Tag: Paid Search

Unlocking Search Success: Unifying Strategies for 2026 Growth

You know what I’m starting to realize? Our customers see the entire search engine results page (SERP). So, if they do, shouldn’t we?
Back in February 2024, Gartner predicted a 25% decrease in traditional search volume by 2026. But guess what? That didn’t happen. Google’s search revenue soared by 17% year-over-year, hitting over $63 billion in just the last quarter of 2025. While query volume is surging, clicks per search are on the decline. It’s like the pie got bigger, but the slices are being divvied up differently, and many of us are still optimizing for that old pie.
I have a question for you: Are we stuck rifling through endless spreadsheets of organic keyword rankings like it’s still 2003? Our customers don’t care about where they get their answers; they just want them to be trustworthy. And they’re finding those answers across a wide array of platforms that our standard rank trackers might not even be aware of.
If our organic, paid, and AI search strategies are operating in separate silos, we might be optimizing for a search experience that’s obsolete.
What Search Really Looks Like Today
Go ahead and Google “best tax software” right now. I’ll wait.
Notice the variety on just one results page: top sponsored ads, an AI Overview citation, a Reddit thread (because people trust real people more than brands), organic listings from CNET and H&R Block, a video carousel, discussion forum links, a product carousel with prices, more sponsored results at the bottom, and a “People also search for” section directing the next inquiry.
This is one search with one keyword, and nobody truly owns it.
Reflect on how different folks use that page. I’ll scroll right to the Reddit thread, seeking genuine human recommendations. My dad clicks the first sponsored ad, trusting Google to display the best option up top. Someone else might read the AI Overview and feel content enough with the answer to avoid further clicking. A fourth person might watch that Smart Family Money video and depart satisfied.
Same query, four distinct paths, four different “winners.” As a brand, if we’re celebrating being third in organic ranking on this page, we should realize that most of the attention and user engagement may be happening beyond those blue links.
That’s why I emphasize understanding the total SERP experience. If our customers are seeing the whole picture, shouldn’t we?
The AI Layer Changes the Equation
AI Overviews now appear on around 25% to 48% of Google queries, according to various studies. ChatGPT processes 2.5 billion prompts daily. Perplexity’s up by 239% year over year—hard figures from platforms shaping consumer opinions about our brands. Yikes, right?
But let’s not start panicking. AI might be shifting the terrain, but it only represents less than 1% of U.S. web traffic. Google, on the other hand, drives referrals 300 times more than all AI platforms combined.
The significant transformation lies in consumer behavior. According to Wynter’s 2026 research, 68% of B2B buyers initiate their research within AI tools before heading to Google. They use ChatGPT to narrow down options, then verify them on Google. AI evaluates, Google validates, and it’s on us to convert. If we aren’t in that initial AI conversation, we’re missing the chance to be a go-to choice.
Why the Click Data is Intriguing, Not Alarming
A Search Engine Land study of 25 million organic impressions revealed that organic CTR drops by 61% when an AI Overview is present, with paid CTR plummeting by 68%.
It’s tempting to go into panic mode but don’t hit the alarm just yet.
Here’s an interesting finding: brands cited in AI Overviews experience a 35% increase in organic clicks and a 91% rise in paid clicks. The AI Overview acts as a trust signal, boosting user engagement below the overview itself.
Interestingly, ranking high in organic doesn’t automatically put you in the AI’s radar. Research by Tom Capper at Moz shows that 88% of AI Mode citations don’t appear in the organic SERPs for the same query. Organic and AI sources differ. You could be the top Google result but completely invisible in a ChatGPT response to the same query.
But here’s a glimmer of hope—traffic from AI tends to convert at quadruple the rate of organic traffic. Its audience arrives informed and ready to make decisions after preliminary evaluation in the AI space.
The Organizational Chart is the Roadblock
Most organizations have SEO reporting to content, PPC to demand gen, and AI search to no one, effectively stranding strategic coherence. BrightEdge found 54% of organizations delegate AI search solely to SEO teams, akin to entrusting your plumber with your electrical work because it’s all in the same house.
The losses here are tangible. One Performance Max campaign paid a staggering $500,000 for clicks that were coming naturally through organic referrals. Google’s studies confirm that when you’re organically ranked first, half of your paid clicks might as well have been free.
Moreover, McKinsey’s findings show a brand’s own website contributes only 5% to 10% of sources AI refers to. AI aggregates from Reddit, review sites, affiliates, and more. A top-tier SEO program might still leave you out in the cold when it comes to AI, as it’s influenced more by collective sentiment than official content.
A unified strategy works wonders. At Level, we cut acquisition costs by 18% and increased SEO leads by 22% by merging paid and organic efforts for a B2B SaaS client. Our Level Intelligence Suite connects performance signals across search surfaces, proving that compartmentalizing these efforts is a missed opportunity for synergy.
Three Audits You Can Kickstart on Monday
If you’re looking for a fast start, here are three audits using your top 20 keywords to pinpoint gaps and opportunities.
Lens 1: Check Where You’re Really Visible. Analyze your organic rankings, paid ad presence, and AI search visibility across platforms like ChatGPT, Perplexity, and Gemini. Use Semrush’s free AI visibility checker to see where you really stand.
Lens 2: Identify Unnecessary Ad Spend. Correlate your top organic rankings with active PPC bids. Begin with branded keywords, where over-expenditure from paying for organic reach is typically largest.
Lens 3: Discover AI Overlooking. Compare your organic presence with AI citations. Only 11% of domains are noted by ChatGPT and Perplexity, so strength in one area doesn’t ensure visibility in the other. Ensure your robots.txt isn’t blocking AI crawlers, or you’ll be invisible in those discussions.
This revealing diagnostic paves the way for action. I’m laying out a detailed unification framework at SMX Advanced, and I’d love to see you there.
The Window Won’t Stay Open Forever
Generative Engine Optimization (GEO) keyword difficulty currently floats between 15 and 20, far lower than traditional SEO terms, which can span 45 to 60. This disparity will soon narrow, as favored sources selected by LLMs end up being perpetually referenced.
Some companies are watching their search traffic nosedive, yet they are surging in actual business growth. These firms stopped isolating channels and started analyzing their customers’ comprehensive search journey.
We’re introducing our unified search strategy at SMX Advanced in our session titled “Organic, Paid, and AI Search: One Strategy to Rule Them All.” If you’re eager to blend your strategies into one cohesive plan, join our session or visit us at Booth #9.
Remember, the search experience we had in 2023 has evolved, and our strategies should too.

