<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Microsoft Ads" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Microsoft’s new asset-level editorial review lets compliant ad components run even when others are disapproved reducing campaign disruption.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Microsoft Ads" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/01/Microsoft-Ads.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Microsoft Advertising is now rolling out asset-level editorial review. This will allow you to view policy approvals for each ad component, rather than the entire ad, reducing delays caused by a single non-compliant element.</p>



<ul class="wp-block-list">
<li>Asset-level ad reviews were <a href="https://searchengineland.com/microsoft-ads-gets-granular-with-new-asset-level-reviews-457690">first spotted in June</a> and <a href="https://about.ads.microsoft.com/en/blog/post/november-2025/asset-level-editorial-review-and-other-updates-for-november">officially introduced</a> last month.</li>
</ul>



<p><strong>What’s new</strong>. Advertisers can now see headlines, descriptions, and images reviewed separately inside the Microsoft Advertising interface. If one asset violates policy, only that component is blocked, while compliant assets continue to serve.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2025/12/asset-level-review.jpg" alt="" class="wp-image-466583" srcset="https://searchengineland.com/wp-content/seloads/2025/12/asset-level-review.jpg 1280w, https://searchengineland.com/wp-content/seloads/2025/12/asset-level-review-768x432.jpg 768w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<p><strong>How it works</strong>. Microsoft Advertising:</p>



<ul class="wp-block-list">
<li>Flags disapproved assets directly in the dashboard.</li>



<li>Displays warning banners when components are blocked.</li>



<li>Shows clear asset-level status alongside campaign details.</li>
</ul>



<p><strong>Why we care.</strong> This change reduces campaign disruption and speeds up approvals. You can pinpoint and fix the exact asset causing an issue instead of rebuilding or resubmitting entire ads, helping campaigns go live faster.</p>


Microsoft Advertising is now rolling out asset-level editorial review. This will allow you to view policy approvals for each ad component, rather than the entire ad, reducing delays caused by a single non-compliant element.
Asset-level ad reviews were first spotted in June and officially introduced last month.
What’s new. Advertisers can now see headlines, descriptions, and images reviewed separately inside the Microsoft Advertising interface. If one asset violates policy, only that component is blocked, while compliant assets continue to serve.




How it works. Microsoft Advertising:
Flags disapproved assets directly in the dashboard.
Displays warning banners when components are blocked.
Shows clear asset-level status alongside campaign details.
Why we care. This change reduces campaign disruption and speeds up approvals. You can pinpoint and fix the exact asset causing an issue instead of rebuilding or resubmitting entire ads, helping campaigns go live faster.

Microsoft’s new asset-level editorial review lets compliant ad components run even when others are disapproved reducing campaign disruption.

Microsoft launches asset-level ad reviews

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google’s policy update expands pharmaceutical advertising access in programmatic channels and shifts greater compliance risk to advertisers.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2015/09/google-mobile3-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google will update its Pharmaceutical policy for AdMob Authorized Buyers in January, allowing prescription drug and prescription drug service ads in select markets without Google certification while clarifying what remains strictly prohibited.</p>



<p><strong>What’s changing</strong>. The policy will be renamed “Pharmaceutical products and services” and updated to let Authorized Buyers promote prescription drugs and prescription drug services in select countries where local law allows, without the Google certification normally required in Google Ads.</p>



<ul class="wp-block-list">
<li>While access is expanding, the rules are not loosening. The policy language is being reorganized to improve clarity and readability, not to relax enforcement.</li>
</ul>



<p><strong>Why we care.</strong> This update expands access to pharmaceutical inventory without Google certification, opening new reach and adding competitive pressure in programmatic auctions. It also shifts more compliance responsibility to advertisers, raising the risk of violations if geo-targeting and creative controls aren’t tightly managed. Even non-pharma advertisers may feel the impact as increased pharma demand can affect pricing, brand safety, and placement strategies.</p>



<p><strong>What’s still banned</strong>. These types of ads remain prohibited across Google Partner Inventory:</p>



<ul class="wp-block-list">
<li>Clinical trials.</li>



<li>Miracle cures.</li>



<li>Unapproved supplements.</li>



<li>Illegal drugs.</li>



<li>Drug paraphernalia.</li>



<li>Addiction treatment and recovery services.</li>



<li>Crisis hotlines.</li>



<li>Speculative or experimental medical treatments (including stem cell and gene therapies) </li>
</ul>



<p><strong>Between the lines</strong>. Google is widening access while pushing responsibility downstream. By removing certification requirements for Authorized Buyers but keeping strict geographic and content controls, Google places compliance risk squarely on buyers and publishers.</p>



<p><strong>What to do now.</strong> App publishers using AdMob should review category blocking and ad controls to prevent unwanted pharma ads, especially as more inventory becomes eligible. Buyers should prepare for country-by-country enforcement and carefully audit creatives.</p>



<p><strong>Bottom line</strong>. <a href="https://support.google.com/authorizedbuyers/answer/6100448" target="_blank" rel="noopener">Google is opening the door wider for pharmaceutical advertising</a> in programmatic environments — but the rules are still complex, localized, and unforgiving for those who get them wrong.</p>


Google will update its Pharmaceutical policy for AdMob Authorized Buyers in January, allowing prescription drug and prescription drug service ads in select markets without Google certification while clarifying what remains strictly prohibited.
What’s changing. The policy will be renamed “Pharmaceutical products and services” and updated to let Authorized Buyers promote prescription drugs and prescription drug services in select countries where local law allows, without the Google certification normally required in Google Ads.
While access is expanding, the rules are not loosening. The policy language is being reorganized to improve clarity and readability, not to relax enforcement.
Why we care. This update expands access to pharmaceutical inventory without Google certification, opening new reach and adding competitive pressure in programmatic auctions. It also shifts more compliance responsibility to advertisers, raising the risk of violations if geo-targeting and creative controls aren’t tightly managed. Even non-pharma advertisers may feel the impact as increased pharma demand can affect pricing, brand safety, and placement strategies.
What’s still banned. These types of ads remain prohibited across Google Partner Inventory:
Clinical trials.
Miracle cures.
Unapproved supplements.
Illegal drugs.
Drug paraphernalia.
Addiction treatment and recovery services.
Crisis hotlines.
Speculative or experimental medical treatments (including stem cell and gene therapies) 
Between the lines. Google is widening access while pushing responsibility downstream. By removing certification requirements for Authorized Buyers but keeping strict geographic and content controls, Google places compliance risk squarely on buyers and publishers.
What to do now. App publishers using AdMob should review category blocking and ad controls to prevent unwanted pharma ads, especially as more inventory becomes eligible. Buyers should prepare for country-by-country enforcement and carefully audit creatives.
Bottom line. Google is opening the door wider for pharmaceutical advertising in programmatic environments — but the rules are still complex, localized, and unforgiving for those who get them wrong.

Google’s policy update expands pharmaceutical advertising access in programmatic channels and shifts greater compliance risk to advertisers.

Google to loosen pharma ad rules for AdMob authorized buyers

<div><img width="800" height="462" src="https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-800x462.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-800x462.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-586x338.jpg 586w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-196x113.jpg 196w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-768x443.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-1536x886.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-150x87.jpg 150w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google accused SerpApi of 'circumventing security measures protecting others’ copyrighted content that appears in Google search results.'

