Diving into the world of SEO can be exciting yet overwhelming. As someone early in their SEO journey, I’ve realized the importance of grasping the business context, mastering search intent, understanding technical basics, and conducting hands-on research before jumping into using AI tools.
Working in SEO means constantly staying on top of trends in a fast-paced, marketing-focused industry. When I started, it often felt like navigating without a map. However, establishing a strong foundation made all the difference.
SEO is multifaceted, with specializations emerging as one advances in their career — including local, technical, content, and more. However, as a newbie, I found it beneficial to first gain a broad understanding of SEO before delving into specific areas.
1. Start with the Business
When I begin an SEO project, whether in-house or at an agency, it’s tempting to jump straight into optimizing meta tags or backlinks. But instead, I’ve learned to start by thoroughly understanding the business itself.
Key questions I consider while exploring the website include:
What product or service is being offered?
Who is the target audience?
What sets the company apart from its competitors?
If I get the chance, I always ask broader questions about the company’s goals and plans to better tailor my SEO strategies.
2. Be Curious, Ask Questions
SEO touches nearly every aspect of digital marketing, making curiosity a critical trait. I continuously ask questions not only to expand my understanding but also to foster collaboration with other departments.
Asking questions, no matter how basic they seem, is a great way to learn quickly and thoroughly.
3. Build from the Foundations of SEO
Starting with basics like understanding website fundamentals and how Google displays search results was crucial for me. Analyzing competitors’ search rankings provided practical insights and helped improve my SEO strategies.
Trying simple exercises, like comparing search results with current page optimization, helped me identify areas for improvement and align more closely with what Google values.
4. Get Technical and Network with Developers
While diving into the technical side of SEO can seem daunting, I found learning from developers to be incredibly rewarding. Building these relationships opened doors for deeper technical insights and support.
Coding courses and personal projects enabled me to enhance my technical skills at a comfortable pace.
5. Familiarize with Google’s Search Features
The evolution of Google’s search result presentations introduced me to a diverse range of features, challenging my ability to optimize different types of content effectively.
Understanding these features not only enhanced my SEO approach but also kept my strategies aligned with Google’s user-focused developments.
6. Understand Query Intent
Grasping the varying intents behind search queries allowed me to create content that aligns more closely with user needs, improving engagement and relevance.
Using Google’s guidelines to classify intents significantly refined my keyword strategies and content planning.
7. Conduct Research Independently Before Using AI
While AI can streamline SEO tasks, I’ve found invaluable learning by initially executing projects manually. This hands-on experience has been critical to my strategic development and understanding of SEO complexities.
Resisting the allure of AI solutions early on helped me build a solid foundation that AI could later enhance without overshadowing the fundamentals.
8. Know How GEO/AEO Differs
Understanding the distinctions between traditional SEO and emerging channels like GEO/AEO has equipped me to advise on brand visibility throughout diverse platforms and optimize accordingly.
Exploring how LLMs work, their training data, and how to effectively influence their output, has added a strategic layer to my SEO toolkit.
Laying the Groundwork for SEO Success
By focusing on the core elements of business understanding, search results, and user intent, I’ve laid a robust foundation that continuously supports my SEO growth and adaptability.
Engaging deeply with the basics has empowered me to navigate the complexities of SEO strategically and effectively.
I’ve realized that many of us, myself included, might be tracking the wrong SEO metrics lately. We need to shake things up, especially with 2026 approaching.
Picture this: I present an impressive chart depicting a 47% increase in site traffic. But instead of excitement, I’m met with puzzled looks from the CMO, wondering why revenue remains stagnant. Or, I celebrate a top-three ranking for a keyword nobody searches for.
The SEO metrics that boosted my confidence back in 2019 might just be steering me wrong in 2026. With AI Overviews taking over search results and zero-click searches becoming the new standard, clinging to outdated metrics might jeopardize my strategy and budget.
