<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization.png" class="attachment-large size-large wp-post-image" alt="How Google Display exclusions guide AI-driven optimization" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Accidental clicks, bot traffic, and low-quality placements contaminate campaign data. Strategic exclusions help keep optimization on track.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization.png" class="attachment-large size-large wp-post-image" alt="How Google Display exclusions guide AI-driven optimization" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/How-Google-Display-exclusions-guide-AI-driven-optimization-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p><a href="https://searchengineland.com/google-display-network-explained-456796">Google Display Network</a> (GDN) placement exclusions have long been treated as basic account hygiene. You block spammy, inappropriate, or low-conversion placements to protect brand safety and avoid wasting budget on junk traffic.</p>



<p>That often meant maintaining massive lists of junk URLs and mobile app categories to keep ads off clickbait blogs, kids’ mobile games, and other low-quality inventory.</p>



<p>But GDN exclusions don’t just block bad placements anymore. They also influence the signals Google uses to optimize automated campaigns.</p>



<p>Here’s how to use placement exclusions to steer campaigns away from low-quality traffic and bad conversion signals.</p>



<h2 class="wp-block-heading" id="h-the-legacy-blueprint-hygiene-and-budget-conservation">The legacy blueprint: Hygiene and budget conservation</h2>



<p>To understand the strategic shift, you first need to understand why blocking placements mattered in traditional <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a>. Placement exclusions historically served two purposes: brand integrity and cost control.</p>



<p>You don’t want your high-end B2B software or consumer brand appearing next to extreme political rants, adult content, or clickbait farms.</p>



<p>GDN spans millions of sites and apps. A massive share of that inventory consists of high-click, zero-conversion black holes, like flashlight apps or mobile puzzle games where users accidentally click banner ads.</p>



<p>Legacy strategies also recognized that even high-quality sites like The New York Times or CNN could become budget killers. For direct-response advertisers focused on immediate ROI rather than broad brand awareness, a single premium placement could consume thousands of dollars with little to no conversion intent behind it.</p>



<p>The traditional fix was straightforward. Build massive static lists of 70,000-plus excluded URLs, block all mobile apps, and review the “Where Ads Showed” report monthly to eliminate outliers. </p>



<p>While those tactics remain necessary foundational steps, they only scratch the surface of how data operates in AI-driven advertising.</p>



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<h2 class="wp-block-heading" id="h-how-ai-changed-the-rules-of-the-gdn">How AI changed the rules of the GDN</h2>



<p>In modern Google Ads setups, Smart Bidding algorithms like Target CPA and Target ROAS acquire customers at a predictable cost, serving ads only to searchers who fit those parameters. Combined with broad or <a href="https://searchengineland.com/google-display-network-optimized-targeting-turn-off-447054">optimized targeting</a>, Google’s AI doesn’t just passively serve ads where you tell it to. It actively hunts for signals.</p>



<p>The AI analyzes who clicks, who converts, and where those actions happen. It then builds predictive models to find more placements like them. That creates a dangerous cycle when bad data enters the system.</p>



<p>If your campaigns lack strategic exclusions, Google’s AI will naturally gravitate toward the cheapest, highest-volume inventory available for testing. A flood of accidental clicks from mobile apps or low-quality click-fraud sites can initially appear to be a positive signal due to high CTRs. </p>



<p>The algorithm may then double down on those placements, burning through your budget before recognizing the traffic produces zero conversions. By the time the system learns the placements are unqualified, your monthly budget is already gone.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/google-ads-placements-guide-websites-apps-youtube-462050">Google Ads placements: Your guide to targeting websites, apps, and YouTube</a></em></strong>



<h2 class="wp-block-heading" id="h-moving-from-hygiene-to-strategy-guardrails-for-the-algorithm">Moving from hygiene to strategy: Guardrails for the algorithm</h2>



<p>Strategic exclusions aren’t just about saying, “I don’t want my ad there.” They help direct the algorithm away from low-quality inventory and toward better signals.</p>



<p>By shaping where AI can and can’t operate, you inject human intent back into automated systems.&nbsp;</p>



<h3 class="wp-block-heading" id="h-campaign-intent-mapping">Campaign intent mapping</h3>



<p>Instead of applying one blanket exclusion list across your account, use exclusions to shape campaign psychology.</p>



<ul class="wp-block-list">
<li><strong>For top-of-funnel brand awareness campaigns:</strong> Keep premium placements, such as major news outlets and industry blogs, active. Exclude niche, low-quality directories so your budget pushes the AI toward high-visibility, reputable sites.</li>



<li><strong>For bottom-of-funnel direct-response campaigns:</strong> Do the opposite. Exclude costly, broad-reach premium websites and force Google’s machine learning to focus on specific, content-rich, long-tail blogs where users actively research niche topics with high conversion intent.</li>
</ul>



<h3 class="wp-block-heading" id="h-preempting-smart-bidding-exhaustion">Preempting Smart Bidding exhaustion</h3>



<p>AI models need data to learn, but learning costs money. If you launch an automated campaign fully open to the Google Display Network, the AI will spend the first 14 to 30 days testing random placements.&nbsp;</p>



<p>Applying robust, prebuilt exclusion lists at launch helps you skip that expensive trial-and-error phase and gives Google’s AI a head start on higher-quality inventory.</p>



<h3 class="wp-block-heading" id="h-fighting-signal-poisoning-in-lead-gen">Fighting ‘signal poisoning’ in lead gen</h3>



<p>Click bots and spam form fills are an AI nightmare. When a bot scrapes a GDN site, clicks your ad, and submits a fake form on your landing page, Google’s AI interprets it as a successful conversion.</p>



<p>The algorithm then optimizes toward more users and sites like it, contaminating your entire data pool. Strategic placement exclusions at the account level act as a firewall, cutting off low-quality inventory where these bots thrive and helping your AI optimize around clean, human traffic.</p>



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<h2 class="wp-block-heading" id="h-advanced-tactics-for-managing-exclusions">Advanced tactics for managing exclusions</h2>



<p>To move beyond manual audits, adopt a more sophisticated framework.</p>



<h3 class="wp-block-heading" id="h-leverage-automated-scripts">Leverage automated scripts</h3>



<p>Don’t wait for monthly reviews to catch budget drains. Deploy Google Ads scripts that monitor placement data daily.</p>



<p>For example, you could set a trigger to automatically exclude any placement that spends more than 1.5 times your target CPA within seven days without generating a conversion.</p>



<h3 class="wp-block-heading" id="h-block-mobile-apps">Block mobile apps</h3>



<p>Unless your KPI is mobile app downloads, block mobile app categories at the account level.&nbsp;</p>



<p>Google’s AI favors app placements because they generate high click volume and low CPCs, but those clicks rarely translate into meaningful business revenue.&nbsp;</p>



<h3 class="wp-block-heading" id="h-use-content-suitability-settings">Use content suitability settings</h3>



<p>Google’s advanced content suitability settings align placements with broader trends, cultural shifts, and legal sensitivities, especially if you run campaigns internationally.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/google-ads-display-keywords-453802">Google Ads Display Keywords: Everything you need to know</a></em></strong>



<h2 class="wp-block-heading" id="h-taking-back-the-reins">Taking back the reins</h2>



<p>AI-driven campaigns perform better when strategic guardrails shape how Google’s algorithm learns and optimizes.</p>



<p>Basic account hygiene keeps your campaigns clean, but strategic placement exclusions also shape campaign performance. By removing low-quality inventory, limiting bad data, and steering Google’s Smart Bidding toward higher-intent leads, you can turn a simple blocklist into a meaningful performance advantage.</p>



<p>You can start with this comprehensive <a href="https://docs.google.com/spreadsheets/d/1NuGE0EuVPL-oJ3EVSy6hVNbCLow9hugcrMj1ZQddM1g/edit?usp=sharing" target="_blank" rel="noopener">website exclusion list</a>.</p>

Google Display Network (GDN) placement exclusions have long been treated as basic account hygiene. You block spammy, inappropriate, or low-conversion placements to protect brand safety and avoid wasting budget on junk traffic.
That often meant maintaining massive lists of junk URLs and mobile app categories to keep ads off clickbait blogs, kids’ mobile games, and other low-quality inventory.
But GDN exclusions don’t just block bad placements anymore. They also influence the signals Google uses to optimize automated campaigns.
Here’s how to use placement exclusions to steer campaigns away from low-quality traffic and bad conversion signals.
The legacy blueprint: Hygiene and budget conservation
To understand the strategic shift, you first need to understand why blocking placements mattered in traditional PPC. Placement exclusions historically served two purposes: brand integrity and cost control.
You don’t want your high-end B2B software or consumer brand appearing next to extreme political rants, adult content, or clickbait farms.
GDN spans millions of sites and apps. A massive share of that inventory consists of high-click, zero-conversion black holes, like flashlight apps or mobile puzzle games where users accidentally click banner ads.
Legacy strategies also recognized that even high-quality sites like The New York Times or CNN could become budget killers. For direct-response advertisers focused on immediate ROI rather than broad brand awareness, a single premium placement could consume thousands of dollars with little to no conversion intent behind it.
The traditional fix was straightforward. Build massive static lists of 70,000-plus excluded URLs, block all mobile apps, and review the “Where Ads Showed” report monthly to eliminate outliers. 
While those tactics remain necessary foundational steps, they only scratch the surface of how data operates in AI-driven advertising.

  
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How AI changed the rules of the GDN
In modern Google Ads setups, Smart Bidding algorithms like Target CPA and Target ROAS acquire customers at a predictable cost, serving ads only to searchers who fit those parameters. Combined with broad or optimized targeting, Google’s AI doesn’t just passively serve ads where you tell it to. It actively hunts for signals.
The AI analyzes who clicks, who converts, and where those actions happen. It then builds predictive models to find more placements like them. That creates a dangerous cycle when bad data enters the system.
If your campaigns lack strategic exclusions, Google’s AI will naturally gravitate toward the cheapest, highest-volume inventory available for testing. A flood of accidental clicks from mobile apps or low-quality click-fraud sites can initially appear to be a positive signal due to high CTRs. 
The algorithm may then double down on those placements, burning through your budget before recognizing the traffic produces zero conversions. By the time the system learns the placements are unqualified, your monthly budget is already gone.
Dig deeper: Google Ads placements: Your guide to targeting websites, apps, and YouTube



Moving from hygiene to strategy: Guardrails for the algorithm
Strategic exclusions aren’t just about saying, “I don’t want my ad there.” They help direct the algorithm away from low-quality inventory and toward better signals.
By shaping where AI can and can’t operate, you inject human intent back into automated systems. 
Campaign intent mapping
Instead of applying one blanket exclusion list across your account, use exclusions to shape campaign psychology.
For top-of-funnel brand awareness campaigns: Keep premium placements, such as major news outlets and industry blogs, active. Exclude niche, low-quality directories so your budget pushes the AI toward high-visibility, reputable sites.
For bottom-of-funnel direct-response campaigns: Do the opposite. Exclude costly, broad-reach premium websites and force Google’s machine learning to focus on specific, content-rich, long-tail blogs where users actively research niche topics with high conversion intent.
Preempting Smart Bidding exhaustion
AI models need data to learn, but learning costs money. If you launch an automated campaign fully open to the Google Display Network, the AI will spend the first 14 to 30 days testing random placements. 
Applying robust, prebuilt exclusion lists at launch helps you skip that expensive trial-and-error phase and gives Google’s AI a head start on higher-quality inventory.
Fighting ‘signal poisoning’ in lead gen
Click bots and spam form fills are an AI nightmare. When a bot scrapes a GDN site, clicks your ad, and submits a fake form on your landing page, Google’s AI interprets it as a successful conversion.
The algorithm then optimizes toward more users and sites like it, contaminating your entire data pool. Strategic placement exclusions at the account level act as a firewall, cutting off low-quality inventory where these bots thrive and helping your AI optimize around clean, human traffic.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
Advanced tactics for managing exclusions
To move beyond manual audits, adopt a more sophisticated framework.
Leverage automated scripts
Don’t wait for monthly reviews to catch budget drains. Deploy Google Ads scripts that monitor placement data daily.
For example, you could set a trigger to automatically exclude any placement that spends more than 1.5 times your target CPA within seven days without generating a conversion.
Block mobile apps
Unless your KPI is mobile app downloads, block mobile app categories at the account level. 
Google’s AI favors app placements because they generate high click volume and low CPCs, but those clicks rarely translate into meaningful business revenue. 
Use content suitability settings
Google’s advanced content suitability settings align placements with broader trends, cultural shifts, and legal sensitivities, especially if you run campaigns internationally.
Dig deeper: Google Ads Display Keywords: Everything you need to know



Taking back the reins
AI-driven campaigns perform better when strategic guardrails shape how Google’s algorithm learns and optimizes.
Basic account hygiene keeps your campaigns clean, but strategic placement exclusions also shape campaign performance. By removing low-quality inventory, limiting bad data, and steering Google’s Smart Bidding toward higher-intent leads, you can turn a simple blocklist into a meaningful performance advantage.
You can start with this comprehensive website exclusion list.

Accidental clicks, bot traffic, and low-quality placements contaminate campaign data. Strategic exclusions help keep optimization on track.

