Tag: AI Overviews

Unveiling Google’s AI Overviews: Impact on PPC Revenue
When I first heard about Google’s AI Overviews, I realized they weren’t just going to affect visibility; they had the potential to hit revenue hard. Adthena’s latest data analysis sheds light on just how significant this impact could be on CTR and CPC.

Adthena dove into a detailed study from late December 2025 through January 2026, involving a comprehensive look across six major industries. This involved tracking performance metrics from millions of ads.

While on the surface, aggregate data seemed stable, a closer inspection revealed a more complex reality. For advertisers like myself, these automated summaries don’t just pose visibility issues; they’re a direct threat to PPC revenue.

What AI Overviews Mean for Paid Search Revenue

AI-generated summaries are altering the very structure of successful campaigns. When a Google AI Overview pushes ads below the page fold, it sets off a sequence of events impacting my profitability:
- Lower CTR = fewer clicks: With diminished visibility, there’s a noticeable drop in visits to landing pages, diminishing the traffic flow.
- Fewer clicks = fewer conversions: A decrease in traffic inevitably means fewer leads or sales.
- Higher CPC = reduced profitability: In industries where AI summaries appear on competitive terms, maintaining relevance costs more, squeezing margins and lowering ROAS.
AI Overviews Impact Across Six Industries

Adthena’s study tracked AI Overview frequency, content themes, and CPC/CTR performance across devices. The results paint a complex picture, with impacts varying by industry, device, query type, and content intent.

Content Themes: The Battle for Mid-Funnel Intent

Adthena pinpoints a shift where Google moves deeper into comparison and instructional content spaces, directly targeting high-converting paid search areas.
- The comparison conflict: In Telecom, Technology, and Retail, AI Overviews frequently deliver comparison content, which could satisfy user curiosity prematurely, preventing a further click on my ads.
- The informational buffer: In Healthcare and Financial Services, themes like news and FAQs can act as intent barriers, potentially safeguarding ad spend by meeting low-intent signals before a user clicks on a paid ad.
- The opportunity gap: Problem-solving content remains mostly unaffected at 0-2%. This creates a safe harbor for advertisers, with minimal AI interference in these areas.
CPC Trends: The Premium for Visibility

By tracking CPC fluctuations, I can identify where the cost of visibility is increasing due to the presence of AI Overviews.
- Technology: AI Overview-related queries consistently yield higher CPCs, signaling increased costs for visibility.
- Automotive & Retail: Across these sectors, costs remain similar regardless of AI Overviews, signifying less immediate impact.
- Financial Services: Even modest CPC spikes can significantly impact profitability in industries with already high CPCs.
Device Splits Expose Desktop Saturation

Breaking down data by device reveals notable differences, showing more nuance than initially apparent.
- Desktop dominance: Queries in Technology and Education are heavily populated by AI Overviews, making ad competition unavoidable.
- Mobile opportunity: While AI Overviews appear less frequently on mobile, they more aggressively displace ads due to limited screen space, unlike desktop where multiple ads can sit below the overview.
CTR Trends Provide Evidence of Traffic Erosion

Examining CTR trends reveals ongoing discrepancies between influenced and standard search outcomes.
- Persistent gaps: In Telecom and Technology, lower CTRs with AI Overviews highlight the direct impact on traffic flow.
- Consumer resilience: Financial Services and Retail show narrower CTR gaps, indicating ad preference despite AI Overviews.
- Late month volatility: Spikes in Healthcare showcase rapid performance fluctuations as Google refines its AI deployment.
Distribution Data Reveals the Zero Click Reality

This data layer exposes a winner-take-all dynamic often obscured by average metrics.
- The baseline gap: In the absence of AI Overviews, CTR remains strong across sectors, particularly Retail. However, where AI Overviews are rampant, the gap reveals the complete story.
- High AI Overviews frequency, low CTR: Ubiquitous AI Overviews mean reduced CTR across sectors, including Technology. As frequency climbs, ad traffic capture decreases.
- Resilience in Automotive: Automotive maintains a relatively diverse spread in mid-frequency ranges, suggesting users bypass summaries for brand information.
Three Immediate Steps to Adapt Your Paid Search Strategy

To protect my margins, here’s what I can do:
1. Monitor Click Through Rates (CTR) and Cost Per Click (CPC) changes: Although they don’t provide the complete picture, shifts in CTR or CPC can warn of AI Overview effects.
2. Segment performance by device: By separating desktop and mobile data, I can discover hidden trends that might be blurred in combined reporting.
3. Use Adthena’s free Market Share reports: These reports allow me to understand AI Overview frequency in my category and recognize at-risk areas for visibility.
Gaining Visibility with Adthena’s AI Overview Solution

To grasp AI Overview effects, continuous and detailed query-level intelligence is crucial. Adthena’s AI Overview solution regularly indexes search results, providing advertisers with insights into:
- AI Overviews frequency patterns by query, industry, and device.
- Content themes and citation sources.
- Performance metrics including impact on CPC and CTR.
- Ad position vs AI Overviews.
These insights help advertisers like me detect and address disruptions to revenue before they impact performance.