I’m ready to take you through the precise metrics that our SEO team should retire and which new, revenue-focused metrics to prioritize instead.
Traffic Metrics
1. Organic Traffic
Organic traffic has been my go-to KPI in SEO reports ever since I started. But relying solely on it doesn’t provide enough context.
Not all traffic is equally valuable. A thousand visitors who bounce instantly are not beneficial. However, a hundred visitors converting at an 8% rate? That’s a success story.
I witnessed a local HVAC company whose traffic dropped by 22%, year on year. Panic, right? Yet, organic revenue increased by 31%. We focused on enriching high-intent service pages, pruning low-intent content. Fewer visitors, but better ones.
Before panicking over traffic drops, I always reassess where traffic is declining. If losses involve informational articles and customer login pages, it’s not a revenue issue. That’s just noise exiting my dashboard.
2. Total Impressions Without Intent Segmentation
This metric can mislead. A million impressions from merely informational queries like “what is SEO” might build some awareness, but they contribute zero revenue. Meanwhile, ten thousand impressions from business-driven queries like “best enterprise SEO agency” could significantly boost my pipeline.
Google Search Console offers this data, but many teams, myself included, often fail to segment it intelligently.
3. Traffic Growth Without Revenue Correlation
This is a risky trap for SEO teams. Bringing a 35% increase in organic traffic to a quarterly review sounds impressive, right until the CFO asks, “And how does this translate to revenue?” If I can’t answer that, I’m just reporting noise.
Ranking Metrics
4. Average Keyword Position
This metric might look compelling in a dashboard, but it doesn’t hold up under scrutiny. If I rank first for a keyword with ten monthly searches and fiftieth for one with 50,000, my average position might seem okay, but I’m losing where it matters most.
The average position treats all keywords as identical when they aren’t. With personalized search results, an “average position” can vary greatly by user and location.
5. Isolated Keyword Tracking
Searchers these days don’t typically use isolated keywords. They pose questions, explore themes, and adjust their queries. Google’s focus has shifted toward semantic search and topic modeling.
Tracking a solitary keyword like “lawyer” is pointless without understanding intent — are searchers interested in criminal defense, divorce services, or merely looking up what lawyers do?
6. Share of Top 10 Rankings
This metric sounds clever until it’s clear that 80% of my top-10 rankings might involve low-intent, low-volume queries. Meanwhile, competitors claim the top-three spots for crucial commercial queries in my niche.
Achieving a No. 1 ranking for a high-converting transactional keyword is more valuable than holding 50 top-10 positions for low-value informational queries.
Authority and Engagement Metrics
7. Domain Authority and Domain Rating
DA and DR might not align with Google’s metrics. They’re proprietary scores from SEO tool companies. Yet, teams often set misguided goals like boosting DA from 42 to 50 by Q3.
I’ve seen how backlink volume is often overrated. Google’s algorithm prioritizes link quality, relevance, and context over sheer volume.
A single link from a high-quality, relevant site outweighs hundreds of low-grade directory links. I’ve seen sites with 100,000+ backlinks struggle to rank for meaningful terms because most links lacked quality.
9. Bounce Rate
I’ve found bounce rate misunderstood for years. If someone searches for my company’s business hours, finds them on the contact page, and leaves, that’s a success with a 100% bounce rate.
Google replaced bounce rate with “engagement rate” in GA4 for a reason. Similarly, session duration and pages per session need context. A high pages-per-session score on my pricing page may indicate confusion, not engagement.
Why These SEO Metrics Are Failing Now
I’ve noticed the search landscape shifting quite a bit. Up to 58.5% of U.S. and 59.7% of EU Google searches now conclude without a click, as per SparkToro’s zero-click study. This means, for every 1,000 searches, only 360 result in a visit to a site.
AI technologies are capturing and synthesizing information, bypassing the need for a click. My content can gain visibility and influence without contributing to sessions in Google Analytics.
Wynter’s latest B2B buyer research indicates nearly 24% of CMOs now utilize AI tools like ChatGPT for research, a significant rise from last year.