<div><img width="800" height="462" src="https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-800x462.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-800x462.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-586x338.jpg 586w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-196x113.jpg 196w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-768x443.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-1536x886.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920-150x87.jpg 150w, https://searchengineland.com/wp-content/seloads/2023/04/google-ninja-robot-crawler-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google said today that it is suing SerpApi, accusing the company of bypassing security protections to scrape, harvest, and resell copyrighted content from Google Search results.</p>



<p><strong>The allegations:</strong> Google said SerpApi:</p>



<ul class="wp-block-list">
<li>Circumvented Google’s security measures and industry-standard crawling controls.</li>



<li>Ignored website directives that specify whether content can be accessed.</li>



<li>Used cloaking, rotating bot identities, and large bot networks to scrape content at scale.</li>



<li>Took licensed content from Search features, including images and real-time data, and resold it for profit.</li>
</ul>



<p><strong>What Google is saying. </strong>“Stealthy scrapers like SerpApi override [crawling] directives and give sites no choice at all,” Google wrote, calling the alleged scraping “brazen” and “unlawful.” Google said SerpApi&#8217;s activity “increased dramatically over the past year.”</p>



<p><strong>Catch up quick.</strong> Google&#8217;s lawsuit <a href="https://searchengineland.com/reddit-sues-perplexity-serpapi-scraping-google-463681">similar legal action taken by Reddit</a>, which named SerpApi, Perplexity, Oxylabs, and AWMProxy and accused them of scraping Reddit content through Google Search results while hiding their identities to bypass restrictions.</p>



<ul class="wp-block-list">
<li>Reddit licenses its data to Google and OpenAI, but alleges others tried to sidestep those deals.</li>



<li>Reddit said it set a “trap” post visible only to Google’s crawler that later appeared in Perplexity results — evidence of scraping, according to the complaint.</li>



<li><a href="https://searchengineland.com/serpapi-reddit-lawsuit-response-463962">SerpApi denied wrongdoing</a> and said it operates lawfully.</li>
</ul>



<p><strong>What SerpApi has said previously</strong>. SerpApi argued that “public search data should be accessible,” framing its work as protected by the First Amendment and warning that lawsuits like Reddit’s threaten the “free and open web.”</p>



<p><strong>Why we care.</strong> If Google wins, reliable SERP data could become harder to get, more expensive, or both — especially for teams that rely on tools powered by services like SerpApi. As AI already reduces clicks and transparency, Google now appears intent on making it even harder for brands to understand how Search works, how they appear in results, and how to measure success.<br><br></p>


Google said today that it is suing SerpApi, accusing the company of bypassing security protections to scrape, harvest, and resell copyrighted content from Google Search results.
The allegations: Google said SerpApi:
Circumvented Google’s security measures and industry-standard crawling controls.
Ignored website directives that specify whether content can be accessed.
Used cloaking, rotating bot identities, and large bot networks to scrape content at scale.
Took licensed content from Search features, including images and real-time data, and resold it for profit.
What Google is saying. “Stealthy scrapers like SerpApi override [crawling] directives and give sites no choice at all,” Google wrote, calling the alleged scraping “brazen” and “unlawful.” Google said SerpApi’s activity “increased dramatically over the past year.”
Catch up quick. Google’s lawsuit similar legal action taken by Reddit, which named SerpApi, Perplexity, Oxylabs, and AWMProxy and accused them of scraping Reddit content through Google Search results while hiding their identities to bypass restrictions.
Reddit licenses its data to Google and OpenAI, but alleges others tried to sidestep those deals.
Reddit said it set a “trap” post visible only to Google’s crawler that later appeared in Perplexity results — evidence of scraping, according to the complaint.
SerpApi denied wrongdoing and said it operates lawfully.
What SerpApi has said previously. SerpApi argued that “public search data should be accessible,” framing its work as protected by the First Amendment and warning that lawsuits like Reddit’s threaten the “free and open web.”
Why we care. If Google wins, reliable SERP data could become harder to get, more expensive, or both — especially for teams that rely on tools powered by services like SerpApi. As AI already reduces clicks and transparency, Google now appears intent on making it even harder for brands to understand how Search works, how they appear in results, and how to measure success.

Google accused SerpApi of 'circumventing security measures protecting others’ copyrighted content that appears in Google search results.'

Google sues SerpApi over scraping and reselling Search data

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Duplicate or similar content on your site makes it hard for AI search engines to interpret your intent signals. 

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/blue-bing-writing-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Duplicate content can hurt your visibility in AI Search. Fabrice Canel and Krishna Madhavan from Microsoft <a href="https://blogs.bing.com/webmaster/December-2025/Does-Duplicate-Content-Hurt-SEO-and-AI-Search-Visibility" target="_blank" rel="noopener">explained</a> that when content is duplicated, AI systems struggle to interpret signals, which reduces &#8220;the likelihood that the correct version will be selected or summarized.&#8221;.</p>



<p>This mirrors how duplicate or near-duplicate content affects traditional search rankings. AI Search on Bing and Google relies on the same underlying signals, so duplication can blur intent and create confusion about which version matters most.</p>



<p><strong>The issue with duplicate content and AI Search. </strong>Here are some bullet points from the Bing blog post on why duplicate or very similar content can cause issues with that content showing in AI Search:</p>



<ul class="wp-block-list">
<li>AI search builds on the same signals that support traditional SEO,&nbsp;but adds additional layers,&nbsp;especially&nbsp;in&nbsp;satisfying&nbsp;intent.</li>



<li>When several pages repeat the same information, those intent signals become harder for AI systems to interpret, reducing the likelihood that the correct version will be selected or summarized.</li>



<li>When multiple pages cover the same topic with similar wording, structure, and metadata, AI systems cannot easily&nbsp;determine&nbsp;which version&nbsp;aligns best with the user’s intent. This reduces the chances that your preferred page will be chosen as a grounding source.</li>



<li>LLMs group near-duplicate URLs into a single cluster and then choose one page to&nbsp;represent&nbsp;the set. If the differences between pages are minimal, the model may select a version that is outdated or not the one you intended to highlight.&nbsp;</li>



<li>Campaign pages, audience segments, and localized versions can satisfy different intents, but only if those differences are meaningful. When variations reuse the same content, models have fewer signals to match each page with a unique&nbsp;user&nbsp;need.&nbsp;</li>



<li>AI systems favor fresh, up-to-date content, but duplicates can slow how quickly changes are reflected. When crawlers revisit duplicate or low-value URLs instead of&nbsp;updated&nbsp;pages,&nbsp;new information&nbsp;may take longer to reach the systems that support AI summaries and comparisons. Clearer intent strengthens AI visibility by helping models understand which version to trust and surface.&nbsp;</li>
</ul>



<p><strong>Syndicated content. </strong>Many people don’t realize that syndicated content — content you publish on your site and allow others to republish — can also create problems. Syndicated content counts as duplicate content, at least by Microsoft’s definition.</p>



<ul class="wp-block-list">
<li>&#8220;When your articles are republished on other sites, identical copies can exist across domains, making it harder for search engines and AI systems to identify the original source,&#8221; Microsoft wrote.</li>
</ul>



<p><strong>How do you reduce duplicate content? </strong>When it comes to syndicated content, you can try to ask the syndication partner to:</p>



<ul class="wp-block-list">
<li>Add a canonical tag from what they published on their site, to the original version on your site</li>



<li>You can ask them to rework the content, so it is not too similar </li>



<li>You can ask them to noindex the content, so search engines don&#8217;t see it</li>
</ul>



