<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset.png" class="attachment-large size-large wp-post-image" alt="The agentic web is here: Why NLWeb makes schema your greatest SEO asset" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset.png 1920w, https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>OpenAI’s high-priced ChatGPT ads promise premium visibility inside AI conversations, despite limited performance data in return.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset.png" class="attachment-large size-large wp-post-image" alt="The agentic web is here: Why NLWeb makes schema your greatest SEO asset" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset.png 1920w, https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/10/ChatGPT-Image-The-agentic-web-is-here-Why-NLWeb-makes-schema-your-greatest-SEO-asset-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>OpenAI is pitching premium-priced ads in ChatGPT — with far less data than advertisers are used to getting.</p>



<p><strong>What’s happening.</strong> According to a report, OpenAI is pricing <a href="https://searchengineland.com/openai-begins-testing-ads-inside-chatgpt-467637">ChatGPT ads</a> at roughly $60 per 1,000 impressions — about three times higher than typical Meta ads. Despite the cost, advertisers will receive only high-level reporting, such as total impressions or clicks, with no insight into downstream actions like purchases.</p>



<p><strong>Why we care.</strong> ChatGPT is emerging as a brand-new, high-attention ad environment — but one that comes with trade-offs. The high CPMs and limited reporting mean early tests will be more about brand exposure and learning than performance efficiency. </p>



<p>For marketers willing to experiment, this offers a first-mover chance to understand how ads perform inside AI conversations before the format scales or measurement improves.</p>



<p><strong>The tradeoff</strong>. OpenAI has left the door open to expanding measurement in the future, but it has publicly committed to never selling user data to advertisers and keeping conversations private. That stance limits the kind of targeting and attribution advertisers expect from platforms like Google or Meta.</p>



<p><strong>Who will see ads</strong>. The first ads will roll out in the coming weeks to users on ChatGPT’s free and lower-cost Go tiers, excluding users under 18 and conversations involving sensitive topics such as mental health or politics.</p>



<p><strong>Between the lines</strong>. OpenAI is positioning ChatGPT ads as a premium, trust-first product — betting that context, attention, and brand safety can justify higher prices even without granular performance data.</p>



<p><strong>Bottom line.</strong> ChatGPT ads may appeal to brands willing to pay more for visibility in a new AI-driven environment, but the lack of measurement will make performance-focused advertisers think twice. </p>



<p><strong>Dig deeper.</strong> <a href="https://www.theinformation.com/articles/openai-seeks-premium-prices-early-ads-push">OpenAI Seeks Premium Prices in Early Ads Push (Subscription needed)</a></p>


OpenAI is pitching premium-priced ads in ChatGPT — with far less data than advertisers are used to getting.
What’s happening. According to a report, OpenAI is pricing ChatGPT ads at roughly $60 per 1,000 impressions — about three times higher than typical Meta ads. Despite the cost, advertisers will receive only high-level reporting, such as total impressions or clicks, with no insight into downstream actions like purchases.
Why we care. ChatGPT is emerging as a brand-new, high-attention ad environment — but one that comes with trade-offs. The high CPMs and limited reporting mean early tests will be more about brand exposure and learning than performance efficiency. 
For marketers willing to experiment, this offers a first-mover chance to understand how ads perform inside AI conversations before the format scales or measurement improves.
The tradeoff. OpenAI has left the door open to expanding measurement in the future, but it has publicly committed to never selling user data to advertisers and keeping conversations private. That stance limits the kind of targeting and attribution advertisers expect from platforms like Google or Meta.
Who will see ads. The first ads will roll out in the coming weeks to users on ChatGPT’s free and lower-cost Go tiers, excluding users under 18 and conversations involving sensitive topics such as mental health or politics.
Between the lines. OpenAI is positioning ChatGPT ads as a premium, trust-first product — betting that context, attention, and brand safety can justify higher prices even without granular performance data.
Bottom line. ChatGPT ads may appeal to brands willing to pay more for visibility in a new AI-driven environment, but the lack of measurement will make performance-focused advertisers think twice. 
Dig deeper. OpenAI Seeks Premium Prices in Early Ads Push (Subscription needed)

OpenAI’s high-priced ChatGPT ads promise premium visibility inside AI conversations, despite limited performance data in return.

ChatGPT ads come with premium prices — and limited data

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction.png" class="attachment-large size-large wp-post-image" alt="Google intent extraction" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google signals search’s next phase: small multimodal models on devices infer intent from behavior before a query is ever typed.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction.png" class="attachment-large size-large wp-post-image" alt="Google intent extraction" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/google-intent-extraction-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is working toward a future where it understands what you want before you ever type a search.</p>



<p>Now Google is pushing that thinking onto the device itself, using small AI models that perform nearly as well as much larger ones.</p>



<p><strong>What’s happening.</strong> In a research paper presented at EMNLP 2025, Google researchers show that a simple shift makes this possible: break “intent understanding” into smaller steps. When they do, small multimodal LLMs (MLLMs) become powerful enough to match systems like Gemini 1.5 Pro — while running faster, costing less, and keeping data on the device.</p>



<ul class="wp-block-list">
<li>The paper, &#8220;<a href="https://aclanthology.org/2025.emnlp-main.949/" target="_blank" rel="noopener">Small Models, Big Results: Achieving Superior Intent Extraction through Decomposition</a>,&#8221; explains how Google infers what someone is trying to do based on how they use apps and websites. That includes taps, clicks, scrolling, and screen changes over time.</li>
</ul>



<p><strong>The future is intent extraction.</strong> Large AI models can already infer intent from user behavior, but they usually run in the cloud. That creates three problems. They’re slower. They’re more expensive. And they raise privacy concerns, because user actions can be sensitive.</p>



<p>Google’s solution is to split the task into two simple steps that small, on-device models can handle well.</p>



<ul class="wp-block-list">
<li><strong>Step one:</strong> Each screen interaction is summarized separately. The system records what was on the screen, what the user did, and a tentative guess about why they did it.</li>



<li><strong>Step two:</strong> Another small model reviews only the factual parts of those summaries. It ignores the guesses and produces one short statement that explains the user’s overall goal for the session.
<ul class="wp-block-list">
<li>By keeping each step focused, the system avoids a common failure mode of small models: breaking down when asked to reason over long, messy histories all at once.</li>
</ul>
</li>
</ul>



<p><strong>How the researchers measure success.</strong> Instead of asking whether an intent summary “looks similar” to the right answer, they use a method called Bi-Fact. Using its main quality metric, an F1 score, small models with the step-by-step approach consistently outperform other small-model methods:</p>



<ul class="wp-block-list">
<li>Gemini 1.5 Flash, an 8B model, matches the performance of Gemini 1.5 Pro on mobile behavior data. </li>



<li>Hallucinations drop because speculative guesses are stripped out before the final intent is written. </li>



<li>Even with extra steps, the system runs faster and cheaper than cloud-based large models.</li>
</ul>



<p><strong>How it works.</strong> Intent is broken into small pieces of information, or facts. Then they measure which facts are missing and which ones were invented. This:</p>



<ul class="wp-block-list">
<li>Shows <strong>how</strong> intent understanding fails, not just that it fails. </li>



<li>Reveals where systems tend to hallucinate meaning versus where they drop important details.</li>
</ul>



<p>The paper also shows that messy training data hurts large, end-to-end models more than it hurts this step-by-step approach. When labels are noisy — which is common with real user behavior — the decomposed system holds up better.</p>



<p><strong>Why we care.</strong> If Google wants agents that suggest actions or answers before people search, it needs to understand intent from user behavior (how people move through apps, browsers, and screens). This research moves this idea closer to reality. Keywords will still matter, but the query will be just one signal. In this future, you&#8217;ll have to optimize for clear, logical user journeys — not just the words typed at the end.</p>



<p><strong>The Google Research blog post.</strong> <a href="https://research.google/blog/small-models-big-results-achieving-superior-intent-extraction-through-decomposition/" target="_blank" rel="noopener">Small models, big results: Achieving superior intent extraction through decomposition</a></p>


Google is working toward a future where it understands what you want before you ever type a search.
Now Google is pushing that thinking onto the device itself, using small AI models that perform nearly as well as much larger ones.
What’s happening. In a research paper presented at EMNLP 2025, Google researchers show that a simple shift makes this possible: break “intent understanding” into smaller steps. When they do, small multimodal LLMs (MLLMs) become powerful enough to match systems like Gemini 1.5 Pro — while running faster, costing less, and keeping data on the device.
The paper, “Small Models, Big Results: Achieving Superior Intent Extraction through Decomposition,” explains how Google infers what someone is trying to do based on how they use apps and websites. That includes taps, clicks, scrolling, and screen changes over time.
The future is intent extraction. Large AI models can already infer intent from user behavior, but they usually run in the cloud. That creates three problems. They’re slower. They’re more expensive. And they raise privacy concerns, because user actions can be sensitive.
Google’s solution is to split the task into two simple steps that small, on-device models can handle well.
Step one: Each screen interaction is summarized separately. The system records what was on the screen, what the user did, and a tentative guess about why they did it.
Step two: Another small model reviews only the factual parts of those summaries. It ignores the guesses and produces one short statement that explains the user’s overall goal for the session.

By keeping each step focused, the system avoids a common failure mode of small models: breaking down when asked to reason over long, messy histories all at once.
How the researchers measure success. Instead of asking whether an intent summary “looks similar” to the right answer, they use a method called Bi-Fact. Using its main quality metric, an F1 score, small models with the step-by-step approach consistently outperform other small-model methods:
Gemini 1.5 Flash, an 8B model, matches the performance of Gemini 1.5 Pro on mobile behavior data. 
Hallucinations drop because speculative guesses are stripped out before the final intent is written. 
Even with extra steps, the system runs faster and cheaper than cloud-based large models.
How it works. Intent is broken into small pieces of information, or facts. Then they measure which facts are missing and which ones were invented. This:
Shows how intent understanding fails, not just that it fails. 
Reveals where systems tend to hallucinate meaning versus where they drop important details.
The paper also shows that messy training data hurts large, end-to-end models more than it hurts this step-by-step approach. When labels are noisy — which is common with real user behavior — the decomposed system holds up better.
Why we care. If Google wants agents that suggest actions or answers before people search, it needs to understand intent from user behavior (how people move through apps, browsers, and screens). This research moves this idea closer to reality. Keywords will still matter, but the query will be just one signal. In this future, you’ll have to optimize for clear, logical user journeys — not just the words typed at the end.
The Google Research blog post. Small models, big results: Achieving superior intent extraction through decomposition

Google signals search’s next phase: small multimodal models on devices infer intent from behavior before a query is ever typed.