How Google Display exclusions guide AI-driven optimization

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment.png" class="attachment-large size-large wp-post-image" alt="The overlooked business value of SEO and affiliate alignment" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>SEO and affiliate teams affect the same revenue, rankings, and LLM visibility. Alignment can reduce costs and strengthen brand performance.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment.png" class="attachment-large size-large wp-post-image" alt="The overlooked business value of SEO and affiliate alignment" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/The-overlooked-business-value-of-SEO-and-affiliate-alignment-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>In most companies, <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> teams and <a href="https://searchengineland.com/guide/affiliate-marketing-for-beginners">affiliates</a> — third parties that advertise your products or services for a commission — often operate in silos. The SEO team usually manages rankings, content, and organic traffic, while the affiliate team manages partner relationships, negotiates placements, and tracks commissions. But rarely do the two sit in the same room to coordinate their impact on the business.</p>



<p>Cross-functionality is key for a growing business. Working with other departments helps me better understand what success looks like to other teams in the company, and it pulls me out of my SEO bubble so I can see the wider business goals. I also learn about new initiatives and how to leverage them for SEO growth.</p>



<p>Coordination between the SEO and affiliate teams is especially important. So let’s talk about brand protection, LLM visibility, tooling, and more, and why a tighter collaboration between these two will improve efficiency, save money, and boost your business.</p>



<h2 class="wp-block-heading" id="h-protect-your-brand-and-search-terms">Protect your brand and search terms</h2>



<p>When working with affiliates, it’s important to protect your brand and rank for search terms that are rightfully yours and not to let an affiliate control them. With my clients, whatever has an impact on organic performance is my or the SEO team’s responsibility.</p>



<p>For example, here are some high-intent conversion terms that use discount codes as part of a marketing strategy:&nbsp;</p>



<ul class="wp-block-list">
<li>[brand] + discount code</li>



<li>[brand] + promo code</li>



<li>Plus dozens of other variants</li>
</ul>



<p>You don’t want to let terms like these slip away. When affiliates rank for your terms, they can send back your own branded traffic and sales and charge you a commission for it.</p>



<p>This can be a disaster, resulting in hefty amounts of affiliate commissions, and it can easily be avoided.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/affiliate-networks-need-use-case-454387">The best affiliate networks by need and use case</a></em></strong>



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<h2 class="wp-block-heading" id="h-how-to-reclaim-your-rankings">How to reclaim your rankings</h2>



<p>Brands can lose branded conversions to their own affiliates as well. Take Trainline, a train ticket buying platform, as an example.&nbsp;</p>



<p>At the time of writing, the term &#8220;trainline promo code&#8221; has 17,000 monthly searches in the UK. Trainline has a dedicated page for the promo, but it&#8217;s not properly optimized to rank for the term. As a result, the site ranks on and off and loses branded traffic and conversions to its own affiliates.</p>



<p>In this case, the solution is simple: a targeted tweak in the meta title, H1, and body copy will better reflect the relevant terms.</p>



<p>By reclaiming those rankings, we</p>



<ul class="wp-block-list">
<li>Increased organic revenue for the organic channel.</li>



<li>Reduced affiliate spending.</li>



<li>Increased profitability for the entire business.</li>
</ul>



<p>Another example: One of the brands I manage lost significant Share of Voice for a high-intent branded discount codes page to affiliates. Our response was a strategic content update. One day after it went live, the page shot from 14% to 31% Share of Voice.</p>



<p>These are successes for the business as a whole, not just SEO. And that’s what SEO should be about — insights that lead to business growth.</p>



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<h2 class="wp-block-heading" id="h-how-seo-and-affiliate-teams-can-work-together-to-compound-returns">How SEO and affiliate teams can work together to compound returns</h2>



<p>Traditionally, affiliates produce content that favors reputational signals: “Best of” articles, comparison articles, category roundups, and more.&nbsp;</p>



<p><a href="https://searchengineland.com/seo-guide-large-language-models-413227">LLMs</a> give significant weight to reputational signals. For example, being mentioned across multiple &#8220;Best of&#8221; articles in your specific niche signals to LLMs that you are good at what you do. And if a lot of authoritative sources in your niche mention you as one of the go-to brands, that reputational signal will compound.</p>



<p>It’s important to educate your affiliate team so your brand will be included in these types of articles. This has two benefits:&nbsp;</p>



<ul class="wp-block-list">
<li>It will give your affiliate visibility, leading to direct traffic and conversions from affiliate placements.</li>



<li>It will give you LLM visibility, boosting reputational signals that feed into how AI models perceive and recommend your brand.</li>
</ul>



<p>On a technical note, affiliate tracking URLs — the parameterized versions of your pages that affiliate platforms generate — need to be handled correctly to avoid indexing issues. This is a great example of an issue that lives on the boundary between SEO and affiliate teams.</p>



<p>The solution is to no-index these, which Google sees as a directive and respects. (A common approach is to add a canonical tag pointing to the clean, non-parameterized version of the page, but I have seen canonicals ignored, resulting in affiliate tracking URLs flooding the index.)</p>



<p>To monitor this, I use SEOTesting, which sends automated alerts whenever new URLs get indexed and start receiving impressions. If an affiliate tracking URL slips through, I can catch it fast and act before it becomes a bigger indexing problem.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/incrementality-affiliate-marketing-471635">What incrementality really means in affiliate marketing</a></em></strong>



<h2 class="wp-block-heading" id="h-collaborate-with-affiliates-today">Collaborate with affiliates today</h2>



<p>SEO and affiliate teams often operate in silos, but each has a direct impact on the other. Affiliates can outrank you and cost you money. But they can also help you build LLM visibility, and those equipped with SEO data can make better decisions for the whole business.</p>



<p>The closer these two teams work together, the better the outcomes are for everyone, and most importantly, the business.</p>

In most companies, SEO teams and affiliates — third parties that advertise your products or services for a commission — often operate in silos. The SEO team usually manages rankings, content, and organic traffic, while the affiliate team manages partner relationships, negotiates placements, and tracks commissions. But rarely do the two sit in the same room to coordinate their impact on the business.
Cross-functionality is key for a growing business. Working with other departments helps me better understand what success looks like to other teams in the company, and it pulls me out of my SEO bubble so I can see the wider business goals. I also learn about new initiatives and how to leverage them for SEO growth.
Coordination between the SEO and affiliate teams is especially important. So let’s talk about brand protection, LLM visibility, tooling, and more, and why a tighter collaboration between these two will improve efficiency, save money, and boost your business.
Protect your brand and search terms
When working with affiliates, it’s important to protect your brand and rank for search terms that are rightfully yours and not to let an affiliate control them. With my clients, whatever has an impact on organic performance is my or the SEO team’s responsibility.
For example, here are some high-intent conversion terms that use discount codes as part of a marketing strategy: 
[brand] + discount code
[brand] + promo code
Plus dozens of other variants
You don’t want to let terms like these slip away. When affiliates rank for your terms, they can send back your own branded traffic and sales and charge you a commission for it.
This can be a disaster, resulting in hefty amounts of affiliate commissions, and it can easily be avoided.
Dig deeper: The best affiliate networks by need and use case




  
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How to reclaim your rankings
Brands can lose branded conversions to their own affiliates as well. Take Trainline, a train ticket buying platform, as an example. 
At the time of writing, the term “trainline promo code” has 17,000 monthly searches in the UK. Trainline has a dedicated page for the promo, but it’s not properly optimized to rank for the term. As a result, the site ranks on and off and loses branded traffic and conversions to its own affiliates.
In this case, the solution is simple: a targeted tweak in the meta title, H1, and body copy will better reflect the relevant terms.
By reclaiming those rankings, we
Increased organic revenue for the organic channel.
Reduced affiliate spending.
Increased profitability for the entire business.
Another example: One of the brands I manage lost significant Share of Voice for a high-intent branded discount codes page to affiliates. Our response was a strategic content update. One day after it went live, the page shot from 14% to 31% Share of Voice.
These are successes for the business as a whole, not just SEO. And that’s what SEO should be about — insights that lead to business growth.
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How SEO and affiliate teams can work together to compound returns
Traditionally, affiliates produce content that favors reputational signals: “Best of” articles, comparison articles, category roundups, and more. 
LLMs give significant weight to reputational signals. For example, being mentioned across multiple “Best of” articles in your specific niche signals to LLMs that you are good at what you do. And if a lot of authoritative sources in your niche mention you as one of the go-to brands, that reputational signal will compound.
It’s important to educate your affiliate team so your brand will be included in these types of articles. This has two benefits: 
It will give your affiliate visibility, leading to direct traffic and conversions from affiliate placements.
It will give you LLM visibility, boosting reputational signals that feed into how AI models perceive and recommend your brand.
On a technical note, affiliate tracking URLs — the parameterized versions of your pages that affiliate platforms generate — need to be handled correctly to avoid indexing issues. This is a great example of an issue that lives on the boundary between SEO and affiliate teams.
The solution is to no-index these, which Google sees as a directive and respects. (A common approach is to add a canonical tag pointing to the clean, non-parameterized version of the page, but I have seen canonicals ignored, resulting in affiliate tracking URLs flooding the index.)
To monitor this, I use SEOTesting, which sends automated alerts whenever new URLs get indexed and start receiving impressions. If an affiliate tracking URL slips through, I can catch it fast and act before it becomes a bigger indexing problem.
Dig deeper: What incrementality really means in affiliate marketing



Collaborate with affiliates today
SEO and affiliate teams often operate in silos, but each has a direct impact on the other. Affiliates can outrank you and cost you money. But they can also help you build LLM visibility, and those equipped with SEO data can make better decisions for the whole business.
The closer these two teams work together, the better the outcomes are for everyone, and most importantly, the business.

SEO and affiliate teams affect the same revenue, rankings, and LLM visibility. Alignment can reduce costs and strengthen brand performance.

The overlooked business value of SEO and affiliate alignment

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image.png" class="attachment-large size-large wp-post-image" alt="What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Search intent still shapes content strategy, but AI Overviews now shape how users behave on the SERP itself.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image.png" class="attachment-large size-large wp-post-image" alt="What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/What-to-do-now-that-AIOs-turned-search-into-reading-sessions-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Intent still tells you what to write. But when an AI Overview (AIO) lands on the SERP, users no longer behave the same way as classic search.&nbsp;</p>



<p>In this memo:</p>



<ul class="wp-block-list">
<li>AIO compresses five distinct search intents into one reading pattern, and the 20-year SEO assumption it breaks.</li>



<li>What winning the “second impression” looks like for product, category, and blog pages.</li>



<li>The one-slide explanation that reassures stakeholders the content team&#8217;s last three years were not wasted <em>(premium)</em>.</li>



<li>A Claude skill that audits your meta descriptions against the competitors sharing your SERP <em>(premium)</em>.</li>
</ul>



<p><a href="https://www.growth-memo.com/embed?transparent=1" rel="noopener noreferrer">View embedded content</a>



<h2 class="wp-block-heading" id="h-the-new-mental-model-of-search-intent">The new mental model of search intent</h2>



<p>Last week, I shared how Eric Van Buskirk of <a href="https://clickstream.cc/" target="_blank" rel="noopener">Clickstream Solutions</a> and I analyzed anonymized clickstream data from approximately 846,000 U.S.-based Google search sessions.</p>



<p>The most significant finding? The time-on-page for a user on the SERP is no longer dependent on search intent when an AIO is present. The AIO compresses search intent behavior to look similar across intent types.&nbsp;</p>



<ul class="wp-block-list">
<li><strong>Old mental model of search intent:</strong> Navigational searches are “fast.” Informational ones are “slow.” Time-on-SERP follows intent, and SERPs without an AIO clearly show this pattern (similar to classic search pre-AI outputs), demonstrated by 12% of navigational searches vs. 32% of local searchers still being on the SERP after 21 seconds.</li>



<li><strong>New mental model of search intent:</strong> There is barely a difference in how long users spend time on SERPs between user intents when there is an AIO present. 42-48.5% of users are still on the SERP after 21 seconds across all the 5 major intents.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2040" height="1208" src="https://searchengineland.com/wp-content/seloads/2026/06/AI-Overviews-keep-searchers-on-SERPs-longer.png" alt="AI Overviews keep searchers on SERPs longer" class="wp-image-479247" srcset="https://searchengineland.com/wp-content/seloads/2026/06/AI-Overviews-keep-searchers-on-SERPs-longer.png 2040w, https://searchengineland.com/wp-content/seloads/2026/06/AI-Overviews-keep-searchers-on-SERPs-longer-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/AI-Overviews-keep-searchers-on-SERPs-longer-1536x910.png 1536w" sizes="(max-width: 2040px) 100vw, 2040px" /></figure>
</div>


<p>From “<a href="https://www.growth-memo.com/p/users-behave-differently-in-ai-overviews" target="_blank" rel="noopener">The same user behaves differently in AIOs vs. AI Mode</a>” (bold added):</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><strong><em>At 21 seconds into a session without an AIO, only 12% of navigational searchers are still on the page. 32% of local searchers are. </em></strong><em>In classic search, time-on-page has always followed intent: navigational users leave fast because they know where they&#8217;re going, local users stay because the SERP is dense with maps and listings, informational users fall somewhere in between.</em>



