Tag: Search Optimization

Why AI Search Challenges Persist Across Industries: Insights and Solutions

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.

Explore further: What AI Search Experiments Reveal About Attribution

3 Ways an Industry Can Vanish from AI Search

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.

Explore deeper: Each AI Search Study Tells a Unique Story

The Critical Point You Shouldn’t Overlook

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.

Inspired by this post on Search Engine Land.

March 5, 2026

Transform Your SEO Workflow with Claude Code
Recently, I’ve found myself immersed in Claude Code, especially within Cursor. I’m not a coder by trade; I run a digital marketing agency. But using Claude Code through Cursor has dramatically sped up how I handle critical tasks such as data extraction and analysis from Google Search Console, GA4, and Google Ads.

Setting up this system takes about an hour, but once it’s done, asking questions like “Which keywords am I overpaying for that I already rank for organically?” becomes a breeze. It provides answers in seconds, eliminating the need for tedious hours spent on spreadsheets.

Let me share the step-by-step process I developed for our agency clients. If any of this seems too intricate, simply paste this article’s URL into Claude, and ask it to guide you through the steps.

Ultimately, you’ll build a project directory where Claude Code can access Python scripts that pull live data from your Google APIs. The data is fetched, stored in JSON files, and you’re free to interact with it without the need for dashboards or complex templates.
```
 
seo-project/
├── config.json               # Client details + API property IDs
├── fetchers/
│   ├── fetch_gsc.py         # Google Search Console
│   ├── fetch_ga4.py         # Google Analytics 4
│   ├── fetch_ads.py         # Google Ads search terms
│   └── fetch_ai_visibility.py  # AI Search data 
├── data/
│   ├── gsc/                 # Query + page performance
│   ├── ga4/                 # Traffic by channel, top pages
│   ├── ads/                 # Search terms, spend, conversions
│   └── ai-visibility/       # AI citation data
└── reports/                 # Generated analysis
```
Begin by setting up Google API authentication. This step requires a Google Cloud service account, which covers GSC and GA4. Google Ads, however, requires its own OAuth setup.

Next, you’ll move on to building the data fetchers. Each fetcher is a Python script that authenticates, pulls data, and saves it in JSON format. You won’t need to dive into API documentation either; Claude Code can write the scripts based on simple descriptions of what you want to achieve.

Once you’ve got your data, Claude Code can answer cross-source questions, such as spotting keywords with paid and organic gaps, or analyzing content performance across platforms.

For AI visibility tracking, consider tools like Scrunch or Semrush. Export your data as CSV or JSON to further enhance your insights through Claude Code.

Overall, this workflow takes about thirty-five minutes for a new client and reduces monthly refresh times to about twenty minutes. It saves you from the hassle of manually managing and deciphering data across multiple platforms.

Claude Code enhances your data analysis capabilities, but it’s not a replacement for strategic insight. Remember to verify results just as you would scrutinize work from a new team member.

Inspired by this post on Search Engine Land.
March 4, 2026
Google’s New Patent May Transform Search Results Through AI

Let me clarify—this is just a patent document, a flicker of a possibility, not an immediate change in Google Search.

A recently published patent from Google hints at a potential shift in how we experience search results. It suggests that instead of landing on a standard webpage, searchers might be directed to an AI-crafted page tailored to individual queries.

Patent Details. Known as AI-generated content page tailored to a specific user, this patent was filed about a year ago and approved just last month.

This patent outlines a system using AI to auto-generate personalized landing pages for businesses or organizations. Instead of simply redirecting me to a generic homepage, it aims to deliver a page that’s directly relevant to my search intent and the organization’s offerings.

Patent Abstract. Here’s an overview from the patent itself:

“Techniques for generating an artificial intelligence (AI)-generated page for a first organization. The system can include a machine-learned model configured to generate the AI-generated page. The system can receive from a user device associated with a user account, the user query. Additionally, the system can generate a search result page for the user query. The search result page can include a first result associated with a first landing page of the first organization. The system can calculate a landing page score for the first landing page. The system can generate an updated search result page based on the landing page score exceeding a threshold value, the updated search result page having a navigation link to an AI-generated page for the first organization. The system can cause a presentation, on a display of the user device, the updated search result page.”

Example Scenario. Picture this: I’m searching for “waterproof hiking boots for wide feet” on a site like REI or Amazon. Normally, I’d end up on a general “Hiking Boots” page and have to sift through countless options. But with AI, Google could direct me to a specially tailored page that zeroes in on exactly what I need.