Google research points to a post-query future for search intent

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior.png" class="attachment-large size-large wp-post-image" alt="From searching to delegating- Adapting to AI-first search behavior" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>As AI replaces clicks with answers, user engagement moves deeper into the funnel. Here’s how SEO and content strategies must adapt.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior.png" class="attachment-large size-large wp-post-image" alt="From searching to delegating- Adapting to AI-first search behavior" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/From-searching-to-delegating-Adapting-to-AI-first-search-behavior-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>AI Overviews, which place generated answers directly at the top of search results, are improving the search experience for users.&nbsp;</p>



<p>For businesses that rely on content to drive traffic from search engines, the impact is far less positive.</p>



<p>Google has been moving toward more “helpful” results for years, and zero-click searches are nothing new.&nbsp;</p>



<p>AI Overviews accelerate that shift, absorbing much of the traffic opportunity that search has historically provided.</p>



<h2 class="wp-block-heading" id="h-how-ai-changes-the-work-of-search">How AI changes the work of search</h2>



<p>For years, search followed a familiar pattern:</p>



<ul class="wp-block-list">
<li>A user entered a short query, such as “team building companies.”</li>



<li>Google returned a page of paid and organic results.</li>



<li>The user did the work of reviewing and refining.</li>
</ul>



<p>Most of the effort happened at the end of the process.&nbsp;</p>



<p>Google organized results based on intent and behavioral signals, but users still had to click through listings, conduct follow-up searches, and piece together an answer.</p>



<p>AI reverses that flow:</p>



<ul class="wp-block-list">
<li>The user asks a more detailed question.</li>



<li>AI runs multiple searches and processes the results.</li>



<li>AI delivers a summarized response.</li>
</ul>



<p>Traditional search allows for refinement, but each new query effectively resets the experience.&nbsp;</p>



<p>AI, by contrast, is conversational. Each interaction builds on the last, narrowing in on what the user actually wants.</p>



<p>The result is a faster, cleaner path to an answer – with far less effort required from the user.</p>



<h2 class="wp-block-heading" id="h-the-path-of-least-resistance">The path of least resistance</h2>



<p>This shift matters because it aligns with a basic human tendency.</p>



<p>People generally choose the easiest available option. If something is easier and produces a better result, adoption follows quickly.</p>



<p>This is <a href="https://www.linkedin.com/newsletters/the-visibility-paradox-7353766643753181185/">how search replaced older marketing channels</a> such as the Yellow Pages.</p>



<p>Seeking the path of least resistance is an evolutionary trait that likely served humans well in earlier eras.&nbsp;</p>



<p>Today, however, it often shapes behavior in less intentional ways, including how people interact with ads and information.</p>



<p>AI is not perfect, but it is typically faster, easier, and more effective than digging through traditional search results.&nbsp;</p>



<p>That advantage makes widespread adoption inevitable, especially as AI continues to be integrated into the websites, apps, and devices people already use.</p>



<h2 class="wp-block-heading" id="h-what-does-this-mean-for-search-marketing">What does this mean for search marketing?</h2>



<p>Recent studies have shown that <a href="https://searchengineland.com/consumers-start-searches-ai-not-google-study-467159">more users are beginning their research with AI tools</a> rather than search engines.&nbsp;</p>



<p>These studies always have their critics, but the broader point is something of a moot one: AI is everywhere.</p>



<p>AI is now so integrated into the tools people already use that it is becoming the default.&nbsp;</p>



<p>Search engines, messaging platforms like WhatsApp, and mobile devices are all moving in this direction, and this is just the beginning.&nbsp;</p>



<p>With <a href="https://searchengineland.com/apple-siri-google-gemini-deal-467404">Google having signed a multiyear deal with Apple</a>, Google AI will power a significant share of mobile devices, accelerating the shift toward AI-first experiences.</p>



<p>It’s easy to envision an AI-first future, much like the shift from desktop to mobile and then mobile-first.</p>



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<h2 class="wp-block-heading" id="h-what-this-change-actually-looks-like">What this change actually looks like</h2>



<p>Generative answers are <a href="https://searchengineland.com/generative-answers-changing-user-journey-460073">shifting where users enter the funnel</a>, with engagement increasingly starting mid-funnel around content that demonstrates experience and expertise.</p>



<p>This is the type of content users historically would only engage with on a company’s website, or through other owned channels such as YouTube.</p>



<p>This does not mean top-of-the-funnel content is no longer important. Blogs, guides, and videos still matter, videos in particular. However, it may be worth reconsidering how that content is distributed rather than relying solely on traditional organic search.</p>



<p>With the rise of AI tools such as Gemini and ChatGPT, users can now handle much of this comparison work through AI, saving significant time.</p>



<p>For example, the shift looks like this:</p>



<ul class="wp-block-list">
<li>From “Mid market ERP platforms.” Where the user must sift through results, compare options, build spreadsheets, and conduct extensive manual review.</li>



<li>To “Which mid-market ERP platforms work best for manufacturing firms, integrate with our existing stack of X, Y, and Z, and won’t collapse during implementation?”</li>
</ul>



<p>This changes where the user must exert effort.</p>



<p>A more detailed question or input produces a far stronger response or output. </p>



<p>You could argue that traditional search had degraded into a form of garbage in, garbage out (GIGO), where short, generic queries produced ad-heavy, blended results that were time-consuming to mine for real answers.</p>



<p>The result is user fatigue. Endless clicking, avoiding ads, and sorting through widely varying content has become a chore.</p>



<p>And the experience often does not improve once users reach the destination. <a href="https://searchengineland.com/website-matters-ai-age-458829">Traffic-starved, ad-heavy websites can be just as difficult to navigate</a> and extract useful information from.</p>



<p>AI offers a cleaner, faster, and less cluttered experience, delivering summarized pros, cons, and supporting evidence at each stage of the decision-making process.</p>



<p>All of this can happen inside an AI tool, without the user ever needing to visit the site where the content originated.</p>



<p>AI is increasingly becoming the default interface for information. These are still early days, and the experience will continue to improve, becoming faster, smoother, and more effective over time.</p>



<p>The crux of the <a href="https://searchengineland.com/guide/seo-vs-geo-is-wrong">SEO vs. GEO/AEO/AIO conversation</a> is often that, despite a changing landscape, SEO and GEO are largely the same.</p>



<p>This is broadly true and, if anything, feels similar to the early days of SEO, when long-tail opportunities were real.&nbsp;</p>



<p>You can now go much deeper with mid-funnel content because it no longer requires humans to read it all.&nbsp;</p>



<p>Instead, AI can consume it and summarize the relevant parts.</p>



<p>The tactics are largely the same. Much of <a href="https://searchengineland.com/why-ai-still-runs-on-search-and-seo-still-runs-the-show-463325">AI still sits on top of traditional search</a>, but <a href="https://searchengineland.com/seo-strategy-strategic-seo-planning-437603">SEO strategies</a> and <a href="https://searchengineland.com/seo-planning-one-page-seo-plan-438449">execution</a> may need adjustment to ensure all bases are covered.</p>



<p>It’s also important not to throw the baby out with the bathwater.&nbsp;</p>



<p><a href="https://searchengineland.com/seo-vs-ppc-vs-ai-the-visibility-dilemma-464973">SEO, PPC, and related channels</a> all retain value in the age of AI.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-geo-aso-new-era-brand-visibility-ai-research-464936">SEO, GEO, or ASO? What to call the new era of brand visibility in AI [Research]</a></em></strong></p>



<h2 class="wp-block-heading" id="h-how-to-adapt-in-an-ai-first-search-environment">How to adapt in an AI-first search environment</h2>



<p>The game has changed. Planning for 2026 and beyond requires accepting that change and making practical adjustments to <a href="https://searchengineland.com/ai-search-seo-fundamentals-462721">thrive in the age of AI search</a>.&nbsp;</p>



<h3 class="wp-block-heading" id="h-website">Website</h3>



<p>In traditional SEO and PPC models, users often land on the most relevant page for their query.&nbsp;</p>



<p>That may be upper-funnel marketing content that leads deeper into the journey or directly to product or service pages.</p>



<p>This still happens, but there is now a noticeable increase in homepage visits driven by brand searches after AI-based research.</p>



<p>As a result, website navigation and messaging must be exceptionally clear.&nbsp;</p>



<p>You need to understand user needs and make the path to relevant content as simple as possible.</p>



<p>The <a href="https://searchengineland.com/website-matters-ai-age-458829">ALCHEMY website planning framework</a> can help restructure sites around the expectations of an AI-savvy user.</p>



<h3 class="wp-block-heading" id="h-content-nbsp">Content&nbsp;</h3>



<p>In the age of AI, the devil is in the details.</p>



<p>If you want AI to recommend your brand or include it in increasingly nuanced research, your most important content must be visible and accessible so it can be retrieved and used to generate AI answers through retrieval-augmented generation, or RAG.</p>



<p>Frameworks such as “They Ask, You Answer” (TAYA) by Marcus Sheridan are particularly effective here.&nbsp;</p>



<p>The premise is simple: If customers ask the question, you should answer it.</p>



<p>The framework focuses on five core areas, identified through extensive research, that address customer needs, drive engagement, and provide AI with the detailed information it needs to map to real user questions.</p>



<p>This approach works because it makes sense. It benefits users, improves visibility, drives leads, and supports sales. It is not an abstract AI strategy. It is good marketing.</p>



<p>These are the five key areas that TAYA focuses on:</p>



<ul class="wp-block-list">
<li><strong>Pricing and cost</strong>: If users search for pricing and cannot find it, they do not assume they should call for details.&nbsp;They often assume the product is too expensive or that information is being withheld, and they move on, or ask AI for a competitor’s pricing. Even when pricing is custom, you should explain the factors that influence cost.</li>



<li><strong>Problems</strong>: Address the obvious issues. This includes problems with your product, your industry, and the drawbacks of specific solutions. Being transparent about limitations builds trust more effectively than excessive positivity.</li>



<li><strong>Versus and comparisons</strong>: Buyers are choosing between alternatives. If you do not create comparison content, someone else will. Be objective. If a competitor is better for a specific use case, say so and focus on your ideal customer profile.</li>



<li><strong>Reviews and ratings</strong>: People look for the best options and trust peer opinions more than brand claims. Create honest reviews of products and services in your space, including competitors. This process is informative for both users and brands.</li>



<li><strong>Best in class</strong>:  Users frequently search for “best” solutions. Lists such as “Top AI marketing agencies in [city]” are effective, even when they include competitors.&nbsp;Including alternatives demonstrates that customer fit matters more than self-promotion.</li>
</ul>



<p>From an AI and SEO perspective in 2026, these five topics represent some of the highest-value data points for RAG systems.</p>



<p>Tools such as the <a href="https://searchengineland.com/generate-seo-content-ideas-value-proposition-canvas-440587">Value Proposition Canvas</a> and <a href="http://searchengineland.com/scamper-seo-content-marketing-ideas-443248">SCAMPER</a> can support ideation and content variation, helping AI better understand your offerings.</p>



<h2 class="wp-block-heading" id="h-checklist-rag-friendly-formatting-tips">Checklist: RAG-friendly formatting tips</h2>



<p>Do not break content into meaningless fragments. Instead, use formatting that helps RAG systems navigate comprehensive resources:</p>



<ul class="wp-block-list">
<li><strong>Use question-based headers:</strong> Mirror real user questions in H2s and H3s, such as “How much does X cost?”</li>



<li><strong>Lead with the answer:</strong> Apply the inverted pyramid. Start with the direct response, then add context.</li>



<li><strong>Use bulleted lists for attributes:</strong> Bullets help RAG systems extract structured information.</li>



<li><strong>Define key terms:</strong> Provide clear, one-sentence definitions for industry jargon.</li>



<li><strong>Link to evidence:</strong> Cite sources for statistics and results to support credibility.</li>
</ul>



<p>Treat blog posts as a knowledge base for AI. The clearer and more specific the information, the more retrievable your brand becomes.</p>



