve witnessed the web operate on a simple transaction: create content to fulfill needs, secure a high search ranking, attract traffic, and then monetize through various channels like products, services, or ads.
However, zero-click answers and AI search are redefining this dynamic. The key question now is whether AI acknowledges you as a source and if that recognition translates into revenue.
In my quest to understand this shift, I conducted over 200 AI visibility audits spanning ten industries.
What I discovered was a pattern: most websites are easily scanned but rarely referenced. Surprisingly, those industries that depend most on organic traffic inadvertently make themselves the hardest to access.
How I Conducted the Audit
I executed 201 audits using a consistent rubric, generating an overall AI visibility score plus four detailed subscores:
Freshness.
Structure.
Authority and evidence.
Extractability.
Spanning ten industries:
Coupons.
Affiliate reviews.
Travel booking.
Local directories.
Personal finance comparison.
Health information.
Legal directories.
Online courses.
Job boards.
Recipes.
The dataset leaned heavily toward homepages, which are often more marketing-driven and less substantiated by concrete evidence.
I also monitored access issues, finding that 38 of the 201 audits (18.9%) returned errors, indicating AI systems were obstructed or couldn’t reliably retrieve content.
Eight more audits scored zero due to missing subscores, pointing to poor content extraction or problematic rendering styles that hinder accessibility.
When analyzing score distributions, I focused on successful audits (163 sites) to differentiate between “unreachable” and “low quality.” Each industry’s error rate acted as a signal of whether AI systems could consistently use a site as a source.
Where Industries Stand in AI Visibility
The table below displays industry performance based on the audits conducted:
Rank
Industry
Error rate
Median overall
Median authority
Median extractability
At risk
1
Travel booking and trip planning
33.3%
45.5
31.0
52.0
High
2
Job boards and career marketplaces
40.0%
64.0
44.0
74.0
High
3
Legal directories and lead gen
35.0%
63.0
44.0
74.0
High
4
Coupons and deals
20.0%
62.0
36.0
74.0
High
5
Local directories and lead gen
5.3%
64.0
38.0
74.0
Medium
6
Online courses and learning marketplaces
30.0%
67.5
46.5
80.0
Medium
7
Health info and symptom lookups
15.0%
69.0
52.0
80.0
Low
8
Personal finance comparison
5.0%
67.0
52.0
78.0
Low
9
Affiliate product reviews
0.0%
69.5
54.0
74.0
Low
10
Recipes and cooking content
5.0%
75.0
55.5
81.5
Low
What the Audits Actually Revealed
The findings illuminated that very few websites were consistently citation-friendly. Here are the critical insights:
Access Issues Are Bigger Than Most Teams Realize
A significant 18.9% of websites experienced access errors. In certain sectors, the issue intensified markedly: job boards (40%), legal directories (35%), travel booking (33%), and course marketplaces (30%).
Therefore, a substantial section of these markets is essentially inaccessible to AI by default.
Most Sites Are Caught in the Middle
Looking at the 163 successful audits:
Average overall score: 61.6
Median overall score: 66
70.6% fell into “Inconsistent visibility” (60 to 79)
Only 4.9% achieved “Strong foundation” (80 to 94)
0% reached “Exceptional” (95 plus)
Conclusion: Most brands aren’t constructed for predictable use and citation.
The Gap Lies in Proof, Not Formatting
Median sub-scores across the audits revealed:
Structure: 92
Extractability: 74
Authority and evidence: 48
Freshness: 45
While pages are easily parsed, fewer justify citation. Key issues included:
114 instances lacked a “last modified header,” demonstrating missing freshness.
Citations or outbound links were rare, appearing only 13 times.
Rather than fearing traffic loss, the larger risk is exclusion from AI’s consideration set.
Industries disappear for specific reasons, fitting three failure modes:
1. Access Failure: AI Can’t Reliably Reach Your Content
If AI agents can’t consistently access your material, they may bypass you, compensating with data from alternative sources.
What access failure entails:
Strict bot protections or WAF rules treating agents as hostile entities.
App-like rendering prevents critical information from loading with initial HTML.
Barriers like popups or scripts impede content access.
How this causes vanishing:
AI’s inability to extract makes citation impossible.
Other sources or AI-native solutions satisfy the user’s query instead.
