Category: SEO

Strengthen Your SEO Results with Effective Agency Collaboration

From the very first kickoff to the technical execution phases, I’ve learned that the true value of hiring an SEO agency lies in our partnership and collaboration. Together, we can eliminate bottlenecks, empower cross-functional teams, and clearly demonstrate the ROI of our SEO investment.

Hiring an SEO agency can truly transform how your brand stands out in search results. But remember, an agency’s effectiveness relies heavily on the partnership we build. Realizing the full potential of SEO requires a shared commitment to our goals and maintaining high momentum.

Here’s what I’ve discovered about maximizing the benefits of working with my SEO agency: Alignment leads to faster progress, which makes it easier for us to prove the value of our efforts.

To ensure we get the most out of this partnership, it’s crucial to align our SEO strategy with what truly drives our business. The company sets the business goals, and it’s the agency’s job to attract the traffic that helps achieve them.

Having open discussions with the agency about how to align these goals right from the start enhances the effectiveness of our SEO program. Including cross-departmental stakeholders only reinforces the alignment and ensures everyone is on the same page.

When the entire team understands the foundation of SEO, they can comprehend its role and their contribution to its success. In this spirit of collaboration, I facilitate SEO training across teams to empower everyone involved.

I always come to the kickoff meeting fully prepared, ready to set agendas for productivity. Sharing pain points, detailing business operations, and clarifying the program’s scope helps everyone understand what to expect and what’s expected of them.

Regular communication with my agency, whether through emails, Slack, or meetings, is vital. Clear reporting methods are another key aspect, ensuring everyone remains accountable and the results are measurable.

Switching from seeing the agency as just a vendor to viewing them as a true expert partner helps cultivate trust in their guidance, the very reason I hired them in the first place.

By giving our agency visibility into past and present performance data, I ensure they have all vital information for optimizing our SEO efforts from day one. This setup includes access to essential tools and crucial performance metrics.

SEO isn’t just an isolated activity—it requires contributions from multiple teams within the company. By including team leaders early in planning, I make sure everyone is engaged and accountable, from SEO briefings to content collaboration.

My agency excels in SEO, but I bring invaluable brand knowledge to create content that aligns both with business goals and customer needs. By maintaining active involvement in content development, we produce material that truly resonates.

Streamlining content reviews and setting clear guidelines helps eliminate approval hurdles that can slow down our SEO progress. Prioritizing high-impact tasks ensures we stay competitive in search results.

Each implementation, however small, contributes significantly to our overall SEO success. I prioritize these tasks during planning phases and involve technical teams early to ensure seamless execution.

Maintaining engagement with my agency beyond the initial excitement stage is crucial for ongoing success. Continual communication, involvement in reviews, and flexibility help adjust to shifting business landscapes effectively.

Ultimately, strong SEO results are built on strong partnerships. By working together, my agency and I drive our SEO program forward, creating a strategic and valuable business initiative.

Inspired by this post on Search Engine Land.

February 16, 2026
Cloudflare’s Markdown Feature: A Game Changer or a Cloaking Risk?

Yesterday, I stumbled upon some exciting news from Cloudflare. They’ve introduced a feature called Markdown for Agents, which provides machine-friendly versions of web content alongside the traditional pages we all see.

Cloudflare describes this update as a proactive measure in response to increasing AI crawler activities and agentic browsing.

When a client requests text/markdown, Cloudflare fetches the HTML from the origin server, converts it right at the edge, and then hands over a Markdown version.

Interestingly, the response includes a token estimate header, which helps developers like me manage context windows more effectively.

Early feedback highlighted not only the efficiency gains but also the potential implications of offering alternate representations of web content.

What’s happening. Being part of the 20% of the web that Cloudflare powers, I learned that Markdown for Agents utilizes standard HTTP content negotiation. If a client sends an Accept: text/markdown header, Cloudflare immediately converts the HTML response on-the-fly to Markdown format. The response, marked with Vary: accept, ensures caches store separate versions.