Inspired by this post on Search Engine Land.

May 5, 2026
Mastering Paid Search: What to Optimize When Keywords Matter Less

In today’s digital landscape, I’ve noticed that paid search platforms are evolving to prioritize who sees my ads, often without depending solely on my chosen keywords.

This shift means I need to focus on optimization strategies beyond just keywords, such as leveraging audience data, enhancing landing page context, and understanding conversion behaviors. Recognizing this shift is crucial for me to know where to focus my efforts now.

A decade ago, keywords gave me a sense of control. Back then, hypersegmentation and single keyword ad groups were the norm.

We’d meticulously create unique landing pages for each keyword in every ad group, reveling in the manual process, convinced that we controlled the machine.

Times have changed, and the forecast of Google and Microsoft phasing out keywords feels more real than ever.

With tools like Performance Max and emerging AI Max solutions, along with contextual LLM-driven searches such as ChatGPT, I see the industry leaning towards a keywordless future.

Still, keywords remain vital as they reveal user intent and indicate where users stand in their journey:

If these signals are now managed behind a black box, my role as a marketer is evolving. So, what am I optimizing for?

Dig deeper: Beyond keywords: Mastering AI-driven campaigns

Intent is now inferred from a web of signals, relegating individual keywords to the background. My optimization focus should now be on three main pillars in 2026.

Google now emphasizes customer match and first-party data over mere queries. With Data Manager API integration, it identifies users in auctions matching my key deals.

No longer do I bid on “cloud security.” Instead, I target IT directors (sharing first-party data) investigating SOC 2 compliance, even if they search for something vague like “scaling infrastructure.”

B2B match rates can be challenging, but this is where I must innovate my strategy, broadening one-to-one list matching and collaborating with integration partners.

Clustering individuals by shared pain points and offering on-site experiences help me understand their verified intent before reaching the remarketing list.