<h2 class="wp-block-heading" id="h-write-for-humans-not-for-bots">Write for humans, not for bots</h2>



<p>It bears repeating: Content should not be simplified solely for AI.&nbsp;</p>



<p>Google Search Liaison Danny Sullivan has clarified that <a href="https://searchengineland.com/google-doesnt-want-you-to-create-bite-sized-chunks-of-your-content-467269">Google does not want content rewritten into bite-sized chunks</a> for AI consumption.</p>



<p>Modern search systems and RAG pipelines can extract relevant information from well-structured, long-form content.&nbsp;</p>



<p>There is no need to dilute expertise or create multiple versions of the same page.</p>



<p>A familiar example is being deep-linked to a specific section of a page from search results. This is established behavior, not new technology.</p>



<p>Some formats, such as FAQs, naturally benefit from concise structure. Use judgment based on the question being answered.</p>



<h2 class="wp-block-heading" id="h-seo-v2026-0">SEO v2026.0</h2>



<p>These are positive changes. SEO is becoming <a href="https://searchengineland.com/integrate-seo-broader-marketing-strategy-452030">more closely aligned with marketing</a> and less of a fringe discipline.</p>



<p>The environment is shifting, and new tools are changing how people find information and make decisions. Yet many fundamentals remain.</p>



<p>SEO tactics still apply, but AI now acts as a superconsumer and summarizer of the information that influences choice.</p>



<p>The task is to identify, create, and structure that information so that when users ask a question, you have already answered it and are part of the conversation.</p>

AI Overviews, which place generated answers directly at the top of search results, are improving the search experience for users. 
For businesses that rely on content to drive traffic from search engines, the impact is far less positive.
Google has been moving toward more “helpful” results for years, and zero-click searches are nothing new. 
AI Overviews accelerate that shift, absorbing much of the traffic opportunity that search has historically provided.
How AI changes the work of search
For years, search followed a familiar pattern:
A user entered a short query, such as “team building companies.”
Google returned a page of paid and organic results.
The user did the work of reviewing and refining.
Most of the effort happened at the end of the process. 
Google organized results based on intent and behavioral signals, but users still had to click through listings, conduct follow-up searches, and piece together an answer.
AI reverses that flow:
The user asks a more detailed question.
AI runs multiple searches and processes the results.
AI delivers a summarized response.
Traditional search allows for refinement, but each new query effectively resets the experience. 
AI, by contrast, is conversational. Each interaction builds on the last, narrowing in on what the user actually wants.
The result is a faster, cleaner path to an answer – with far less effort required from the user.
The path of least resistance
This shift matters because it aligns with a basic human tendency.
People generally choose the easiest available option. If something is easier and produces a better result, adoption follows quickly.
This is how search replaced older marketing channels such as the Yellow Pages.
Seeking the path of least resistance is an evolutionary trait that likely served humans well in earlier eras. 
Today, however, it often shapes behavior in less intentional ways, including how people interact with ads and information.
AI is not perfect, but it is typically faster, easier, and more effective than digging through traditional search results. 
That advantage makes widespread adoption inevitable, especially as AI continues to be integrated into the websites, apps, and devices people already use.
What does this mean for search marketing?
Recent studies have shown that more users are beginning their research with AI tools rather than search engines. 
These studies always have their critics, but the broader point is something of a moot one: AI is everywhere.
AI is now so integrated into the tools people already use that it is becoming the default. 
Search engines, messaging platforms like WhatsApp, and mobile devices are all moving in this direction, and this is just the beginning. 
With Google having signed a multiyear deal with Apple, Google AI will power a significant share of mobile devices, accelerating the shift toward AI-first experiences.
It’s easy to envision an AI-first future, much like the shift from desktop to mobile and then mobile-first.
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See terms.
What this change actually looks like
Generative answers are shifting where users enter the funnel, with engagement increasingly starting mid-funnel around content that demonstrates experience and expertise.
This is the type of content users historically would only engage with on a company’s website, or through other owned channels such as YouTube.
This does not mean top-of-the-funnel content is no longer important. Blogs, guides, and videos still matter, videos in particular. However, it may be worth reconsidering how that content is distributed rather than relying solely on traditional organic search.
With the rise of AI tools such as Gemini and ChatGPT, users can now handle much of this comparison work through AI, saving significant time.
For example, the shift looks like this:
From “Mid market ERP platforms.” Where the user must sift through results, compare options, build spreadsheets, and conduct extensive manual review.
To “Which mid-market ERP platforms work best for manufacturing firms, integrate with our existing stack of X, Y, and Z, and won’t collapse during implementation?”
This changes where the user must exert effort.
A more detailed question or input produces a far stronger response or output. 
You could argue that traditional search had degraded into a form of garbage in, garbage out (GIGO), where short, generic queries produced ad-heavy, blended results that were time-consuming to mine for real answers.
The result is user fatigue. Endless clicking, avoiding ads, and sorting through widely varying content has become a chore.
And the experience often does not improve once users reach the destination. Traffic-starved, ad-heavy websites can be just as difficult to navigate and extract useful information from.
AI offers a cleaner, faster, and less cluttered experience, delivering summarized pros, cons, and supporting evidence at each stage of the decision-making process.
All of this can happen inside an AI tool, without the user ever needing to visit the site where the content originated.
AI is increasingly becoming the default interface for information. These are still early days, and the experience will continue to improve, becoming faster, smoother, and more effective over time.
The crux of the SEO vs. GEO/AEO/AIO conversation is often that, despite a changing landscape, SEO and GEO are largely the same.
This is broadly true and, if anything, feels similar to the early days of SEO, when long-tail opportunities were real. 
You can now go much deeper with mid-funnel content because it no longer requires humans to read it all. 
Instead, AI can consume it and summarize the relevant parts.
The tactics are largely the same. Much of AI still sits on top of traditional search, but SEO strategies and execution may need adjustment to ensure all bases are covered.
It’s also important not to throw the baby out with the bathwater. 
SEO, PPC, and related channels all retain value in the age of AI.
Dig deeper: SEO, GEO, or ASO? What to call the new era of brand visibility in AI [Research]
How to adapt in an AI-first search environment
The game has changed. Planning for 2026 and beyond requires accepting that change and making practical adjustments to thrive in the age of AI search. 
Website
In traditional SEO and PPC models, users often land on the most relevant page for their query. 
That may be upper-funnel marketing content that leads deeper into the journey or directly to product or service pages.
This still happens, but there is now a noticeable increase in homepage visits driven by brand searches after AI-based research.
As a result, website navigation and messaging must be exceptionally clear. 
You need to understand user needs and make the path to relevant content as simple as possible.
The ALCHEMY website planning framework can help restructure sites around the expectations of an AI-savvy user.
Content 
In the age of AI, the devil is in the details.
If you want AI to recommend your brand or include it in increasingly nuanced research, your most important content must be visible and accessible so it can be retrieved and used to generate AI answers through retrieval-augmented generation, or RAG.
Frameworks such as “They Ask, You Answer” (TAYA) by Marcus Sheridan are particularly effective here. 
The premise is simple: If customers ask the question, you should answer it.
The framework focuses on five core areas, identified through extensive research, that address customer needs, drive engagement, and provide AI with the detailed information it needs to map to real user questions.
This approach works because it makes sense. It benefits users, improves visibility, drives leads, and supports sales. It is not an abstract AI strategy. It is good marketing.
These are the five key areas that TAYA focuses on:
Pricing and cost: If users search for pricing and cannot find it, they do not assume they should call for details. They often assume the product is too expensive or that information is being withheld, and they move on, or ask AI for a competitor’s pricing. Even when pricing is custom, you should explain the factors that influence cost.
Problems: Address the obvious issues. This includes problems with your product, your industry, and the drawbacks of specific solutions. Being transparent about limitations builds trust more effectively than excessive positivity.
Versus and comparisons: Buyers are choosing between alternatives. If you do not create comparison content, someone else will. Be objective. If a competitor is better for a specific use case, say so and focus on your ideal customer profile.
Reviews and ratings: People look for the best options and trust peer opinions more than brand claims. Create honest reviews of products and services in your space, including competitors. This process is informative for both users and brands.
Best in class:  Users frequently search for “best” solutions. Lists such as “Top AI marketing agencies in [city]” are effective, even when they include competitors. Including alternatives demonstrates that customer fit matters more than self-promotion.
From an AI and SEO perspective in 2026, these five topics represent some of the highest-value data points for RAG systems.
Tools such as the Value Proposition Canvas and SCAMPER can support ideation and content variation, helping AI better understand your offerings.
Checklist: RAG-friendly formatting tips
Do not break content into meaningless fragments. Instead, use formatting that helps RAG systems navigate comprehensive resources:
Use question-based headers: Mirror real user questions in H2s and H3s, such as “How much does X cost?”
Lead with the answer: Apply the inverted pyramid. Start with the direct response, then add context.
Use bulleted lists for attributes: Bullets help RAG systems extract structured information.
Define key terms: Provide clear, one-sentence definitions for industry jargon.
Link to evidence: Cite sources for statistics and results to support credibility.
Treat blog posts as a knowledge base for AI. The clearer and more specific the information, the more retrievable your brand becomes.
Write for humans, not for bots
It bears repeating: Content should not be simplified solely for AI. 
Google Search Liaison Danny Sullivan has clarified that Google does not want content rewritten into bite-sized chunks for AI consumption.
Modern search systems and RAG pipelines can extract relevant information from well-structured, long-form content. 
There is no need to dilute expertise or create multiple versions of the same page.
A familiar example is being deep-linked to a specific section of a page from search results. This is established behavior, not new technology.
Some formats, such as FAQs, naturally benefit from concise structure. Use judgment based on the question being answered.
SEO v2026.0
These are positive changes. SEO is becoming more closely aligned with marketing and less of a fringe discipline.
The environment is shifting, and new tools are changing how people find information and make decisions. Yet many fundamentals remain.
SEO tactics still apply, but AI now acts as a superconsumer and summarizer of the information that influences choice.
The task is to identify, create, and structure that information so that when users ask a question, you have already answered it and are part of the conversation.

As AI replaces clicks with answers, user engagement moves deeper into the funnel. Here’s how SEO and content strategies must adapt.