Community Reactions. Brandon Lazovic spotted this, and it was shared by Joshua Squires on LinkedIn stating, “In short, Google would use AI to generate a page that mimics your website but rebuilds it dynamically.” This has raised concerns among professionals. Glenn Gabe noted, “If you thought AIOs angered people, just wait for AI-generated landing pages from Google.” Lily Ray added, “Terrifying to be honest.”

Why It Matters. This is a mere patent and might never see the light of day. However, it’s intriguing to ponder Google’s potential direction and what it could mean for the future of search.

In any scenario, these insights offer a glimpse into the forward-thinking strategies within Google.

Inspired by this post on Search Engine Land.

February 27, 2026
Navigating the New SEO Landscape: Visibility Over Traffic

I’ve noticed a shift in SEO from the traditional “rank, click, and convert” strategy towards a new model that emphasizes being scraped, summarized, and recommended. This change marks the beginning of the dark SEO funnel era, transforming how we measure success in search engine optimization.

Today, up to 84% of B2B buyers use AI tools to discover vendors, and an astounding 68% initiate their search journey with AI rather than Google, according to recent data from Wynter. It’s clear that tools like ChatGPT influence initial decisions, with Google merely acting as a verifier.

If, like me, you’re still considering SEO success through traffic, you’re likely focusing on an outdated model. Here’s what we need to prepare for.

Marketing professionals are already acquainted with the concept of dark social, where sharing happens away from trackable channels. Dark SEO is its algorithmic counterpart, where AI, rather than peers, offers brand recommendations, followed by a Google search for validation.

In this new phase, traditional analytics fail to capture the path from ingestion to recommendation to verification—all obscured within the dark SEO funnel. This gives direct or branded search undue credit, even though the groundwork was laid by SEO.

In this evolving dynamic, Google’s role is changing. A surveyed CMO mentioned using Google only when they know exactly which software or product they want. AI is for evaluation, Google is for verifying—a fundamental shift in our understanding of search behavior.

To succeed, we must understand two visibility types: brand mentions and LLM citations. In traditional SEO, the aim was to get clicks from links. In AI-driven search, it’s about visibility. An LLM could highlight your brand when relevant, impacting how users perceive and search for it.

Brand mentions occur when an LLM explicitly names your brand as a preferred solution—something influenced by your brand’s presence in relevant conversations and media. On the other hand, URL citations represent instances where AI uses your data as a credible source, an opportunity driven by unique data and information gain.

Emphasizing on relevant platforms like review sites and communities helps establish authority. As AI algorithms recognize your brand’s consistent presence, it can become an authoritative recommendation source.

When direct traffic is no longer a primary metric, leadership desires proof that SEO remains effective. This involves measuring more than just clicks. We should pivot to metrics like LLM recommendations visibility, branded traffic, product page visits, and conversion rates.

Ultimately, we’re heading towards a state where brand visibility is the triumph, and traffic is its byproduct. Adapting to this dark funnel era means we need to prioritize inclusion, recommendation, and intent over traditional traffic metrics. By focusing on high-intent queries and third-party visibility, you ensure the strategic progression of your brand in this new SEO landscape.

Inspired by this post on Search Engine Land.

February 27, 2026
Google Resolves Brief Search Result Glitch Overnight

I woke up to some interesting news this morning — Google experienced a minor hiccup in serving search results around 1:30 am ET on Wednesday, February 25th. From what I gather, the issue was resolved swiftly, which is why there weren’t too many complaints flooding in.
Google kindly informed us that, “We fixed the issue with serving search results. There will be no more updates.” It’s always reassuring when they keep us in the loop, isn’t it?
Why I care. If you noticed a sudden drop in your website’s traffic close to midnight, don’t panic. It might very well be linked to this brief serving issue.

Although Google posted about the issue and its resolution almost instantly, it doesn’t necessarily mean the problem lasted just a minute. This was the timeframe they chose to update us.
And here’s the screenshot from the status dashboard notice that caught my eye:

Inspired by this post on Search Engine Land.

February 25, 2026
Master SEO with These 8 Essential Tips for Beginners
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.

Inspired by this post on Search Engine Land.
February 23, 2026
Retire These SEO Metrics to Supercharge Your 2026 Strategy
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.

It’s possible for a competitor with a DA of 35 to outperform my DA of 65 if their content aligns better with search intent. So, let’s keep these out of executive dashboards.