<p><strong>Campaign pages. </strong>Microsoft also said that &#8220;Campaign pages can become duplicate content when multiple versions target the same intent and differ only by minor changes, such as headlines, imagery, or audience messaging.&#8221;  So you want to make sure to be very careful about your internal site&#8217;s page organization and URL structure.</p>



<ul class="wp-block-list">
<li>Select one primary campaign page to collect links and engagement.&nbsp;</li>



<li>Use canonical&nbsp;tags on variations that&nbsp;do not&nbsp;represent&nbsp;a distinct search intent</li>



<li>Only keep separate pages when intent clearly changes, such as seasonal offers, localized pricing, or comparison-focused content.&nbsp;</li>



<li>Consolidate&nbsp;or&nbsp;301&nbsp;redirect older or redundant campaign pages&nbsp;that no longer serve a unique purpose.&nbsp;</li>
</ul>



<p><strong>Localization pages. </strong>Yes, localization can also create duplicate content. If many pages say the same thing and only swap the city or location, they’re too similar and can cause issues.</p>



<ul class="wp-block-list">
<li>&#8220;Localization creates duplicate content when regional or language pages are nearly identical and do not provide meaningful differences for users in each market,&#8221; Microsoft wrote.</li>
</ul>



<p>To fix it, Microsoft suggests:</p>



<ul class="wp-block-list">
<li>Localize with meaningful changes such as terminology, examples, regulations, or product details.&nbsp;</li>



<li>Avoid creating multiple pages in the same language that serve the same purpose.&nbsp;</li>



<li>Use&nbsp;hreflang&nbsp;to define&nbsp;language and regional&nbsp;targeting</li>
</ul>



<p><strong>Other technical SEO issues. </strong>Technical issues can also create duplicate content. A single page can end up with multiple URLs, which splits signals. Search engines can often sort this out, but you shouldn’t rely on them.</p>



<p>Take control by making sure each piece of content has a clear URL. Common causes include URL parameters, HTTP vs. HTTPS versions, uppercase and lowercase URLs, trailing slashes, printer-friendly pages, staging or test sites, and similar variations.</p>



<p>To fix this, Microsoft suggests:</p>



<ul class="wp-block-list">
<li>Use 301 redirects to&nbsp;consolidate&nbsp;variants into a single preferred URL.&nbsp;</li>



<li>Apply&nbsp;canonical&nbsp;tags when multiple versions must remain accessible.&nbsp;</li>



<li>Enforce consistent URL structures across the site.&nbsp;</li>



<li>Prevent staging or archive URLs from being crawled or indexed.&nbsp;</li>
</ul>



<p><strong>Why we care. </strong>Duplicate content in SEO is not a new topic and it will carry over from traditional search to AI search.  Many of you have a lot of experience dealing with duplicate or nearly identical content and how that negatively impacts indexing and ranking.</p>



<p></p>


Duplicate content can hurt your visibility in AI Search. Fabrice Canel and Krishna Madhavan from Microsoft explained that when content is duplicated, AI systems struggle to interpret signals, which reduces “the likelihood that the correct version will be selected or summarized.”.
This mirrors how duplicate or near-duplicate content affects traditional search rankings. AI Search on Bing and Google relies on the same underlying signals, so duplication can blur intent and create confusion about which version matters most.
The issue with duplicate content and AI Search. Here are some bullet points from the Bing blog post on why duplicate or very similar content can cause issues with that content showing in AI Search:
AI search builds on the same signals that support traditional SEO, but adds additional layers, especially in satisfying intent.
When several pages repeat the same information, those intent signals become harder for AI systems to interpret, reducing the likelihood that the correct version will be selected or summarized.
When multiple pages cover the same topic with similar wording, structure, and metadata, AI systems cannot easily determine which version aligns best with the user’s intent. This reduces the chances that your preferred page will be chosen as a grounding source.
LLMs group near-duplicate URLs into a single cluster and then choose one page to represent the set. If the differences between pages are minimal, the model may select a version that is outdated or not the one you intended to highlight. 
Campaign pages, audience segments, and localized versions can satisfy different intents, but only if those differences are meaningful. When variations reuse the same content, models have fewer signals to match each page with a unique user need. 
AI systems favor fresh, up-to-date content, but duplicates can slow how quickly changes are reflected. When crawlers revisit duplicate or low-value URLs instead of updated pages, new information may take longer to reach the systems that support AI summaries and comparisons. Clearer intent strengthens AI visibility by helping models understand which version to trust and surface. 
Syndicated content. Many people don’t realize that syndicated content — content you publish on your site and allow others to republish — can also create problems. Syndicated content counts as duplicate content, at least by Microsoft’s definition.
“When your articles are republished on other sites, identical copies can exist across domains, making it harder for search engines and AI systems to identify the original source,” Microsoft wrote.
How do you reduce duplicate content? When it comes to syndicated content, you can try to ask the syndication partner to:
Add a canonical tag from what they published on their site, to the original version on your site
You can ask them to rework the content, so it is not too similar 
You can ask them to noindex the content, so search engines don’t see it
Campaign pages. Microsoft also said that “Campaign pages can become duplicate content when multiple versions target the same intent and differ only by minor changes, such as headlines, imagery, or audience messaging.”  So you want to make sure to be very careful about your internal site’s page organization and URL structure.
Select one primary campaign page to collect links and engagement. 
Use canonical tags on variations that do not represent a distinct search intent
Only keep separate pages when intent clearly changes, such as seasonal offers, localized pricing, or comparison-focused content. 
Consolidate or 301 redirect older or redundant campaign pages that no longer serve a unique purpose. 
Localization pages. Yes, localization can also create duplicate content. If many pages say the same thing and only swap the city or location, they’re too similar and can cause issues.
“Localization creates duplicate content when regional or language pages are nearly identical and do not provide meaningful differences for users in each market,” Microsoft wrote.
To fix it, Microsoft suggests:
Localize with meaningful changes such as terminology, examples, regulations, or product details. 
Avoid creating multiple pages in the same language that serve the same purpose. 
Use hreflang to define language and regional targeting
Other technical SEO issues. Technical issues can also create duplicate content. A single page can end up with multiple URLs, which splits signals. Search engines can often sort this out, but you shouldn’t rely on them.
Take control by making sure each piece of content has a clear URL. Common causes include URL parameters, HTTP vs. HTTPS versions, uppercase and lowercase URLs, trailing slashes, printer-friendly pages, staging or test sites, and similar variations.
To fix this, Microsoft suggests:
Use 301 redirects to consolidate variants into a single preferred URL. 
Apply canonical tags when multiple versions must remain accessible. 
Enforce consistent URL structures across the site. 
Prevent staging or archive URLs from being crawled or indexed. 
Why we care. Duplicate content in SEO is not a new topic and it will carry over from traditional search to AI search.  Many of you have a lot of experience dealing with duplicate or nearly identical content and how that negatively impacts indexing and ranking.

Duplicate or similar content on your site makes it hard for AI search engines to interpret your intent signals.