Cloudflare views this opt-in feature as a shift in content discovery and consumption, benefitting AI crawlers and agents with its structured text that requires less overhead.

They claim Markdown can reduce token usage by up to 80% compared to HTML, which is quite impressive!

Security concern. SEO consultant David McSweeney raised a concern, citing that Cloudflare’s Markdown for Agents feature might make AI cloaking incredibly simple because the Accept: text/markdown header tips off origin servers that the request is AI-related.

Regular requests deliver the usual content, but those for Markdown can trigger a unique HTML response that gets converted for AI consumption, McSweeney explained on LinkedIn.

The worry is that sites might inject hidden instructions, altered product data, or other machine-only content, creating a hidden “shadow web” for bots, unless the header is stripped before reaching the origin.

Google and Bing’s markdown smackdown. Here’s the kicker. Representatives from Google and Microsoft advised against creating separate markdown pages for large language models. Google’s John Mueller noted:

“Given that LLMs have always trained on and parsed normal web pages, it seems obvious they have no issues with HTML. Why serve a page that no end user sees? Plus, if they validate equivalence, why not stick to HTML?”

Microsoft’s Fabrice Canel added:

“Do you really want to double crawl load? We’ll check for similarity anyway. Non-user versions (like crawlable AJAX) are often neglected and broken. Human oversight fixes both user and bot views. Schemas help, and AI makes us even better at deciphering web pages. Less is more in SEO!”

Cloudflare’s feature doesn’t generate another URL but does create varied representations based on request headers.

The case against markdown. Technical SEO consultant Jono Alderson pointed out that once a machine-targeted representation exists, platforms must choose to trust it, verify it against the human version, or outright ignore it:

“Flattening a page to markdown doesn’t only remove clutter. It strips away judgment and context.”

“The instant you publish a machine-exclusive page representation, you craft a secondary candidate version of reality. Regardless of source promises or claims of identical content, a system now views two representations and must determine the true reflection of the page.”

Dig deeper. Why LLM-only pages aren’t the answer to AI search

Why we care. With Cloudflare’s advancements, AI ingestion might become more cost-effective and streamlined. But does serving distinct content to humans and crawlers verge on cloaking? Stay tuned…

Inspired by this post on Search Engine Land.

February 13, 2026
Top AI Search Engines to Boost Your Brand’s Visibility

As I dive into the ever-evolving world of AI search engines, I find myself asking: which one should my brand optimize for first? The options are plentiful, with ChatGPT, Google AI Overviews, Perplexity, Bing, and others vying for attention. The goal is clear: prioritize AI visibility leading into 2026, but the path there is not so straightforward.

Each of these AI platforms offers unique features and potential benefits that can cater to different business needs. It’s crucial for me to assess their capabilities and align them with my brand’s strategic objectives. Whether it’s the conversational prowess of ChatGPT or the data-rich insights from Google AI Overviews, the choice has to drive brand value.

In the process of optimization, understanding the nuances of each platform helps to leverage their full potential. By comparing these engines, I can tailor my approach, ensuring my brand stays ahead in AI visibility, making informed decisions today that will resonate in the future.

Inspired by this post on HiGoodie Blog.

February 13, 2026

Stop Chasing SEO Rankings: Build a Robust Visibility System

I’ve learned that SEO is evolving beyond just marketing and into the realm of organizational design. It’s about structuring, validating, and aligning information across the business to enhance visibility.

When our information becomes fragmented, visibility suffers, leading to more than just rank instability; it threatens our brand’s interpretation and mentions.

For those of us leading SEO, the choice is clear: remain as channel optimizers or become architects of systems that define brand understanding and citation. With AI systems now assembling information at scale, this transformation isn’t happening in isolation.

The visibility shift beyond rankings

As we look to the future, LLMs will shape organic search alongside traditional algorithms. Simply chasing rankings isn’t enough. We need to optimize for interpretation, citation, and synthesis across AI systems.