From searching to delegating: Adapting to AI-first search behavior

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist.png" class="attachment-large size-large wp-post-image" alt="Is your account ready for Google AI Max? A pre-test checklist" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Ads’ new Experiment Center gives advertisers a single hub to test strategies and measure impact before scaling.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist.png" class="attachment-large size-large wp-post-image" alt="Is your account ready for Google AI Max? A pre-test checklist" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Is-your-account-ready-for-Google-AI-Max-A-pre-test-checklist-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Ads is rolling out a new Experiment Center, giving advertisers a single place to test, measure, and compare campaign performance.</p>



<p><strong>What’s new</strong>. Google has launched a new help page introducing the Experiment Center, a unified dashboard that brings together traditional Experiments and Lift Studies under one roof. Advertisers can now manage tests around bidding, targeting, and creatives alongside studies measuring brand, search, or conversion lift.</p>



<p><strong>Why we care.</strong> Experimentation in Google Ads has historically been fragmented, with A/B tests and lift studies living in different places. A centralized hub lowers friction and makes it easier for advertisers to validate strategy before scaling spend.</p>



<p><strong>How it works:</strong> The new layout streamlines setup and reporting, surfacing key insights from tests in one place instead of across multiple tools. This makes it easier to compare outcomes, understand impact, and move from testing to action faster.</p>



<p><strong>Between the lines</strong>. The Experiment Center builds on Google’s recent push toward experimentation, following updates like expanded <a href="https://searchengineland.com/google-ads-tests-a-b-experiments-for-shopping-ad-product-data-467644">A/B testing in Shopping and Performance Max campaigns</a> and more recently their <a href="https://searchengineland.com/google-adds-cross-campaign-testing-with-new-mix-experiments-beta-467837">Campaign Mix Experiments beta</a>. As automation takes on more decision-making, advertisers will need these new ways to test changes, prove impact, and regain confidence in an increasingly opaque system.</p>



<p><strong>Bottom line:</strong> Advertisers should start using the <a href="https://support.google.com/google-ads/answer/16856494">Experiment Center</a> to formalize testing around bidding, targeting, and creative, using lift studies and experiments to validate changes before rolling them out at scale.</p>



<p><strong>First seen. </strong>This update was discovered by Hana Kobzová of <a href="https://ppcnewsfeed.com/ppc-news/2026-01/google-ads-launches-new-experiment-center/">PPC News Feed</a>.</p>


Google Ads is rolling out a new Experiment Center, giving advertisers a single place to test, measure, and compare campaign performance.
What’s new. Google has launched a new help page introducing the Experiment Center, a unified dashboard that brings together traditional Experiments and Lift Studies under one roof. Advertisers can now manage tests around bidding, targeting, and creatives alongside studies measuring brand, search, or conversion lift.
Why we care. Experimentation in Google Ads has historically been fragmented, with A/B tests and lift studies living in different places. A centralized hub lowers friction and makes it easier for advertisers to validate strategy before scaling spend.
How it works: The new layout streamlines setup and reporting, surfacing key insights from tests in one place instead of across multiple tools. This makes it easier to compare outcomes, understand impact, and move from testing to action faster.
Between the lines. The Experiment Center builds on Google’s recent push toward experimentation, following updates like expanded A/B testing in Shopping and Performance Max campaigns and more recently their Campaign Mix Experiments beta. As automation takes on more decision-making, advertisers will need these new ways to test changes, prove impact, and regain confidence in an increasingly opaque system.
Bottom line: Advertisers should start using the Experiment Center to formalize testing around bidding, targeting, and creative, using lift studies and experiments to validate changes before rolling them out at scale.
First seen. This update was discovered by Hana Kobzová of PPC News Feed.

Google Ads’ new Experiment Center gives advertisers a single hub to test strategies and measure impact before scaling.

Google Ads debuts centralized Experiment Center

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Why Performance Max looks different for B2B in 2026" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>PMax for B2B depends on conversion signals, market size, and tolerance for automation. Learn when it’s worth testing.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Why Performance Max looks different for B2B in 2026" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/01/Why-Performance-Max-looks-different-for-B2B-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google doesn’t build products with B2B marketers in mind.&nbsp;</p>



<p>Its largest budgets and transaction volume come from DTC and B2C brands, so that’s where product development naturally starts.</p>



<p>That’s why new Google products rarely work for B2B out of the gate.&nbsp;</p>



<p>Over my 15+ years in advertising, I’ve seen this pattern repeat: initial release, poor B2B fit, then gradual improvement after about two years.&nbsp;</p>



<p>We saw it with responsive search ads, broad match (yes, I thought it was the end of times, too), and dynamic search ads.</p>



<p><a href="https://searchengineland.com/google-performance-max-431821">Performance Max</a> follows the same trajectory.</p>



<p>Three years ago, I would have said “absolutely not” for B2B organizations. In 2026, that answer looks very different.</p>



<p>Does Performance Max work for every B2B advertiser?&nbsp;</p>



<p>No, and it shouldn’t.&nbsp;</p>



<p>This article focuses on who is a good fit and who should still stay away. Because if you’re not testing new tactics, you aren&#8217;t meaningfully changing the results you’re getting today.</p>



<h2 class="wp-block-heading" id="h-pmax-101-for-b2bs">PMax 101 for B2Bs</h2>



<p>If you’re reading this article, I’m assuming one of three things:&nbsp;</p>



<ul class="wp-block-list">
<li>Performance Max isn’t working for you.</li>



<li>You haven’t dared to try it yet.</li>



<li>Or you’re simply curious about what you could improve.</li>
</ul>



<p>Let’s start with a quick refresher.&nbsp;</p>



<p>Performance Max is a goal-based campaign type that allows advertisers to access all Google Ads inventory from a single campaign.</p>



<p>Today, that inventory includes YouTube, Display, Search, Discover, Gmail, and Maps.&nbsp;</p>



<p>We’re also starting to see ads in AI Overviews powered by Performance Max.&nbsp;</p>



<p>If AI Overviews are already showing up in your industry, this alone should put Performance Max on your radar.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/top-performance-max-optimization-tips-461913">Top Performance Max optimization tips for 2026</a></em></strong></p>



<p>Seeing ads run across all Google networks can feel intimidating, especially for lead generation organizations without a shopping feed. That’s fine – you don’t need one.</p>



<p>One of the biggest benefits we’ve seen is the ability to reach people within the buying group who wouldn’t normally engage through traditional search alone.&nbsp;</p>



<p>Performance Max expands visibility beyond the small set of high-intent users who actively raise their hand.</p>



<p>It has also proven effective for nurturing prospects across long, complex sales cycles.&nbsp;</p>



<p>For B2B advertisers, where decisions can take months and involve multiple stakeholders, that sustained presence can make a meaningful difference.</p>



<h2 class="wp-block-heading" id="h-what-needs-to-be-in-place-before-testing-performance-max">What needs to be in place before testing Performance Max</h2>



<p>There are a few requirements you can’t avoid.&nbsp;</p>



<p>With Performance Max, you’re not targeting keywords. You’re targeting signals. That distinction matters.</p>



<p>These are the signals I need to see before even starting a conversation about Performance Max readiness.</p>



<p>First, you need to import your source of truth by connecting to Salesforce or your CRM of choice.&nbsp;</p>



<p>Optimization should be tied to a meaningful online event, such as a qualified lead submission or an appointment booked.&nbsp;</p>



<p>If the conversion action isn’t meaningful, Performance Max won’t be either.</p>



<p>Your bid strategy must be set to maximize conversions or target CPA. Performance Max is built to learn and optimize around outcomes, not traffic.</p>



<p>You should also import a customer list of existing customers so the system can identify and model similar characteristics.&nbsp;</p>



<p>While website remarketing audiences can be used, they don’t deliver the same level of performance as first-party customer data.</p>



<p>As noted earlier, what makes Performance Max work is its ability to nurture leads over time.&nbsp;</p>



<p>Providing truly down-funnel signals is the foundation of a successful test – and ultimately, a successful campaign.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/b2b-brands-shift-keywords-performance-max-464327">Why B2B brands are shifting from keywords to Performance Max</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-when-pmax-is-not-the-right-fit">When PMax is not the right fit</h2>



<p>Performance Max is not a universal solution, and that’s important to say out loud.&nbsp;</p>



<p>If your B2B motion relies on a small, highly controlled target list, this is likely not the right tool.&nbsp;</p>



<p>Account-based marketing with a few hundred named accounts still performs better with more manual control.</p>



<p>Market fit matters. You need a reasonably sized total addressable market.&nbsp;</p>



<p>If you’re only targeting private equity firms, for example, Performance Max is unlikely to be effective.&nbsp;</p>



<p>The same applies when the audience is extremely restricted. In those cases, Performance Max simply doesn’t have enough room to learn and scale.</p>



<p>The same is true if your conversion actions are too high level or disconnected from revenue.&nbsp;</p>



<p>If the only signal you can provide is a form fill with no qualification behind it, Performance Max will struggle to understand what success actually looks like.</p>



<p>Lastly, Performance Max can be frustrating if your organization isn’t ready to let automation run without constant intervention.&nbsp;</p>



<p>It rewards patience and clean inputs. If every fluctuation triggers a reset or rebuild, results will never stabilize.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-optimize-b2b-ppc-spend-when-budgets-and-confidence-are-low-454592">How to optimize B2B PPC spend when budgets and confidence are low</a></em></strong></p>



<h2 class="wp-block-heading" id="h-what-performance-max-can-and-can-t-do-for-b2b">What Performance Max can and can’t do for B2B</h2>



<p>Performance Max is not a silver bullet for B2B advertising, and it never was.&nbsp;</p>



<p>But it’s also no longer the immediate no it once was for many B2B organizations.</p>



<p>When the fundamentals are in place – meaningful conversion signals, a sufficiently large addressable market, and the patience to let automation do its job – Performance Max can play a valuable role in supporting long, complex buying journeys, especially when the goal isn’t just capturing demand, but helping create and nurture it.</p>



<p>The key is honesty. Be honest about your data, your audience, and your internal tolerance for automation.&nbsp;</p>



<p>If those pieces aren’t ready, Performance Max will likely disappoint.&nbsp;</p>



<p>If they are, it can become a strong complement to existing search and demand generation efforts.</p>



<p>As with most things in B2B advertising, success doesn’t come from chasing the newest feature.&nbsp;</p>



<p>It comes from testing intentionally, measuring what actually matters, and knowing when a tool fits your business and when it doesn’t.</p>