<p><em>With an AIO present, the spread compresses to barely 6 points. </em><strong><em>All five intent types</em></strong><em>(informational, local, navigational, transactional, video) </em><strong><em>cluster between 41.9% and 48.5% time-on-page at 21 seconds</em></strong><em>.</em>
</blockquote>



<p>Notice how much longer average SERP sessions are — almost 4x! So, we can conclude that AI Overviews don’t just compress user intent but also prolong the time users spend with search results.&nbsp;</p>



<p>The reason? <em>Additional context.</em> Direct answers from the AIOs provide more information and take longer to read. The intent behind the initial query matters less.</p>



<p>This is the gap between links and answers in the new AIO-filled SERP. In the past, giving users a list of (10 blue) links meant the user was responsible for verifying accuracy and finding the information after the click through. Therefore, Google gets user feedback from their behavior.&nbsp;</p>



<p>But when Google (or other LLMs) gives the answer directly, that onus is on the answer engine.</p>



<p>Bing’s blog, “<a href="https://blogs.bing.com/search/May-2026/Evolving-role-of-the-index-From-ranking-pages-to-supporting-answers" target="_blank" rel="noopener">Evolving the role of the index</a>,” brings this to a point:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><em>Grounding an AI–generated answer introduces a fundamentally different constraint: </em><strong><em>The system is no longer just pointing to information, it is using it.</em></strong><em> The goal shifts from “fetch the best documents” to “fetch the best information to synthesize into a reliable, verifiable answer.”</em>
</blockquote>



<p>Lastly, it also means there is utility in tracking branded prompts more diligently and making sure LLMs return the desired information about a brand. Just like companies bid on their brand as a defense mechanism, they should monitor branded prompts, not just product- or painpoint-related ones.</p>



<p><strong>Heads up: </strong><em>The </em><a href="https://www.growth-memo.com/i/176171733/bonus-resource-stakeholder-slide-deck-template-and-open-questions" target="_blank" rel="noopener"><em>Adapting for AI-Mode Based Search deck</em></a> <em>gives directors a validated, data-backed story to present to executives who keep asking what changed. Find it in the </em><a href="https://www.growth-memo.com/p/exclusive-growth-premium-resources" target="_blank" rel="noopener"><em>Premium Subscribers Resource Library</em></a><em>.</em>



<h3 class="wp-block-heading" id="h-why-this-matters">Why this matters</h3>



<p>For 20 years, what you searched told Google and SEOs how you&#8217;d behave. Type a brand name (navigational search), and you&#8217;re in and out in seconds. Search &#8220;best CRM for startups&#8221; (comparison search), and you settle into a set of comparison pages. Intent sorted everyone.</p>



<p>The AIO erased that tell. By dropping a block of answer text at the top of the page, it pulls every searcher into a reading session, no matter why they came. The brand-name searcher reads the AIO. The product researcher reads another. Both slow down, both stay, both behave alike on the SERP page. <em>That</em> flattening is the intent compression.</p>



<p>Most Google users never chose this, because most Google users are not AI early adopters. They meet AI through Google’s search results as Google <s>forces</s> guides them into AIOs and AI Mode at the top of the results. AI is changing its search behavior passively and without searchers’ explicit consent. Many Google users might not even realize they’re using AI, and that’s one reason we’re seeing <a href="https://techcrunch.com/2026/05/26/duckduckgo-installs-are-up-30-as-users-reject-being-force-fed-googles-ai-search/" target="_blank" rel="noopener">growing installs</a> of DuckDuckGo.</p>



<p>Google reports <a href="https://search.google/pdf/google-about-AI-overviews-AI-Mode.pdf" target="_blank" rel="noopener">more than 1.5 billion people</a> use AI Overviews, so this is not an edge case. It&#8217;s how the web is searching now.</p>



<h2 class="wp-block-heading" id="h-what-winning-the-second-impression-looks-like">What winning the second impression looks like</h2>



<p>The <a href="https://www.growth-memo.com/p/users-behave-differently-in-ai-overviews" target="_blank" rel="noopener">AI Overviews vs. AI Mode behavior analysis</a> revealed the significance and optimization opportunity of the second look. The second impression is what searchers see on the back-scroll, after they&#8217;ve already passed your listing once. It’s like a double-take made by a grocery shopper in the cereal aisle who has dozens of options: The shopper scans every box in view, then circles back to reread the one that caught their eye.</p>



<p>Metadata is the trigger for selecting search results. Rich snippets catch attention early on, but they might not be enough to convert users to a click, especially if new search behavior has shifted to include a thorough reading of the SERP <em>and</em> a second scroll up. What can earn the click is what shows up next to your listing on that second pass, and it has to be relevant and trustworthy.</p>



<p>Different page types require different relevance and trust indicators.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1624" height="1112" src="https://searchengineland.com/wp-content/seloads/2026/06/The-second-impression-has-3-playbooks.png" alt="The second impression has 3 playbooks" class="wp-image-479249" srcset="https://searchengineland.com/wp-content/seloads/2026/06/The-second-impression-has-3-playbooks.png 1624w, https://searchengineland.com/wp-content/seloads/2026/06/The-second-impression-has-3-playbooks-768x526.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/The-second-impression-has-3-playbooks-1536x1052.png 1536w" sizes="(max-width: 1624px) 100vw, 1624px" /></figure>
</div>


<h3 class="wp-block-heading" id="h-product-detail-pages-pdp">Product detail pages (PDP)</h3>



<p>Users compare star ratings, review count, price, and stock status.</p>



<p>Three things to control outside the meta:</p>



<ul class="wp-block-list">
<li><strong>Product schema</strong> with aggregateRating, review, offers, and availability. Miss any one of these, and a competitor&#8217;s listing renders fuller than yours.</li>



<li><strong>Review count is a comparison field.</strong> 47 reviews next to a competitor&#8217;s 2,300 loses on the second pass even if your description is sharper. Review velocity is a competitive moat.</li>



<li><strong>Multiple images in the schema array</strong> so Google has options for different SERP layouts.</li>
</ul>



<h3 class="wp-block-heading" id="h-category-detail-pages-cdp">Category detail pages (CDP)</h3>



<p>Category pages compete with the AIO&#8217;s own list. If the AIO already enumerated 5 options, your category page has to look like the place where the user goes to actually choose between them.</p>



<p>Three things to control outside the meta:</p>



<ul class="wp-block-list">
<li><strong>ItemList schema on the category page</strong> so Google can render product carousels in the SERP. A carousel takes more vertical space than a single listing and dominates the back-scroll.</li>



<li><strong>Filter and sort UI visible in the SERP preview.</strong> Google sometimes surfaces sitelinks for category facets (&#8220;by price&#8221; or &#8220;by brand&#8221;). Internal linking to those facets makes them eligible.</li>



<li><strong>Page count and depth.</strong> A category page with 12 products competes badly against one with 240. The second impression carries an implicit <em>&#8220;Is this comprehensive?&#8221; </em>check.</li>
</ul>



<h3 class="wp-block-heading" id="h-blog-content">Blog content</h3>



<p>The AIO has already given the user the answer. To earn a possible <a href="https://www.growth-memo.com/i/163392865/top-takeaways-for-operators" target="_blank" rel="noopener">validation click</a> or at least a thorough second impression for your brand, what the user is looking for is credibility on who said it and when.</p>



<p>Two things to control outside the meta:</p>



<ul class="wp-block-list">
<li><strong>Visible datePublished or dateModified in the SERP.</strong> A 2024 article next to a 2026 article likely loses, whether the user considers the description or not.</li>



<li><strong>Article schema with a named author field</strong> that links to a sameAs URL (LinkedIn, author bio page). This makes the author an entity Google can resolve, which matters for E-E-A-T scoring even if no visible card renders.</li>
</ul>



<p><em>The </em><a href="https://www.growth-memo.com/i/188880019/for-premium-subscribers-your-ai-seo-change-management-plan" target="_blank" rel="noopener"><em>AI SEO Change Management Plan</em></a> <em>alone saves directors 10+ planning hours for retraining your team against current best practices, </em><strong><em>but Premium is only $150/year.</em></strong> <a href="https://www.growth-memo.com/p/exclusive-growth-premium-resources" target="_blank" rel="noopener"><em>See the full library.</em></a>



<h2 class="wp-block-heading" id="h-what-intent-compression-means-for-operators">What intent compression means for operators</h2>



<p>The last three years of intent-based content work produced the right pages for the right queries. What&#8217;s shifting is one prediction layer on top of that strategy: how long users stay, where they look, when they click.</p>



<p>That layer is now AIO-driven, not intent-driven. User search intent still drives what your brand needs to write, but it is no longer a good estimate of <em>how</em> users will behave on a SERP page.</p>



<p>Therefore, more optimization work moves to the SERP, focusing how your listing reads against the AIO and the results around it, separate from the intent logic that decides <em>what</em> the page content should be to answer the query.&nbsp;</p>



<p>Your core optimization efforts don’t change. A content team built around intent clusters keeps its cluster map intact. What gets updated is the optimization pattern per page (meta descriptions, title tags, the second-impression framing from <a href="https://www.growth-memo.com/i/198815058/7-optimize-for-clickability" target="_blank" rel="noopener">finding 7 shared last week with Premium subscribers</a>), not the underlying taxonomy or content strategy.</p>



<p><em><em>This post first appeared on the author’s website and is republished here with permission.</em></em>


Intent still tells you what to write. But when an AI Overview (AIO) lands on the SERP, users no longer behave the same way as classic search. 
In this memo:
AIO compresses five distinct search intents into one reading pattern, and the 20-year SEO assumption it breaks.
What winning the “second impression” looks like for product, category, and blog pages.
The one-slide explanation that reassures stakeholders the content team’s last three years were not wasted (premium).
A Claude skill that audits your meta descriptions against the competitors sharing your SERP (premium).
View embedded content



The new mental model of search intent
Last week, I shared how Eric Van Buskirk of Clickstream Solutions and I analyzed anonymized clickstream data from approximately 846,000 U.S.-based Google search sessions.
The most significant finding? The time-on-page for a user on the SERP is no longer dependent on search intent when an AIO is present. The AIO compresses search intent behavior to look similar across intent types. 
Old mental model of search intent: Navigational searches are “fast.” Informational ones are “slow.” Time-on-SERP follows intent, and SERPs without an AIO clearly show this pattern (similar to classic search pre-AI outputs), demonstrated by 12% of navigational searches vs. 32% of local searchers still being on the SERP after 21 seconds.
New mental model of search intent: There is barely a difference in how long users spend time on SERPs between user intents when there is an AIO present. 42-48.5% of users are still on the SERP after 21 seconds across all the 5 major intents.




From “The same user behaves differently in AIOs vs. AI Mode” (bold added):
At 21 seconds into a session without an AIO, only 12% of navigational searchers are still on the page. 32% of local searchers are. In classic search, time-on-page has always followed intent: navigational users leave fast because they know where they’re going, local users stay because the SERP is dense with maps and listings, informational users fall somewhere in between.



With an AIO present, the spread compresses to barely 6 points. All five intent types(informational, local, navigational, transactional, video) cluster between 41.9% and 48.5% time-on-page at 21 seconds.




Notice how much longer average SERP sessions are — almost 4x! So, we can conclude that AI Overviews don’t just compress user intent but also prolong the time users spend with search results. 
The reason? Additional context. Direct answers from the AIOs provide more information and take longer to read. The intent behind the initial query matters less.
This is the gap between links and answers in the new AIO-filled SERP. In the past, giving users a list of (10 blue) links meant the user was responsible for verifying accuracy and finding the information after the click through. Therefore, Google gets user feedback from their behavior. 
But when Google (or other LLMs) gives the answer directly, that onus is on the answer engine.
Bing’s blog, “Evolving the role of the index,” brings this to a point:
Grounding an AI–generated answer introduces a fundamentally different constraint: The system is no longer just pointing to information, it is using it. The goal shifts from “fetch the best documents” to “fetch the best information to synthesize into a reliable, verifiable answer.”




Lastly, it also means there is utility in tracking branded prompts more diligently and making sure LLMs return the desired information about a brand. Just like companies bid on their brand as a defense mechanism, they should monitor branded prompts, not just product- or painpoint-related ones.
Heads up: The Adapting for AI-Mode Based Search deck gives directors a validated, data-backed story to present to executives who keep asking what changed. Find it in the Premium Subscribers Resource Library.



Why this matters
For 20 years, what you searched told Google and SEOs how you’d behave. Type a brand name (navigational search), and you’re in and out in seconds. Search “best CRM for startups” (comparison search), and you settle into a set of comparison pages. Intent sorted everyone.
The AIO erased that tell. By dropping a block of answer text at the top of the page, it pulls every searcher into a reading session, no matter why they came. The brand-name searcher reads the AIO. The product researcher reads another. Both slow down, both stay, both behave alike on the SERP page. That flattening is the intent compression.
Most Google users never chose this, because most Google users are not AI early adopters. They meet AI through Google’s search results as Google forces guides them into AIOs and AI Mode at the top of the results. AI is changing its search behavior passively and without searchers’ explicit consent. Many Google users might not even realize they’re using AI, and that’s one reason we’re seeing growing installs of DuckDuckGo.
Google reports more than 1.5 billion people use AI Overviews, so this is not an edge case. It’s how the web is searching now.
What winning the second impression looks like
The AI Overviews vs. AI Mode behavior analysis revealed the significance and optimization opportunity of the second look. The second impression is what searchers see on the back-scroll, after they’ve already passed your listing once. It’s like a double-take made by a grocery shopper in the cereal aisle who has dozens of options: The shopper scans every box in view, then circles back to reread the one that caught their eye.
Metadata is the trigger for selecting search results. Rich snippets catch attention early on, but they might not be enough to convert users to a click, especially if new search behavior has shifted to include a thorough reading of the SERP and a second scroll up. What can earn the click is what shows up next to your listing on that second pass, and it has to be relevant and trustworthy.
Different page types require different relevance and trust indicators.