Buyers discover brands via AI tools and use Google to validate those discoveries. This alters my SEO focus from merely driving traffic to ensuring my brand is visible during pivotal decision-making stages.
Modern customer journeys can be erratic. Often, users who initially find us through organic search might return through paid ads or direct links. If we use last-click attribution, the true value of SEO is obscured, although this organic start was critical for conversion.
For ecommerce, I aim to track revenue from organic sessions by product category and landing pages. For lead-generation, I’ll track how many leads convert to customers. Integrating with a CRM helps in connecting those dots.
No one’s interested in your DA if you can demonstrate $1.2 million in revenue attributed to organic channels.
Conversion-weighted Visibility
I’ll focus on visibility for high-value terms that lead to conversions.
A franchise client noticed they dominated low-intent queries but were invisible for crucial local terms. We adjusted priorities, and their qualified leads doubled in four months.
Topic Cluster Performance
This metric supersedes individual keyword rankings. Monitoring how I rank across full topic clusters, and the aggregate visibility and conversions from these clusters, gives a comprehensive view of topic authority.
SERP Real Estate Ownership
By gauging control over the entirety of search pages, not just listings, including snippets and local packs, I can effectively keep competitors at bay for crucial queries.
AI Platform Visibility and Brand Mentions
My focus will also be on how frequently my brand is mentioned in AI responses. Mentions are becoming as crucial as click-through rates.
For instance, if I secure a favorable recommendation rate across multiple AI platforms for vital topics, it’s a win, even if website traffic appears unchanged.
While tools are emerging to monitor this, manual spot checks can reveal valuable insights, enhancing authority and awareness, eventually leading to brand searches and conversions.
Branded Search and Direct Traffic as AI Visibility Proxies
I notice when buyers find out about my brand through zero-click searches, they often search the brand name directly instead of clicking through. This reflects in my branded and direct traffic rather than organic metrics.
If I see no change in nonbranded organic traffic but an increase in branded search and direct visits, it usually indicates that my content gains attention in AI Overviews.
How to Transition My Reporting
Revamping reporting around new metrics might feel daunting. Stakeholders are comfortable with old metrics.
I start by evaluating my current dashboard, ensuring relevant metrics face business outcomes directly rather than just tallying activities.
Transition by gradually omitting vanity metrics. If organic traffic was my focal KPI, I now introduce it segmented by intent and accompany it with organic-attributed revenue. Gradually, I pivot focus and phase out the dated metrics.
When I introduce new metrics, I frame them in relatable terms. Avoid using “conversion-weighted visibility.” Opt for “visibility metrics for top-converting terms.”
The Metrics That Prove SEO’s Value
The metrics we’ve relied upon — organic traffic, average keyword position, domain authority, bounce rate — aren’t inherently harmful. They’re just incomplete, providing a potentially false sense of security while others prioritize revenue-generating metrics.
Newly adopted metrics — revenue contributions, conversion-oriented visibility, topic authority, SERP dominance, AI platform mentions — directly relate SEO to tangible business outcomes. They prove ROI, justify budgets, and align strategies with business growth.
Consider which metrics in your dashboard lend false impressions of activity over effectiveness. Retire them. Replace them.
Ultimately, no one’s concerned with traffic numbers or DA scores. They want to know if SEO drives growth. Make sure your metrics affirm it.
With over twenty years in SEO, I’ve experienced every major industry disruption—from the days of keyword stuffing on AltaVista to the era of Google’s search algorithms, mobile-first indexing, and now the rise of AI.
What’s striking today is the rapid pace of change and the emotional challenges it brings. I notice mounting pressure among teams, even those who have navigated previous shifts successfully.
The common apprehension is valid: If AI improves speed, where does that leave me? This isn’t just a technical question—it’s deeply personal.
This uncertainty can lower morale and slow adoption. Productivity can wane, and experimentation might stall, leading teams to either over-rely on AI or completely avoid it.