<p></p>

Google doesn’t build products with B2B marketers in mind. 
Its largest budgets and transaction volume come from DTC and B2C brands, so that’s where product development naturally starts.
That’s why new Google products rarely work for B2B out of the gate. 
Over my 15+ years in advertising, I’ve seen this pattern repeat: initial release, poor B2B fit, then gradual improvement after about two years. 
We saw it with responsive search ads, broad match (yes, I thought it was the end of times, too), and dynamic search ads.
Performance Max follows the same trajectory.
Three years ago, I would have said “absolutely not” for B2B organizations. In 2026, that answer looks very different.
Does Performance Max work for every B2B advertiser? 
No, and it shouldn’t. 
This article focuses on who is a good fit and who should still stay away. Because if you’re not testing new tactics, you aren’t meaningfully changing the results you’re getting today.
PMax 101 for B2Bs
If you’re reading this article, I’m assuming one of three things: 
Performance Max isn’t working for you.
You haven’t dared to try it yet.
Or you’re simply curious about what you could improve.
Let’s start with a quick refresher. 
Performance Max is a goal-based campaign type that allows advertisers to access all Google Ads inventory from a single campaign.
Today, that inventory includes YouTube, Display, Search, Discover, Gmail, and Maps. 
We’re also starting to see ads in AI Overviews powered by Performance Max. 
If AI Overviews are already showing up in your industry, this alone should put Performance Max on your radar.
Dig deeper: Top Performance Max optimization tips for 2026
Seeing ads run across all Google networks can feel intimidating, especially for lead generation organizations without a shopping feed. That’s fine – you don’t need one.
One of the biggest benefits we’ve seen is the ability to reach people within the buying group who wouldn’t normally engage through traditional search alone. 
Performance Max expands visibility beyond the small set of high-intent users who actively raise their hand.
It has also proven effective for nurturing prospects across long, complex sales cycles. 
For B2B advertisers, where decisions can take months and involve multiple stakeholders, that sustained presence can make a meaningful difference.
What needs to be in place before testing Performance Max
There are a few requirements you can’t avoid. 
With Performance Max, you’re not targeting keywords. You’re targeting signals. That distinction matters.
These are the signals I need to see before even starting a conversation about Performance Max readiness.
First, you need to import your source of truth by connecting to Salesforce or your CRM of choice. 
Optimization should be tied to a meaningful online event, such as a qualified lead submission or an appointment booked. 
If the conversion action isn’t meaningful, Performance Max won’t be either.
Your bid strategy must be set to maximize conversions or target CPA. Performance Max is built to learn and optimize around outcomes, not traffic.
You should also import a customer list of existing customers so the system can identify and model similar characteristics. 
While website remarketing audiences can be used, they don’t deliver the same level of performance as first-party customer data.
As noted earlier, what makes Performance Max work is its ability to nurture leads over time. 
Providing truly down-funnel signals is the foundation of a successful test – and ultimately, a successful campaign.
Dig deeper: Why B2B brands are shifting from keywords to Performance Max
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See terms.
When PMax is not the right fit
Performance Max is not a universal solution, and that’s important to say out loud. 
If your B2B motion relies on a small, highly controlled target list, this is likely not the right tool. 
Account-based marketing with a few hundred named accounts still performs better with more manual control.
Market fit matters. You need a reasonably sized total addressable market. 
If you’re only targeting private equity firms, for example, Performance Max is unlikely to be effective. 
The same applies when the audience is extremely restricted. In those cases, Performance Max simply doesn’t have enough room to learn and scale.
The same is true if your conversion actions are too high level or disconnected from revenue. 
If the only signal you can provide is a form fill with no qualification behind it, Performance Max will struggle to understand what success actually looks like.
Lastly, Performance Max can be frustrating if your organization isn’t ready to let automation run without constant intervention. 
It rewards patience and clean inputs. If every fluctuation triggers a reset or rebuild, results will never stabilize.
Dig deeper: How to optimize B2B PPC spend when budgets and confidence are low
What Performance Max can and can’t do for B2B
Performance Max is not a silver bullet for B2B advertising, and it never was. 
But it’s also no longer the immediate no it once was for many B2B organizations.
When the fundamentals are in place – meaningful conversion signals, a sufficiently large addressable market, and the patience to let automation do its job – Performance Max can play a valuable role in supporting long, complex buying journeys, especially when the goal isn’t just capturing demand, but helping create and nurture it.
The key is honesty. Be honest about your data, your audience, and your internal tolerance for automation. 
If those pieces aren’t ready, Performance Max will likely disappoint. 
If they are, it can become a strong complement to existing search and demand generation efforts.
As with most things in B2B advertising, success doesn’t come from chasing the newest feature. 
It comes from testing intentionally, measuring what actually matters, and knowing when a tool fits your business and when it doesn’t.

PMax for B2B depends on conversion signals, market size, and tolerance for automation. Learn when it’s worth testing.

Why Performance Max looks different for B2B in 2026

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026.png" class="attachment-large size-large wp-post-image" alt="Why first-touch analytics matters more than ever for SEO in 2026" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI-driven search is breaking last-touch attribution. First-touch analytics reveals SEO’s role in discovery, influence, and revenue.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026.png" class="attachment-large size-large wp-post-image" alt="Why first-touch analytics matters more than ever for SEO in 2026" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Why-first-touch-analytics-matters-more-than-ever-for-SEO-in-2026-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Throughout 2025, <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> professionals reported the same story to leadership: organic traffic was down, clicks were declining, and attribution no longer made sense. </p>



<p>AI-driven search experiences, zero-click results, and platform-level answers widened the gap between discovery and measurable visits, making it harder than ever to accurately report on organic performance.</p>



<p>For many organizations, this showed up as double-digit, year-over-year declines in reported organic traffic and leads. </p>



<p>The C-suite asked the obvious questions: Why are clicks down? Why does organic traffic look 25% lower than last year? Is SEO actually hurting the business?</p>



<p>The problem wasn’t that organic search stopped working. It was that the way most organizations measure it no longer reflects how discovery happens today.</p>



<h2 class="wp-block-heading" id="h-why-last-touch-attribution-is-the-wrong-model-for-2026">Why last-touch attribution is the wrong model for 2026</h2>



<p>We have not been accurately measuring organic search. </p>



<p>Many organizations still rely on last-touch attribution, which measures the end of the customer journey – not the start.</p>



<p>Our <a href="https://searchengineland.com/marketing-attribution-models-the-pros-and-cons-451733">attribution models</a> are linear – <em>Search → Click → Convert</em> – but user behavior is not.</p>



<p>Most traditional attribution models assume discovery leads to a measurable click. </p>



<p>Today, AI-driven SERPs are challenging that assumption and widening the gap between influence and revenue credit.</p>



<p>Last-touch attribution rewards the finish line – not the start of the race. </p>



<p>Which is to say, last-touch attribution collapses in an AI-first, zero-click world, especially for organic search. AI-driven search is accelerating attribution blind spots.</p>



<p>Our measurement is not broken. It&#8217;s outdated and doesn&#8217;t tell us the holistic story.</p>



<p>As an industry, we need to rethink our KPIs and how to measure success. </p>



<p>We need to tell the full data story throughout the entire customer journey, from the very top and down to the click and conversion.</p>



<p><em><strong>Dig deeper: </strong></em><a href="https://searchengineland.com/guide/marketing-attribution"><strong><em>Marketing attribution guide: Models, tools, &amp; best practices</em></strong></a></p>



<h2 class="wp-block-heading" id="h-so-why-is-last-touch-a-problem">So why is last touch a problem?</h2>



<p>Last-touch attribution only measures the end of the customer journey.</p>



<p>Because of that, it misses all interactions that occur before the conversion, across channels like Google, Reddit, YouTube, AI Overviews, AI Mode, ChatGPT, Instagram, email, paid SERP listings, and more.</p>



<p>Most users of Google Analytics or Adobe Analytics rely on last-touch attribution when setting up their analytics. </p>



<p>This works as a baseline, but to tell the full story, you also need to understand where your first touches are coming from.</p>



<p>This is especially true as traditional organic traffic – click-throughs from the SERPs – continues to decline with the rise of AI Overviews and AI Mode.</p>



<h2 class="wp-block-heading" id="h-do-you-have-the-data-you-need-for-first-touch-attribution">Do you have the data you need for first-touch attribution?</h2>



<p>Many organizations have data that is messy, siloed, and replete with quality and integrity issues.</p>



<p>Take a look at yours and ask yourself whether you can easily find the answer to these questions: </p>



<ul class="wp-block-list">
<li>How are my customers entering the marketing funnel through organic?</li>



<li>Should it be paid, direct, referral, or AI that gets the conversion attribution?</li>



<li>Do I have a sense of AI referrals? Have we set up a different channel in our analytics platform to capture AI referrals specifically?</li>



<li>Can we tell the difference in conversion rates based on which channel is the first touchpoint? For example, how is the paid conversion rate different when organic is the first touch point? Or when it’s not?</li>
</ul>



<p>If users aren’t searching more and clicking through to your site, it doesn’t mean organic is necessarily down or that your SEO program is not working well and is not worth it. </p>



<p>It’s likely that you&#8217;re either not measuring SEO accurately or appropriately.</p>



<p>So what’s the answer here? </p>



<p>Clean up your data, invest time in analyzing every channel that’s driving traffic to your website, and really dig into how organic search is still impacting your overall SEO efforts.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/guide/measuring-visibility-in-zero-click-world">Measuring zero-click search: Visibility-first SEO for AI results</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-why-first-touch-analytics-will-prove-organic-results-still-matter">Why first-touch analytics will prove organic results still matter</h2>



<p>When a user searches and your brand is mentioned – but not linked – in an AI response, discovery has still happened.</p>



<p>If that same user visits your site the next day through social or direct, or shows up at a brick-and-mortar store, does that mean SEO didn’t work?</p>



<p>Of course not!</p>



<p>Organic results brought the user into the funnel just by being referenced, cited, visible – top of mind. </p>



<p>But how do you measure that when the last-touch was a direct, or social, or referral click and/or conversion?</p>



<p>Organic search was the entry point – even without a click – and arguably extremely important to other channels. </p>



<p>Without knowing and measuring first-touch and last-touch attribution, marketers can’t answer this question. </p>



<p>Organic search often introduces the category, frames the problem, and establishes credibility and perception about your brand before a buyer ever visits a website, watches a video, or visits a forum.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/marketing-attribution-definitions-438907">7 must-know marketing attribution definitions to avoid getting gamed</a></em></strong></p>



<h2 class="wp-block-heading" id="h-visibility-is-the-key-seo-phrase-of-2026">Visibility is the key SEO phrase of 2026</h2>



<p>The new SEO currency in 2026 isn’t keywords, impressions, or clicks – it’s visibility through mentions and citations.</p>



<p>If AI systems select which brands to cite, organic visibility becomes a prerequisite for consideration, not just traffic.</p>



<p>Remember what “organic” means today: a user searches and discovers your brand on their own, without paid promotion. Ten or 15 years ago, that usually meant Google.</p>



<p>Today, however, a potential customer can search, discover, and research brands everywhere: YouTube, Reddit, Instagram, TikTok, ChatGPT, and, yes, still &#8220;Google it.&#8221;</p>



<p>They can also get answers and information summarized through Web Guide, AI Overviews, and AI Mode without a visit to the company’s website.&nbsp;</p>



<p>As marketers, we need to get clever about what visibility means today and how we will expand it.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/build-search-visibility-before-demand-exists-466516">How to build search visibility before demand exists</a></em></strong></p>



<h2 class="wp-block-heading" id="h-2026-is-the-year-to-grow-seo-not-shrink-it">2026 is the year to grow SEO, not shrink it</h2>



<p>As search becomes more fragmented and AI-driven experiences reduce clicks, SEO’s role in discovery has not diminished – it has moved earlier in the journey. </p>



<p>The problem isn’t that organic search stopped working. It’s that post-click measurement no longer captures where influence actually begins.</p>



<p>Last-touch attribution undervalues early discovery and systematically under-credits SEO, especially in an AI-first, zero-click environment. </p>



<p>First-touch analysis helps correct that by connecting organic visibility to downstream influence, conversions, and revenue.</p>



<p>AI Overviews, AI Mode, and platforms like ChatGPT are accelerating these measurement gaps, and best practices are still emerging. </p>



<p>But this isn’t a new challenge for the industry. We’ve navigated data silos and attribution blind spots before.</p>



<p>In 2026, the teams that collaborate across analytics, SEO, and other channels – and invest in first-touch measurement – will be best positioned to prove organic’s impact and make better, more complete decisions. </p>



<p>Those who modernize how SEO is measured will be the ones who continue to justify and grow investment, even as clicks decline.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/mta-vs-mmm-which-marketing-attribution-model-is-right-for-you-452368">MTA vs. MMM: Which marketing attribution model is right for you?</a></em></strong></p>