Product detail pages (PDP)
Users compare star ratings, review count, price, and stock status.
Three things to control outside the meta:
Product schema with aggregateRating, review, offers, and availability. Miss any one of these, and a competitor’s listing renders fuller than yours.
Review count is a comparison field. 47 reviews next to a competitor’s 2,300 loses on the second pass even if your description is sharper. Review velocity is a competitive moat.
Multiple images in the schema array so Google has options for different SERP layouts.
Category detail pages (CDP)
Category pages compete with the AIO’s own list. If the AIO already enumerated 5 options, your category page has to look like the place where the user goes to actually choose between them.
Three things to control outside the meta:
ItemList schema on the category page so Google can render product carousels in the SERP. A carousel takes more vertical space than a single listing and dominates the back-scroll.
Filter and sort UI visible in the SERP preview. Google sometimes surfaces sitelinks for category facets (“by price” or “by brand”). Internal linking to those facets makes them eligible.
Page count and depth. A category page with 12 products competes badly against one with 240. The second impression carries an implicit “Is this comprehensive?” check.
Blog content
The AIO has already given the user the answer. To earn a possible validation click or at least a thorough second impression for your brand, what the user is looking for is credibility on who said it and when.
Two things to control outside the meta:
Visible datePublished or dateModified in the SERP. A 2024 article next to a 2026 article likely loses, whether the user considers the description or not.
Article schema with a named author field that links to a sameAs URL (LinkedIn, author bio page). This makes the author an entity Google can resolve, which matters for E-E-A-T scoring even if no visible card renders.
The AI SEO Change Management Plan alone saves directors 10+ planning hours for retraining your team against current best practices, but Premium is only $150/year. See the full library.



What intent compression means for operators
The last three years of intent-based content work produced the right pages for the right queries. What’s shifting is one prediction layer on top of that strategy: how long users stay, where they look, when they click.
That layer is now AIO-driven, not intent-driven. User search intent still drives what your brand needs to write, but it is no longer a good estimate of how users will behave on a SERP page.
Therefore, more optimization work moves to the SERP, focusing how your listing reads against the AIO and the results around it, separate from the intent logic that decides what the page content should be to answer the query. 
Your core optimization efforts don’t change. A content team built around intent clusters keeps its cluster map intact. What gets updated is the optimization pattern per page (meta descriptions, title tags, the second-impression framing from finding 7 shared last week with Premium subscribers), not the underlying taxonomy or content strategy.
This post first appeared on the author’s website and is republished here with permission.

Search intent still shapes content strategy, but AI Overviews now shape how users behave on the SERP itself.

What to do now that AI Overviews turned search into reading sessions

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>These features are rolling out to subset of website owners in the UK and will expand it to more in the future.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/06/google-search-console-controls-report-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is rolling out new Search Generative AI performance reports within Google Search Console and is also testing the ability to block your content from showing up in AI Mode and AI Overviews with a &#8220;toggle&#8221; within Search Console.</p>



<p><strong>Search Generative AI Performance report. </strong>Google Search Console, as <a href="https://www.seroundtable.com/google-search-console-ai-contribution-41153.html">expected</a>, is rolling out a new report to give you some data, but not all, on how well your content and websites are performing within the AI responses, AI Mode and AI Overviews, within Google Search.  The reporting includes impressions, pages, countries, devices and dates but does not include click data.  Yea, Google won&#8217;t be telling us how many searchers click from AI responses in Google Search to our sites &#8211; there is no surprise there.</p>



<p>Google <a href="https://blog.google/products-and-platforms/products/search/new-controls-website-owners">said</a>:</p>



<ul class="wp-block-list">
<li>We’re also starting to roll out new insights for website owners in Search Console about the appearance of their pages in generative AI Search features. These insights include impressions metrics and information about which pages appear in AI responses and in what countries. We&#8217;re continuing to work with website owners to understand what insights will be most helpful to inform their strategies, and we’ll introduce additional metrics over time.&nbsp;</li>
</ul>



<p>Google <a href="https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports">shared</a> more details on the metrics you will get from this new report, they include:</p>



<ul class="wp-block-list">
<li><strong>Impressions</strong>: How often URLs from your site appeared in generative AI features in Search and Discover.&nbsp;</li>



<li><strong>Pages</strong>: Check which URLs appeared within AI features.</li>



<li><strong>Countries</strong>: Understand your visibility on a country basis.</li>



<li><strong>Devices</strong>: Identify the devices people are using when seeing your website (available for Search results).</li>



<li><strong>Dates</strong>: Monitor your performance over time with hourly, daily, weekly, and monthly granularity.</li>
</ul>



<p>I asked about click data and a Google spokesperson told me, &#8220;We&#8217;re continuing to work with website owners to understand what insights will be most helpful to inform their strategies, and we’ll introduce additional metrics over time.&#8221;</p>



<p>This new report is rolling out to a subset of website owners in the UK at first and will expand globally at some point in the future. </p>



<p>Here is a screenshot of this report from Google:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="1571" src="https://searchengineland.com/wp-content/seloads/2026/06/generative-ai-features-performance-report.png" alt="" class="wp-image-479323" srcset="https://searchengineland.com/wp-content/seloads/2026/06/generative-ai-features-performance-report.png 2048w, https://searchengineland.com/wp-content/seloads/2026/06/generative-ai-features-performance-report-768x589.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/generative-ai-features-performance-report-1536x1178.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>For more details on this report, see this Google <a href="https://support.google.com/webmasters/answer/16984139">help center document</a>.</p>



<p><strong>AI blocking controls. </strong>Google also said it is adding a &#8220;new toggle&#8221; within Google Search Console to allow sites to block their content from showing in AI search features such as AI Overviews, AI Mode or AI Overviews in Discover.  Google wrote, &#8220;website owners can decide if they want their site to appear in and help ground responses in our generative AI Search features.&#8221;</p>



<p>Google noted that &#8220;sites that opt out will not receive traffic or impressions from our generative AI features.&#8221; However, this control will not be used as a ranking signal for search results outside of these generative AI Search features, so it should not negatively impact your site on core web search.</p>



<p>Google added that this control is just for a subset of website owners in the UK. Google will expand access to more site owners in the future, after sufficient testing is completed.  Google <a href="https://searchengineland.com/google-may-give-sites-a-way-to-opt-out-of-ai-search-generative-features-468063">did promise</a> these controls were coming after some <a href="https://searchengineland.com/google-faces-eu-antitrust-complaint-over-ai-overviews-458123">backlash from the EU</a>, so now they are starting to roll out.</p>



<p>Early studies showed that <a href="https://searchengineland.com/1-3rd-of-publishers-say-they-will-block-google-search-ai-generative-features-like-ai-overviews-468107">1/3rd of SEOs</a> would block Google from showing their content in AI search features.</p>



<p><strong>UK requirement/law. </strong>Google was forced to do this by the <a href="https://www.gov.uk/government/news/cma-secures-fairer-deal-for-publishers-and-improves-google-search-services-in-uk">UK government</a>, which is why this was released first in the UK only. Google does say this will be expanded but right now, it is only available in the UK. The CMA wrote:</p>



<ul class="wp-block-list">
<li>Google will now also have to allow publishers to opt-out of allowing their content to be used for the ‘fine-tuning’ of AI models. This provides publishers with confidence that they will have control over the full range of AI use-cases of their content.</li>
</ul>



<p><strong>Why we care. </strong>Site owners and publishers have been asking for controls over if and how their content is shown in Google&#8217;s AI features since Google launched these a couple of years ago.  Well, now Google is rolling out such a feature to some users today.  It is unclear how soon everyone will gain access to these controls, but they should come to all eventually.</p>



<p>Plus, we have been asking Google for AI Search reporting since day one as well. This is Google&#8217;s first step towards that, shortly after <a href="https://searchengineland.com/bing-webmaster-tools-ai-performance-report-468751">Bing Webmaster Tools released</a> its AI performance report.  Neither Google or Bing&#8217;s reports have click data, and we don&#8217;t expect them ever to, but for now, at least Bing&#8217;s report is global while Google&#8217;s report is a subset of UK site owners.</p>


Google is rolling out new Search Generative AI performance reports within Google Search Console and is also testing the ability to block your content from showing up in AI Mode and AI Overviews with a “toggle” within Search Console.
Search Generative AI Performance report. Google Search Console, as expected, is rolling out a new report to give you some data, but not all, on how well your content and websites are performing within the AI responses, AI Mode and AI Overviews, within Google Search.  The reporting includes impressions, pages, countries, devices and dates but does not include click data.  Yea, Google won’t be telling us how many searchers click from AI responses in Google Search to our sites – there is no surprise there.
Google said:
We’re also starting to roll out new insights for website owners in Search Console about the appearance of their pages in generative AI Search features. These insights include impressions metrics and information about which pages appear in AI responses and in what countries. We’re continuing to work with website owners to understand what insights will be most helpful to inform their strategies, and we’ll introduce additional metrics over time. 
Google shared more details on the metrics you will get from this new report, they include:
Impressions: How often URLs from your site appeared in generative AI features in Search and Discover. 
Pages: Check which URLs appeared within AI features.
Countries: Understand your visibility on a country basis.
Devices: Identify the devices people are using when seeing your website (available for Search results).
Dates: Monitor your performance over time with hourly, daily, weekly, and monthly granularity.
I asked about click data and a Google spokesperson told me, “We’re continuing to work with website owners to understand what insights will be most helpful to inform their strategies, and we’ll introduce additional metrics over time.”
This new report is rolling out to a subset of website owners in the UK at first and will expand globally at some point in the future. 
Here is a screenshot of this report from Google:




For more details on this report, see this Google help center document.
AI blocking controls. Google also said it is adding a “new toggle” within Google Search Console to allow sites to block their content from showing in AI search features such as AI Overviews, AI Mode or AI Overviews in Discover.  Google wrote, “website owners can decide if they want their site to appear in and help ground responses in our generative AI Search features.”
Google noted that “sites that opt out will not receive traffic or impressions from our generative AI features.” However, this control will not be used as a ranking signal for search results outside of these generative AI Search features, so it should not negatively impact your site on core web search.
Google added that this control is just for a subset of website owners in the UK. Google will expand access to more site owners in the future, after sufficient testing is completed.  Google did promise these controls were coming after some backlash from the EU, so now they are starting to roll out.
Early studies showed that 1/3rd of SEOs would block Google from showing their content in AI search features.
UK requirement/law. Google was forced to do this by the UK government, which is why this was released first in the UK only. Google does say this will be expanded but right now, it is only available in the UK. The CMA wrote:
Google will now also have to allow publishers to opt-out of allowing their content to be used for the ‘fine-tuning’ of AI models. This provides publishers with confidence that they will have control over the full range of AI use-cases of their content.
Why we care. Site owners and publishers have been asking for controls over if and how their content is shown in Google’s AI features since Google launched these a couple of years ago.  Well, now Google is rolling out such a feature to some users today.  It is unclear how soon everyone will gain access to these controls, but they should come to all eventually.
Plus, we have been asking Google for AI Search reporting since day one as well. This is Google’s first step towards that, shortly after Bing Webmaster Tools released its AI performance report.  Neither Google or Bing’s reports have click data, and we don’t expect them ever to, but for now, at least Bing’s report is global while Google’s report is a subset of UK site owners.

These features are rolling out to subset of website owners in the UK and will expand it to more in the future.