The real leadership challenge is building confidence, capability, and trust in AI-assisted teams.
4 Ways to Boost AI Confidence in SEO Teams
Instilling genuine AI confidence within an SEO team goes beyond just adopting the latest tools—it’s a cultural shift.
The most effective SEO teams don’t just accumulate tools; they use AI purposefully and with discipline—automating data pulls, summarizing research, and clustering keywords—to devote more time to strategy, storytelling, and aligning with stakeholders.
As noted by Harvard Business School, technology adoption is largely cultural. Tools themselves don’t drive change—trust does. This insight is crucial for SEO teams navigating AI today.
Below are four strategies for enhancing AI confidence in your teams through clarity, participation, and shared ownership, instead of pressure or hype.
1. Earn Trust by Involving the Team in AI Tool Selection and Workflow Design
Strengthening trust can effectively be achieved by transitioning from a top-down approach to shared ownership. People generally trust what they help create.
When AI tools are imposed, resistance can increase. Inviting team members to participate in evaluation and workflow design makes AI seem less daunting and more empowering. Involving teams early provides real-world insights into where AI can reduce friction or introduce new challenges.
Effective leaders:
Invite teams to test tools and share feedback.
Run small experiments before scaling adoption.
Communicate clearly about what you’re adopting, what you’re rejecting, and why.
When teams feel included, they are more willing to experiment, and growth and innovation are fueled.
2. Meet People Where They Are—Not Where You Want Them to Be
AI capability varies widely across SEO teams. Some members might experiment daily, while others feel inundated or skeptical, influenced by past automation trends that have come and gone.
Leaders who boost confidence know that capability develops at different speeds. They cultivate environments where curiosity is encouraged, uncertainty is acceptable, and learning is continuous rather than mandated.
This means:
Normalizing different comfort levels.
Creating psychological safety around “I don’t know yet.”
Avoiding the shaming or over-celebration of early adopters.
Offering multiple learning paths.
Acknowledging different starting points makes growth seem attainable rather than intimidating.
When a team member uses AI to reduce a task from hours to minutes, it’s a moment worth recognizing. It demonstrates AI’s potential to support meaningful work without sidelining human insight.
Successful teams:
Share clear examples of AI improving quality and efficiency.
Highlight internal champions who can mentor others.
Create opportunities for demos and knowledge sharing.
Foster a culture of exploration, not criticism.
My agency created AI focus groups with members from various departments. One group worked on integrating AI into project management, including representatives from SEO, operations, and leadership.
This collaborative ownership resulted in more successful implementation. Teams were not just introducing AI; they were defining how it fit within real-world workflows. This approach led to enhanced buy-in, improved collaboration, and increased confidence.
Each group shared its achievements and lessons learned, building awareness of what succeeded and the reasons behind that success. When teams observe their peers embracing AI effectively, momentum flourishes.
4. Frame AI as a Collaborative Partner, Not a Replacement
The fear of being replaced by AI is genuine. Ignoring this concern won’t make it disappear. It’s vital for teams to understand where human expertise remains indispensable.
AI accelerates analysis. Humans interpret meaning.
AI drafts. Humans validate, refine, and contextualize.
AI scales output. Humans build trust and influence.
While AI aids execution, it cannot replace strategic instincts, contextual judgment, or cross-functional leadership—skills that ultimately drive performance.
Why Experience Still Matters in AI-Driven SEO
AI has lowered the entry barrier for many SEO tasks. With effective prompts, nearly anyone can produce keyword lists, outlines, or summaries. However, this accessibility often results in fleeting tactics and recycled quick fixes.
Anyone with a lengthy tenure in SEO recognizes this cycle. Tactics evolve. Fundamentals remain. Experience is the key differentiator here.
AI Can Generate Outputs, Not Accountability
AI can create content and analyze data, but it doesn’t bear responsibility for outcomes. It doesn’t uphold brand reputation, compliance, or long-term performance.