Microsoft Bing explains how duplicate content hurts AI search visibility

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents.jpg" class="attachment-large size-large wp-post-image" alt="Your next customer might not be human: Designing journeys for people and AI agents" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI agents increasingly filter options and shape shortlists before people ever engage, shifting where visibility and influence are earned.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents.jpg" class="attachment-large size-large wp-post-image" alt="Your next customer might not be human: Designing journeys for people and AI agents" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/Your-next-customer-might-not-be-human-Designing-journeys-for-people-and-AI-agents-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>For the past decade, customer journey design has assumed one thing: the customer is human.&nbsp;</p>



<p>A real person. Messy. Emotional. Overloaded.&nbsp;</p>



<p>Someone who needs clarity, reassurance, and a sense of progress to keep moving forward.</p>



<p>But in 2026, that assumption no longer holds.</p>



<p>AI agents are starting to influence how people search, compare, choose, and buy.&nbsp;</p>



<p>They filter results, generate shortlists, book services, and soon may even negotiate on our behalf.</p>



<p>While much of AI usage is still task-based, it marks a critical shift.&nbsp;</p>



<p>Once AI becomes part of how information is gathered, filtered, and prioritized, it begins to shape the decisions that follow.</p>



<p>That means the customer journey is no longer a single track. It is now a dual journey, one for the person and one for the agent.</p>



<p>This article does not promise all the answers. The landscape is changing fast.&nbsp;</p>



<p>What it can do is explore why this shift matters, what dual journeys look like, and how marketers can start designing for both.</p>



<h2 class="wp-block-heading" id="h-the-customer-is-no-longer-the-only-decision-maker">The customer is no longer the only decision-maker</h2>



<p>When an AI agent filters 200 options down to just three, your customer is only seeing the surface of that decision.&nbsp;</p>



<p>Visibility is being won or lost long before the person is even aware of it.</p>



<p>Agents are not just another channel. They are becoming gatekeepers in the decision-making process.&nbsp;</p>



<p>That means your journey now has two layers:</p>



<ul class="wp-block-list">
<li>The human journey.</li>



<li>The agent journey.</li>
</ul>



<p>They overlap, but they work in very different ways.</p>



<h2 class="wp-block-heading" id="h-humans-and-agents-decide-in-fundamentally-different-ways">Humans and agents decide in fundamentally different ways</h2>



<p>The human journey is emotional and unpredictable.&nbsp;</p>



<p>We get distracted. We procrastinate.&nbsp;</p>



<p>We need reassurance. We are influenced by how something feels, not just what it says.</p>



<p>Agents are different. They don&#8217;t:</p>



<ul class="wp-block-list">
<li>Get distracted.</li>



<li>Need clarity or persuasion.</li>



<li>Feel risk. They evaluate it.</li>



<li>Get overwhelmed. They operate on logic, rules, and data.</li>
</ul>



<p>This means the same piece of content could succeed with one and fail with the other.&nbsp;</p>



<p>A person might skim your copy and feel like it “just gets them,” while an agent scans your entire site, finds a key attribute missing, and removes you from the shortlist.</p>



<p>When you treat these two journeys as one, you risk missing both.</p>



<h2 class="wp-block-heading" id="h-it-s-time-to-map-two-paths">It’s time to map two paths</h2>



<p><strong>The human journey:</strong> You know this one. It includes:</p>



<ul class="wp-block-list">
<li>Emotional drivers.</li>



<li>Trust signals.</li>



<li>Clarity and reassurance.</li>



<li>Cognitive load management.</li>



<li>Social proof.</li>



<li>Personal preferences and brand affinity.</li>
</ul>



<p>This is the part of the journey that reflects how humans think, feel, and decide.</p>



<p><strong>The agent journey: </strong>This is newer territory, and it requires a different playbook:</p>



<ul class="wp-block-list">
<li>Structured, machine-readable data.</li>



<li>Consistent schema and clean attributes.</li>



<li>Up-to-date information and availability.</li>



<li>Clear logic and authority signals.</li>
</ul>



<p>Agents are not reading your copy. They are parsing your data.&nbsp;</p>



<p>If that data is not structured well, you may be invisible, no matter how compelling your brand story is.</p>



<h2 class="wp-block-heading" id="h-agents-are-not-necessarily-doing-the-whole-journey-yet">Agents are not necessarily doing the whole journey yet</h2>



<p>One of the biggest unknowns right now is how much of the journey an agent will actually take on. That will depend heavily on human trust.</p>



<p>In the short term, agents are more likely to be used for filtering, refining, and shortlisting, not making the final call.&nbsp;</p>



<p>A person might say, “Find me the best two options with free delivery,” or, “I need something that can arrive tomorrow without paying extra.”&nbsp;</p>



<p>The agent’s role is to surface the right recommendations, not make the decision.</p>



<p>That means the data the agent sees and passes back is what the human will be judging.&nbsp;</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"/>



<p>If your content does not clearly show that free delivery is available, or that next-day shipping applies above a certain spend, you may miss out.&nbsp;</p>



<p>Even if the human were happy with your offer, they would never hear about it if the agent could not find or interpret that information.</p>



<p>This is why marketers need to design for different lengths of agent journeys.&nbsp;</p>



<p>In some cases, agents act as helpers that scan, filter, and report back.&nbsp;</p>



<p>In others, they may go much further.&nbsp;</p>



<p>In both scenarios, agents still need access to the most critical marketing messages.&nbsp;</p>



<p>Even on the cleanest, most structured path, those value points need to be front and center.</p>



<h2 class="wp-block-heading" id="h-why-this-matters-now">Why this matters now</h2>



<p>Most brands are still designing only for people, which creates gaps for agents.</p>



<p>Here are a few scenarios already emerging:</p>



<ul class="wp-block-list">
<li>Agents bypass brands because key data fields are missing.</li>



<li>Pages do not match the structures agents are trained to look for.</li>



<li>Competitors win simply because their data is cleaner and easier to parse.</li>
</ul>



<p>Designing only for agents is also a mistake. People still make the final call in many decisions, and emotion continues to play a major role in building trust.</p>



<p>This is not a trade-off. It is not either-or. It is both-and.</p>



<p>You now have two audiences: the human and the agent acting on their behalf. You need to show up for both.</p>



<h2 class="wp-block-heading" id="h-how-to-start-designing-dual-journeys">How to start designing dual journeys</h2>



<p>There is no perfect playbook yet. But here are six early principles to start experimenting with.</p>



<ul class="wp-block-list">
<li><strong>Make your information work at two levels: </strong>Copy should connect with people. Structure should support agents. One does not replace the other. They work in tandem.</li>



<li><strong>Reduce ambiguity:</strong> People can cope with some gray area. Agents cannot. Be as clear and unambiguous as possible, especially around key product and service data.</li>



<li><strong>Create agent-friendly versions of your propositions:</strong> You do not need separate pages, just separate representations. Think emotion and empathy for humans, logic and validation for agents.</li>



<li><strong>Identify where agents already shape your journey: </strong>From filtering products to estimating costs, agents are already stepping in. Start designing with those moments in mind.</li>



<li><strong>Redefine trust:</strong> People trust stories, tone, and design. Agents trust structured data, freshness, and citation strength. Treat both as equally important.</li>



<li><strong>Test and learn:</strong> No one is getting this exactly right yet. The brands that start testing now will have a meaningful head start when it matters most.</li>
</ul>



<h2 class="wp-block-heading" id="h-what-you-can-practically-do-in-2026">What you can practically do in 2026</h2>



<p>Here is a short list to get moving:</p>



<ul class="wp-block-list">
<li>Audit your site for both readability for people and interpretability for agents.</li>



<li>Map your current journeys and overlay the agent version.</li>



<li>Close data gaps that would prevent an agent from recommending you.</li>



<li>Make sure key attributes are structured and complete.</li>



<li>Include critical value propositions in structured formats, such as delivery rules, price thresholds, availability, and authority signals.</li>