Google Search Console AI performance reports and controls to block your content in AI responses

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-search-g.png" class="attachment-large size-large wp-post-image" alt="Google Search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-search-g.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-search-g-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google's Invalid Activity Credit Report gives advertisers a clearer view of refunded spend from invalid clicks and traffic.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-search-g.png" class="attachment-large size-large wp-post-image" alt="Google Search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-search-g.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-search-g-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google published new documentation highlighting its Invalid Activity Credit Report, bringing renewed attention to a little-known tool that helps advertisers track refunds issued for invalid clicks and interactions.</p>



<p><strong>The big picture</strong>. It&#8217;s unclear whether the Invalid Activity Credit Report itself is new as advertisers have seen several of those metrics, like invalid click rate before. However, the help document makes it clear the report gives advertisers a more detailed view of credits issued for invalid traffic across Search and Performance Max campaigns.</p>



<p id="h-how-it-works"><strong>How it works. </strong>Google says it uses automated systems to detect and block invalid traffic before advertisers are charged. But some invalid activity is identified only after billing has occurred.</p>



<p>When that happens, Google may issue credits to advertisers for the associated spend.</p>



<p>While those credits already appear in billing and transaction histories, the Invalid Activity Credit Report provides a more detailed breakdown of:</p>



<ul class="wp-block-list">
<li>Credited clicks</li>



<li>Credited interactions</li>



<li>Credited spend</li>



<li>Campaign-level impact</li>



<li>Adjusted performance metrics after credits are applied</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="1241" src="https://searchengineland.com/wp-content/seloads/2026/06/google-ads-invalid-acitibity-credit-report-78fkbpSq-scaled.png" alt="" class="wp-image-479293" srcset="https://searchengineland.com/wp-content/seloads/2026/06/google-ads-invalid-acitibity-credit-report-78fkbpSq-scaled.png 2048w, https://searchengineland.com/wp-content/seloads/2026/06/google-ads-invalid-acitibity-credit-report-78fkbpSq-768x465.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/google-ads-invalid-acitibity-credit-report-78fkbpSq-1536x931.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p><strong>Why we care. </strong>The Invalid Activity Credit Report provides a clearer picture of how much campaign spend is being refunded due to invalid clicks and traffic, helping advertisers better understand their true performance and costs. </p>



<p>The new help documentation also raises awareness of a reporting tool that many advertisers may not know exists, making it easier to audit traffic quality and verify Google&#8217;s fraud protection efforts.</p>



<p id="h-why-google-created-it"><strong>Why Google created it.</strong> According to Google, the report is designed to provide a clearer picture of campaign performance after invalid traffic adjustments.</p>



<p>The company says the report helps advertisers:</p>



<ul class="wp-block-list">
<li>View adjusted costs, clicks and interactions after credits are applied.</li>



<li>Reduce the need for manual reconciliation between billing credits and campaign performance.</li>



<li>Better understand how Google&#8217;s invalid traffic protections affect individual campaigns.</li>
</ul>



<p id="h-how-to-access-it"><strong>How to access it. </strong>Advertisers can find the report through the Report Editor in Google Ads.</p>



<p>From the Template Gallery, users can select &#8220;Invalid Activity Credit Report: Search &amp; PMax&#8221; to generate a report populated with standard campaign metrics alongside new columns for credited clicks, credited interactions and credited amounts.</p>



<p>Additional adjusted performance metrics can also be added to reflect campaign results after credits have been applied.</p>



<p id="h-what-to-watch"><strong>What to watch.</strong> <a href="https://support.google.com/google-ads/answer/16826168?hl=en">The report</a> could become a valuable auditing tool for advertisers running large Search and Performance Max budgets, particularly those monitoring traffic quality and investigating discrepancies between reported performance and billing.</p>



<p>As AI-powered campaign automation continues to expand, visibility into invalid traffic and refunded spend is likely to become an increasingly important part of campaign management.</p>


Google published new documentation highlighting its Invalid Activity Credit Report, bringing renewed attention to a little-known tool that helps advertisers track refunds issued for invalid clicks and interactions.
The big picture. It’s unclear whether the Invalid Activity Credit Report itself is new as advertisers have seen several of those metrics, like invalid click rate before. However, the help document makes it clear the report gives advertisers a more detailed view of credits issued for invalid traffic across Search and Performance Max campaigns.
How it works. Google says it uses automated systems to detect and block invalid traffic before advertisers are charged. But some invalid activity is identified only after billing has occurred.
When that happens, Google may issue credits to advertisers for the associated spend.
While those credits already appear in billing and transaction histories, the Invalid Activity Credit Report provides a more detailed breakdown of:
Credited clicks
Credited interactions
Credited spend
Campaign-level impact
Adjusted performance metrics after credits are applied




Why we care. The Invalid Activity Credit Report provides a clearer picture of how much campaign spend is being refunded due to invalid clicks and traffic, helping advertisers better understand their true performance and costs. 
The new help documentation also raises awareness of a reporting tool that many advertisers may not know exists, making it easier to audit traffic quality and verify Google’s fraud protection efforts.
Why Google created it. According to Google, the report is designed to provide a clearer picture of campaign performance after invalid traffic adjustments.
The company says the report helps advertisers:
View adjusted costs, clicks and interactions after credits are applied.
Reduce the need for manual reconciliation between billing credits and campaign performance.
Better understand how Google’s invalid traffic protections affect individual campaigns.
How to access it. Advertisers can find the report through the Report Editor in Google Ads.
From the Template Gallery, users can select “Invalid Activity Credit Report: Search & PMax” to generate a report populated with standard campaign metrics alongside new columns for credited clicks, credited interactions and credited amounts.
Additional adjusted performance metrics can also be added to reflect campaign results after credits have been applied.
What to watch. The report could become a valuable auditing tool for advertisers running large Search and Performance Max budgets, particularly those monitoring traffic quality and investigating discrepancies between reported performance and billing.
As AI-powered campaign automation continues to expand, visibility into invalid traffic and refunded spend is likely to become an increasingly important part of campaign management.

Google's Invalid Activity Credit Report gives advertisers a clearer view of refunded spend from invalid clicks and traffic.

Google spotlights invalid click credits with new Ads help documentation

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google has confirmed a test of healthcare ads in AI Mode, offering an early look at how advertising may evolve within AI search.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-ai-optimization-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google confirmed it is testing healthcare-related ads in AI Mode, marking the latest expansion of advertising into the company&#8217;s AI-powered search experiences.</p>



<p><strong>The big picture</strong>. The test is currently limited to healthcare advertisers in the U.S. and only applies to English-language queries in AI Mode, according to Google Ads Liaison Ginny Marvin.</p>



<p>The confirmation comes after weeks of industry speculation that healthcare ads had started appearing within AI-generated search experiences.</p>



<p id="h-what-google-is-saying"><strong>What Google is saying</strong>. Responding to questions on LinkedIn, Marvin confirmed that Google is &#8220;beginning a small test of ads in AI Mode for the healthcare vertical.&#8221;</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1076" height="828" src="https://searchengineland.com/wp-content/seloads/2026/06/linkedin-google-ads-healthcare-ads-response-lFlHGb3V.png" alt="" class="wp-image-479267" srcset="https://searchengineland.com/wp-content/seloads/2026/06/linkedin-google-ads-healthcare-ads-response-lFlHGb3V.png 1076w, https://searchengineland.com/wp-content/seloads/2026/06/linkedin-google-ads-healthcare-ads-response-lFlHGb3V-768x591.png 768w" sizes="(max-width: 1076px) 100vw, 1076px" /></figure>



<p id="h-what-google-is-saying">She added that several campaign types are eligible to participate, including:</p>



<ul class="wp-block-list">
<li>Performance Max (PMax)</li>



<li>AI Max with search term matching</li>



<li>Shopping campaigns</li>



<li>Broad match campaigns</li>
</ul>



<p>The same campaign types are also eligible to serve ads in AI Overviews.</p>



<p><strong>Why we care.</strong> Healthcare is one of Google&#8217;s most heavily regulated advertising categories, making this test an important signal for how the company plans to monetize AI-powered search experiences. </p>



<p>If the rollout expands, healthcare marketers could gain access to a new source of visibility in AI Mode, while advertisers in other regulated industries may get a preview of how ads will eventually appear in Google&#8217;s AI-generated results.</p>



<p id="h-the-fine-print"><strong>The fine print</strong>. The initial test comes with creative restrictions.</p>



<p>According to Marvin, the first phase is limited to ads that do not use pinned assets or text disclaimers, narrowing the pool of eligible healthcare creatives.</p>



<p id="h-what-to-watch"><strong>What to watch</strong>. The test is currently small, but advertisers will be watching closely to see whether Google expands eligibility to more healthcare advertisers, additional ad formats, and other regulated industries.</p>



<p>The move could also provide an early indication of how Google plans to balance monetization and user trust as AI Mode becomes a larger part of the search experience.</p>



<p><strong>First spotted.</strong> Senior Strategist Ben Goldman shared that he spotted the test in reply to her GML 2026 takeaways on <a href="https://www.linkedin.com/feed/update/urn:li:activity:7463015175336611840/?dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287465140913162612736%2Curn%3Ali%3Aactivity%3A7463015175336611840%29&amp;dashReplyUrn=urn%3Ali%3Afsd_comment%3A%287466141854187749376%2Curn%3Ali%3Aactivity%3A7463015175336611840%29">LinkedIn</a>.</p>


Google confirmed it is testing healthcare-related ads in AI Mode, marking the latest expansion of advertising into the company’s AI-powered search experiences.
The big picture. The test is currently limited to healthcare advertisers in the U.S. and only applies to English-language queries in AI Mode, according to Google Ads Liaison Ginny Marvin.
The confirmation comes after weeks of industry speculation that healthcare ads had started appearing within AI-generated search experiences.
What Google is saying. Responding to questions on LinkedIn, Marvin confirmed that Google is “beginning a small test of ads in AI Mode for the healthcare vertical.”




She added that several campaign types are eligible to participate, including:
Performance Max (PMax)
AI Max with search term matching
Shopping campaigns
Broad match campaigns
The same campaign types are also eligible to serve ads in AI Overviews.
Why we care. Healthcare is one of Google’s most heavily regulated advertising categories, making this test an important signal for how the company plans to monetize AI-powered search experiences. 
If the rollout expands, healthcare marketers could gain access to a new source of visibility in AI Mode, while advertisers in other regulated industries may get a preview of how ads will eventually appear in Google’s AI-generated results.
The fine print. The initial test comes with creative restrictions.
According to Marvin, the first phase is limited to ads that do not use pinned assets or text disclaimers, narrowing the pool of eligible healthcare creatives.
What to watch. The test is currently small, but advertisers will be watching closely to see whether Google expands eligibility to more healthcare advertisers, additional ad formats, and other regulated industries.
The move could also provide an early indication of how Google plans to balance monetization and user trust as AI Mode becomes a larger part of the search experience.
First spotted. Senior Strategist Ben Goldman shared that he spotted the test in reply to her GML 2026 takeaways on LinkedIn.

Google has confirmed a test of healthcare ads in AI Mode, offering an early look at how advertising may evolve within AI search.

Google begins testing healthcare ads in AI Mode

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg" class="attachment-large size-large wp-post-image" alt="Why Google Ads auctions now run on intent, not keywords" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google's updated Ads terms expand its use of AI-driven automation, raising advertiser concerns about reduced control and ownership.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg" class="attachment-large size-large wp-post-image" alt="Why Google Ads auctions now run on intent, not keywords" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/02/Why-Google-Ads-auctions-now-run-on-intent-not-keywords-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p id="h-google-is-updating-its-google-ads-terms-of-service-to-reflect-how-advertisers-inputs-can-be-used-across-ai-powered-and-automated-advertising-tools-while-reinforcing-advertisers-responsibility-for-campaign-oversight">Google is updating its Google Ads Terms of Service to reflect how advertisers&#8217; inputs can be used across AI-powered and automated advertising tools, while reinforcing advertisers&#8217; responsibility for campaign oversight.</p>



<p><strong>The big picture</strong>. The changes apply only to Google Ads accounts and do not affect other Google products, including Google Workspace or Cloud Identity. The updated terms take effect July 1st, and require no action from advertisers.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="465" height="781" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Terms-and-conditions.jpg" alt="" class="wp-image-479256"/></figure>
</div>


<p id="h-what-s-changing"><strong>What&#8217;s changing.</strong> Google says the updates are designed to support the growing use of automation and AI within its advertising platform.</p>



<p>Key changes include:</p>



<ul class="wp-block-list">
<li>Expanded language explaining how advertiser-provided inputs may be used across Google Ads features to improve campaign performance.</li>



<li>Clarification that information entered into conversational experiences and similar Google Ads tools may be utilized by Google&#8217;s systems.</li>



<li>Updated provisions covering URLs and accounts that advertisers authorize Google to access and crawl for automated campaign setup.</li>
</ul>



<p><strong>Why we care. </strong>The updated terms appear to give Google broader authority to use automated systems and AI to generate, select, and optimize campaign elements on advertisers&#8217; behalf. At the same time, advertisers remain responsible for reviewing and approving those campaigns and any resulting ad assets. </p>



<p>For brands and agencies already concerned about transparency and control in increasingly automated ad platforms, the changes could have implications for governance, compliance, and performance accountability.</p>



<p><strong>Significant shift. </strong>One notable change is the language surrounding automated campaign management.</p>



<p>Previous terms generally stated that Google could provide tools to help advertisers generate targets, ads, or landing destinations, while allowing advertisers to opt in or opt out of many automation features.</p>



<p>The new terms state that:</p>



<ul class="wp-block-list">
<li>&#8220;Customer authorizes Google and its affiliates to serve ads, including through the use of automated program features to format, select, or generate targets, ads, or destinations on Customer&#8217;s behalf.&#8221;</li>
</ul>



<p>The terms also maintain that advertisers remain responsible for the resulting campaigns and ad assets.</p>



<p><strong>What critics are saying. </strong>Not everyone is convinced the changes benefit advertisers. Anthony Higman, founder of AdSQUIRE, argued the updated terms further erode two of what he considers the core pillars of Google Ads: relevance and control. </p>



<p>He pointed to new language authorizing Google to use automated features to format, select, or generate targets, ads, and destinations on an advertiser&#8217;s behalf, while advertisers remain responsible for the resulting campaigns.</p>



<p>Higman also criticized Google&#8217;s broader push toward AI-driven automation, arguing the previous terms gave advertisers more explicit opportunities to opt in or out of automated campaign features. </p>



<p>He said the latest revisions, combined with updates to liability and arbitration provisions in some regions, signal a continued shift of decision-making authority from advertisers to Google&#8217;s systems.</p>



<p id="h-between-the-lines"><strong>Between the lines. </strong>The revised terms place additional emphasis on advertiser responsibility.</p>



<p>Advertisers must:</p>



<ul class="wp-block-list">
<li>Ensure they have the necessary rights to any information, content, URLs, or other inputs provided to Google Ads.</li>



<li>Continue reviewing, approving, editing, or removing campaigns and ad assets that may be generated automatically through Google&#8217;s advertising tools.</li>
</ul>



<p id="h-regional-updates"><strong>Regional updates.</strong> Google is also making jurisdiction-specific changes in several markets.</p>



<p>Those include:</p>



<ul class="wp-block-list">
<li>Updates to arbitration agreement language in certain regions, including revisions reflecting current legal practices or the removal of arbitration provisions where applicable.</li>



<li>New references to regulatory operating fees and other country-specific charges that may apply to ads served in certain jurisdictions.</li>



<li>In Brazil, revised language clarifying the role of Google BR as the entity authorized to commercially operate and monetize advertising inventory owned by Google LLC.</li>
</ul>



<p id="h-what-s-next"><strong>What&#8217;s next.</strong> The new Google Ads Terms of Service become effective on July 1st.</p>



<p>Advertisers are encouraged to review the updated terms, though no acceptance or account changes are required before the rollout date.</p>






Google is updating its Google Ads Terms of Service to reflect how advertisers’ inputs can be used across AI-powered and automated advertising tools, while reinforcing advertisers’ responsibility for campaign oversight.
The big picture. The changes apply only to Google Ads accounts and do not affect other Google products, including Google Workspace or Cloud Identity. The updated terms take effect July 1st, and require no action from advertisers.