My landing page serves as a vital data source. Google’s AI examines it to grasp the nuances of my offerings, making creative assets crucial signals that align with my target themes and keywords.

If my landing page effectively communicates “mid-market manufacturing,” AI identifies relevant users regardless of specific keyword use, transforming my “keyword strategy” into a content strategy.

Opting for a creative approach similar to Meta’s, where Andromeda elevates the creative as a primary targeting signal, is beneficial. These creative inputs define my audience, demanding a balance between creative and technical input.

Journey-aware bidding and value-based bidding mean algorithms now analyze a user’s journey beyond the final click.

Optimization now targets “high-value need states,” feeding the system data about mid-funnel behaviors that result in significant contracts.

Dig deeper: Why better signals drive paid search performance

The most profound change for digital marketers, including myself, is shifting focus from query-level to user-level intent.

While the previously ignored query “how to manage payroll” might not have targeted enterprise SaaS companies, AI now understands if that user is a financial VP at a large firm, indicating commercial intent.

If it’s the right user, the right signals should prompt AI to act on their purchasing stage.

As AI handles matching, my role shifts towards becoming a data architect.

Data quality determines my success. I must feed AI with valuable leads to optimize for value-based bidding effectively.

Assessing the health of my signal, from landing pages optimized for AI readability to correct technical content, ensures Google accurately targets my audience.

I now focus less on micromanaging search terms and more on managing brand exclusions and negative themes.

The future of search is about being the best solution for the right individual at their evolving need state.

Keywords served as training wheels, but it’s time to see how quickly my data can propel me forward.

Dig deeper: Why PPC teams are becoming data teams

Inspired by this post on Search Engine Land.

April 27, 2026
Discover How Google Ads Now Appear in Mobile Image Searches

I’ve recently discovered that Google has begun integrating sponsored ad units directly within the Images tab of mobile search results. This exciting new placement is accessible to eligible campaigns without requiring any changes to their existing keyword targeting.

What’s happening? Every time I check the Images tab on Google Search via mobile, I may now encounter sponsored units tucked within the image grid. Each ad displays a complete image creative as the primary visual element alongside text, and it is prominently labeled “Sponsored,” aligning with Google’s standard ad labeling throughout search results.

How it works. It amazes me how eligible campaigns can seamlessly serve into the Images tab without altering any keyword targeting or campaign structure. This placement leverages existing image assets, positioning advertisers who run Search or Performance Max campaigns with compelling visual creatives to gain the most. Thankfully, there’s no need to set up separate image-only campaigns.

Why it matters to us. This move significantly expands Google’s paid search real estate. For those of us engaged in product-led or catalog-heavy advertising, the Images tab is crucial, as it often serves as the starting point for purchase-intent discoveries — and now, our ads can appear right in that moment. If we are using robust image assets in our campaigns, we might be enjoying incremental impressions without any effort on our part.

The big picture. I’m noticing that this placement behaves more like a visual discovery surface rather than traditional paid search. While we should expect high impression volumes, the click-through rates might be lower, similar to display or Shopping ads instead of conventional text ads. Yet, the assist value in multi-touch conversion paths could be quite significant, especially for retail and direct-to-consumer brands. It’s an upper-funnel reach strategy, not a last-click channel.

What we should watch. Even though Google hasn’t officially announced it, nor is there a specific reporting breakdown for these Image tab placements yet, it’s crucial for us to monitor our impression share and segment data closely. This will help us understand its contribution, and whether it impacts organic image visibility for our competitors.

First seen. The innovative placement was first noticed by Google Ads Expert Matteo Braghetta, who shared this update on LinkedIn. At the time of writing, Google hasn’t published any official documentation regarding this development.

Inspired by this post on Search Engine Land.

April 7, 2026
Mastering Paid Search: Strategy Over Keywords

In my extensive three-decade career, I’ve witnessed keywords dominate the landscape of paid search. However, in today’s world, they have become just a part of a larger puzzle. What truly drives performance now is strategy.

I remember spending weeks meticulously researching keywords, crafting strategies around them, and managing every aspect, from bid adjustments to audience targeting. It was the foundation of success in this industry.