SEO professionals remain responsible for:
Deciding what to exclude from publication.
Assessing technical, reputational, and compliance risks.
Weighing long-term consequences against short-term gains.
AI executes. Humans decide. That distinction matters more than ever.
Pattern Recognition Is Learned, Not Automated
AI excels at identifying patterns but struggles to explain their significance or relevance in specific contexts.
Experienced SEOs bring a depth of understanding AI can’t replicate. Their historical insights help them identify true shifts instead of simply reacting to industry noise.
Few industries witness as many tactic fluctuations as SEO. Experience fosters strategic thinking beyond previously successful approaches and avoids repeating tactics that later failed.
AI suggests possibilities. Experience evaluates relevance.
Professional Integrity Remains a Differentiator
In high-visibility search environments, mistakes scale quickly. AI may produce inaccuracies, risking brand trust and compliance dangers.
Teams with strong professional SEO foundations:
Validate AI output instead of assuming correctness.
Prioritize accuracy over speed.
Maintain ethical SEO standards.
Protect brand voice and credibility.
Integrity isn’t automated. It’s a practiced discipline. In a fast-paced AI environment, it holds increasing importance.
As routine tasks become automated, the role of an SEO professional shifts to strategic oversight. Time previously spent on manual analysis can now focus on interpreting user intent, shaping search strategy, guiding stakeholders, and assessing risks.
This evolution makes fundamentals even more critical. Teams still need sound judgment, technical expertise, and accountability. While AI supports execution, professionals remain responsible for decisions, quality, and long-term performance.
Developing future SEOs necessitates more than tool proficiency; it requires teaching:
When to rely on AI.
When to question AI outputs.
How to apply experience and context to its output.
In my ideal world, reaching out to a top customer for feedback on a piece of content would be a breeze. However, the reality is often different—conducting audience interviews can be both challenging and time-consuming, especially when I’m crafting a new topic or refining an existing one.
A few years back, content marketing was a simpler game—just focus on keyword intent and excellent content to capture clicks from Google’s top search results. Now, in the AI-driven era, the stakes and expectations have evolved significantly.
Audience research has now become a non-negotiable aspect of my strategy. Sadly, not every company has the resources to carry it out effectively.
To bridge this gap, I’ve learned to create custom GPTs in ChatGPT that draw on my persona research. While these don’t entirely replace traditional audience research methods, they certainly help me pinpoint gaps or discrepancies in my content quickly.
Let me share how GPTs work, so you, too, can employ them for audience research.
Perform Audience Research
With the SEO scene constantly shifting, audience research is my strongest ally in understanding the motivations behind search intent.
Here’s a rundown of some intuitive methods and tools I’ve found useful for getting started with research:
SparkToro: By exploring websites, interests, or specific URLs, I can segment audience types, whether I’m looking for an overview or diving deeper.
Review Mining: I use various tools to automate the scraping of reviews about my company or competitors, which I then analyze to understand customer likes, dislikes, and their reasons.
Listening to Calls/Review Leads: An invaluable resource, listening to customer interactions with my sales team gives me real-time insight into their questions and what prompted their calls.
AI-generated analysis isn’t definitive. If you’re skeptical of GPT’s accuracy, confirm its claims by checking the evidence drawn from the data you provided.
The GPT can revise itself when errors are found; just ask for corroboration from the persona data.
Update Your Persona-Based GPT
My GPT is never static. I enhance it with more data for greater effectiveness.
Returning to ChatGPT’s Explore GPTs, I access My GPTs to update my persona.
By clicking on Configure, I can add, adjust, or remove persona details. This constant updating ensures relevance as I learn more about my audience.
A persona is always evolving, so the more I learn, the better my GPT becomes.
Leverage Persona GPTs for SEO Content
Though not foolproof, GPTs and AI-generated personas are helpful allies in optimizing content.
Once comfortable, I begin creating personas for wider audiences, niche segments, or particular campaigns.