What’s changing. Google says the updates are designed to support the growing use of automation and AI within its advertising platform.
Key changes include:
Expanded language explaining how advertiser-provided inputs may be used across Google Ads features to improve campaign performance.
Clarification that information entered into conversational experiences and similar Google Ads tools may be utilized by Google’s systems.
Updated provisions covering URLs and accounts that advertisers authorize Google to access and crawl for automated campaign setup.
Why we care. The updated terms appear to give Google broader authority to use automated systems and AI to generate, select, and optimize campaign elements on advertisers’ behalf. At the same time, advertisers remain responsible for reviewing and approving those campaigns and any resulting ad assets. 
For brands and agencies already concerned about transparency and control in increasingly automated ad platforms, the changes could have implications for governance, compliance, and performance accountability.
Significant shift. One notable change is the language surrounding automated campaign management.
Previous terms generally stated that Google could provide tools to help advertisers generate targets, ads, or landing destinations, while allowing advertisers to opt in or opt out of many automation features.
The new terms state that:
“Customer authorizes Google and its affiliates to serve ads, including through the use of automated program features to format, select, or generate targets, ads, or destinations on Customer’s behalf.”
The terms also maintain that advertisers remain responsible for the resulting campaigns and ad assets.
What critics are saying. Not everyone is convinced the changes benefit advertisers. Anthony Higman, founder of AdSQUIRE, argued the updated terms further erode two of what he considers the core pillars of Google Ads: relevance and control. 
He pointed to new language authorizing Google to use automated features to format, select, or generate targets, ads, and destinations on an advertiser’s behalf, while advertisers remain responsible for the resulting campaigns.
Higman also criticized Google’s broader push toward AI-driven automation, arguing the previous terms gave advertisers more explicit opportunities to opt in or out of automated campaign features. 
He said the latest revisions, combined with updates to liability and arbitration provisions in some regions, signal a continued shift of decision-making authority from advertisers to Google’s systems.
Between the lines. The revised terms place additional emphasis on advertiser responsibility.
Advertisers must:
Ensure they have the necessary rights to any information, content, URLs, or other inputs provided to Google Ads.
Continue reviewing, approving, editing, or removing campaigns and ad assets that may be generated automatically through Google’s advertising tools.
Regional updates. Google is also making jurisdiction-specific changes in several markets.
Those include:
Updates to arbitration agreement language in certain regions, including revisions reflecting current legal practices or the removal of arbitration provisions where applicable.
New references to regulatory operating fees and other country-specific charges that may apply to ads served in certain jurisdictions.
In Brazil, revised language clarifying the role of Google BR as the entity authorized to commercially operate and monetize advertising inventory owned by Google LLC.
What’s next. The new Google Ads Terms of Service become effective on July 1st.
Advertisers are encouraged to review the updated terms, though no acceptance or account changes are required before the rollout date.

Google's updated Ads terms expand its use of AI-driven automation, raising advertiser concerns about reduced control and ownership.

Google Ads updates terms of service ahead of July 2026 rollout

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Microsoft releases a search service just for AI-agents, because agents search differently from humans.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/06/microsoft-bing-agent-robot-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Microsoft has released its new grounding API named Web IQ. Web IQ is a &#8220;suite of AI-native grounding APIs built for the agentic era, connecting AI systems and agents to fresh, real-world intelligence from across the web — including web pages, news, images, and videos,&#8221; Microsoft <a href="http://aka.ms/nextgengrounding">announced</a>.</p>



<p><strong>What is Web IQ</strong>. Web IQ is a suite of Microsoft’s AI-native grounding APIs built for the agentic era, for AI-agents work. Web IQ connects AI systems and agents to fresh, real-world information from across the web, including web pages, news, images, and videos. This is powered by Bing&#8217;s index and the its best of how Bing understands the web. </p>



<p>Web IQ utilizes the same API infrastructure operating at inside Microsoft Copilot and many other leading AI systems, including ChatGPT.</p>



<p>But this is not the same APIs that Copilot and ChatGPT initially used when those LLMs launched, it is rebuilt from the ground up to be efficient, fast and of course, relevant, Jordi Ribas, President of Search &amp; AI at Microsoft.  It is used by Bing to show the Copilot answers at the top of the Bing search results for some queries, it is used by ChatGPT for some of its web answers and it is used directly in Copilot for answers.</p>



<p><strong>Search for agents (not humans). </strong>Web IQ provides search results designed for AI-agents, not humans. While Bing Search for humans prioritizes ranking, ranking is less important for agents, Jordi Ribas told Search Engine Land. Agents want to extract the right information from the documents, package it and deliver it quickly.</p>



<p>Agents don&#8217;t just enter a single query and stop searching, like many humans. Agents go deeper and continue to search, fan-out, if you will. &#8220;It required re-architecting the system from the ground up from indexing and retrieval to ranking, passage selection, and orchestration so every layer is aligned around the needs of inference-time grounding,&#8221; Microsoft said.</p>



<p>Because of how often agents search, Microsoft built Web IQ to be efficient and use the fewest tokens as possible. Microsoft said, &#8220;fewer tokens in, better answers out, lower cost per call.&#8221; It is also fast, <br>roughly 2.5x faster than the next best alternative, Microsoft said.</p>



<p><strong>Access</strong> <strong>and availability. </strong>Right now, Web IQ is being used by Microsoft for Copilot and by OpenAI&#8217;s ChatGPT, and other larger LLM platforms.  Microsoft does plan to expand access as it scales. </p>



<p>Microsoft said to express interest in Web IQ, <a href="https://webiq.microsoft.ai/">go to this page</a>.</p>



<p><strong>Why we care. </strong>As the web adapts and begins to support agentic experiences, like AI-agents, these are changes we need to watch careful and be ready to adopt as they become available.</p>



<p>The web is changing, adapting, for AI and so you need to make sure your websites change and adapt along with it.</p>



<p>It doesn&#8217;t mean humans are going away but AI-agents will be coming, if not already, so you need to prepare for this next evolution of the web.</p>


Microsoft has released its new grounding API named Web IQ. Web IQ is a “suite of AI-native grounding APIs built for the agentic era, connecting AI systems and agents to fresh, real-world intelligence from across the web — including web pages, news, images, and videos,” Microsoft announced.
What is Web IQ. Web IQ is a suite of Microsoft’s AI-native grounding APIs built for the agentic era, for AI-agents work. Web IQ connects AI systems and agents to fresh, real-world information from across the web, including web pages, news, images, and videos. This is powered by Bing’s index and the its best of how Bing understands the web. 
Web IQ utilizes the same API infrastructure operating at inside Microsoft Copilot and many other leading AI systems, including ChatGPT.
But this is not the same APIs that Copilot and ChatGPT initially used when those LLMs launched, it is rebuilt from the ground up to be efficient, fast and of course, relevant, Jordi Ribas, President of Search & AI at Microsoft.  It is used by Bing to show the Copilot answers at the top of the Bing search results for some queries, it is used by ChatGPT for some of its web answers and it is used directly in Copilot for answers.
Search for agents (not humans). Web IQ provides search results designed for AI-agents, not humans. While Bing Search for humans prioritizes ranking, ranking is less important for agents, Jordi Ribas told Search Engine Land. Agents want to extract the right information from the documents, package it and deliver it quickly.
Agents don’t just enter a single query and stop searching, like many humans. Agents go deeper and continue to search, fan-out, if you will. “It required re-architecting the system from the ground up from indexing and retrieval to ranking, passage selection, and orchestration so every layer is aligned around the needs of inference-time grounding,” Microsoft said.
Because of how often agents search, Microsoft built Web IQ to be efficient and use the fewest tokens as possible. Microsoft said, “fewer tokens in, better answers out, lower cost per call.” It is also fast, 
roughly 2.5x faster than the next best alternative, Microsoft said.
Access and availability. Right now, Web IQ is being used by Microsoft for Copilot and by OpenAI’s ChatGPT, and other larger LLM platforms.  Microsoft does plan to expand access as it scales. 
Microsoft said to express interest in Web IQ, go to this page.
Why we care. As the web adapts and begins to support agentic experiences, like AI-agents, these are changes we need to watch careful and be ready to adopt as they become available.
The web is changing, adapting, for AI and so you need to make sure your websites change and adapt along with it.
It doesn’t mean humans are going away but AI-agents will be coming, if not already, so you need to prepare for this next evolution of the web.

Microsoft releases a search service just for AI-agents, because agents search differently from humans.

Microsoft releases Web IQ, powered by Bing but designed for how AI-agents search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/How-SEO-turns-customer-success-into-AI-readable-proof.png" class="attachment-large size-large wp-post-image" alt="How SEO turns customer success into AI-readable proof" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/How-SEO-turns-customer-success-into-AI-readable-proof.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/How-SEO-turns-customer-success-into-AI-readable-proof-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/How-SEO-turns-customer-success-into-AI-readable-proof-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/How-SEO-turns-customer-success-into-AI-readable-proof-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Much of the evidence AI systems rely on lives inside customer success, support, and delivery teams. Here’s how SEO can surface it.

SEO has expanded beyond conversion into the operational side of the business, because that’s where the signals AI engines increasingly rely on get created.
When AI systems decide whether to recommend a brand, they evaluate post-sale signals like onboarding accuracy, performance outcomes, integration depth, and customer advocacy. Most of that information lives inside sales, support, customer success, and delivery teams, not inside marketing calendars or publishing workflows.
That creates a major SEO opportunity. Much of the evidence that could influence AI visibility still dies in CRMs, support platforms, and quarterly retrospectives rather than being codified into machine-readable form.
Bots and algorithms need to understand your business: what you offer, how you deliver it, and what customers think about it, in as much detail as possible. Here’s how.
5 stages that turn customer success into SEO signals
OPIDC stands for onboarded, performed, integrated, devoted, and codified. 
The first four stages map to the customer-success lifecycle most service and SaaS businesses already run: onboarding, adoption, retention, and advocacy. 
Codified is the addition. It describes the work of turning post-sale experiences into machine-legible evidence that AI systems can evaluate, compare, and recommend.

My termWhat everyone else calls it
OnboardedOnboarding
PerformedAdoption, first value, time-to-value
IntegratedRetention, expansion, stickiness
DevotedAdvocacy, loyalty
CodifiedNo established term





The first four stages — onboarded, performed, integrated, and devoted — describe what the business already does as part of its operations. The fifth stage — codified — describes what SEO does with what the business produces.
Together, those five stages form the people phase, which sits after the first 10 gates of the AI engine pipeline: discovered, selected, crawled, rendered, indexed, annotated, recruited, grounded, displayed, and won.
Combined, the 15-gate sequence extends the AI assistive agent optimization approach I was exploring when I first coined AEO.
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OPID is the business, not a content opportunity
The four OPID stages are the active core of business operations, and they’re where the business actually makes money.
Onboarded is the operational practice of getting new clients from sale to delivery. Performed is the operational practice of achieving measurable outcomes against a baseline. Integrated is the operational practice of becoming structurally embedded in clients’ lives. Devoted is the operational practice of earning unprompted advocacy.
The people who run these stages are the sales, service, support, customer success, and delivery teams. Marketing shapes the message, but the raw material comes from the people doing the delivery. What’s changed is that SEO now has work to do inside that operational core: harvesting from it.
Frame the work as harvesting the output of other teams, and the service team turns from gatekeeper into collaborator. You walk away with large amounts of raw material to publish, codify, and distribute, where AI engines can read it. 
Walk into a customer-success meeting saying, “I need content for my blog,” and nobody pays attention. Walk in saying, “The evidence your team produces every week influences whether AI recommends us to the next prospect, and I want to help you capture it,” and they’ll engage and help you.
Run OPIDC properly, and the work benefits the entire business. James Dooley told me his sales team now mostly fills in onboarding forms because AI has already done much of the selling before anyone picks up the phone. Inquiry volume is down, sales are up, and buyers often arrive already convinced. 
That’s what OPID looks like once you harvest it, codify it, and distribute it.