We used to focus heavily on precise placements, structured URLs, and audience targeting, primarily with Google’s influence leading the charge. Our profession thrived on the tactical control this model offered.

We enjoyed the ability to identify which queries triggered ads and make informed decisions to optimize budgets accordingly. Sometimes we would even segment ad groups intricately to maximize returns.

What Changed Across Platforms

Now, advertising has embraced a significant shift: automation, driven by AI, has taken over critical tasks like bidding and creative assembly. While keywords remain relevant, they serve as just one of many signals that AI systems use.

With tools like AI Max for Search, Google has transformed keywords from being the focal point to just signals in guiding ad delivery. It’s fascinating how AI now uses elements like existing keywords and landing page content to enhance performance.

Advertisers employing AI Max often experience notable gains, with some campaigns seeing up to 27% more conversions. Integrating it with other tools like Performance Max can further amplify reach across various platforms.

Dig deeper: Google Ads no longer runs on keywords. It runs on intent.

The New Primary Levers

When I mention strategy as the new keyword, I mean focusing on specific inputs shaping ad performance. These include conversion data quality, a critical factor for systems like Google’s Smart Bidding, which relies on quality data to optimize campaigns.

We now prioritize which conversions hold the most value. It’s a shift from purely manual adjustments to strategic evaluations that highlight what truly matters for campaign success.

First-party data, enriched and well-structured, is paramount. It’s akin to the foundational keyword research of the past, vital for driving performance on today’s platforms.

Creative assets have evolved beyond mere deliverables; they’re now strategic signals that AI uses to target effectively. These visuals and messages have become an integral part of how we engage audiences.

The quality of landing pages and websites has also taken on new importance. AI determines relevance based on post-click experiences, emphasizing the need for seamless user journeys.

Dig deeper: In Google Ads automation, everything is a signal in 2026

What It Means for Practitioners

Our roles have adapted to these changes. It’s less about managing keywords or bids manually and more about creating strategic frameworks that guide AI systems effectively.

Subject-matter experts like us now focus on ensuring data quality, defining creative strategies, and identifying when human intervention is necessary.

We guide AI through a careful mix of conversion architecture, audience signal quality, and creative frameworks rather than traditional methods of keyword lists and bidding.

It’s crucial to understand how these advanced systems and platforms operate, as well as to emphasize the signals that matter most. Building strong first-party data and strategic frameworks will enhance AI capabilities and redefine the future.

Embracing this evolution, practitioners focusing on strategy over technical execution positions will find themselves best equipped to thrive in this changing landscape.

The keyword list remains, but our primary focus now is on strategy.

Dig deeper: 4 times PPC automation still needs a human touch

Inspired by this post on Search Engine Land.

April 3, 2026
Boost Your Paid Search with High-Quality Signals

In today’s automated landscape, I’ve learned that paid search performance largely depends on the quality of signals fed into algorithms. Algorithms are like chefs—they expertly cook with whatever ingredients they’re provided. By enhancing these signals, I’ve found a reliable path to better results.

While this might sound simple, I’ve noticed that many of us still cling to signals that don’t truly reflect business outcomes. Let me share my insights into how algorithms work, how I can shape them, and where common pitfalls lie.

Modern bidding systems often evoke the image of a “black box,” shrouded in mystery. However, I’ve found that understanding their function requires breaking down their capabilities. These algorithms are vast pattern recognition systems.

Initially, these systems relied on straightforward statistical methods, like rules-based logic or regression models. Today, they’ve evolved into complex learning systems capable of evaluating countless data inputs simultaneously, such as query intent and location-specific behavior, in real-time.

Despite the technological advancements, I understand the core mechanisms remain unchanged. They identify patterns that match desired outcomes, calculate probabilities, and adjust bids accordingly. It’s crucial for me to align the feedback loops with real business values to ensure these algorithms optimize effectively.

As a marketer, I’m aware algorithms lack business context—they only see what they get. If we provide them with weak or irrelevant data, even the most sophisticated systems can’t deliver the results we need.

Therefore, I focus on the controllable signals that have the greatest influence over these algorithms. These include campaign structure, bidding strategies, and how I allocate my budget.

Most importantly, I’ve found conversion data to be the key driver of success. It’s the critical signal that guides algorithmic learning and optimization.