8. Total Backlink Volume

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.

Dig deeper: Measuring zero-click search: Visibility-first SEO for AI results

What to Measure Instead

Revenue and Pipeline Contribution From Organic

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.

Inspired by this post on Search Engine Land.
February 19, 2026
Unlock Enterprise AI Potential with Conductor Data API

I’ve discovered how essential it is to integrate trusted search intelligence across our enterprise. With the Conductor Data API, we’re extending these capabilities in ways I hadn’t imagined.

Seeing our data work harmoniously across platforms feels transformative, allowing us to leverage AI infrastructure like never before. This powerful insight has reshaped how we view our enterprise integration strategies.

Inspired by this post on Conductor Blog.

February 17, 2026
Unlocking the Secrets of Query Fan-Out in AI SEO

When I first stumbled upon the concept of query fan-out, I realized how misunderstood it often is in the world of AEO and SEO. It’s fascinating how AI searches can take a single prompt and transform it into numerous sub-queries, expanding the scope of search in unimaginable ways.
Understanding this process opened my eyes to the hidden potential these sub-queries hold. By leveraging the data generated from them, I discovered new strategies to enhance SEO effectiveness, making my digital marketing efforts more robust.

Inspired by this post on HiGoodie Blog.

January 29, 2026
U.S. Google Searches Drop: The Impact of AI on User Behavior
I recently came across a fascinating Datos/SparkToro report revealing a significant change in our search habits. It’s no surprise that U.S. Google users are searching less than they did a year ago. While Google isn’t losing users, it’s clear they’re experiencing fewer repeat searches.
Why this matters to me. Google still reigns supreme in the search world, but fewer searches mean dwindling opportunities for clicks, ads, and traffic—even if the total search volume seems stable.
The numbers speak for themselves. The report showed a nearly 20% year-over-year decline in desktop searches per U.S. user, based on data from millions of users.
- This sharp decline is unlike the European trend, where searches only fell by 2-3%.
- Despite fewer searches per person, traditional search still constitutes about 10% of all U.S. desktop activity—a share that held steady throughout 2025.
Reasons behind the drop. The rise of AI-powered answers and instant results appears to be the main culprit:
- Users now get the information they need without conducting multiple follow-up searches.
- Zero-click searches remain high but have leveled off in the low-20% range by year-end.
- Little change is observed in repeat searches and clicks within Google-owned properties, hinting at a plateau in user behavior.
The reshaping of search by AI. AI isn’t pulling users away from search; rather, it’s enhancing it. Despite ongoing AI buzz, the report discovered:
- AI tools contribute to less than 1% of total U.S. desktop activity (0.77%), though they’ve seen remarkable growth.
- Google AI Mode remains small, accounting for about 0.06% of U.S. desktop events by December, with steady adoption increase.
Query evolution. One notable behavior change is how we phrase our searches:
- Mid-length queries of six to nine words are increasing rapidly in the U.S.
- Very long queries (15 words or more) are still rare but show significant experimentation and volatility.
- People seem to find it easier to express complex needs directly in their searches.
Discovery becomes a challenge. With concentrated search-driven discovery, breaking into post-search destinations is tougher:
- YouTube, Reddit, Amazon, Wikipedia, and Facebook remain dominant.
- ChatGPT soared to No. 7 among U.S. search destinations, a rare significant mover.
- Meanwhile, Quora has fallen out of the top 15.
AI’s few dominators. AI-driven traffic largely directs users to already established platforms like Google, YouTube, GitHub, and Wikipedia rather than new or independent publishers. When it comes to AI platforms:
- ChatGPT is the leading tool in the U.S., reaching around one-quarter to one-third of desktop AI users.
- Google’s Gemini emerged as a strong No. 2, consistently growing throughout 2025 and surpassing DeepSeek.
- Other tools like Claude, Perplexity, and Copilot stay niche with modest reach.
Industry insight. Rand Fishkin, co-founder and CEO of SparkToro, highlighted in the report:
“The big highlight here is the decline in # of Google searches/searcher from 2024–2025. It’s a nearly 20% decline in the US, though only 2–3% in the EU/UK. Other studies have shown that Google is sending less traffic than in years past, especially to the long-tail of the web, and I suspect that AI answers have dramatically altered the way many users engage with Google, answering their questions before they ever need to click on an organic result or perform a second/third/fourth search.”
The complete report. Discover more in the Q4 State of Search report

Inspired by this post on Search Engine Land.
January 28, 2026