Coming soon: Adthena’s enhancement to the AI Overviews solution will include visibility into ads within AI Overviews, offering a comprehensive assessment of ad performance throughout the SERP.

The SERP Has Changed: Adapt or Fall Behind

While Google’s AI Overviews are here to stay, their effect isn’t uniform nor unsurmountable. Successful advertisers, like those who are vigilant, understand precisely where and how AI Overviews appear, what content they promote, and how their audience reacts.

Precision is vital. Assumptions lead to downfall.

Book a demo to see exactly how AI Overviews are impacting your campaigns.

Inspired by this post on Search Engine Land.
February 26, 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
Text Ads Soar as Organic Search Declines: Key Study Insights
I’ve recently come across an interesting study highlighting a significant shift in search click dynamics. It turns out that text ad clicks have dramatically increased year over year, while the traditional organic clicks in major verticals have taken a sharp decline.

This transformation isn’t solely due to AI Overviews for sure. Google’s expansion of paid search real estate is playing a pivotal role here. In the U.S., data reveals a steep drop in classic organic click share across product categories like headphones, jeans, greeting cards, and online games between January 2025 and January 2026.

The numbers are quite telling. Classic organic click share fell significantly across these categories, making way for text ads, which emerged as the biggest beneficiaries, gaining a notable share of clicks.

Why does this shift matter to us? As digital marketers, it’s no longer just AI-powered features that we’re contending with. Text ads have won substantial ground, capturing about one-third of the clicks in several product categories. For brands seeing a dip in organic visibility, increasing paid efforts seems to be a necessary strategy.

Numbers tell the story. When diving into four main verticals, text ads showed consistent click-share increases. Classic organic lost between 11 to 23 percentage points, while text ads gained anywhere from 7 to 13 percentage points across the board. Paid click share has doubled in several key product categories.

Comprehensive breakdown: Classic organic click shares have seen a year-over-year decline across all verticals. For instance, headphones lost dramatically, shrinking from 73% to 50%, and even organic-heavy areas like online games dropped by double digits. Such declines emphasize the urgent need for many brands to reassess their search strategies.

Data shows that text ads inched forward share-wise in every industry examined. For instance:
- Headphones: Rose from 3% to 16%
- Online games: Up from 3% to 13%
- Jeans: Climbed from 7% to 16%
- Greeting cards: Up from 9% to 16%
Moreover, Product Listing Ads (PLAs) are further supporting this change in product sectors:
- Headphones: Increased from 16% to 36%
- Jeans: Went from 18% to 34%
- Greeting Cards: Rose from 10% to 19%
AI Overviews have seen a diverse impact. While the presence of Google AI Overviews on SERPs has certainly increased, the extent varies significantly across sectors:
- Headphones: 2.28% → 32.76%
- Online games: 0.38% → 29.80%
- Greeting cards: 0.94% → 21.97%
- Jeans: 2.28% → 12.06%
Zero-click searches remain significant but stable. Even though the overall zero-click rates haven’t seen dramatic changes, online games have witnessed a noticeable uptick:
- Headphones: 63% (unchanged)
- Jeans: Down from 65% to 61%
- Online games: Up from 43% to 50%
- Greeting cards: Increased from 51% to 53%
Brands adapt by increasing paid presence. In the headphones market, for example, companies like Amazon boosted paid clicks by 35% despite losing organic traffic, while Walmart increased theirs nearly sixfold.

In the jeans sector, Gap saw a 137% growth in paid clicks, rising to become the leading paid player.

For online games, CrazyGames quadrupled its paid clicks, and Arkadium entered the paid scene after a significant drop in organic clicks.

These shifts have led to a self-reinforcing cycle, as pointed out by Aleyda Solis, the study’s author. Organic share declines, competition increases, and brands continuously boost their paid-search budgets.