Throughout 2025, SEO professionals reported the same story to leadership: organic traffic was down, clicks were declining, and attribution no longer made sense. 
AI-driven search experiences, zero-click results, and platform-level answers widened the gap between discovery and measurable visits, making it harder than ever to accurately report on organic performance.
For many organizations, this showed up as double-digit, year-over-year declines in reported organic traffic and leads. 
The C-suite asked the obvious questions: Why are clicks down? Why does organic traffic look 25% lower than last year? Is SEO actually hurting the business?
The problem wasn’t that organic search stopped working. It was that the way most organizations measure it no longer reflects how discovery happens today.
Why last-touch attribution is the wrong model for 2026
We have not been accurately measuring organic search. 
Many organizations still rely on last-touch attribution, which measures the end of the customer journey – not the start.
Our attribution models are linear – Search → Click → Convert – but user behavior is not.
Most traditional attribution models assume discovery leads to a measurable click. 
Today, AI-driven SERPs are challenging that assumption and widening the gap between influence and revenue credit.
Last-touch attribution rewards the finish line – not the start of the race. 
Which is to say, last-touch attribution collapses in an AI-first, zero-click world, especially for organic search. AI-driven search is accelerating attribution blind spots.
Our measurement is not broken. It’s outdated and doesn’t tell us the holistic story.
As an industry, we need to rethink our KPIs and how to measure success. 
We need to tell the full data story throughout the entire customer journey, from the very top and down to the click and conversion.
Dig deeper: Marketing attribution guide: Models, tools, & best practices
So why is last touch a problem?
Last-touch attribution only measures the end of the customer journey.
Because of that, it misses all interactions that occur before the conversion, across channels like Google, Reddit, YouTube, AI Overviews, AI Mode, ChatGPT, Instagram, email, paid SERP listings, and more.
Most users of Google Analytics or Adobe Analytics rely on last-touch attribution when setting up their analytics. 
This works as a baseline, but to tell the full story, you also need to understand where your first touches are coming from.
This is especially true as traditional organic traffic – click-throughs from the SERPs – continues to decline with the rise of AI Overviews and AI Mode.
Do you have the data you need for first-touch attribution?
Many organizations have data that is messy, siloed, and replete with quality and integrity issues.
Take a look at yours and ask yourself whether you can easily find the answer to these questions: 
How are my customers entering the marketing funnel through organic?
Should it be paid, direct, referral, or AI that gets the conversion attribution?
Do I have a sense of AI referrals? Have we set up a different channel in our analytics platform to capture AI referrals specifically?
Can we tell the difference in conversion rates based on which channel is the first touchpoint? For example, how is the paid conversion rate different when organic is the first touch point? Or when it’s not?
If users aren’t searching more and clicking through to your site, it doesn’t mean organic is necessarily down or that your SEO program is not working well and is not worth it. 
It’s likely that you’re either not measuring SEO accurately or appropriately.
So what’s the answer here? 
Clean up your data, invest time in analyzing every channel that’s driving traffic to your website, and really dig into how organic search is still impacting your overall SEO efforts.
Dig deeper: Measuring zero-click search: Visibility-first SEO for AI results
Get the newsletter search marketers rely on.
  
				
								
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See terms.
Why first-touch analytics will prove organic results still matter
When a user searches and your brand is mentioned – but not linked – in an AI response, discovery has still happened.
If that same user visits your site the next day through social or direct, or shows up at a brick-and-mortar store, does that mean SEO didn’t work?
Of course not!
Organic results brought the user into the funnel just by being referenced, cited, visible – top of mind. 
But how do you measure that when the last-touch was a direct, or social, or referral click and/or conversion?
Organic search was the entry point – even without a click – and arguably extremely important to other channels. 
Without knowing and measuring first-touch and last-touch attribution, marketers can’t answer this question. 
Organic search often introduces the category, frames the problem, and establishes credibility and perception about your brand before a buyer ever visits a website, watches a video, or visits a forum.
Dig deeper: 7 must-know marketing attribution definitions to avoid getting gamed
Visibility is the key SEO phrase of 2026
The new SEO currency in 2026 isn’t keywords, impressions, or clicks – it’s visibility through mentions and citations.
If AI systems select which brands to cite, organic visibility becomes a prerequisite for consideration, not just traffic.
Remember what “organic” means today: a user searches and discovers your brand on their own, without paid promotion. Ten or 15 years ago, that usually meant Google.
Today, however, a potential customer can search, discover, and research brands everywhere: YouTube, Reddit, Instagram, TikTok, ChatGPT, and, yes, still “Google it.”
They can also get answers and information summarized through Web Guide, AI Overviews, and AI Mode without a visit to the company’s website. 
As marketers, we need to get clever about what visibility means today and how we will expand it.
Dig deeper: How to build search visibility before demand exists
2026 is the year to grow SEO, not shrink it
As search becomes more fragmented and AI-driven experiences reduce clicks, SEO’s role in discovery has not diminished – it has moved earlier in the journey. 
The problem isn’t that organic search stopped working. It’s that post-click measurement no longer captures where influence actually begins.
Last-touch attribution undervalues early discovery and systematically under-credits SEO, especially in an AI-first, zero-click environment. 
First-touch analysis helps correct that by connecting organic visibility to downstream influence, conversions, and revenue.
AI Overviews, AI Mode, and platforms like ChatGPT are accelerating these measurement gaps, and best practices are still emerging. 
But this isn’t a new challenge for the industry. We’ve navigated data silos and attribution blind spots before.
In 2026, the teams that collaborate across analytics, SEO, and other channels – and invest in first-touch measurement – will be best positioned to prove organic’s impact and make better, more complete decisions. 
Those who modernize how SEO is measured will be the ones who continue to justify and grow investment, even as clicks decline.
Dig deeper: MTA vs. MMM: Which marketing attribution model is right for you?

AI-driven search is breaking last-touch attribution. First-touch analytics reveals SEO’s role in discovery, influence, and revenue.

Why first-touch analytics matters more than ever for SEO in 2026

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Apple Ads- What you need to know" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Apple is adding more ad slots to App Store search results, creating new install opportunities while increasing competition for high-intent searches.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Apple Ads- What you need to know" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Apple is expanding ads in App Store search results, giving advertisers more opportunities to reach users at the moment they’re looking to download apps.</p>



<p>Starting March 3rd, Apple Ads will begin showing additional ads per search query in the UK, followed by Japan. The expansion is expected to roll out to all Apple Ads markets by the end of March.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="488" height="960" src="https://searchengineland.com/wp-content/seloads/2026/01/0082-search-results.png" alt="" class="wp-image-467906"/></figure></div>


<p><strong>Why we care</strong>. More ad slots in App Store search results mean more chances to win installs—but also more competition for the same high-intent queries, which could push up costs. With no ability to choose placements, performance may vary by position, making creative relevance, keyword strategy, and conversion tracking more important than ever.</p>



<p><strong>What’s changing</strong>. Until now, Apple Ads search results featured a single sponsored placement at the top of the page. Beginning in March, multiple ad positions may appear for a single search query, including the existing top slot and new placements further down the results.</p>



<p>The new placements will be supported on devices running iOS and iPadOS 26.2 and later.</p>



<p><strong>How eligibility works</strong>. Advertisers don’t need to make any changes to access the new inventory. Any existing search results campaign will automatically be eligible to appear in all available positions.</p>



<p>However, advertisers can’t choose or bid for specific placements. Apple will decide where an ad appears within search results.</p>



<p><strong>Ad formats and pricing stay the same</strong>. Ads will look the same regardless of placement, using either a default product page or a custom product page. Optional deep links can send users directly to a specific in-app destination.</p>



<p>Billing remains unchanged, with advertisers paying on a cost-per-tap or cost-per-install basis.</p>



<p><strong>How ads are matched to searches</strong>. Search results ads continue to rely on keywords, either selected by advertisers or suggested by Apple. Apple says its relevance-based matching delivers more than a 60% average conversion rate for top-of-search ads.</p>



<p>Placement is determined by a combination of relevance and bid, but relevance is non-negotiable. Apple says ads won’t enter auctions if they aren’t a strong match for the user’s query — regardless of bid size.</p>



<p><strong>What advertisers should watch</strong>. More ad slots mean more opportunities — but also more competition within the same search results page. Advertisers may need to closely monitor performance by query, creative alignment, and conversion rates as the rollout expands globally.</p>



<p><strong>What’s next</strong>. The phased rollout will continue through March, bringing <a href="https://ads.apple.com/app-store/help/ad-placements/0082-search-results?cid=ads-app-store-em-c00376-M02485">additional App Store search ads</a> to all Apple Ads markets. For app marketers, it marks a meaningful shift in how search visibility — and competition — will work inside the App Store.</p>



<p></p>


Apple is expanding ads in App Store search results, giving advertisers more opportunities to reach users at the moment they’re looking to download apps.
Starting March 3rd, Apple Ads will begin showing additional ads per search query in the UK, followed by Japan. The expansion is expected to roll out to all Apple Ads markets by the end of March.

Why we care. More ad slots in App Store search results mean more chances to win installs—but also more competition for the same high-intent queries, which could push up costs. With no ability to choose placements, performance may vary by position, making creative relevance, keyword strategy, and conversion tracking more important than ever.
What’s changing. Until now, Apple Ads search results featured a single sponsored placement at the top of the page. Beginning in March, multiple ad positions may appear for a single search query, including the existing top slot and new placements further down the results.
The new placements will be supported on devices running iOS and iPadOS 26.2 and later.
How eligibility works. Advertisers don’t need to make any changes to access the new inventory. Any existing search results campaign will automatically be eligible to appear in all available positions.
However, advertisers can’t choose or bid for specific placements. Apple will decide where an ad appears within search results.
Ad formats and pricing stay the same. Ads will look the same regardless of placement, using either a default product page or a custom product page. Optional deep links can send users directly to a specific in-app destination.
Billing remains unchanged, with advertisers paying on a cost-per-tap or cost-per-install basis.
How ads are matched to searches. Search results ads continue to rely on keywords, either selected by advertisers or suggested by Apple. Apple says its relevance-based matching delivers more than a 60% average conversion rate for top-of-search ads.
Placement is determined by a combination of relevance and bid, but relevance is non-negotiable. Apple says ads won’t enter auctions if they aren’t a strong match for the user’s query — regardless of bid size.
What advertisers should watch. More ad slots mean more opportunities — but also more competition within the same search results page. Advertisers may need to closely monitor performance by query, creative alignment, and conversion rates as the rollout expands globally.
What’s next. The phased rollout will continue through March, bringing additional App Store search ads to all Apple Ads markets. For app marketers, it marks a meaningful shift in how search visibility — and competition — will work inside the App Store.

Apple is adding more ad slots to App Store search results, creating new install opportunities while increasing competition for high-intent searches.

Apple Ads adds more ad slots to App Store search results

<div><img width="1600" height="900" src="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png 1600w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-1536x864.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></div>One early-career PPC mistake nearly took campaigns offline on Black Friday, but it became a defining lesson in staying calm, &#038; owning errors.