<li>Help teams see agents as an audience, not just a technical layer.</li>



<li>Experiment with conversational search to better understand how agents interpret information.</li>
</ul>



<p>This shift may be as significant as mobile, just less visible. Many decisions are now being made before the customer ever reaches you.</p>



<h2 class="wp-block-heading" id="h-the-point-of-convergence-between-people-and-agents">The point of convergence between people and agents</h2>



<p>If you design only for humans, you will lose the agent.</p>



<p>If you design only for agents, you will miss the human.</p>



<p>The real opportunity sits in the middle, designing for both.</p>



<p>This will become a core skill for marketers over the next 12 to 18 months.&nbsp;</p>



<p>No one has all the answers yet, but the direction is clear. Agents are becoming part of the customer journey.</p>



<p>The brands that start designing for that reality now will be the ones that remain visible, chosen, and relevant.</p>

For the past decade, customer journey design has assumed one thing: the customer is human. 
A real person. Messy. Emotional. Overloaded. 
Someone who needs clarity, reassurance, and a sense of progress to keep moving forward.
But in 2026, that assumption no longer holds.
AI agents are starting to influence how people search, compare, choose, and buy. 
They filter results, generate shortlists, book services, and soon may even negotiate on our behalf.
While much of AI usage is still task-based, it marks a critical shift. 
Once AI becomes part of how information is gathered, filtered, and prioritized, it begins to shape the decisions that follow.
That means the customer journey is no longer a single track. It is now a dual journey, one for the person and one for the agent.
This article does not promise all the answers. The landscape is changing fast. 
What it can do is explore why this shift matters, what dual journeys look like, and how marketers can start designing for both.
The customer is no longer the only decision-maker
When an AI agent filters 200 options down to just three, your customer is only seeing the surface of that decision. 
Visibility is being won or lost long before the person is even aware of it.
Agents are not just another channel. They are becoming gatekeepers in the decision-making process. 
That means your journey now has two layers:
The human journey.
The agent journey.
They overlap, but they work in very different ways.
Humans and agents decide in fundamentally different ways
The human journey is emotional and unpredictable. 
We get distracted. We procrastinate. 
We need reassurance. We are influenced by how something feels, not just what it says.
Agents are different. They don’t:
Get distracted.
Need clarity or persuasion.
Feel risk. They evaluate it.
Get overwhelmed. They operate on logic, rules, and data.
This means the same piece of content could succeed with one and fail with the other. 
A person might skim your copy and feel like it “just gets them,” while an agent scans your entire site, finds a key attribute missing, and removes you from the shortlist.
When you treat these two journeys as one, you risk missing both.
It’s time to map two paths
The human journey: You know this one. It includes:
Emotional drivers.
Trust signals.
Clarity and reassurance.
Cognitive load management.
Social proof.
Personal preferences and brand affinity.
This is the part of the journey that reflects how humans think, feel, and decide.
The agent journey: This is newer territory, and it requires a different playbook:
Structured, machine-readable data.
Consistent schema and clean attributes.
Up-to-date information and availability.
Clear logic and authority signals.
Agents are not reading your copy. They are parsing your data. 
If that data is not structured well, you may be invisible, no matter how compelling your brand story is.
Agents are not necessarily doing the whole journey yet
One of the biggest unknowns right now is how much of the journey an agent will actually take on. That will depend heavily on human trust.
In the short term, agents are more likely to be used for filtering, refining, and shortlisting, not making the final call. 
A person might say, “Find me the best two options with free delivery,” or, “I need something that can arrive tomorrow without paying extra.” 
The agent’s role is to surface the right recommendations, not make the decision.
That means the data the agent sees and passes back is what the human will be judging. 
Get the newsletter search marketers rely on.
  
				
								
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See terms.
If your content does not clearly show that free delivery is available, or that next-day shipping applies above a certain spend, you may miss out. 
Even if the human were happy with your offer, they would never hear about it if the agent could not find or interpret that information.
This is why marketers need to design for different lengths of agent journeys. 
In some cases, agents act as helpers that scan, filter, and report back. 
In others, they may go much further. 
In both scenarios, agents still need access to the most critical marketing messages. 
Even on the cleanest, most structured path, those value points need to be front and center.
Why this matters now
Most brands are still designing only for people, which creates gaps for agents.
Here are a few scenarios already emerging:
Agents bypass brands because key data fields are missing.
Pages do not match the structures agents are trained to look for.
Competitors win simply because their data is cleaner and easier to parse.
Designing only for agents is also a mistake. People still make the final call in many decisions, and emotion continues to play a major role in building trust.
This is not a trade-off. It is not either-or. It is both-and.
You now have two audiences: the human and the agent acting on their behalf. You need to show up for both.
How to start designing dual journeys
There is no perfect playbook yet. But here are six early principles to start experimenting with.
Make your information work at two levels: Copy should connect with people. Structure should support agents. One does not replace the other. They work in tandem.
Reduce ambiguity: People can cope with some gray area. Agents cannot. Be as clear and unambiguous as possible, especially around key product and service data.
Create agent-friendly versions of your propositions: You do not need separate pages, just separate representations. Think emotion and empathy for humans, logic and validation for agents.
Identify where agents already shape your journey: From filtering products to estimating costs, agents are already stepping in. Start designing with those moments in mind.
Redefine trust: People trust stories, tone, and design. Agents trust structured data, freshness, and citation strength. Treat both as equally important.
Test and learn: No one is getting this exactly right yet. The brands that start testing now will have a meaningful head start when it matters most.
What you can practically do in 2026
Here is a short list to get moving:
Audit your site for both readability for people and interpretability for agents.
Map your current journeys and overlay the agent version.
Close data gaps that would prevent an agent from recommending you.
Make sure key attributes are structured and complete.
Include critical value propositions in structured formats, such as delivery rules, price thresholds, availability, and authority signals.
Help teams see agents as an audience, not just a technical layer.
Experiment with conversational search to better understand how agents interpret information.
This shift may be as significant as mobile, just less visible. Many decisions are now being made before the customer ever reaches you.
The point of convergence between people and agents
If you design only for humans, you will lose the agent.
If you design only for agents, you will miss the human.
The real opportunity sits in the middle, designing for both.
This will become a core skill for marketers over the next 12 to 18 months. 
No one has all the answers yet, but the direction is clear. Agents are becoming part of the customer journey.
The brands that start designing for that reality now will be the ones that remain visible, chosen, and relevant.

AI agents increasingly filter options and shape shortlists before people ever engage, shifting where visibility and influence are earned.