Whenever I experience a plateau in performance, my instinct is no longer to blame budget constraints or ineffective tactics. Instead, I analyze conversion data since it’s often the root cause of stagnation. Ensuring quality over quantity in conversions has consistently elevated my results.

Ultimately, aligning conversion signals with genuine business KPIs is vital. Platforms don’t understand business profitability; they follow the instructions given. If any conversion increase jangles alarms rather than cheers, it shouldn’t drive the primary optimization signal.

To ensure effective learning and optimization, I strengthen conversion signals with rich data sources, beyond standard browser tracking, to overcome privacy and attribution challenges.

By integrating first-party identifiers and accurate transaction values, I’ve improved how platforms recognize and learn from conversions. This method offers robust feedback loops, optimizing both accuracy and performance.

Determining the right conversion goals requires balancing volume and value precision. Often, I use proxy metrics for a faster optimization cycle without sacrificing real business value.

I’ve found setting conversion goals is not straightforward; it’s about balancing volume with value accuracy and stability. This balance helps me optimize efficiently without data becoming too sparse or too noisy.

Regularly revisiting these goals and refining conversion definitions are essential. Asking myself if I truly celebrate any increase in a certain outcome guides me toward refining my signals and enhancing performance in paid search.

Inspired by this post on Search Engine Land.

March 24, 2026
Master Google’s AI Impact: 4 Paid Search Strategies for Success

AI Overviews are reshaping the landscape of paid search by lowering click-through rates, increasing cost-per-click, and compressing the buyer journey. As I’ve seen in my own campaigns, adapting to these changes is crucial for maintaining performance and staying competitive.

I’ve noticed Google’s AI Overviews appear across search results with varying frequency. However, in some categories, they take over completely. According to Adthena:

Finance queries with five or more words see AI Overviews on 79% of searches.

Retail shows an 84% visibility for comparison and product discovery queries in the 9-10 word range.

Healthcare keywords, even short ones (1-3 words), trigger high AI Overview penetration.

I realize that organic traffic faces obvious challenges, yet the downstream impact on paid search is more severe than I thought. Here’s how that manifests in practice.

AI Overviews systematically alter paid search by affecting click volume, auction dynamics, and user behavior during conversion. They speed up structural trends that reshape search, such as SERP saturation, automated bidding, and Performance Max adoption.

The speed at which Google rolled out AI Overviews is staggering. Many verticals have seen transitions that typically spanned years compressed into months. To understand how this impacts my paid search, I must consider how AI Overviews have reshaped each component of campaign performance.

So now, how much have the response rates been affected by AI Overviews? Recent data from Seer Interactive shows the decline’s scale. Paid CTR on queries featuring AI Overviews plummeted by 68%, dropping from 19.7% to 6.34% between June 2024 and September 2025.

At the same time, organic CTR fell 61% on the same queries, but the steeper decline in paid traffic suggests AI Overviews reshape where paid ads appear and who clicks them, not simply their overall presence.

The drop accelerated sharply in July 2025, when paid CTR collapsed from approximately 11% to 3% within a month due to Google aggressively expanding AI Overviews.

Non-branded informational queries saw the most severe declines. But it’s not all bad news. Branded searches and high-intent queries exhibited greater resilience, and many advertisers noticed minimal impact on key conversion terms.

There’s a direct link between AI Overviews and rising campaign costs. As response rates decline, CPC inflation occurs due to supply and demand mechanics. Google Search spending grew 9% YoY in Q1 2025, but click growth was just 4%. The 5% gap reflects more money chasing fewer clicks.

AI Overviews boost CPC inflation via several mechanisms, including ad positioning. Research on ad positioning reveals that ads performing well above an AI Overview see a performance dip for those below, reducing impression share and CTR.

AI Overviews also accelerate the consideration phase of the buyer’s journey. Activities that once took days are now compressed into minutes, facilitating research and comparisons across sessions.

For instance, what used to be a multi-day process in 2023, like looking for the [best project management software for remote teams], can now convert users in a single session with the help of AI Overviews.

This shift affects campaigns in three ways: smaller retargeting pools, diminished brand awareness, and AI Overviews mentions being a must for visibility.