<div><img width="1600" height="900" src="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png 1600w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-1536x864.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></div>
<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe title="The URL Mistake That Killed Black Friday ft Nick Handley" width="500" height="281" src="https://www.youtube.com/embed/IadRhqbz6ws?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p>On episode 338 of PPC Live The Podcast, I speak to Nick Handley Paid Media Lead at Impression, about one of the most formative mistakes of his career — and why those early errors often shape the strongest marketers.</p>



<p>The podcast series focuses on PPC professionals’ biggest “F-ups,” but never without exploring how they recovered, who helped them, and what lasting lessons came out the other side. Nick’s story is a textbook example of how a single mistake can permanently change how you work — for the better.</p>



<h2 class="wp-block-heading" id="h-the-black-friday-mistake-that-took-everything-down">The Black Friday mistake that took everything down</h2>



<p>Nick takes listeners back nearly ten years, to the very start of his career at <em>Tyres on the Drive</em> (now owned by Halfords). With only around seven months of PPC experience, he was left managing campaigns during the Black Friday period while a senior colleague was on holiday.</p>



<p>The task sounded simple: update URLs across multiple campaigns using Google Ads Editor. The execution, however, went very wrong.</p>



<p>Nick mistyped part of the landing page URL — a small error with massive consequences. Once uploaded, ads across the account were disapproved, effectively taking paid search offline during one of the most important trading periods of the year. At the time, PPC accounted for around 70% of the company’s conversions.</p>



<p>“It was full panic,” Nick admits. “I genuinely thought I was going to lose my job.”</p>



<h2 class="wp-block-heading" id="h-panic-makes-problems-worse">Panic makes problems worse</h2>



<p>What made the situation harder wasn’t just the typo — it was what came next. In a stressed state, Nick tried to fix the issue without properly re-syncing Google Ads Editor with the live account. Changes didn’t apply, errors stacked up, and confusion grew.</p>



<p>The turning point came when Max Hopkinson, a senior colleague, stepped in. Instead of blaming or escalating, Max calmly walked Nick through the fix: re-sync the account, undo the changes properly, re-upload, and get campaigns live again.</p>



<p>The downtime was resolved in about an hour, and the team worked strategically to recover performance by increasing spend later in the day. The Black Friday period ultimately performed well — but the emotional impact of the mistake stuck.</p>



<h2 class="wp-block-heading" id="h-the-real-lesson-de-escalate-yourself-first">The real lesson: de-escalate yourself first</h2>



<p>One of the biggest takeaways from Nick’s experience isn’t technical — it’s psychological.</p>



<p>When things go wrong, panic actively makes solutions harder to see. Nick stresses the importance of stepping away, calming yourself down, and then methodically identifying the issue. Five minutes away from the screen can prevent five hours of damage.</p>



<p>This mindset now underpins how he works — and how he manages others.</p>



<h2 class="wp-block-heading" id="h-from-junior-panic-to-leadership-principles">From junior panic to leadership principles</h2>



<p>As a leader today, Nick is intentional about building systems that reduce risk and pressure. At Impression, large changes go through a buddy-based QA system, where someone outside the immediate account team sense-checks major updates before they go live.</p>



<p>The goal isn’t mistrust — it’s safety. Fresh eyes catch errors tired ones miss, especially when working at speed.</p>



<p>Nick is clear that this approach isn’t just for agencies. In-house teams, freelancers, and solo marketers can adapt it using automation, AI checks, or structured workflows to ensure nothing slips through.</p>



<h2 class="wp-block-heading" id="h-ai-is-helpful-but-only-if-you-know-the-basics">AI is helpful — but only if you know the basics</h2>



<p>Nick also warns against leaning too heavily on AI without understanding fundamentals first. While automation and AI can help sense-check work, speed up QA, or manage budgets, they can’t replace foundational knowledge.</p>



<p>“If you don’t know what ‘right’ looks like,” he explains, “you won’t know when AI is wrong.”</p>



<p>This applies to everything from ad copy and keyword research to budget pacing and performance analysis. AI should amplify expertise — not replace it.</p>



<h2 class="wp-block-heading" id="h-accountability-beats-perfection">Accountability beats perfection</h2>



<p>Perhaps the most important message from the episode is that mistakes are inevitable — but hiding them is optional.</p>



<p>Nick emphasizes accountability over blame. When errors happen, the best response is to clearly explain what went wrong, what the impact was, and how it’s being fixed. Most clients and managers are far more understanding than people expect, especially when transparency comes early.</p>



<p>This culture of openness not only protects performance — it protects mental health.</p>



<h2 class="wp-block-heading" id="h-why-sharing-mistakes-makes-better-marketers">Why sharing mistakes makes better marketers</h2>



<p>Nick believes leaders should openly share their failures, not just their wins. Digital marketing already carries intense pressure, constant change, and unrealistic expectations of perfection. Hearing that respected experts still make mistakes — and survive them — normalizes the learning curve.</p>



<p>“We’re not robots,” he says. “We’re people doing complex work in fast-moving systems.”</p>



<h2 class="wp-block-heading" id="h-the-big-takeaway">The big takeaway</h2>



<p>Nick’s early-career mistake didn’t derail his career — it defined it. It shaped how he approaches QA, leadership, automation, and stress. More importantly, it reinforced a truth many PPC professionals need to hear:</p>



<p>Mistakes don’t end careers. Panic, silence, and lack of accountability do.</p>


On episode 338 of PPC Live The Podcast, I speak to Nick Handley Paid Media Lead at Impression, about one of the most formative mistakes of his career — and why those early errors often shape the strongest marketers.
The podcast series focuses on PPC professionals’ biggest “F-ups,” but never without exploring how they recovered, who helped them, and what lasting lessons came out the other side. Nick’s story is a textbook example of how a single mistake can permanently change how you work — for the better.
The Black Friday mistake that took everything down
Nick takes listeners back nearly ten years, to the very start of his career at Tyres on the Drive (now owned by Halfords). With only around seven months of PPC experience, he was left managing campaigns during the Black Friday period while a senior colleague was on holiday.
The task sounded simple: update URLs across multiple campaigns using Google Ads Editor. The execution, however, went very wrong.
Nick mistyped part of the landing page URL — a small error with massive consequences. Once uploaded, ads across the account were disapproved, effectively taking paid search offline during one of the most important trading periods of the year. At the time, PPC accounted for around 70% of the company’s conversions.
“It was full panic,” Nick admits. “I genuinely thought I was going to lose my job.”
Panic makes problems worse
What made the situation harder wasn’t just the typo — it was what came next. In a stressed state, Nick tried to fix the issue without properly re-syncing Google Ads Editor with the live account. Changes didn’t apply, errors stacked up, and confusion grew.
The turning point came when Max Hopkinson, a senior colleague, stepped in. Instead of blaming or escalating, Max calmly walked Nick through the fix: re-sync the account, undo the changes properly, re-upload, and get campaigns live again.
The downtime was resolved in about an hour, and the team worked strategically to recover performance by increasing spend later in the day. The Black Friday period ultimately performed well — but the emotional impact of the mistake stuck.
The real lesson: de-escalate yourself first
One of the biggest takeaways from Nick’s experience isn’t technical — it’s psychological.
When things go wrong, panic actively makes solutions harder to see. Nick stresses the importance of stepping away, calming yourself down, and then methodically identifying the issue. Five minutes away from the screen can prevent five hours of damage.
This mindset now underpins how he works — and how he manages others.
From junior panic to leadership principles
As a leader today, Nick is intentional about building systems that reduce risk and pressure. At Impression, large changes go through a buddy-based QA system, where someone outside the immediate account team sense-checks major updates before they go live.
The goal isn’t mistrust — it’s safety. Fresh eyes catch errors tired ones miss, especially when working at speed.
Nick is clear that this approach isn’t just for agencies. In-house teams, freelancers, and solo marketers can adapt it using automation, AI checks, or structured workflows to ensure nothing slips through.
AI is helpful — but only if you know the basics
Nick also warns against leaning too heavily on AI without understanding fundamentals first. While automation and AI can help sense-check work, speed up QA, or manage budgets, they can’t replace foundational knowledge.
“If you don’t know what ‘right’ looks like,” he explains, “you won’t know when AI is wrong.”
This applies to everything from ad copy and keyword research to budget pacing and performance analysis. AI should amplify expertise — not replace it.
Accountability beats perfection
Perhaps the most important message from the episode is that mistakes are inevitable — but hiding them is optional.
Nick emphasizes accountability over blame. When errors happen, the best response is to clearly explain what went wrong, what the impact was, and how it’s being fixed. Most clients and managers are far more understanding than people expect, especially when transparency comes early.
This culture of openness not only protects performance — it protects mental health.
Why sharing mistakes makes better marketers
Nick believes leaders should openly share their failures, not just their wins. Digital marketing already carries intense pressure, constant change, and unrealistic expectations of perfection. Hearing that respected experts still make mistakes — and survive them — normalizes the learning curve.
“We’re not robots,” he says. “We’re people doing complex work in fast-moving systems.”
The big takeaway
Nick’s early-career mistake didn’t derail his career — it defined it. It shaped how he approaches QA, leadership, automation, and stress. More importantly, it reinforced a truth many PPC professionals need to hear:
Mistakes don’t end careers. Panic, silence, and lack of accountability do.

One early-career PPC mistake nearly took campaigns offline on Black Friday, but it became a defining lesson in staying calm, & owning errors.

The URL mistake that killed Black Friday ft Nick Handley

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png" class="attachment-large size-large wp-post-image" alt="Dealing with Google Ads frustrations: Poor support, suspensions and rising costs" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>A Google Ads bug is causing the option to add account notes to disappear for some advertisers, complicating change tracking and documentation.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png" class="attachment-large size-large wp-post-image" alt="Dealing with Google Ads frustrations: Poor support, suspensions and rising costs" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Some Google Ads advertisers are seeing a bug that causes the option to add notes to disappear from the account change popup, making it harder to document optimizations and performance shifts.</p>



<p>The issue was flagged by paid search consultant Odi Caspi, who says the problem has appeared intermittently over the past couple of weeks.</p>



<p>What advertisers should be seeing:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1302" height="336" src="https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19.png" alt="" class="wp-image-467896" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19.png 1302w, https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19-768x198.png 768w" sizes="(max-width: 1302px) 100vw, 1302px" /></figure>



<p>Caspi shares his view below:</p>



<figure class="wp-block-image size-full is-resized"><img decoding="async" width="800" height="362" src="https://searchengineland.com/wp-content/seloads/2026/01/1769187329142.jpeg" alt="" class="wp-image-467897" style="width:840px;height:auto" srcset="https://searchengineland.com/wp-content/seloads/2026/01/1769187329142.jpeg 800w, https://searchengineland.com/wp-content/seloads/2026/01/1769187329142-768x348.jpeg 768w" sizes="(max-width: 800px) 100vw, 800px" /></figure>



<p><strong>Why we care</strong>. Account notes are a key workflow tool for agencies and in-house teams tracking changes over time. Losing easy access to notes makes troubleshooting performance swings harder and weakens institutional memory across teams.</p>



<p><strong>What users are seeing</strong>. In affected accounts, the “Add note” option no longer appears in the standard popup where advertisers typically annotate changes. The issue appears to be <strong>sporadic</strong>, working normally at times and disappearing at others.</p>



<p><strong>Workarounds, for now</strong>. Caspi says one workaround is clicking on an existing note, which then reveals the option to add a new one. The downside: this only works if a note exists in the current date range.</p>



<p>Another option, shared by Paid Media Specialist, <strong>Dids Reeve</strong>, is to open the Notes panel from the “More” (burger) menu, where the add-note function may still be accessible.</p>



<p><strong>What’s next</strong>. Google has not publicly acknowledged the bug or shared a timeline for a fix. Until then, advertisers relying on notes may need to use alternative entry points — and double-check that important changes are being properly documented.</p>



<p><strong>First seen. </strong>This error was first spotted by Caspi who shared his view of camapign reports on <a href="https://www.linkedin.com/feed/update/urn:li:activity:7420509497137463296/">LinkedIn</a></p>


Some Google Ads advertisers are seeing a bug that causes the option to add notes to disappear from the account change popup, making it harder to document optimizations and performance shifts.
The issue was flagged by paid search consultant Odi Caspi, who says the problem has appeared intermittently over the past couple of weeks.
What advertisers should be seeing:




Caspi shares his view below:




Why we care. Account notes are a key workflow tool for agencies and in-house teams tracking changes over time. Losing easy access to notes makes troubleshooting performance swings harder and weakens institutional memory across teams.
What users are seeing. In affected accounts, the “Add note” option no longer appears in the standard popup where advertisers typically annotate changes. The issue appears to be sporadic, working normally at times and disappearing at others.
Workarounds, for now. Caspi says one workaround is clicking on an existing note, which then reveals the option to add a new one. The downside: this only works if a note exists in the current date range.
Another option, shared by Paid Media Specialist, Dids Reeve, is to open the Notes panel from the “More” (burger) menu, where the add-note function may still be accessible.
What’s next. Google has not publicly acknowledged the bug or shared a timeline for a fix. Until then, advertisers relying on notes may need to use alternative entry points — and double-check that important changes are being properly documented.
First seen. This error was first spotted by Caspi who shared his view of camapign reports on LinkedIn

A Google Ads bug is causing the option to add account notes to disappear for some advertisers, complicating change tracking and documentation.