Your next customer might not be human: Designing journeys for people and AI agents

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world.jpg" class="attachment-large size-large wp-post-image" alt="How to use broad match without losing control in a Smart Bidding world" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Broad match now runs with Smart Bidding. Learn how drift happens, why it matters, and how to keep performance aligned with real intent.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world.jpg" class="attachment-large size-large wp-post-image" alt="How to use broad match without losing control in a Smart Bidding world" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/How-to-use-broad-match-without-losing-control-in-a-Smart-Bidding-world-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p><a href="https://searchengineland.com/broad-match-keywords-test-avoid-445116">Broad match</a> used to mean “more reach, less relevance.”</p>



<p>Now it means more reach, with a machine learning layer deciding what relevance looks like.</p>



<p>Google has been steadily steering advertisers toward fewer moving parts – fewer match types, fewer manual levers, and more automation.&nbsp;</p>



<p>Making broad match the <a href="https://searchengineland.com/google-ads-broad-match-default-new-search-campaigns-444003?utm_source=chatgpt.com">default for new Search campaigns</a> in July 2024 was the clearest signal yet that this is the direction of travel.</p>



<p>If you still think of broad match as “the loosest match type,” you will manage it like it is 2016.&nbsp;</p>



<p>That is where the pain comes from: CPC inflation, irrelevant search terms, and leads that look fine in Google Ads but do not survive contact with sales.</p>



<p>Today’s broad match is designed to work as part of a system, including query matching, <a href="https://searchengineland.com/your-guide-to-google-ads-smart-bidding-453765">Smart Bidding</a>, and conversion signals, with optional guardrails such as audiences, negatives, and brand controls. </p>



<p>Google positions broad match as a growth lever for Smart Bidding campaigns, not a standalone reach tactic.</p>



<p>This article breaks down what changed, why Google wants you using it, and how to run it safely without giving up standards.</p>



<h2 class="wp-block-heading" id="h-the-real-risk-with-broad-match-isn-t-relevance-it-s-direction">The real risk with broad match isn’t relevance, it’s direction</h2>



<p>Broad match rarely fails all at once. Instead, it drifts.</p>



<p>If your optimization goal is shallow, broad match combined with Smart Bidding will find the fastest way to hit it at scale. That can mean:</p>



<ul class="wp-block-list">
<li>Informational queries that trigger cheap form fills.</li>



<li>Users who convert easily but never buy.</li>



<li>Lead types that make CPA look great and pipeline look weak.</li>
</ul>



<p>Nothing is technically “wrong” in the interface. Spend is efficient. Conversions are happening.</p>



<p>But the account is optimizing away from commercial intent.</p>



<p>That is why the conversation about broad match has to start with how it actually behaves today.</p>



<h2 class="wp-block-heading" id="h-what-broad-match-actually-is-now">What broad match actually is now</h2>



<p>Broad match no longer operates as a standalone keyword setting.&nbsp;</p>



<p>It functions as part of a larger optimization system.</p>



<h3 class="wp-block-heading" id="h-it-s-built-to-work-with-smart-bidding">It’s built to work with Smart Bidding</h3>



<p>Google is explicit that <a href="https://support.google.com/google-ads/answer/7478529">broad match is intended to run alongside Smart Bidding</a>, because <a href="https://support.google.com/google-ads/answer/6294203">bidding decisions now happen at auction time</a> using signals like:</p>



<ul class="wp-block-list">
<li>Device.</li>



<li>Location.</li>



<li>Time of day.</li>



<li>Query context.</li>



<li>User behavior</li>
</ul>



<p>Broad match expands the pool of eligible queries. Smart Bidding decides which of those queries are worth paying for and how much.</p>



<p>Running broad match without Smart Bidding is no longer how the product is designed to work.</p>



<h3 class="wp-block-heading" id="h-google-has-materially-improved-broad-match-matching">Google has materially improved broad match matching</h3>



<p>In its 2024 updates, Google said AI improvements to quality, relevance, and language understanding led to a <a href="https://support.google.com/google-ads/answer/15616606" target="_blank" rel="noopener">10% performance uplift</a> for broad match campaigns using Smart Bidding.</p>



<p>That does not mean broad match is safe by default.&nbsp;</p>



<p>It means Google believes the matching layer is now strong enough to justify wider adoption.</p>



<h3 class="wp-block-heading" id="h-it-s-no-longer-positioned-as-optional">It’s no longer positioned as optional</h3>



<p>From July 2024, new Search campaigns launch with <a href="https://searchengineland.com/google-ads-broad-match-default-search-campaigns-444653">broad match enabled by default</a>.</p>



<p>There is also a <a href="https://support.google.com/google-ads/answer/14126367" target="_blank" rel="noopener">campaign-level setting</a> that enforces broad match usage and is available only when conversion-based Smart Bidding is active.</p>



<p>This is not a quiet test. It is a directional shift.</p>



<h2 class="wp-block-heading" id="h-why-google-wants-advertisers-to-adopt-broad-match">Why Google wants advertisers to adopt broad match</h2>



<p>Google’s reasoning is consistent across documentation and announcements:</p>



<ul class="wp-block-list">
<li>Search behavior is increasingly long-tail and unpredictable.</li>



<li>Manual keyword lists cannot keep up with language and intent shifts.</li>



<li>Machine learning can interpret intent at auction time more effectively than rigid match logic.</li>
</ul>



<p>Google frames broad match as a growth lever for Smart Bidding campaigns, <a href="https://support.google.com/google-ads/answer/13882874" target="_blank" rel="noopener">giving algorithms access to more auctions</a> and then optimizing toward conversion goals.</p>



<p>You do not have to agree with the philosophy. But if you are advertising on Google Search, you are operating inside it.</p>



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<h2 class="wp-block-heading" id="h-a-framework-for-using-broad-match-without-losing-control">A framework for using broad match without losing control</h2>



<p>Broad match increases surface area. Control comes from the constraints you apply beneath it.</p>



<h3 class="wp-block-heading" id="h-conversion-goals-that-reflect-quality-not-convenience">Conversion goals that reflect quality, not convenience</h3>



<p>Smart Bidding optimizes exactly to <a href="https://support.google.com/google-ads/answer/6294203" target="_blank" rel="noopener">the conversion actions and values you define</a>.</p>



<p>If your primary conversion is low intent, broad match will scale low intent.</p>



<p>Safer setups usually include:</p>



<ul class="wp-block-list">
<li>Optimizing for deeper-funnel actions where possible.</li>



<li>Using conversion values to differentiate lead quality tiers.</li>



<li>Importing offline conversions, such as qualified leads or revenue.</li>
</ul>



<p>This prevents the system from learning that cheap volume equals success.</p>



<h3 class="wp-block-heading" id="h-intent-filters-through-audience-signals">Intent filters through audience signals</h3>



<p>Broad match decides which queries to match. Audience signals influence who sees the ad when those queries occur.</p>



<p>Use audiences to add context, not just for reporting:</p>



<ul class="wp-block-list">
<li>Customer lists to bias optimization toward known buyers.</li>



<li>Remarketing lists for controlled expansion.</li>



<li>Audience insights to identify which segments correlate with quality.</li>
</ul>



<p>Even in observation mode, these signals help diagnose whether broad match growth is happening in the right places.</p>



<h3 class="wp-block-heading" id="h-negative-keyword-structures-that-scale">Negative keyword structures that scale</h3>



<p>With broad match, <a href="https://searchengineland.com/negative-keywords-paid-search-strategies-438960">negative keywords</a> stop being clean-up and start being infrastructure.</p>



<p>Effective accounts usually have:</p>



<ul class="wp-block-list">
<li>Account-level shared negative lists, such as jobs, free, definition, training, and template terms.</li>



<li>Campaign-level exclusions tied to intent boundaries.</li>



<li>A consistent cadence for search terms reviews, especially early on.</li>
</ul>



<p>Broad match explores by design. Negatives define where exploration stops.</p>



<h3 class="wp-block-heading" id="h-brand-controls-to-protect-intent">Brand controls to protect intent</h3>



<p>Google has introduced brand controls that can materially reduce unwanted broad match behavior.</p>



<p>You can apply:&nbsp;</p>



<ul class="wp-block-list">
<li><a href="https://support.google.com/google-ads/answer/14126038">Brand inclusions</a>, which restrict matching so ads show only when specified brands appear in the query.</li>