The compression of the buyer journey results in a surprising economic outcome. While click volume shrinks, conversion rates improve. An analysis of 16,446 campaigns showed enhanced conversion rates in 65% of industries despite reduced click volume.

Enhanced conversion rates signify that AI Overviews are filtering out casual inquiries, leaving high-intent prospects to convert. While this could offset CPC inflation, the need for strategic adaptation in campaigns remains vital.

Therefore, let’s discuss the four strategic pivots I find essential in today’s AI-driven search environment.

First, monitor and optimize informational intent performance. Given AI Overviews’ impact, systematic observation and adaptation are necessary to identify profitable versus draining keywords.

Second, prioritize feed quality. AI can summarize but not invent details like price and inventory. Robust product feeds offer a competitive advantage here.

Third, craft creative that stands out. Ads need to answer why customers should choose your service over others and why now.

Fourth, leverage audience data over keyword targeting. Audience lists built from first-party data allow targeting based on customer relationships.

In conclusion, AI Overviews are reshaping paid search, leaving advertisers at a crossroads. Personalized strategies that embrace new realities will help navigate these challenges effectively.

Inspired by this post on Search Engine Land.

February 26, 2026
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
Write Competitive Paid Search Ads That Capture Attention

When I’m crafting paid search ads that beat the competition, I always remember to review them in context, not isolation. This helps me understand how my ads stand against others. By doing this, I gain practical insights to enhance messaging, leverage AI effectively, and create PPC copy that truly converts.

How frequently do I analyze my PPC ad copy? I don’t just focus on performance metrics within the ad platform. I make it a point to assess how my ads appear alongside competitor ads, ensuring my message stands out.

Am I using the same messaging as my competitors? What makes my offer unique? I strive to create ads that feature clear calls to action and convincing selling points, avoiding bland and generic content.

Here are several strategies I follow to make my paid search ads stand out and attract customers to my brand.

1. Think about how assets will appear together, not just individually

When I’m working on Responsive Search Ads, it can be tempting to simply fill out all 15 headline options and the four descriptions. But I know that if each headline essentially repeats the same message with minor variations, the ad copy can appear monotonous and repetitive.

To avoid this, I ensure the headlines offer a variety of angles and points of interest. For example, instead of having headlines like “Project Management Software – Project Management Solution – Project Management,” I use options such as “Project Management Software – Trusted by 3 Million Users.”

If I want to experiment with several headlines, I pin them to the same position so the platform can rotate between them without showing similar options simultaneously.

Dig deeper: The anatomy of compelling search ad copy

2. Don’t obsess over ad strength

While checking the ad strength rating is common, I focus on the bigger picture instead of just chasing an Excellent score.

I’m more concerned about whether each headline and description accurately reflects my benefit points. Although pinning can negatively impact ad strength, it’s worth it for cleaner messaging.

3. Use AI as a partner, but don’t blindly outsource all your copy to AI

I utilize AI tools from Google and Microsoft to generate text for my ad assets, but I don’t use them without review. These tools provide a starting point, but I always add the human touch to ensure alignment with my brand voice and compliance with industry guidelines.

Dig deeper: How to write high-performing Google Ads copy with generative AI

4. Include value propositions, and back them up

When I claim to be the “Best Local Contractor,” I provide evidence, such as “Voted Best Local Contractor by [News Outlet].” I use numbers where possible to enhance credibility and reinforce my claims.

5. Highlight ease of effort

I emphasize how my product or service saves time and effort. Whether it’s “Open an account in 10 minutes” or “Schedule a same-day appointment,” I ensure these claims reflect reality to build trust.

Dig deeper: How to assemble captivating Google Ads copy

6. Offer a ‘free’ hook

To catch potential customers’ attention, I highlight free offerings like “Free trial” or “Free quote.” Such offers encourage prospects to take the next step.

7. Turn off automated assets

Given the possibility for concerns over compliance and accuracy, I disable the setting for automatically generated assets. This ensures the messages and links presented are ones I’ve approved.

8. Highlight pricing where it makes sense for your brand

In scenarios where I can highlight competitive pricing, I do so to help my ad stand out, especially during comparison shopping. When pricing is higher, mentioning it can effectively filter out less suitable prospects.