2. Trust Failure: AI Can Read You, But Can’t Justify Citing You
Trust failure is subtle: your page is understandable, yet lacks authoritative proof for AI to source it.
This was a common trend. In simple terms, the content reads well, but lacks defensibility.
A telling observation compares page types:
Articles’ median authority score: 76
Homepages’ median authority score: 45
A crisp homepage isn’t proof of authority. Citable proof resides in articles, policy pages, and similar in-depth resources.
3. Utility Failure: Even If You’re Visible, the Click May Not Happen
Utility failure is frustrating. You’re visible, potentially cited, but if your value is purely informative, AI creates an answer and the user never visits.
Visibility dictates your role in discussions, but utility affects revenue realization.
An applicable perception:
If your page answers the question, AI can replace it.
Where your product or service completes a user’s need, AI still requires you.
Access issues leave you ignored, trust issues mean you’re bypassed, and utility failures get your content summarized.
Why Certain Industries Are Vulnerable
Examining access, trust, and utility together reveals why some industries appear particularly exposed.
Categories repeatedly showing high risk in my findings shared three characteristics:
Inconsistent access due to blocking and extraction issues.
Content easily condensed into a single-answer format.
Limited business progression after the user obtains an answer.
This is why travel booking, job boards, legal directories, and coupons emerged as the most exposed in my analysis.
The larger implication is that while your business might thrive, your website might inadvertently be structured for exclusion.
This transformation impacts some industries more than others. Websites sustained by high-volume searches face heightened zero-click risks. However, even in these realms, a singular focus on information is perilous.
The misstep lies in equating AI search changes with ranking shifts; it’s truly an economic shift. From the audits, I realized:
Many industries render themselves inaccessible, ensuring models circumvent them.
Even when models interpret a page, lacking proof often prevents mentioning it.
The danger is becoming invisible. Triumph doesn’t come from concealment; it comes from proving your worth and offering something indispensable post-answer.
Trust combined with utility forms the new moat. Anything else remains outdated strategy.
I’ve discovered that structuring content with a clear layout not only aids readers in scanning effectively but also helps AI systems in identifying precise answers. Let me guide you on how to break down ideas into concise, self-contained sections.
At first glance, structuring content might seem straightforward, but there’s more to it than meets the eye. Despite Google’s suggestion to avoid creating bite-sized chunks exclusively for AI benefits, the practice of chunking plays a crucial role in both enhancing online readability and catching the eye of AI models.
Chunking doesn’t just make content easier to find or cite in AI search; it naturally enhances content flow, making concepts more digestible for human readers like us. Let me walk you through the chunking process and its best applications.
What is chunking?
Chunking involves organizing text into clear, self-contained units of meaning. Each paragraph should focus on one idea, ensuring that readers grasp each concept quickly and thoroughly, without needing background context from surrounding text.
Does chunking help AI or people?
Recently, Google criticized chunking as being overly optimized for AI queries, implying it might not serve human readers well. However, based on my experience, chunking enhances content understanding for both readers and AI systems, providing a structured way to communicate ideas effectively.
When content is well-organized, it aligns with how we naturally read online, making it easier to scan. It benefits AI as well, since these systems process text by passages. A concise paragraph following a relevant heading offers a clear solution to AI searches, like identifying ‘how to measure keyword cannibalization.’
When to chunk content
I suggest integrating chunking from the beginning when creating new content. While it may not always be necessary to revise old content just for chunking, consider prioritizing high-traffic articles with low engagement for updates.
Articles with significant traffic but high bounce rates.
Content that ranks well but isn’t being cited effectively.
Complex topics where clarity is needed for quick understanding.
How to chunk content
I find a chunk should succinctly cover a singular idea. Clear headings prepare readers for what’s next, and the corresponding paragraph fulfills that expectation. Here’s a simple approach to effective content chunking:
Build chunking into your content outline
Begin with a clear outline where each H2 or H3 represents a key concept with comprehensive explanation in the chunks below. This way, both writers and readers can see the content flow naturally.
How to edit existing content into chunks
Start by focusing on high-value pages, especially those with good traffic but poor engagement. Revise your headings to reflect their section’s content and break apart any paragraphs with multiple ideas to keep each thought independent and clear.
To chunk or not to chunk?
Don’t be swayed by the notion that chunking is just a trick. For me, chunking improves content for everyone—from readers hunting for specific answers to AI systems striving to connect queries to results.