Study insights. This study was conducted using Similarweb data, thoroughly examining the SERP composition and click patterns for the top 5,000 U.S. queries in the areas of headphones, jeans, and online games, alongside the top 956 greeting card-related queries. Over time, it has highlighted a marked shift in click distribution among classic organic results, text ads, PLAs, zero-click searches, and AI Overviews.

If you’re curious about deeper insights, you can check out the full study by Aleyda Solis.

Inspired by this post on Search Engine Land.
February 18, 2026
Discover Google’s New Interactive AI Link Pop-Up Feature

I’ve just discovered that Google is introducing a dynamic new feature within AI Overviews and AI Mode—more visible links that appear as pop-ups when I hover over them on my desktop. These enhanced link cards offer clearer details about the website content.

After testing this feature, Google has now made it live. If you’re curious about what these new pop-up menus look like, here’s a screenshot that showcases them:

Robby Stein from Google recently shared on X: “New on Search: In AI Overviews and AI Mode, groups of links will automatically appear in a pop-up as you hover over them on desktop, so you can jump right into a website to learn more. And we’ll show more descriptive and prominent link icons within the response across both desktop and mobile.”

He also mentioned, “Our testing shows this new UI is more engaging, making it easier to get to great content across the web.”

This update has the potential to drive more traffic to websites, and I personally look forward to seeing increased visitor numbers from Google’s AI enhancements. Although, at the moment, there’s no way to measure its impact in Search Console.

Inspired by this post on Search Engine Land.

February 17, 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
Google Ads: From Keywords to Intent-Driven Success
I’ve noticed a significant shift in how Google Ads operates. No longer is it about simply targeting keywords. Now, it’s all about understanding and leveraging user intent. Here’s what this evolution means for eligibility, structure, and PPC strategy.

Most PPC teams, myself included, have operated on autopilot: compiling keyword lists, assigning match types, and structuring ad groups around search terms. This was the norm.

However, Google’s auction process has transformed. Search interactions are evolving into more conversational experiences. People engage with AI as if they’re having a dialogue, asking follow-up questions and refining their inquiries. AI now reasons through a question before linking it to suitable ads.

Today, the auction isn’t kicked off by a keyword but by the user’s implied intent. If I’m still relying on exact and phrase match structures, I’m planning for a system that’s no longer there. It’s time to embrace intent as the foundation—not the specific words typed, but the underlying goals they signify.

With this intent-first approach, I find a more resilient strategy. It allows me to effectively design campaigns, creativity, and metrics, especially as Google rolls out new AI-focused formats.

While keywords still play a role, they no longer serve as the framework.

Recently, I’ve learned about changes happening under the hood during a search.

Google’s AI now utilizes a method called “query fan out,” which breaks down complex queries into subtopics and conducts simultaneous searches to provide a comprehensive response.

The auction begins even before users finish typing. Importantly, AI can deduce commercial intent from purely informational searches.

For example, if someone asks, “Why is my pool green?” Google understands they’re troubleshooting, not shopping, but identifies potential product needs and displays ads for pool-cleaning supplies. The AI’s reasoning layer recognizes the solution products offer.

This change in auction logic focuses on matching offerings to the user’s inferred intent, rather than merely matching keywords to queries. Recognizing this shift is crucial, or I risk misinterpreting the user journey.

I’ve come to appreciate the intricacies of an intent-first approach. It doesn’t eliminate the need for keyword research but changes how I prioritize keywords. Now, I align campaigns to the user’s intent.

This strategy encourages me to consider:
- What problem is the user addressing?
- What stage of decision-making are they in?
- What role does the product play in solving their issue?
Realizing that the same intent can emerge from various queries and that identical queries can express different intents based on context has been illuminating. Phrases like “Best CRM” might indicate a need for feature comparison or a readiness to purchase; Google’s AI can now make those distinctions, and so should my campaigns.

This shift is more mental than tactical. While I still build keyword lists, they’re now organized by intent rather than match type. My ad copy speaks directly to user goals instead of echoing search terms.

Moving from keywords to intent isn’t merely a tactical alteration—it’s a strategic lens through which I plan for future campaigns, especially as Google enhances its AI-driven ad formats.

Reorganizing campaigns around intent rather than keywords has its immediate effects, impacting eligibility and landing page efficacy while fundamentally influencing system learning.

Inspired by this post on Search Engine Land.
February 5, 2026
How AI is Transforming Google Search Engagement
Google Search is currently experiencing what I see as an ‘expansionary moment,’ powered by the dynamics of AI technology. The search experience I rely on has transformed through longer queries, follow-up questions, and the increasing use of voice and images. This was highlighted during Alphabet’s recent earnings call, where executives shared these evolving trends.