<li>And <a href="https://support.google.com/google-ads/answer/12195147">brand exclusions</a>, which prevent ads from showing on queries that include certain brand names,</li>
</ul>



<p>These controls are especially useful when broad match starts bleeding into competitor brand intent or misaligned brand searches.</p>



<h2 class="wp-block-heading" id="h-how-broad-match-succeeds-and-where-it-breaks">How broad match succeeds – and where it breaks</h2>



<p>A low-risk rollout usually looks like this:</p>



<ul class="wp-block-list">
<li>Choose one campaign with reliable tracking and sufficient conversion volume.</li>



<li>Use Smart Bidding aligned to meaningful outcomes.</li>



<li>Launch with shared negatives already in place.</li>



<li>Review search terms frequently in the first month.</li>



<li>Validate lead quality outside Google Ads before scaling.</li>
</ul>



<p>Broad match can work.&nbsp;</p>



<p>Google’s improvements are real, and the default shift reflects confidence in the system. But it is not a shortcut.</p>



<p>When broad match fails, it is usually because of one of three avoidable mistakes:</p>



<ul class="wp-block-list">
<li><strong>Optimizing to the wrong conversion: </strong>The algorithm will do exactly what you asked.</li>



<li><strong>No negative keyword system: </strong>Exploration without boundaries always turns expensive.</li>



<li><strong>Judging success using platform metrics alone: </strong>CPC and CPA can improve while revenue quality declines.</li>
</ul>



<h2 class="wp-block-heading" id="h-broad-match-is-a-system-not-a-setting">Broad match is a system, not a setting</h2>



<p>Broad match is becoming the default because Google wants Search to run on systems, not keyword spreadsheets.</p>



<p>That does not mean control disappears. It just moves.</p>



<p>Broad match rewards accounts that:</p>



<ul class="wp-block-list">
<li>Define quality clearly.</li>



<li>Constrain intent deliberately.</li>



<li>Measure success beyond the interface.</li>
</ul>



<p>Used properly, it can unlock incremental demand.</p>



<p>Used casually, it will optimize you into a corner.</p>

Broad match used to mean “more reach, less relevance.”
Now it means more reach, with a machine learning layer deciding what relevance looks like.
Google has been steadily steering advertisers toward fewer moving parts – fewer match types, fewer manual levers, and more automation. 
Making broad match the default for new Search campaigns in July 2024 was the clearest signal yet that this is the direction of travel.
If you still think of broad match as “the loosest match type,” you will manage it like it is 2016. 
That is where the pain comes from: CPC inflation, irrelevant search terms, and leads that look fine in Google Ads but do not survive contact with sales.
Today’s broad match is designed to work as part of a system, including query matching, Smart Bidding, and conversion signals, with optional guardrails such as audiences, negatives, and brand controls. 
Google positions broad match as a growth lever for Smart Bidding campaigns, not a standalone reach tactic.
This article breaks down what changed, why Google wants you using it, and how to run it safely without giving up standards.
The real risk with broad match isn’t relevance, it’s direction
Broad match rarely fails all at once. Instead, it drifts.
If your optimization goal is shallow, broad match combined with Smart Bidding will find the fastest way to hit it at scale. That can mean:
Informational queries that trigger cheap form fills.
Users who convert easily but never buy.
Lead types that make CPA look great and pipeline look weak.
Nothing is technically “wrong” in the interface. Spend is efficient. Conversions are happening.
But the account is optimizing away from commercial intent.
That is why the conversation about broad match has to start with how it actually behaves today.
What broad match actually is now
Broad match no longer operates as a standalone keyword setting. 
It functions as part of a larger optimization system.
It’s built to work with Smart Bidding
Google is explicit that broad match is intended to run alongside Smart Bidding, because bidding decisions now happen at auction time using signals like:
Device.
Location.
Time of day.
Query context.
User behavior
Broad match expands the pool of eligible queries. Smart Bidding decides which of those queries are worth paying for and how much.
Running broad match without Smart Bidding is no longer how the product is designed to work.
Google has materially improved broad match matching
In its 2024 updates, Google said AI improvements to quality, relevance, and language understanding led to a 10% performance uplift for broad match campaigns using Smart Bidding.
That does not mean broad match is safe by default. 
It means Google believes the matching layer is now strong enough to justify wider adoption.
It’s no longer positioned as optional
From July 2024, new Search campaigns launch with broad match enabled by default.
There is also a campaign-level setting that enforces broad match usage and is available only when conversion-based Smart Bidding is active.
This is not a quiet test. It is a directional shift.
Why Google wants advertisers to adopt broad match
Google’s reasoning is consistent across documentation and announcements:
Search behavior is increasingly long-tail and unpredictable.
Manual keyword lists cannot keep up with language and intent shifts.
Machine learning can interpret intent at auction time more effectively than rigid match logic.
Google frames broad match as a growth lever for Smart Bidding campaigns, giving algorithms access to more auctions and then optimizing toward conversion goals.
You do not have to agree with the philosophy. But if you are advertising on Google Search, you are operating inside it.
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See terms.
A framework for using broad match without losing control
Broad match increases surface area. Control comes from the constraints you apply beneath it.
Conversion goals that reflect quality, not convenience
Smart Bidding optimizes exactly to the conversion actions and values you define.
If your primary conversion is low intent, broad match will scale low intent.
Safer setups usually include:
Optimizing for deeper-funnel actions where possible.
Using conversion values to differentiate lead quality tiers.
Importing offline conversions, such as qualified leads or revenue.
This prevents the system from learning that cheap volume equals success.
Intent filters through audience signals
Broad match decides which queries to match. Audience signals influence who sees the ad when those queries occur.
Use audiences to add context, not just for reporting:
Customer lists to bias optimization toward known buyers.
Remarketing lists for controlled expansion.
Audience insights to identify which segments correlate with quality.
Even in observation mode, these signals help diagnose whether broad match growth is happening in the right places.
Negative keyword structures that scale
With broad match, negative keywords stop being clean-up and start being infrastructure.
Effective accounts usually have:
Account-level shared negative lists, such as jobs, free, definition, training, and template terms.
Campaign-level exclusions tied to intent boundaries.
A consistent cadence for search terms reviews, especially early on.
Broad match explores by design. Negatives define where exploration stops.
Brand controls to protect intent
Google has introduced brand controls that can materially reduce unwanted broad match behavior.
You can apply: 
Brand inclusions, which restrict matching so ads show only when specified brands appear in the query.
And brand exclusions, which prevent ads from showing on queries that include certain brand names,
These controls are especially useful when broad match starts bleeding into competitor brand intent or misaligned brand searches.
How broad match succeeds – and where it breaks
A low-risk rollout usually looks like this:
Choose one campaign with reliable tracking and sufficient conversion volume.
Use Smart Bidding aligned to meaningful outcomes.
Launch with shared negatives already in place.
Review search terms frequently in the first month.
Validate lead quality outside Google Ads before scaling.
Broad match can work. 
Google’s improvements are real, and the default shift reflects confidence in the system. But it is not a shortcut.
When broad match fails, it is usually because of one of three avoidable mistakes:
Optimizing to the wrong conversion: The algorithm will do exactly what you asked.
No negative keyword system: Exploration without boundaries always turns expensive.
Judging success using platform metrics alone: CPC and CPA can improve while revenue quality declines.
Broad match is a system, not a setting
Broad match is becoming the default because Google wants Search to run on systems, not keyword spreadsheets.
That does not mean control disappears. It just moves.
Broad match rewards accounts that:
Define quality clearly.
Constrain intent deliberately.
Measure success beyond the interface.
Used properly, it can unlock incremental demand.
Used casually, it will optimize you into a corner.