Your customer is now two customers, and only one of them can watch you work
Whether your next customer is a person or an agent, the work is the same: engineer the business to serve both, then make sure machines can see, ingest, and evaluate the quality of what you do. 
Here’s the trap: OPID is some of the most persuasive evidence you can generate, and it’s invisible to everyone except the client being served in that moment. Every other prospect, and every agent weighing you against a competitor, stands outside the room while your best work happens inside it.
The agent is the exception. In agential mode, the agent sees the delivery, evaluates it against the promised terms, and decides whether to return. That means you now have a second audience to satisfy, and the agent may control repeat transactions. 
Please the human and lose the agent, and you risk losing the repeat business the agent influences. Please the agent, and you may earn a customer who reselects you every cycle without a sales call. 
Dave Davies at Weights and Biases has explored this idea through the lens of “my client is an agent, how do I provide after-sales service for a machine?”
The agent checks your story against the open web
The catch is that the agent sits inside a walled garden. It evaluates the quality of what you delivered, but when an experience disappoints, it may return to the open web to verify whether it got you wrong. It looks for public evidence that supports or contradicts its experience with your brand.
If the open web reinforces your credibility, the agent may treat the bad experience as an exception and continue recommending you. If the open web confirms weaknesses or inconsistency, the agent may conclude it backed the wrong brand and quietly switch to a competitor. You never see that decision happen.
An agent’s loyalty is shaped by its direct experience with you, but public proof still matters when it goes looking for validation.
And it goes deeper than that. The agent runs on a model trained on the open web, built from the same public record you’re either feeding or neglecting. Your digital footprint shapes what the machine thinks about you long before any individual query. It’s what the model learned from, what the agent checks against, and one of the few assets you can actively build. 
Neglect it, and you become invisible in training data and difficult to verify in the moment. Build it, and you’re known before the conversation starts and reinforced when it does. This helps with both humans and assistive engines: your digital footprint supports both discovery and trust.
Here’s the part that matters more than the labels themselves: OPID isn’t a marketing program bolted onto the business. It’s the business, the way companies operate to make money, whether they’re B2B, B2C, ecommerce, or SaaS. Every one of these companies onboards customers, performs against a promise, embeds itself into customer workflows, and earns advocacy, because that’s what operating a business requires. 
The new requirement is codifying those experiences and distributing them back into the open web. That’s the flywheel, and it applies across business models.
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Onboarded: Getting the customer from sale to first success
Onboarded is what you do to take a customer from the moment they pay to the moment they get what they paid for, and get them there without the wheels coming off. Whatever you sell, the job is the same: close the gap between what you promised in the sale and what the customer actually experiences when delivery begins.
That’s the satisfaction gap. You close it before the contract is even signed by asking two questions many businesses skip:
What matters most to you here?
How will you know you’ve got it?
If you don’t ask the second question, your team and the customer end up measuring success against different scorecards, and the relationship starts breaking down in the first few weeks because you were working toward different outcomes. 
So you get the answer up front, write it down, and carry it across every part of the business that touches the account. You’ve defined what success looks like in the customer’s own words before you deliver a thing. Get that right, and you can codify it and distribute it as proof of delivery.
Harvest: When the client tells you the first win landed, capture it in their words, include the date, then codify it and distribute it.
Performed: Delivering a measurable outcome against a baseline
Performed is doing the thing you were paid to do and proving it made a difference. You increase the client’s revenue, reduce their processing time, solve the problem they hired you to solve, and deliver the result they came in wanting. Then you do the part many businesses miss: show the difference from where they started.
“Reduced support tickets by 43% in six months against a baseline of 1,200 a month” is proof that a machine can evaluate confidently. “We helped them grow” is a claim every human and every engine will question.
The trap is measuring only what the customer happens to notice — the project finished, the order shipped, the feature launched — while never capturing the comparison against the prior state. That comparison is the proof. Capture it, and you have evidence machines can evaluate and support.
Harvest: Results only matter in context, so capture the before and after to create evidence instead of unsupported claims.
Integrated: When the customer makes you a repeatable use case
Integrated is earning a permanent place in how the customer operates, not by trapping them, but by becoming the answer they reach for every time the need comes around again. This is the customer who has stopped shopping. They have a recurring job, you’re the one they call, and they’re happy keeping it that way.
When you sell something ongoing, it’s the account that renews without a conversation because you’ve become how a particular thing gets done. When you sell something bought once, it’s the buyer who comes straight back without comparing, the brand an agent drops into the basket because it already ran the comparison and you won.
Different shape, same outcome: you become the use case they’ve assigned to you, and you keep earning it so they never feel the need to reopen the question. Win that, and the renewal happens before anyone thinks to reconsider.
Harvest: Listen for lines like, “I can’t imagine XYZ without them.” That’s the customer telling you you’ve become a repeatable use case worth keeping.
Devoted: When the customer sells you to the next customer
Devoted is turning a happy customer into one who says so publicly. It’s one of the strongest signals in the model because engines can distinguish earned advocacy from manufactured promotion. A manufactured testimonial carries little weight. A customer praising you independently carries much more.
The B2B client naming you on a panel, the SaaS user posting a workflow to their network, the ecommerce buyer leaving an unsolicited review, and the B2C customer recommending you to a friend are all doing the same thing: describing what you do in their own words, in language the next buyer actually needs to hear.
That phrasing often carries more weight than brand messaging because it serves as independent corroboration rather than self-description. The challenge is that customers rarely do it on their own, so part of the work is creating opportunities for them to share those experiences publicly.
Harvest: Encourage customers to share their experiences publicly, capture those stories, publish them on your own channels, and encourage customers to publish them on theirs.
The proof AI needs already exists
Here’s the thing many SEOs have been getting half-right for years. You create content to satisfy machines, and always have, but too much of it gets created at a desk instead of being extracted from how the business actually serves its customers. You end up talking to the machines without gathering the material they actually need.
That material doesn’t live in your head or your content calendar. It lives in the business: in sales calls, support desks, account managers, founders taking difficult calls, and the day-to-day reality of delivering the right thing to the right people. Your job is to extract it, codify it, and feed it back into the ecosystem.
That’s the foundation under everything else, because codifying isn’t about writing content and guessing what people want to hear. It’s about pulling sales calls, FAQs, success stories, and product attributes from a central source and consolidating them. 
The unique marketing content you create still matters — the pieces where you demonstrate topical authority and show you know what you’re talking about — but that’s one stream, not the whole river.
This is where much of the SEO community has it backward. We overlook the bigger truth sitting in plain sight: businesses are already delivering the right products and services to the right people every day. That delivery is what convinces both machines and humans. You don’t have to invent it. You have to codify it and make it visible.
And this extends beyond AI assistants. The model we’re discussing includes assistive engines like Google, ChatGPT, Perplexity, and Copilot, but codifying isn’t an AI-specific tactic. It’s the discipline of making what you do legible to any machine that reads content, which is exactly what marketing teams already try to do on LinkedIn, Facebook, Instagram, and other platforms. 
The moment they codify content for those channels, they’re feeding assistive engines too, because those systems read many of the same sources. One discipline supports every machine, and marketing teams have already been laying much of the groundwork.
So stand where your audience is looking. Show them how well you serve people they recognize as themselves, invite them down the funnel by demonstrating you can solve their problem, and let them see the proof in your delivery. 
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Codifying is your job, and every channel depends on it
Codifying gives SEO a coordinating role across the business. The business creates value every day, serves customers, and delivers results. Someone has to extract that evidence, turn it into something machines can read, and distribute it into the world. Increasingly, that responsibility falls to SEO.
And here’s the broader shift: machine-driven distribution now shapes nearly every major platform. Google, ChatGPT, LinkedIn, YouTube, Facebook, and Instagram all rely on systems deciding what gets surfaced. That means every platform increasingly depends on structured, machine-readable content. 
Marketing teams can publish raw posts and hope they land, but machines can’t reliably interpret unstructured information. Distribution works better when someone codifies the message first, turning it into structured proof that can travel across search, assistive engines, and social platforms.
That content has to come from the business itself: real delivery, real customer feedback, and real proof, not marketing copy invented to fill a calendar. That’s why business operations, marketing, and SEO increasingly depend on each other. Business teams generate the evidence. Marketing shapes the message. SEO codifies and distributes it in ways machines can understand.
Because increasingly, once communication moves through a screen, a machine helps determine whether people see it. Codify for that machine, and you do more than feed search and AI systems. You organize information in a way that also makes it easier for humans to understand. The structure that helps algorithms interpret content also helps people process it.
The takeaway is simple: codify the real business. Use real delivery, real customer feedback, and real proof, then distribute it where your audience is already looking. Machines increasingly mediate what people see online, so feeding those systems has become part of reaching humans in the first place. That’s why codifying matters, and why SEO is well positioned to lead it.
This is the 16th piece in my AI authority series.




Part 1, “Rand Fishkin proved AI recommendations are inconsistent, here’s why and how to fix it,” introduced cascading confidence.
Part 2, “AAO: Why assistive agent optimization is the next evolution of SEO,” named the discipline.
Part 3, “The AI engine pipeline: 10 gates that decide whether you win the recommendation,” mapped the full pipeline.
Part 4, “The five infrastructure gates behind crawl, render, and index,” walked through the infrastructure phase.
Part 5, “5 competitive gates hidden inside ‘rank and display’,” covered the competitive phase.
Part 6, “The entity home: The page that shapes how search, AI, and users see your brand,” mapped the raw material.
Part 7, “The push layer returns: Why ‘publish and wait’ is half a strategy,” extended the entry model.
Part 8, “How AI decides what your content means and why it gets you wrong,” covered annotation, the last gate where you’re alone with the machine.
Part 9, “Why topical authority isn’t enough for AI search,” opened the competitive phase proper with topical ownership.
Part 10, “The funnel flip: Why AI forces a bottom-up acquisition strategy,” named the process.
Part 11, “The framing gap: Why AI can’t position your brand,” exposed the gap between evidence and recommendation.
Part 12, “The 10-gate AI search pipeline: Find where your content fails,” showed you how to find (and repair) your F grades in the AI engine pipeline.
Part 13, “The delegation boundary: How AI decides which brands win,” mapped how delegation moves between user and engine across Search, Assistive, and Agent modes.
Part 14, “The funnel query pathway: A framework for measuring AI visibility,” built the measurement instrument.
Part 15, “The micro-macro shift: How to measure AI visibility now that precision is gone,” moved measurement from micro precision to macro trend.
Up next: How you turn harvested operational evidence into machine-legible content.

Much of the evidence AI systems rely on lives inside customer success, support, and delivery teams. Here’s how SEO can surface it.

How SEO turns customer success into AI-readable proof

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget.png" class="attachment-large size-large wp-post-image" alt="Why high-ROAS campaigns don&#039;t always deserve more budget" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>More budget doesn’t always create more revenue. Identify when scaling paid search will drive incremental value versus higher costs.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget.png" class="attachment-large size-large wp-post-image" alt="Why high-ROAS campaigns don&#039;t always deserve more budget" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Why-high-ROAS-campaigns-dont-always-deserve-more-budget-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>It’s one of the best “problems” you can have in paid media. </p>



<p>You’re running a campaign that delivers on every front. Cost per acquisition is strong. Return on ad spend is exceptional. <a href="https://searchengineland.com/query-intent-vs-conversion-intent-476445">Lead quality meets expectations</a>. Average order value is exactly where it should be. </p>



<p>Then the ask comes in: Double the budget and keep the momentum going.</p>



<p>Before you take that step, pause. Increasing budget can unlock more performance, but only if there’s real room for that budget to be productive. If you’ve already maximized what the campaign can deliver on its own, adding budget can lead to higher costs without meaningful incremental revenue gains.</p>



<p>There are times when increasing budget is the right choice, and those are covered later. First, it’s important to understand when not to increase spend.</p>



<p><em>(</em><strong><em>Disclosure</em></strong><em>: I’m a Microsoft Ads employee, and while I’ll share some Microsoft insights, this is intended to be a platform-agnostic piece.)</em>



<h2 class="wp-block-heading" id="h-what-to-evaluate-before-increasing-budget">What to evaluate before increasing budget</h2>



<p>Before you increase spend, make sure the campaign can support more scale without sacrificing efficiency.</p>



<h3 class="wp-block-heading" id="h-learning-periods-matter">Learning periods matter</h3>



<p>Any meaningful change to budget, target CPA, or target ROAS can trigger a learning period.</p>



<p>In Microsoft Advertising, changes exceeding approximately 15% are likely to introduce performance volatility. This can result in short-term fluctuations in efficiency and volume while the system recalibrates.</p>



<p>If you increase budget too aggressively, you risk disrupting a high-performing campaign. A more stable approach is to increase budgets incrementally week over week. It’s also important to set expectations with stakeholders that growth will be gradual rather than immediate.</p>