While our click rates may vary, the real transformation means treating visibility as an interpretation issue rather than just positioning. AI systems rely on cohesive data, narratives, and mentions. Discrepancies lead to inconsistent output.

Now, collaboration can’t be casual. LLMs demand clarity and consistency in the information they process. When our messages and data are fragmented, so too is our visibility.

This is a leadership challenge. Our visibility shouldn’t exist in silos but as a system that manages information creation, validation, and distribution across our organization.

If we want structural visibility, we must build the system to support it.

```json
{
"alt": "Flowchart of the visibility supply chain with gates for strategic relevance, SEO, content quality, UX, and distribution.",
"caption": "Discover the visibility supply chain! Navigate through strategic relevance, SEO fundamentals, content value, user engagement, and more to achieve maximum online visibility.",
"description": "This image illustrates the visibility supply chain, presenting a series of gates aimed at optimizing content visibility. Starting with raw content, it proceeds through Gate 1 (Strategic Relevance), Gate 2 (Technical SEO Fundamentals), Gate 3 (Content Quality & Value), Gate 4 (UX & Engagement), and Gate 5 (Distribution & Amplification), ultimately achieving Maximum Visibility. Each stage addresses key questions like alignment with business goals, crawlability, uniqueness, user interaction, and audience reach, presenting a structured approach to enhancing digital content visibility."
}
```

Building the visibility supply chain

I’ve realized that collaboration needs to be ingrained in the supply chain. It shouldn’t rely on the relationship between the SEO manager and PR manager.

For a seamless transition from a marketing silo to an operational framework, we must treat content as a product needing precise refinement before entering the broader ecosystem.

Enter visibility gates—nonnegotiable checkpoints filtering brand data for AI consumption.

Implementing visibility gates

Think of our content moving through a pipeline. At each joint, a gate refines the output:

The technical gate (parsing)
- Does the product page template use valid schema.org markup (product, FAQ, review)? The goal here is to ensure that the data is structured for seamless AI consumption.
The brand signal gate (clustering)
- Does our PR align with core entities? Are we using consistent terminology to help LLMs cluster our brand? This phase aims to prevent linguistic drift.
The accessibility/readability gate (chunking)
- Is the content ready for RAG systems? Here, we focus on delivering high-information-density prose suitable for AI retrieval.
The authority and de-duplication gate (governance)
- Does this asset induce “knowledge cannibalization” or unnecessary noise? This step filters out conflicting information to ensure a single source of truth.
The localization gate (verification)
- Is entity information consistent globally? This ensures alignment in cross-referencing data to build trust in models.

While gates guard the ecosystem entry points, accountability is key to ensure changes translate into actions.

Embedding visibility into cross-functional OKRs

Alignment without visible results can’t sustain change. Sophisticated infrastructure will fail without cross-functional influence.

To advance beyond mere collaboration, visibility must be embedded into our organizational performance strategy.

We need shared visibility OKRs, not just SEO-specific goals.

When stakeholders are incentivized with visibility KPIs, SEO becomes more than just a team job. It becomes a vital business priority.

For product teams: “Achieve 100% schema validation and <100ms time-to-first-byte for top-tier entity pages.”
For PR and communications: “Increase ‘brand-as-a-source’ citations in LLM responses by 15%.”
For content teams: “Ensure 90% of new assets meet ‘high information density’ for RAG retrieval.”

This collective focus aligns our organization with modern search engine mechanisms.

Measuring visibility across the organization

While gates assess the quality entering our ecosystem, a unified dashboard measures output, enhancing transparency.

If PR teams understand which mentions drive AI citations, they’ll focus on authoritative publications rather than any media outlet.

We need to transition from rank reporting to assessing entity health and Share of Model (SoM). This dashboard becomes our brand’s single truth source.