Google Ads bug removes notes option for some advertisers

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Search marketing jobs" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-550x310.jpg 550w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Land your next job in SEO or PPC. These brands and agencies are hiring to fill open search marketing positions right now.

Looking to take the next step in your search marketing career? 
Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.
Newest SEO Jobs 
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(Provided to Search Engine Land by SEOjobs.com) 

SEO Specialist ~ Amplifyed ~ $80,000 ~ Remote (US)
January 26, 2026 
Do you love nerding out on SEO and working with clients? If your friends & family are sick of hearing about your latest search rankings, then we’re your kind of people and you will love this job. $80k in year 1 + potential bonuses You will get an absolute masterclass on SEO and working with […]

Head of Search Strategy ~ Reboot Online ~ £65,000+ ~ Remote (UK)
January 26, 2026 
Reboot Online is hiring a Head of Search Strategy to be the senior external voice of our organic search offering. This is not a delivery-heavy SEO role. It’s a visibility, strategy, and influence role for someone who thrives in pitches, on stage, and in senior client conversations. You’ll help shape how organic search is sold, […]

SEO Manager ~ MC Management ~ $95,000-110,000 ~ Hybrid – Fort Lauderdale, Florida (US)
January 26, 2026 
The SEO Manager will own and scale the company’s organic search performance across a portfolio of brands and websites (currently four). This role is responsible for developing, executing, and continuously optimizing a comprehensive SEO strategy that drives qualified traffic, engagement, and conversions. This is a hands-on, data-driven leadership role that blends technical SEO expertise, content […]

Local SEO Specialist / Assistant  ~ Opt Digital ~ $20,000-$30,000 ~ Remote WW (Philippines Based)
January 26, 2026 
We’re looking for a Local SEO Specialist to lead the client-side execution on GMB’s and local SEO for a growing SEO agency Opt Digital – APPLICATION LINK BELOW The OTE compensation will be $1,200 – $1,700/month/ with performance incentives tied to client retention, referrals, and campaign outcomes. We’re a digital marketing agency focused on helping […]

Marketing Manger – Social Media, Email, SEM/SEO ~ Outdoor Afro ~ $90,000 – $110,000 ~ In-office (USA) ~ Oakland, CA, United States
January 26, 2026 
Job Description This is a remote position. Marketing Manager – Social Media, Email, SEM/SEO Type: Full-Time, Exempt Location: Remote (U.S.-based) Salary: $90,000 – $110,000 annually plus benefits Application Window: Open until filled About Outdoor Afro Outdoor Afro celebrates and inspires Black connections and leadership in nature. Our network connects Black people with our lands, water, […]

Director of Content Marketing ~ Samba TV ~ $170,000 – $180,000 ~ In-office (USA) ~ San Francisco, CA, United States
January 25, 2026 
Job Description Samba TV tracks streaming and broadcast video across the world with our proprietary data and technology. We are on a mission to fundamentally transform the viewing experience for everyone. Our data enables media companies to connect with audiences for new shows and movies, and enables advertisers to engage viewers and measure reach across […]

Content Marketing Lead ~ 829 Studios ~ $80,000 – $95,000 ~ Remote (USA)
January 25, 2026 
The Content Marketing Department at 829 Studios is looking for a dynamic, versatile, and highly collaborative Content Marketing Lead to manage a small team of copywriters and create a variety of compelling content assets for our clients. The role of the Content Marketing Lead will play a supportive role to other departments across the organization […]

Product Marketing & Content Marketing Manager ~ LightSource ~ $91,000-$155,000 ~ Hybrid (San Francisco, CA, United States)
January 24, 2026 
Who We Are LightSource is the next-generation operating system for Procurement. We build SaaS software for procurement managers—the people responsible for managing suppliers and vendors. Sales has Salesforce. HR has Workday. And now, finally, procurement has LightSource. Think of us like a CRM, but instead of helping sales professionals find customers, we help procurement managers […]

Manager, Growth Content Marketing, Subproduct specialization ~ Airwallex ~ $200,000-$250,000 ~ In-office (USA) ~ San Francisco, CA, United States
January 24, 2026 
About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and […]

SEO Strategist ~ Ramp ~ $60,000-$80,000 ~ Hybrid (New York, NY/San Francisco, CA, United States)
January 23, 2026 
At Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it. Ramp is a financial operations platform designed to […]

Newest PPC and paid media jobs
(Provided to Search Engine Land by PPCjobs.com) 
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Junior Digital Marketing Strategist – PPC ~ Dealer eProcess ~ $45,000 ~ In-office (USA) ~ Lisle, IL, United States
January 24, 2026 
Job Description Please be advised that DEP will never request bank information for equipment. All communications will exclusively come through our recruiting platform and our HR team. We urge you to disregard any unsolicited requests outside of these official channels. This is an in-office position located in Lisle, IL Position open to US applicants only.  […]

Director, Performance Media, Paid Social & Display ~ Etsy ~ $120,000-$160,000 ~ Hybrid (Brooklyn, NY, United States)
January 24, 2026 
We’re thrilled to be hiring a Director, Low Funnel Paid Social & Display to join Etsy’s Brand Marketing team! This is an exciting opportunity to develop a new capability for Etsy: building and leading our in-house performance media buying function across Paid Social and Display. We’re looking for someone who brings deep technical expertise and […]

PPC/Google Ads Specialist ~ ITVibes, Inc. ~ $60,000-$80,000 ~ In-office (USA) ~ The Woodlands, TX, United States
January 23, 2026 
PPC/SEM & GOOGLE ADS SPECIALIST ITVibes, an SEO and digital marketing agency located in The Woodlands, TX, is seeking a PPC/SEM & Google Ads Specialist to become a part of our amazing team! The PPC/SEM & Google Ads Specialist position involves the management of digital advertising campaigns using various platforms including but not limited to […]

Associate Director, Paid Search (SEM) ~ Starcom ~ $95,950 – $137,865 ~ In-office (USA) ~ Chicago, IL, United States
January 23, 2026 
Company Description With a history that dates back over 80 years, Starcom is a global communications planning and media leader. We are an agency still grounded in our founding principle that people are at center of all we do. Each day, we apply this belief to harness the transformative power of data and technology to […]

Paid Digital Media Specialist ~ Explore Industries USA, Inc. ~ $48,000 – $58,000 ~ In-office (USA) ~ Knoxville, TN, United States
January 23, 2026 
Salary Range: $48,000.00 To $58,000.00 Annually Location: Knoxville, TN Manufacturing and Corporate Headquarters Island Campus Join the Explore Industries Team! At Explore Industries, we’re more than a leader in fiberglass swimming pool design and manufacturing — we’re a team driven by respect, integrity, and innovation. Home to industry‑leading pool brands including Leisure Pools, Aviva Pools, […]

Other roles you may be interested in
Senior Manager of Paid Search at High-Performing Independent Media Agency, Grey Matter Recruitment (Remote)
Salary: $110,000 – $125,000
Own the activation and execution of Paid Search & Shopping activity across the Google Suite
Support wider eCommerce, Search and Digital team on strategy and plans
Performance Marketing Manager, E.S. Kluft & Company (Rancho Cucamonga, CA)
Salary; $100,000
Define a comprehensive paid and earned strategy, in line with the overall company and marketing strategy.
Effectively manage and communicate with multiple agencies and partners (media, PR).
Digital Marketing Manager, DEPLOY (Hybrid, Tuscaloosa, AL)
Salary: $80,000
Strong knowledge of digital marketing tools, analytics platforms (e.g., Google Analytics), and content management systems (CMS).
Experience Managing Google Ads and Meta ad campaigns.
Paid Search Marketing Manager, LawnStarter (Remote)
Salary: $90,000 – $125,000
Manage and optimize large-scale, complex SEM campaigns across Google Ads, Bing Ads, Meta Ads and other search platforms
Activate, optimize and make efficient Local Services Ads (LSA) at scale
Senior Manager, SEO, Turo (Hybrid, San Francisco, CA)
Salary: $168,000 – $210,000
Define and execute the SEO strategy across technical SEO, content SEO, on-page optimization, internal linking, and authority building.
Own business and operations KPIs for organic growth and translate them into clear quarterly plans.
SEM (Search Engine Marketing) Manager, Tribute Technology (Remote)
Salary: $85,000 – $90,000
PPC Campaign Management: Execute and optimize multiple Google Ad campaigns and accounts simultaneously.
SEO Strategy Management: Develop and manage on-page SEO strategies for client websites using tools like Ahrefs.
ASO/SEO/Blog Marketing Manager, Alia Services (Remote)
Salary: $75,000 – $85,000
Lead ASO strategy across iOS App Store and Google Play, optimizing metadata, visuals, and ratings to improve rankings and conversion rates
Manage SEO strategy for shopkick.com, driving growth through keyword research, technical optimization, and on-page improvements
Search Engine Optimization Manager, Robert Half (Hybrid, Boston MA)
Salary: $150,000 – $160,000
Strategic Leadership: Define and lead the strategy for SEO, AEO, and LLMs, ensuring alignment with overall business and product goals.
Roadmap Execution: Develop and implement the SEO/AEO/LLM roadmap, prioritizing performance-based initiatives and driving authoritative content at scale.
Search Engine Op imization Manager, NoGood (Remote)
Salary: £80,000 – $100,000
Act as the primary strategic lead for a portfolio of enterprise and scale-up clients.
Build and execute GEO/AEO strategies that maximize brand visibility across LLMs and AI search surfaces.
Senior Content  Manager, TrustedTech (Irvine, CA)
Salary: $110,000 – $130,000
Develop and manage a content strategy aligned with business and brand goals across blog, web, email, paid media, and social channels.
Create and edit compelling copy that supports demand generation and sales enablement programs.
Note: We update this post weekly. So make sure to bookmark this page and check back.

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