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<h3 class="wp-block-heading" id="h-validate-that-performance-is-real">Validate that performance is real</h3>



<p>High return on ad spend only matters if it reflects real business value. Before increasing investment, confirm that:</p>



<ul class="wp-block-list">
<li>Conversion tracking is accurate and complete.</li>



<li>Lead quality aligns with downstream outcomes.</li>



<li>Revenue signals reflect actual profitability.</li>
</ul>



<p>Document any changes to conversion tracking or values, and clearly communicate what’s being measured and why.</p>



<h3 class="wp-block-heading" id="h-market-saturation-is-real">Market saturation is real</h3>



<p>Doubling down on a single audience or geography can lead to diminishing returns.</p>



<p>If you increase budget without expanding reach, you may oversaturate the available audience. This can drive up costs without expanding opportunity. Effective scaling often requires:</p>



<ul class="wp-block-list">
<li>Expanding into new markets or geographies.</li>



<li>Introducing new audience segments or personas.</li>



<li>Structuring additional campaigns instead of overloading a single one.</li>
</ul>



<h3 class="wp-block-heading" id="h-define-the-goal-efficiency-or-scale">Define the goal: Efficiency or scale?</h3>



<p>There’s a natural trade-off between efficiency and scale. At higher volume, it’s difficult to maintain peak return on ad spend. If stakeholders expect the same efficiency at significantly higher spend, misalignment is likely.</p>



<p>Be explicit about the objective:</p>



<ul class="wp-block-list">
<li>Are you trying to maintain efficiency?</li>



<li>Are you trying to grow volume while staying within profitable limits?</li>
</ul>



<p>Clarity here prevents frustration later.</p>



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<hr class="wp-block-separator has-text-color has-cyan-bluish-gray-color has-css-opacity has-cyan-bluish-gray-background-color has-background"/>



<h2 class="wp-block-heading" id="h-3-strategic-questions-to-ask-before-increasing-budget">3 strategic questions to ask before increasing budget</h2>



<h3 class="wp-block-heading" id="h-1-do-you-actually-have-impression-share-room-to-grow">1. Do you actually have impression share room to grow?</h3>



<p>Impression share and share of voice are critical indicators of growth potential.</p>



<ul class="wp-block-list">
<li>If you’re losing impression share due to budget, increasing spend can unlock gains.</li>



<li>If you’re losing impression share due to rank, increasing budget alone won’t solve the problem.</li>
</ul>



<p>In those cases, you may be dealing with:</p>



<ul class="wp-block-list">
<li>Bids that aren’t competitive relative to auction prices.</li>



<li>Campaign structure issues that limit performance.</li>



<li>Inefficient or irrelevant keyword coverage.</li>
</ul>



<p>If impression share lost due to rank exceeds 50%, increasing budget is unlikely to drive incremental value because there’s either a structural issue or you’re underbidding. Raising the budget might solve the latter problem. However, you need to be prepared for higher CPCs.</p>



<p>Before increasing budget, audit the following:</p>



<ul class="wp-block-list">
<li>Keyword duplication and overall coverage.</li>



<li>Bid levels relative to daily budgets and auction dynamics.</li>



<li>Search term quality and relevance.</li>
</ul>



<p>Budget can’t compensate for structural inefficiencies.</p>



<h3 class="wp-block-heading" id="h-2-is-there-room-for-more-demand-or-are-you-just-bidding-higher">2. Is there room for more demand, or are you just bidding higher?</h3>



<p>Return on ad spend alone isn’t a sufficient signal for scaling.</p>



<p>Search campaigns primarily capture existing demand. They don’t lend themselves to creating it outside of AI surfaces.</p>



<p>If you increase budget without increasing demand, the system often responds by:</p>



<ul class="wp-block-list">
<li>Bidding more aggressively on existing queries.</li>



<li>Increasing cost per click to win more auctions.</li>



<li>Recycling the same demand pool at a higher cost.</li>
</ul>



<p>Sustainable growth requires expanding demand, not just competing harder for the same users.</p>



<p>This includes investing in:</p>



<ul class="wp-block-list">
<li>Upper- and mid-funnel channels such as video and social formats.</li>



<li>Creative that communicates clear value propositions such as speed, reliability, or cost efficiency.</li>



<li>Messaging that influences how users think about your brand before they search.</li>
</ul>



<p>AI-powered surfaces also play a role. Campaigns that use automation and broader matching approaches are more likely to capture incremental demand signals, especially when supported by strong visual and text creative.</p>



<h3 class="wp-block-heading" id="h-3-should-this-budget-go-into-a-new-campaign-instead">3. Should this budget go into a new campaign instead?</h3>



<p>Not all growth should happen within a single campaign.</p>



<p>If a campaign is already optimized and stable, allocating additional budget to it can introduce risk without creating new opportunities.</p>



<p>Consider alternatives such as:</p>



<ul class="wp-block-list">
<li>Launching a new campaign targeting a distinct market or geography.</li>



<li>Creating new audience segments or product groupings.</li>



<li>Testing new campaign types or formats to expand reach.</li>
</ul>



<p>This approach allows you to scale while protecting what’s already working, and it enables clearer measurement of incremental impact.</p>



<h2 class="wp-block-heading" id="h-when-increasing-budget-does-make-sense">When increasing budget does make sense</h2>



<h3 class="wp-block-heading" id="h-you-re-constrained-by-budget-rather-than-rank">You’re constrained by budget rather than rank</h3>



<p>If impression share lost due to budget is high and conversion tracking is reliable, <a href="https://searchengineland.com/top-ppc-mistakes-452357">increasing budget can unlock incremental volume</a>.</p>



<p>In this scenario, you’re not fully participating in available auctions, which creates room for additional spend to perform. This can mean more budget for high-performing keywords and more advertising hours.</p>



<h3 class="wp-block-heading" id="h-the-campaign-is-new-and-still-learning">The campaign is new and still learning</h3>



<p>For newer campaigns, additional budget can accelerate the learning phase by providing more data.</p>



<p>If you’re already in a learning period and willing to accept short-term variability, increasing budget early can help the system stabilize and identify performance patterns more quickly.</p>



<h3 class="wp-block-heading" id="h-you-re-scaling-demand-alongside-spend">You’re scaling demand alongside spend</h3>



<p>Budget increases are most effective when paired with <a href="https://searchengineland.com/socialized-paid-media-437308">demand generation</a> efforts.</p>



<p>This includes:</p>



<ul class="wp-block-list">
<li>Expanding reach through new channels.</li>



<li>Increasing creative coverage.</li>



<li>Investing in AI-powered formats.</li>
</ul>



<p>In this context, increasing budget becomes part of a broader growth strategy rather than a standalone tactic.</p>



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<h2 class="wp-block-heading" id="h-what-deliberate-scaling-looks-like">What deliberate scaling looks like</h2>



<p>A high-performing campaign with strong return on ad spend is a strong foundation, but it doesn’t guarantee that additional budget will drive additional value.</p>



<p>Before increasing spend:</p>



<ul class="wp-block-list">
<li>Validate that performance reflects real business outcomes.</li>



<li>Confirm that there’s room to grow.</li>



<li>Align on efficiency versus scale.</li>



<li>Decide whether growth belongs in the current campaign or a new one.</li>
</ul>



<p>Deliberate scaling protects existing performance while unlocking new opportunity.</p>

It’s one of the best “problems” you can have in paid media. 
You’re running a campaign that delivers on every front. Cost per acquisition is strong. Return on ad spend is exceptional. Lead quality meets expectations. Average order value is exactly where it should be. 
Then the ask comes in: Double the budget and keep the momentum going.
Before you take that step, pause. Increasing budget can unlock more performance, but only if there’s real room for that budget to be productive. If you’ve already maximized what the campaign can deliver on its own, adding budget can lead to higher costs without meaningful incremental revenue gains.
There are times when increasing budget is the right choice, and those are covered later. First, it’s important to understand when not to increase spend.
(Disclosure: I’m a Microsoft Ads employee, and while I’ll share some Microsoft insights, this is intended to be a platform-agnostic piece.)



What to evaluate before increasing budget
Before you increase spend, make sure the campaign can support more scale without sacrificing efficiency.
Learning periods matter
Any meaningful change to budget, target CPA, or target ROAS can trigger a learning period.
In Microsoft Advertising, changes exceeding approximately 15% are likely to introduce performance volatility. This can result in short-term fluctuations in efficiency and volume while the system recalibrates.
If you increase budget too aggressively, you risk disrupting a high-performing campaign. A more stable approach is to increase budgets incrementally week over week. It’s also important to set expectations with stakeholders that growth will be gradual rather than immediate.

  
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Start Free Trial
    
Get started with
Validate that performance is real
High return on ad spend only matters if it reflects real business value. Before increasing investment, confirm that:
Conversion tracking is accurate and complete.
Lead quality aligns with downstream outcomes.
Revenue signals reflect actual profitability.
Document any changes to conversion tracking or values, and clearly communicate what’s being measured and why.
Market saturation is real
Doubling down on a single audience or geography can lead to diminishing returns.
If you increase budget without expanding reach, you may oversaturate the available audience. This can drive up costs without expanding opportunity. Effective scaling often requires:
Expanding into new markets or geographies.
Introducing new audience segments or personas.
Structuring additional campaigns instead of overloading a single one.
Define the goal: Efficiency or scale?
There’s a natural trade-off between efficiency and scale. At higher volume, it’s difficult to maintain peak return on ad spend. If stakeholders expect the same efficiency at significantly higher spend, misalignment is likely.
Be explicit about the objective:
Are you trying to maintain efficiency?
Are you trying to grow volume while staying within profitable limits?
Clarity here prevents frustration later.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
3 strategic questions to ask before increasing budget
1. Do you actually have impression share room to grow?
Impression share and share of voice are critical indicators of growth potential.
If you’re losing impression share due to budget, increasing spend can unlock gains.
If you’re losing impression share due to rank, increasing budget alone won’t solve the problem.
In those cases, you may be dealing with:
Bids that aren’t competitive relative to auction prices.
Campaign structure issues that limit performance.
Inefficient or irrelevant keyword coverage.
If impression share lost due to rank exceeds 50%, increasing budget is unlikely to drive incremental value because there’s either a structural issue or you’re underbidding. Raising the budget might solve the latter problem. However, you need to be prepared for higher CPCs.
Before increasing budget, audit the following:
Keyword duplication and overall coverage.
Bid levels relative to daily budgets and auction dynamics.
Search term quality and relevance.
Budget can’t compensate for structural inefficiencies.
2. Is there room for more demand, or are you just bidding higher?
Return on ad spend alone isn’t a sufficient signal for scaling.
Search campaigns primarily capture existing demand. They don’t lend themselves to creating it outside of AI surfaces.
If you increase budget without increasing demand, the system often responds by:
Bidding more aggressively on existing queries.
Increasing cost per click to win more auctions.
Recycling the same demand pool at a higher cost.
Sustainable growth requires expanding demand, not just competing harder for the same users.
This includes investing in:
Upper- and mid-funnel channels such as video and social formats.
Creative that communicates clear value propositions such as speed, reliability, or cost efficiency.
Messaging that influences how users think about your brand before they search.
AI-powered surfaces also play a role. Campaigns that use automation and broader matching approaches are more likely to capture incremental demand signals, especially when supported by strong visual and text creative.
3. Should this budget go into a new campaign instead?
Not all growth should happen within a single campaign.
If a campaign is already optimized and stable, allocating additional budget to it can introduce risk without creating new opportunities.
Consider alternatives such as:
Launching a new campaign targeting a distinct market or geography.
Creating new audience segments or product groupings.
Testing new campaign types or formats to expand reach.
This approach allows you to scale while protecting what’s already working, and it enables clearer measurement of incremental impact.
When increasing budget does make sense
You’re constrained by budget rather than rank
If impression share lost due to budget is high and conversion tracking is reliable, increasing budget can unlock incremental volume.
In this scenario, you’re not fully participating in available auctions, which creates room for additional spend to perform. This can mean more budget for high-performing keywords and more advertising hours.
The campaign is new and still learning
For newer campaigns, additional budget can accelerate the learning phase by providing more data.
If you’re already in a learning period and willing to accept short-term variability, increasing budget early can help the system stabilize and identify performance patterns more quickly.
You’re scaling demand alongside spend
Budget increases are most effective when paired with demand generation efforts.
This includes:
Expanding reach through new channels.
Increasing creative coverage.
Investing in AI-powered formats.
In this context, increasing budget becomes part of a broader growth strategy rather than a standalone tactic.

  
complete picture of your search visibility.
      
Start Free Trial
    
Get started with
What deliberate scaling looks like
A high-performing campaign with strong return on ad spend is a strong foundation, but it doesn’t guarantee that additional budget will drive additional value.
Before increasing spend:
Validate that performance reflects real business outcomes.
Confirm that there’s room to grow.
Align on efficiency versus scale.
Decide whether growth belongs in the current campaign or a new one.
Deliberate scaling protects existing performance while unlocking new opportunity.

More budget doesn’t always create more revenue. Identify when scaling paid search will drive incremental value versus higher costs.

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Read the Latest Trends and Headlines in Digital Marketing.

Here are some of the latest headlines on digital marketing insights, search, and ecommerce:

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Reach out with any questions you might have regarding how RSO can help you with digital marketing.

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