While systems and incentives are important, they need active management.

```json
{
"alt": "Venn diagram titled 'Hacker vs. Convincer' highlighting elements of technical feasibility and organizational buy-in.",
"caption": "Exploring the balance between technical feasibility and organizational buy-in, this Venn diagram reveals the sweet spot for maximum visibility in project management.",
"description": "This Venn diagram titled 'Hacker vs. Convincer' illustrates the intersection between technical feasibility and organizational buy-in. On the left, technical aspects such as code optimization and site speed are highlighted, while on the right, elements like stakeholder management and ROI demonstration are key. The center emphasizes 'Maximum visibility' as the area where technical excellence meets strategic alignment, critical for successful project management. Keywords: Venn diagram, technical feasibility, organizational buy-in, project management."
}
```

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

Join us at Semrush for tools to enhance your brand’s visibility.

Hiring for AI-era visibility

Building a visibility system isn’t enough; we need a workforce matching this model. We should hire beyond generalists, focusing on two pillars: the hacker and the convincer.

Feature	The hacker (technical architect)	The convincer (visibility advocate)
Core mission	Ensuring the brand is discoverable by machines.	Ensuring the brand is supported by humans.
Primary domain	RAG architecture, schema, and LLM testing.	Cross-departmental OKRs, C-suite buy-in, and PR alignment.
Success metric	Share of model (SoM) and information density.	Resource allocation and budget growth.
The gate focus	Technical, accessibility, and authority gates.	Brand signal and localization gates.

The hacker: The engine room

The technical visionary, constantly pushing boundaries. They optimize beyond just search bars, ensuring our brand’s discoverability by AI.

This individual bridges technical insights with business results, ensuring the hacker’s ideas are realized in practice.

Dig deeper: Why governance maturity is a competitive advantage for SEO

Leading the transition in the first 90 days

As we adapt to operational SEO, consider these first steps:

Set the vision: Define what visibility-first looks like for your business.
Take stock of talent: Do you have the hackers and convincers? Evaluate for skills and mindset.
Audit the gaps: Identify and address communication breakdowns between SEO and PR, or SEO and product teams.
Shift the KPIs: Focus on authority, impressions, sentiment share, and revenue, not just rankings.
Be radically transparent: Share data in real time, without siloed thinking.

During the first 90 days, focus on:

Days 1-30 (Audit): Map your brand’s entity footprint to identify conflicts.
Days 31-60 (Infrastructure): Integrate visibility gates into your CMS or project management tools like Jira or Asana.
Days 61-90 (Incentives): Link 10% of PR and product teams’ bonuses to entity integrity or citation growth in AI.

The SEO leader as a systems architect

As AI advances, an effective SEO leader transitions to becoming a systems architect, crafting the infrastructure for both machine and human brand interactions.

This journey is complex, demanding upfront changes to ingrained processes and transparent communication.

The future goes beyond keywords to optimizing how information flows through the digital ecosystem, embracing this transition will build a resilient organization visible by default.

Dig deeper: AI governance in SEO: Balancing automation and oversight

Inspired by this post on Search Engine Land.

February 13, 2026

Boost Your News Visibility in Google’s Social-First Era

We’re stepping into an era where the visibility of web content is spreading across a multitude of search and social platforms. Google has always been a force to reckon with, but it’s no longer the only player in the search experience. Video-based social media platforms like TikTok and community sites such as Reddit are carving out spaces as go-to search engines for their dedicated audiences.

This evolving landscape is reshaping how we consume news content. Google’s news SERP is adapting to the era of personalized query responses afforded by LLMs and the influence of social media platforms. To keep up, Google has introduced AI-powered SERP features like AI Overviews and AI Mode. These features prioritize content that is “helpful, reliable, and people-first,” drawing heavily from social media platforms.

As search and social media intertwine more closely than ever before, we need to embrace a new strategy. This involves creating newsroom teams comprising social media experts, SEO specialists, and AI enthusiasts working together towards a unified content visibility goal.

When I optimize news content for social platforms, I also consider the potential performance of these posts on the Google SERP. I’ll delve into optimizing specific SERP features, but first, let’s explore making news content friendly for social platforms.