In the ever-shifting landscape of SEO and marketing, I can’t afford to be complacent. As audience insights and intentions evolve, I ensure my GPT remains relevant by updating and pruning irrelevant details.
When used correctly, these tools are powerful companions to SEO efforts, channeling traffic and boosting conversions.
I’m thrilled to share that Profound Agents now offer direct integration with Contentful CMS. This integration brings native Contentful support right to your AEO automation stack, enhancing your strategy and capabilities.
With this development, I’m sure you’ll find managing content and automations far more streamlined and efficient. Having the power of Contentful within reach means we can align more closely with modern content management needs.
I’m eager to see how this integration will open up new avenues for optimizing our automated processes and elevating overall performance.
Do you want to take your Answer Engine Optimization (AEO) to the next level? Content siloing might just be the strategy you need. It’s a tactic that has transformed how I approach structuring topics to enhance authority and improve crawlability. Let’s delve into what content siloing is and how you can successfully implement it to boost AI citations.
Think of content siloing as creating a tightly knit topic network within your website, where each piece of content supports and strengthens the others. By organizing related content into isolated ‘silos,’ you not only streamline user navigation but also make it easier for search engines to index and understand the relevance of your content. This improved visibility can lead to better ranking in AI-powered search results.
Implementing content siloing involves a strategic approach to linking content. Begin by identifying your core topics and create subtopics that branch off these main areas. Each article within a silo should link to related content, reinforcing the overall theme and strengthening your site’s authority on the subject matter. This method ensures that your website becomes a trusted source of information in the eyes of both users and search algorithms.
I’ve noticed that when I leave Performance Max campaigns running without proper setup, they tend to focus on getting easy conversions, often leading to a rise in low-quality leads. While this can quickly rack up conversion numbers, the quality isn’t always great. Google tends to prioritize cheaper conversions, benefiting their revenue, but not necessarily my pipeline.
Many times, brands are surprised by these results after following Google’s sales advice too closely. Although low CPA metrics look tempting, they can often mask the fact that these new leads aren’t contributing to the real growth of my business.
That said, with the right adjustments, Performance Max can be optimized to generate high-quality leads. Building these ‘guardrails’ effectively is key to success, and I’m here to share what I’ve learned.
This guide will walk you through which strategies work for improving lead quality, tactics that don’t deliver desired results, and the notable differences between using Performance Max in Google versus Bing.
How to Improve Lead Quality in PMax Campaigns
Here are the actionable steps I’ve found to consistently impact lead quality:
Focus on conversion goals that align with higher quality targets. Try targeting metrics like closed-won leads or sales-qualified leads, which provide more valuable insights than just form fills. For this to work, ensure my CRM is accurately tracking offline conversions.
Utilize high-value audience signals. Target more specific behaviors, such as users who have ‘booked a meeting’ rather than just anyone who converts.
Concentrate on the correct audiences. Exclude irrelevant segments, and use Customer Match to help Google’s algorithms find users similar to my best customers.
Optimize campaign settings smartly. Examples include using brand exclusions, targeting high-performing geos, strategic scheduling, analyzing search themes, and employing site link extensions to channel traffic efficiently.
Refine forms for better lead filtering. Integrate reCAPTCHA to deter bots, implement field validation to block disposable domains, and include quality-check questions such as how they heard about my company or if they have budget allocations.
Some common optimizations don’t significantly enhance lead quality:
Switching bid strategies offers minimal impact.
Adding more assets or budget doesn’t inherently improve lead caliber.
I’ve learned to be cautious when seeking help from Google support, as results can vary.
Important Differences Between Google and Bing PMax Campaigns
Google and Bing both offer Performance Max campaigns, but they differ significantly. Google’s expansive network includes search, display, YouTube, discovery campaigns, and Gmail. If not carefully managed, this can lead to spam-driven conversions, particularly from display and YouTube.