In other words: Google’s search interface is becoming increasingly AI-driven, facilitating interactions within its system. This isn’t about replacing old queries—instead, we’re witnessing a new era of digital exploration.

Why we care. The integration of AI into Google Search is not just a trial. For me, it’s a structural transformation altering how we discover, interact with, and navigate the web.

By the numbers: Alphabet’s Q4 advertising revenue reached $82.284 billion, marking a 13.5% increase from $72.461 billion in 2024.
- Google Search & other: $63.073 billion (up 16.7%)
- YouTube: $11.383 billion (up 8.7%)
- Google Network: $7.828 billion (down 1.5%)
For the 2025 fiscal year, Alphabet’s advertising revenue climbed to $294.691 billion, a growth of 11.4% from the previous year.
- Google Search & other: $224.532 billion (up 13.4%)
- YouTube: $40.367 billion (up 11.7%)
- Google Network: $29.792 billion (down 1.9%)
AI Overviews and AI Mode are now core to Search. Sundar Pichai, Alphabet/Google’s CEO, emphasized how central AI has become to Google’s search products, with over 250 AI-related product launches in just the last quarter.

Google has recently upgraded its AI Overviews to the Gemini 3 model, a move that connects AI Overviews more seamlessly with conversational search experiences.
- “We have also made the search experience more cohesive, ensuring the transition from an AI overview to a conversation in AI mode is completely seamless,” Pichai noted.
AI is driving more Google Search usage. As Google puts it, AI-driven search is expanding the ways people use search rather than replacing traditional searches.
- “Search saw more usage in Q4 than ever before, as AI continues to drive an expansionary moment,” Pichai emphasized.
- “Once people start using these new experiences, they use them more,” he added.
Changing search behavior. AI Mode is making searches longer, more conversational, and multimodal. “Queries in AI mode are three times longer than traditional searches,” said Pichai.

Not only are queries longer, but sessions are also becoming more conversational, often leading to follow-up questions.
- “We are also seeing sessions become more conversational, with a significant portion of queries in AI Mode now leading to a follow-up question,” he said.
- “Nearly one in six AI mode queries are now non-text, using voice or images,” Pichai shared.
Google’s visual search capabilities continue expanding with “Circle to Search” available on over 580 million Android devices.
- “We haven’t seen any evidence of cannibalization,” Pichai said about the coexistence of Google Search and the Gemini app.
- “The combination of all of that, I think, creates an expansionary moment,” he concluded.
Inspired by this post on Search Engine Land.
February 5, 2026
How AI Search Shapes SEO Visibility in Higher Education

I recently delved into fascinating research that sheds light on how higher education data informs SEO visibility and AI search. This exploration reveals what truly enhances visibility in this AI-driven era.

Contrary to some beliefs, AI search hasn’t rendered SEO obsolete. Now, the challenge is to excel both in ranking and in earning those vital AI citations.

Every time I Google something these days, there’s a significant chance an AI Overview will appear before any organic results or ads, framing my query, shortlisting sources, and shaping which brands I consider.

According to Ahrefs, AI Overviews now feature for about 21% of keywords. This means that while search rankings remain crucial, AI summaries increasingly dictate early brand consideration.

I’ve noticed that brands aren’t losing visibility just because they slip from the third to the seventh position on search engines. They’re often losing because they’re not even mentioned in AI answers.

Research conducted by Search Influence and UPCEA, where I serve as CEO, reveals insights into AI-assisted search usage and organizational adaptation in the higher education space.

Key Takeaways

AI citations are emerging as a trust signal: Being cited by AI can enhance credibility and secure early user consideration before direct source comparison occurs.

AI visibility is collective: AI pulls from various sources like YouTube, LinkedIn, and beyond—your URL isn’t everything.

Established brands need to adapt: Even well-known brands can be overlooked if their content doesn’t align with how users ask questions.

Most organizations recognize AI’s importance but lack action plans: Awareness exists, but execution is hindered by a lack of ownership and processes.

Content structure determines inclusion: Content that is structured for easy retrieval and decision-making often gets cited over long narratives.

To grasp the evolving search landscape, we need to examine both user behavior and organizational responses.

The study “AI Search in Higher Education: How Prospects Search in 2025” surveyed prospective adult learners and revealed significant patterns in online discovery using AI tools.

The findings show increased AI-assisted discovery and shifts in trust signals. Meanwhile, a UPCEA member institution poll uncovers gaps in AI strategy adoption.