First, let me offer some sanity tips. It’s tempting to optimize content for every social media platform, but I find it more effective to focus on one or two where my audience is active and my growth opportunities are highest. By reviewing analytics and conducting audience surveys, I can identify the platforms where my audience consumes news content.

Optimize News Content for Social Media Platforms

I begin by considering how my content might appear on different platforms. Here’s my breakdown of which content types work best on each platform and how they might appear on Google:

YouTube

Creating YouTube video content involves following video SEO best practices. With guidance from this comprehensive YouTube SEO guide, I create a successful video strategy by ensuring my video titles align with the content.

Google prioritizes YouTube’s search ranking through relevance, engagement, and quality. I make sure my metadata accurately reflects my video content to ensure it stands out as relevant in a search.

One trend I’ve noted is that older event content on YouTube continues to rank well on Google, even after related articles have faded. Similarly, explainer videos show longevity on the SERP.

Facebook

Facebook, though perhaps not as trendy as it once was, still reaches a diverse audience. This platform excels with community-based content and entertainment news that incites conversation.

Even though Facebook’s dedicated news tab was removed, its posts are becoming more visible on Google’s SERP, which might make it worth reconsidering from a search perspective.

X

Since Elon Musk’s takeover, X’s audience has shifted more to the political right, while its role as a hub for breaking news, live updates, and political content remains strong. Sports content also performs well here, especially in the U.S.

Instagram

For Instagram, focusing on visually-driven stories, such as celebrity fashion and health topics, is key. The platform also performs well for sports highlights, often appearing in Google’s dedicated publisher carousel or “What people are saying.”

Reddit

Reddit’s unique user base requires a specific strategy to engage niche communities outside other platforms. Whether the content is about tech trends, health, or sports, it’s crucial to understand Reddit’s audience and adhere to its guidelines.

TikTok

The predominantly young, diverse user base on TikTok gravitates towards visual, conversational, and opinion-based content. Short-form videos that are authentic and engaging perform best.

Pinterest

Pinterest might be old-school, but it’s growing with Gen Z, making it ideal for lifestyle content. When I create on Pinterest, I focus on fashion, DIY, and motivational content, using high-quality visuals and a more relaxed posting schedule.

Social Content Opportunities by Google SERP Feature

Understanding how social content appears in different SERP features helps me maximize visibility. For instance, Top Stories capture breaking news while the “What people are saying” feature emphasizes emotionally engaging user-driven content.

Threat or Opportunity?

Instead of viewing social media content on Google’s SERPs as competition, we can leverage it as an opportunity to increase visibility. Our focus should be on integrating social-forward strategies to expand brand engagement and not solely relying on traditional SEO tactics.

Inspired by this post on Search Engine Land.

February 13, 2026
Why SaaS AI Traffic Declined by 53%: Insights and Lessons

I recently discovered some fascinating insights into what’s really behind the 53% drop in SaaS AI traffic. It turns out, AI traffic isn’t actually collapsing—it’s just becoming more focused. While Copilot experiences a surge in in-workflow engagement, a significant 41% lands on search pages, all influenced by the ebbs and flows of Q4 budget cycles.

As the SaaS market navigates a downturn, driven largely by the emergence of autonomous AI agents like Claude Cowork, new data reveals a substantial 53% decline in AI-driven discovery sessions. This phenomenon has been dramatically labeled the “SaaSpocalypse” by Wall Street.

The overarching question of whether AI agents will eventually replace SaaS products looms larger than what this particular dataset can resolve. However, amidst the panic, the data offers clarity for SEO teams, highlighting key areas they should be monitoring closely.

Between November 2024 and December 2025, the SaaS sector experienced 774,331 sessions driven by large language models (LLM). Interestingly, ChatGPT was responsible for 82.3% of this traffic, yet Copilot’s remarkable growth tells a unique story.

Copilot started with a modest 148 sessions at the close of 2024, only to expand more than twentyfold by May 2025. From there, it averaged 3,822 sessions monthly from June through December, emerging as the second biggest AI referrer by year-end 2025.