Bing’s campaigns, on the other hand, focus on Bing search and their audience network, which covers display, Outlook, and MSN. I haven’t observed significant performance differences, but staying updated with platform changes is crucial.
Performance Max Isn’t Broken, but It Needs Control
Entering PMax for lead generation with caution is a wise approach. Although promising for ecommerce revenue, lead quality demands stringent campaign guidelines. For instance, preventing misaligned conversions for a luxury retailer requires effective PMax guardrails.
Considering Google’s shift towards automation and AI, it’s essential to continuously test and adapt. Recent updates like channel-level reporting and exclusion options offer new tools to shape my campaigns.
Achieving quality leads and a healthy ROI is possible by navigating the algorithm strategically. If past PMax efforts were paused due to poor returns, revisiting and applying lessons learned could significantly improve future outcomes.
Every day, millions turn to ChatGPT for answers, but have you noticed your brand isn’t included in those results? I’ve been there, wondering why my brand isn’t gaining visibility and how to change that. If you’re like me and want to understand what’s happening, I’ve gathered the seven main reasons why ChatGPT might be ignoring your brand.
Understanding these reasons is the first step to making a change. You’ll learn specific steps to enhance your visibility in AI searches, and I can tell you from experience, it’s worth the effort.
Perhaps you’re wondering: what can I do to ensure my brand stands out? Don’t worry, I’m here to guide you through actionable strategies for gaining prominence in AI search results.
Let me guess: I just spent three months meticulously crafting an optimized product taxonomy, complete with schema markup, internal linking, and standout metadata.
Then, out of nowhere, the product team decided to launch a site redesign without looping me in. Now half of my URLs are broken, the new templates have stripped away my structured data, and my boss is wondering why our organic traffic plummeted by 40%.
Sound familiar?
Here’s the thing: this isn’t an SEO failure, but a governance failure. It’s been costing us countless nights and weekends trying to fix problems that never should have occurred.
This article sheds light on why weak governance keeps breaking SEO, how AI advancements have raised the stakes, and how a visibility governance maturity model can help SEO teams transition from firefighting to prevention.
Governance isn’t bureaucracy – it’s your insurance policy
I know what you’re thinking. “Great, another framework that means more meetings and approval forms.” But hear me out.
The Visibility Governance Maturity Model (VGMM) isn’t about creating red tape. It’s about establishing clear ownership, documented processes, and decision rights that prevent your work from being accidentally destroyed by teams who don’t understand SEO.
Think of it this way: VGMM is the difference between being the person who gets blamed when organic traffic tanks versus being the person who can point to documentation showing exactly where the process broke down – and who approved skipping the SEO review.
This maturity model:
Protects your work from being undone by releases you weren’t consulted on.
Documents your standards so you’re not explaining canonical tags for the 47th time.
Establishes clear ownership so you’re not expected to fix everything across six different teams.
Gets you a seat at the table when decisions affecting SEO are being made.
Makes your expertise visible to leadership in ways they understand.
The real problem: AI just made everything harder
Remember when SEO was mostly about your website and Google? Those were simpler times.
Now I’m trying to optimize for:
AI Overviews that rewrite your content.
ChatGPT citations that may or may not link back.
Perplexity summaries that pull from competitors.
Voice assistants that only cite one source.
Knowledge panels that conflict with your site.
And I’m still dealing with:
Content teams who write AI-generated fluff.
Developers who don’t understand crawl budget.
Product managers who launch features that break structured data.
Marketing directors who want “just one small change” that tanks rankings.
Without governance, I’m the only person who understands how all these pieces fit together.
When something breaks, everyone expects me to fix it – usually yesterday. When traffic is up, it’s because marketing ran a great campaign. When it’s down, it’s my fault.
I become the hero the organization depends on, which sounds great until I realize I can never take a real vacation, and I’m working 60-hour weeks.