The question isn’t whether AI search will impact your field; it’s whether your brand will be cited, overlooked, or represented by competitors.

Inspired by this post on Search Engine Land.

February 4, 2026
Plan Your AI Search Budget for Maximum Visibility

When it comes to navigating the world of AI search, I’ve found that understanding AEO costs and pricing models can make a big difference in gaining visibility across platforms like ChatGPT, AI Overviews, and answer engines. This budget planner is designed to break down those costs and guide you on where to invest wisely.

As I delve into the specifics of AEO, I’m learning how crucial it is to take into account different pricing models. They don’t just affect the budget but also influence where and how resources should be spent to optimize search outcomes.

I’m excited to explore the strategies that enhance visibility in AI-powered platforms. This process not only boosts my understanding but also equips me with the necessary tools to allocate my budget more effectively, ensuring my efforts in AI search yield the best results.

Inspired by this post on HiGoodie Blog.

February 3, 2026
SEO as a Brand and Performance Channel: The New Reality

I’ve come to realize that SEO now serves as both a brand and performance channel. The traditional traffic model has been disrupted by AI Overviews and zero-click SERPs, making brand strength crucial for SEO ROI.

For years, SEO was straightforward: rank higher, get more traffic, then boost the sales pipeline. However, this simple equation is rapidly evolving, much to the frustration of marketing leaders.

With AI Overviews and users getting answers directly from LLMs, the idea of “rank and receive traffic and leads” is less effective now. Even top keyword positions don’t guarantee the clicks they once did.

This shift has sparked challenging discussions in boardrooms. Executives often question, “If traffic is down, how can we measure SEO success?”

It’s obvious now: the traffic model has changed, yet the demand for ROI remains. We must treat SEO as a brand-dependent performance channel, not just a traffic provider.

Why traffic and pipeline are no longer in lockstep

Linear attribution has never fully reflected the dynamic nature of organic search. While ChatGPT isn’t replacing Google, it’s augmenting it.

Users now verify information across platforms due to skepticism of search and LLM results. Where research once happened solely within Google’s ecosystem, it has become more scattered.

Today’s organic search is akin to a pinball machine, with buyers bouncing across channels unpredictably. This introduces complexity that traditional attribution software struggles to follow.

Such complexity has broken the linearity executives crave. Traffic and pipeline charts, once aligned, now often diverge.

Across B2B SaaS portfolios, a common pattern emerges: organic sessions may be flat or declining, yet rankings for high-intent terms stay stable, and the pipeline from organic search grows.

This mismatch doesn’t indicate SEO failure. Rather, it shows that traffic is no longer a reliable business impact measure.

The traffic lost to zero-click searches often consists of informational, low-intent content. What remains is higher-intent traffic, closer to conversion.

We’re seeing the “atomization” of search demand. Short-head, broad keywords are declining, while specific, long-tail queries with higher intent are rising.

Many leaders mistakenly react to dropping sessions by pushing for quantity, aiming to regain the lost numbers through top-of-funnel content. This often inflates vanity metrics without delivering qualified leads.

SEO ROI is now the downstream outcome of brand traction

For years, SEO was viewed as a pure performance channel. We believed optimizing some keywords would suffice.

In reality, SEO has always depended on brand strength. The rise of AI-driven engines highlights this, expecting reputations, not just keywords.

If your brand lacks authority, technical optimizations alone won’t elevate your status. Brand strength determines organic performance limits. Search engines seek web-wide consensus, and weak associations hinder results.

Brand strength for LLMs means owning topical authority, aligning with customer queries, being validated by trusted sources, and having clear positioning.

SEO captures pre-existing demand validated by your brand, not creating it from nothing.

The new defensibility metrics for SEO

As traffic no longer headlines KPIs, new defensibility metrics are necessary. Successful teams focus on revenue and reputation impact, not just volume.

Metrics proving business impact include stable top-10 rankings for commercial keywords, increased Ahrefs traffic value, stable solution page traffic, growing homepage traffic, and developing LLM referral traffic.

When pipeline per organic visitor rises, even with falling sessions, the dialogue shifts from “SEO is broken” to recognizing SEO’s evolution.

Modern SEO is moving from acquisition to influence

Successful SEO isn’t about recovering traffic but influencing buyer decisions and enhancing organic visibility. In an AI-first context, zero-click doesn’t imply zero-value.

SEO remains key in building market readiness, positioning brands as authorities even before buyers enter the funnel.

Inspired by this post on Search Engine Land.

January 30, 2026