This data indicates that while investor sentiment wiped out $300 billion from SaaS market caps over concerns about AI replacing enterprise software, the real driver of change is occupancy in the workflow. Copilot is flourishing because it seizes the moment of intent within a given task. By comparison, standalone AI tools suffered a steep 53% traffic drop, while workflow-embedded AI solutions saw an exponential 20x growth.

AI-led SaaS discovery predominantly directs users to internal search pages rather than directly to product or pricing pages. Over 320,615 sessions were directed to search results—surpassing blogs, pricing, and even product pages—reflecting potential LLM shortcomings rather than content superiority. Essentially, when LLMs lack direct answers, they lean on internal search as a fallback.

This scenario isn’t detrimental but points to a crawlability issue that can be rectified; it underscores the importance of well-structured, indexable search pages. Smart design strategies can ensure that your internal search feature becomes an effective API for AI agents.

Seasonal work cycles also play a role. SaaS AI traffic hits its zenith in July, attributable to active work cycles and available Q3 budgets, before waning through Q4 due to holiday pauses and budget limitations, following typical B2B purchase patterns.

For SEO teams out there, it’s crucial to concentrate efforts not merely based on traffic numbers but on penetration rates and landing page relevance. Consider tracking AI traffic by page type, ensuring indexability of search results, and structuring both pricing and blog content to be LLM-friendly by making crucial data visible and accessible.

In essence, AI discovery is here to stay, but to thrive in this evolving landscape, SaaS companies must enhance their visibility. Those who invest in transparent, crawlable, and comparison-centric content now are setting themselves apart in a competitive space.

Inspired by this post on Search Engine Land.

February 12, 2026
Explore Google’s WebMCP: Revolutionizing AI Web Interactions
Is this the new technical SEO frontier? This question is top of mind for many of us as Google has recently unveiled an early preview of WebMCP, a protocol shaping the way AI agents engage with websites. According to André Cipriani Bandarra from Google, “WebMCP aims to provide a standard way for exposing structured tools, ensuring AI agents can perform actions on your site with increased speed, reliability, and precision.”

WebMCP offers developers the capability to communicate with LLMs through our websites about the specific actions that various buttons and links should initiate. With this protocol, websites can publish a “Tool Contract” using the new browser API, navigator.modelContext. This means rather than leaving the AI to guess, our websites can present a structured list of functions, like buyTicket(destination, date), allowing the AI to execute these functions directly.

Structured interactions for the agentic web. WebMCP introduces two new APIs enabling browser agents to act on behalf of users:
- Declarative API: This offers standard actions that can be simply defined within HTML forms.
- Imperative API: For more complex, dynamic interactions that need JavaScript execution.
These APIs serve as a crucial bridge, making our websites “agent-ready” and facilitating more reliable and high-performance agent workflows compared to raw DOM actuation.

Use cases that Google has put forward highlight how AI agents can tackle complex tasks efficiently and confidently for users:
- Travel: With structured data, agents can help users search for, filter, and book the exact flights they want, ensuring accuracy in results.
- Customer support: Agents can automatically populate detailed customer support tickets, filling in all required technical details without user intervention.
- Ecommerce: Enhancing shopping experiences where agents can locate, configure, and navigate purchasing options flawlessly.
How to access the preview. If you’re interested in trying out WebMCP, you can apply for the preview through this link.

Why we care. The advent of agentic experiences marks a significant shift in search and potentially SEO. Esteemed voices in the industry, such as Dan Petrovic and Glenn Gabe, have highlighted this as a pivotal transformation, comparable to the impact of structured data and described it as a big deal.

Exploring these cutting-edge protocols could be extremely valuable for anyone keen on staying at the forefront of SEO developments.