9. Mention locations in regional campaigns

Mentioning specific locations in my ad copy, like “Now Open in Buckwheat County,” helps create a local alignment, making the ad more relevant to users in that area.

Dig deeper: Localization in Google Ads: How to structure multi-market campaigns

10. Review and revise your ad copy

With these strategies in mind, I consistently review and refine my ad copy. I ask myself where I can improve asset combinations, highlight unique value propositions, or better tailor my wording to customer concerns.

In the end, my ad doesn’t just compete in isolation; it competes in the search results alongside others. Understanding this helps me ensure my ad stands out and delivers results.

Inspired by this post on Search Engine Land.

February 24, 2026
ChatGPT Ads: Bridging the Gap Between SEO and Paid Media

ChatGPT ads are reshaping the landscape, merging the once distinct worlds of SEO and paid media through prompt intelligence, fanout keywords, and LLM visibility.

For years, our focus has been split between optimizing for SEO and paid media. The questions were always the same: Who controls the keyword? Who deserves the budget? Who can prove ROI more convincingly?

Traditionally, SEO focused on organic rankings, while paid media honed in on auctions. They each aimed for visibility on the same search results page but functioned under different motivations and systems.

Now, with the advent of ChatGPT ads, that distinction is fading. The divide between organic and paid is not only blurred—it’s being dismantled by conversational AI.

The new battleground for visibility isn’t the SERP; it’s the prompt. The convergence of PPC and SEO is happening within ChatGPT ads.

Keywords have always been the foundation of search marketing, shaping bidding strategies, landing page optimization, and attribution modeling.

In contrast, generative AI thrives on multi-variable, intent-driven prompts. General terms like “Best CRM” evolve into nuanced queries like “What’s the best CRM for a B2B SaaS company under 50 employees?”

Such prompts encapsulate richer context and specificity, unlike traditional keyword research which often simplifies complex inquiries to fit SERP strategies.

When ChatGPT ads appear under its contextual answers rather than next to a search term, everything changes.

ChatGPT ads are unique in their structure, as they appear beneath AI-generated responses, clearly labeled as “Sponsored,” and don’t manipulate the AI’s answers. They focus on context and the user’s session.

This is not merely a keyword auction strategy. It’s about aligning context within a conversational user experience. This affects us as marketers by emphasizing the importance of enriched intent and context, requiring tight coordination of SEO and PPC at the prompt level.

Leveraging prompt intelligence becomes crucial in this new demand capture environment, raising the question: Which prompts should we prioritize?

The solution lies not in traditional tools like Google Search Console or Keyword Planner, but in analyzing LLM performance, which SEO teams have been doing in recent months.

We can jumpstart a ChatGPT ads strategy by examining high-performing LLM prompts, understanding when our brand appears, the types of prompts we want to be part of, and the most cited use cases.

This process reveals fanout keywords, the new long-tail indicators embedded within prompts, like in the query “Best CRM for B2B SaaS startups with under 50 employees that integrates with HubSpot.”

Traditional tools target root terms, but fanout keywords highlight specifics like “SaaS startups with under 50 employees” or “HubSpot integration.” They offer layered quality, uncovering underserved audiences and potential gaps in paid strategies.

Aligning these fanout keywords with paid strategies is crucial. By auditing our paid coverage, we can ensure we address these nuanced variants and don’t overly rely on base keywords.

The opportunity lies where organic LLM visibility and paid gaps meet. Frequently appearing conversationally in responses without targeting paid ads around that intent is missing out on additional demand.

Optimizing landing pages is another overlooked area. Traditionally, SEO and PPC teams have driven traffic to the same pages, optimizing them based on different criteria, but this won’t suffice with conversational AI.

To reduce conversion friction, our landing pages must reflect the nuanced specifics of prompts, allowing deeper engagement with tailored content and conversational phrasing.

By improving landing page clarity, we boost both conversion and the likelihood of LLMs recognizing and appropriately surfacing our brand, forming a crucial feedback loop between SEO and paid strategy.

In the realm of conversational AI, the once distinct worlds of SEO and paid are now intersecting, requiring us to think in systems rather than channels. ChatGPT ads highlight this shift, showing that AI isn’t just influencing search methods—it’s redefining growth strategy.

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