What VGMM actually measures – in terms you care about
VGMM doesn’t care about your keyword rankings or whether you have perfect schema markup. It evaluates whether your organization is set up to sustain SEO performance without burning you out. Below are the five maturity levels that translate to your daily reality:
Level 1: Unmanaged (your current nightmare)
Nobody knows who’s responsible for SEO decisions.
Changes happen without SEO review.
You discover problems after they’ve tanked traffic.
You’re constantly firefighting.
Documentation doesn’t exist or is ignored.
Level 2: Aware (slightly better)
Leadership admits SEO matters.
Some standards exist but aren’t enforced.
You have allies but no authority.
Improvements happen but get reversed next quarter.
You’re still the only one who really gets it.
Level 3: Defined (getting somewhere)
SEO ownership is documented.
Standards exist, and some teams follow them.
You’re consulted before major changes.
QA checkpoints include SEO review.
You’re working normal hours most weeks.
Level 4: Integrated (the dream)
SEO is built into release workflows.
Automated checks catch problems before they ship.
Cross-functional teams share accountability.
You can actually take a vacation without a disaster.
Your expertise is respected and resourced.
Level 5: Sustained (unicorn territory)
SEO survives leadership changes.
Governance adapts to new AI surfaces automatically.
Problems are caught before they impact traffic.
You’re doing strategic work, not firefighting.
The organization values prevention over reaction.
Most organizations sit at Level 1 or 2. That’s not your fault – it’s a structural problem that VGMM helps diagnose and fix.
VGMM coordinates multiple domain-specific maturity models. Imagine it as a health checkup that evaluates all your vital signs, not just one metric.
It evaluates maturity across domains like:
SEO governance: Your core competency.
Content governance: Are writers following standards?
Performance governance: Is the site actually fast?
Accessibility governance: Is the site inclusive?
Workflow governance: Do processes exist and work?
Each domain gets scored independently, then VGMM looks at how they work together. Because excellent SEO maturity doesn’t matter if the performance team deploys code that breaks the site every Tuesday or if the content team publishes AI-generated nonsense that tanks your E-E-A-T signals.
VGMM produces a 0–100% score based on:
Domain scores: How mature is each area?
Weighting: Which domains matter most for your business?
Dependencies: Are weaknesses in one area breaking strengths in another?
Coherence: Do decision rights and accountability actually align?
The final score isn’t about effort – it’s about whether governance actually works.
Most importantly, VGMM translates your expertise into language that leadership understands. It protects your work from accidental destruction, so you can focus on strategic, creative, growth-focused work that truly matters.
I recently came across an intriguing study by SALT.agency, focused on Google’s AI Mode and its citation practices. Contrary to popular belief, this analysis shows that AI Mode doesn’t have a preference for content placed “above the fold.”
After sifting through over 2,300 URLs cited by AI Mode, researchers discovered no link between a text’s vertical position on a page and its likelihood of being cited by Google.
Pixel depth is irrelevant. The study revealed that AI Mode pulls text from all over a page, even from content located thousands of pixels down.
Page layout vs. content visibility. While different layouts like large hero images or narrative formats might push text deeper down the page, this doesn’t impact whether it gets cited.
Subheadings make a difference. One key pattern identified was AI Mode’s tendency to highlight a subheading and the subsequent sentence. This suggests Google’s heading structures are crucial for content navigation.
Google’s approach. The assumption is that AI Mode employs fragment indexing technology, breaking pages into sections and pulling the most relevant fragment, irrespective of its position.
Dan Taylor, a partner at SALT.agency, confirms that there’s no secret formula for appearing in AI Mode citations. The focus should always be on crafting well-structured, authoritative content that meets customer needs.
Our takeaway. This study challenges the notion that specific AI-focused templates or rigid structures enhance content visibility in AI Mode. The real work lies in creating meaningful, structured content.
Research background. SALT scrutinized 2,318 URLs in AI Mode responses. The vertical pixel position of each cited fragment was meticulously recorded using a Chrome bookmarklet and a 1920×1080 viewport.