Inspired by this post on Search Engine Land.
February 11, 2026
AI Search Impact: Revealing Attribution and Buying Decisions

AI search has a subtle impact on trust, sales velocity, and potential client shortlists, which often isn’t reflected in analytics data. These insights came to light through a series of revealing experiments I’ve been involved in.

It was a chance encounter with a new prospect who mentioned, “I actually found you via Grok.” That was a pivotal moment for me. Not only had we not attempted to rank on Grok, but we also weren’t monitoring it. Yet, here it was, influencing potential buyers’ search and evaluation processes.

This realization permeated conversations with other clients; fascination with AI search was rampant, but there was skepticism regarding data credibility. Many wanted visibility on platforms like ChatGPT but hesitated due to unclear attribution.

So, I embarked on structured testing using resources I could control entirely—our agency website, personal experiments, e-commerce ventures, and select domains for testing purposes. The goal wasn’t to attain AI rankings but to decode which elements remain crucial once AI integrates into buying decisions.

These inquiries involved figuring out if AI search altered purchasing preferences or merely the ranking of brands. Additionally, I wanted to understand if revenue metrics could be influenced by AI visibility without hitting the analytics tracking radar and how AI-driven recommendations might affect performance across other channels.

I realized early conversations around AI search revolved around visibility metrics—think brand citations, visibility screenshots from AI tracking platforms, and more. I believed that the primary role of search remains to aid decision-making. My experiments aimed to determine if AI search retained this capability and transformed business outcomes.

Focusing on measurement was crucial. Instead of just relying on API data—which often diverges from user interactions—I observed live interfaces of ChatGPT, Perplexity, Gemini, and Google AI Overviews. Prompt tracking aided in identifying patterns but was not a definitive gauge of success.

During my first experiment, the creation of self-promotional ‘best of’ lists on my own website revealed fascinating insights. Agencies frequently leveraged a tactic where they placed themselves atop ‘best X’ lists, allowing AI systems to inadvertently amplify their prominence.

Inspired by Glen Allsopp’s extensive research, which highlighted how ‘best’ lists were frequently cited by ChatGPT, I tested the findings on my brand webpage. I was intrigued by the rapid visibility of my site, LawrenceHitches.com, across AI platforms for queries like “best SEO agency Sydney.”

However, ranking visibility alone lacked significance. Similarly, when I fabricated a landscaping site to further test self-promotional tactics, it also appeared swiftly in AI responses, reaffirming visibility alone’s limited value.

Through these experiments, it became evident that while AI simplifies appearing on search radars, building and sustaining trust remains pivotal—a sentiment ringing true from the likes of Wil Reynolds. Self-lauding across one’s platform may catalyze skepticism rather than assurance.

I’ve also seen how prompt tracking tools became popular, with demand from clients ever-increasing. Yet, reliability remained a challenge. Surfer SEO research suggested brands often appeared differently in API outputs versus real user sessions. With overlap sometimes as low as 24%, discrepancies remind us that prompt appearances could be misleading.

This is where the narrative eases away from where brands show up and involves questioning efficacy: How did AI influence sales velocity? Did consultations eliminate the need for education? Was buying speedily initiated?

I discovered that signals—where leads factored AI tools into decision-making without prompting—started appearing, shaking traditional attribution’s foundation. A telling instance was Kadi, an e-commerce brand we support, encountering a buyer who, influenced by AI, engaged in a thorough purchasing journey yet showed attribution through Instagram.

For Kadi, digital PR efforts garnered visibility spurt, but gaps in fundamentals meant traditional SEO foundation work was essential to move past quick traction and truly compete. AI played a silent role in buyer decisions, even when attribution data failed to capture its essence.

My journey with StudioHawk provided another layer of understanding. Post a rebranding and digital migration, SEO emerged as a potent channel, complemented by AI leads that became more recurrent.

Sales processes further illustrated the transformation, where AI-affected leads saw reduced education requirements and minimized objections, closing deals notably faster than traditional SEO leads. The blend of ChatGPT, Perplexity, and Grok-influenced conversions stood testament to AI’s influence, even as traditional paths remained evasive in attribution reporting.

Throughout these endeavors, I’ve realized that while AI doesn’t redefine discovery, it compresses consideration significantly. The buyer’s journey is evolving beyond static funnels. AI provides succinct answer summaries, reshaping the ‘messy middle’ where amenities like risk reduction, vendor shortlisting, and trust assurance occur.

It’s evident AI aids decision-making once foundational trust is laid. Traditional SEO confirms search engines recognize your entity, but its real value is now within supporting thoughtful content that pre-sells your services.

So, as I reflect, brands need to realign focuses. Record where AI’s footprints actually land beyond mere appearances. Prioritize intelligibility over creativeness in content. Opt for consistency in entity-driven narratives and prioritize content resonating with comparison and risk evaluations.

Inspired by this post on Search Engine Land.

February 11, 2026
Unlock AI Insights: New Bing Webmaster Tools Feature

Today, I stumbled upon some exciting news from Microsoft. They have officially launched the AI Performance feature in Bing Webmaster Tools, albeit in beta. Now, I have a tool that lets me see where and how often my content is cited in AI-generated answers across platforms like Microsoft Copilot and Bing’s AI summaries.

What I find particularly useful is how AI Performance details exactly which URLs from my website are cited, the queries that trigger those citations, and how this activity evolves over time. It feels like a game-changer for understanding my content’s footprint in the AI domain.

Initially, Search Engine Land reported on January 27 that Microsoft was testing the AI Performance report. Today, I can tell you firsthand that this new dashboard in Bing Webmaster Tools is a treasure trove for tracking citation visibility across AI interfaces.

What’s new? I now have access to a specific dashboard dedicated to AI Performance. Unlike typical SEO tools that measure clicks or rankings, this one reveals if my content is grounding AI-generated answers. Microsoft describes it as an early step toward Generative Engine Optimization (GEO), helping me comprehend how my work appears in AI-oriented discovery.

What it looks like? Thanks to Microsoft, I’ve seen an image of the AI Performance feature in action. It’s sleek and provides clear insights into how my content is performing across AI experiences.

Insights from the dashboard? The AI Performance dashboard offers several new metrics, which include:

Total citations: This tells me how many times my site is used as a source for AI-generated answers over a set period.

Average cited pages: This metric gives me the average number of unique URLs from my site that AI systems reference daily.

Grounding queries: These are sample query phrases that AI systems utilize to retrieve and cite my content.

Page-level citation activity: Showing citation counts by URL, it highlights which pages of mine are popular in AI responses.

Visibility trends over time: I can see a timeline view that shows how citation activity changes throughout different AI platforms.

Though these metrics are informative, they only reflect citation frequency. They don’t give insights into my content’s ranking, prominence, or its specific contribution to AI answers. That’s something I’d have to explore further.

Why I care? Knowing where and how my content is cited is fantastic, yet Bing Webmaster Tools doesn’t yet show how these citations convert into clicks, traffic, or concrete business results. Without click data, it’s still an open question whether AI visibility provides actual value.

How can I use this? Microsoft suggests I utilize this data to:

– Verify which pages of mine already appear in AI answers.

– Spot topics that frequently show up across AI-generated responses.

– Enhance clarity, structure, and completeness on less frequently cited pages.

The advice echoes familiar best practices: maintaining clear headings, evidence-backed claims, up-to-date information, and consistent entity representation.

What comes next? Microsoft has promised improvements in inclusion, attribution, and visibility across both search results and AI experiences, and to keep evolving these capabilities moving forward.

Microsoft’s announcement. For more details, you can check out their announcement here: Introducing AI Performance in Bing Webmaster Tools Public Preview

Inspired by this post on Search Engine Land.

February 10, 2026
Elevate SEO Success with Strong Governance Models
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.

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

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.

Dig deeper: SEO’s future isn’t content. It’s governance

How VGMM works: The less boring explanation

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.

Inspired by this post on Search Engine Land.
February 10, 2026