Broad match now runs with Smart Bidding. Learn how drift happens, why it matters, and how to keep performance aligned with real intent.

How to use broad match without losing control

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights.jpg" class="attachment-large size-large wp-post-image" alt="Google vs. publishers: What the EU probe means for SEO, AI answers, and content rights" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>An antitrust case puts AI Overviews, opt-outs, and zero-click visibility under scrutiny amid growing debate over content use and attribution.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights.jpg" class="attachment-large size-large wp-post-image" alt="Google vs. publishers: What the EU probe means for SEO, AI answers, and content rights" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/12/Google-vs.-publishers-What-the-EU-probe-means-for-SEO-AI-answers-and-content-rights-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>In one of the most consequential regulatory moves yet for the future of search, the European Commission has <a href="https://searchengineland.com/google-faces-eu-antitrust-complaint-over-ai-overviews-458123">launched a formal antitrust investigation</a> into Google.&nbsp;</p>



<p>At the center of the complaint is Google’s use of publisher content to train and power <a href="https://searchengineland.com/google-ai-overviews-everything-you-need-to-know-449399">AI Overviews</a> and other generative AI features – while potentially diverting traffic away from original sources.</p>



<p>For anyone working in <a href="https://searchengineland.com/guide/what-is-seo">SEO</a>, content strategy, or brand visibility, the implications are immediate.&nbsp;</p>



<p>Is Google crossing a line by repurposing publisher content for AI-generated answers, or is this simply the cost of participating in an open, crawlable web?</p>



<p>With regulators now stepping in, the industry is being compelled to reassess how machine-readable content is used, managed, and valued – and what it may cost brands, publishers, and agencies if regulation fails to keep pace with innovation.</p>



<p>Here’s what’s happening, why it matters, and how the industry is already responding.</p>



<h2 class="wp-block-heading" id="h-what-s-actually-happening-core-allegations-in-the-complaint">What’s actually happening: Core allegations in the complaint</h2>



<p>This EU move comes amid a growing wave of lawsuits and policy disputes over AI training data, from high-profile publisher cases against OpenAI and others to <a href="https://searchengineland.com/penske-media-sues-google-ai-overviews-461997">Penske Media’s recent antitrust suit</a> targeting Google’s AI products.&nbsp;</p>



<p>Publishers increasingly describe Google’s approach as a forced choice: accept unlicensed use of their content for AI training and answers, or risk losing critical search traffic.</p>



<p>At the same time, technical controls such as <a href="https://searchengineland.com/robots-txt-seo-453779">robots.txt </a>directives, <a href="https://searchengineland.com/google-updates-crawlers-and-user-triggered-fetchers-documentation-446594">Google-Extended</a>, and emerging noai and nopreview meta conventions reflect an industry trying to regain control over a web that was never designed for large language model training.&nbsp;</p>



<p>The core dispute is whether AI training and answer generation are extensions of traditional indexing and snippet creation, or a distinct use that requires licensing, attribution, or both.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/robots-exclusions-new-rules-definitions-ietf-464990">New web standards could redefine how AI models use your content</a></em></strong></p>



<h3 class="wp-block-heading" id="h-what-does-the-complaint-target">What does the complaint target</h3>



<p>With publishers reporting traffic drops of 20–50% on informational queries, the complaint – led by a coalition of European news and specialist publishers – targets three practices:</p>



<ul class="wp-block-list">
<li>Google’s scraping of publisher content to train and ground models such as Gemini for AI Overviews and AI Mode.</li>



<li>A lack of meaningful opt-out options that preserve search visibility.</li>



<li>AI summaries that capture user attention above organic links, reducing clicks to original publishers.</li>
</ul>



<p>Regulators are being asked to examine three core questions:</p>



<ul class="wp-block-list">
<li>How Google trains and grounds its models on publisher content.</li>



<li>Whether publishers have meaningful ways to opt out without sacrificing search visibility.</li>



<li>Whether AI Overviews reinforce Google’s dominance by keeping users inside Google’s own interface.</li>
</ul>



<h2 class="wp-block-heading" id="h-zero-click-search-evolution-is-the-market-ready">Zero-click search evolution: Is the market ready?</h2>



<p>For the SEO community, this probe marks what may be the start of the post-click era, where the battle for visibility shifts from the SERP to the LLM context window.&nbsp;</p>



<p>The open question is whether Google is ready for that shift.</p>



<p>The zero-click search experience is often discussed, but for it to work for all parties, three conditions need to be met:</p>



<ul class="wp-block-list">
<li>Users must be able to get what they need within the SERP, AI Overviews, or <a href="https://searchengineland.com/guides/google-ai-mode">AI Mode</a>.</li>



<li>Google must seamlessly blend content types – text, images, video, products, services, and even checkout – into a coherent, useful experience.</li>



<li>Publishers must be fairly compensated for participating in this ecosystem.</li>
</ul>



<p>At present, Google appears eager to move toward a fully zero-click experience, but is not yet able to support it end to end:</p>



<ul class="wp-block-list">
<li>Users still encounter hallucinated or outdated answers.</li>



<li>Assistive chats remain fragmented and cannot support full discovery or purchase flows.</li>



<li>Publishers remain unclear about how, or whether, they are compensated when their content is quoted.</li>
</ul>



<h2 class="wp-block-heading" id="h-what-is-the-opt-out-version-and-how-effective-is-it">What is the opt-out version, and how effective is it?</h2>



<p>In its defense around content repurposing, Google points to opt-out mechanisms such as Google-Extended in robots.txt.&nbsp;</p>



<p>While Google-Extended can block Gemini training, it does not prevent AI-generated answers from fetching live data from publishers’ websites.</p>



<p>In practice, blocking LLM training has several limitations:</p>



<ul class="wp-block-list">
<li>It does not prevent content from appearing in AI Overviews. If Google has indexed a page, it can still summarize or rephrase that content in AI answers, even when Google-Extended is blocked.</li>



<li>It is opt-out, not opt-in. Content is used by default, and publishers must be aware of Google-Extended and actively implement it to stop training.</li>



<li>It does not provide granular control. Publishers cannot allow traditional snippets while blocking LLM training, or vice versa.</li>
</ul>



<h3 class="wp-block-heading" id="h-why-opting-out-may-be-a-bad-idea">Why opting out may be a bad idea</h3>



<p>Many publishers want to opt out of crawling or having their content used in AI-generated answers.&nbsp;</p>



<p>However, if AI answers become the default interface as search moves further toward a zero-click experience, relying solely on direct or organic traffic may become increasingly risky.</p>



<p>In practice, this creates a lose-lose dynamic.&nbsp;</p>



<p>Blocking usage may protect intellectual property but reduce visibility, while staying open preserves presence at the cost of control.&nbsp;</p>



<p>Without regulatory protections in place, publishers are largely left to play within the system as it exists today.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-answers-disrupting-publisher-revenue-advertising-465185">How AI answers are disrupting publisher revenue and advertising</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-the-big-debate-google-doesn-t-owe-you-vs-it-s-not-their-content">The big debate: ‘Google doesn’t owe you’ vs. ‘it’s not their content’</h2>



<p>Since websites exist, we tend to assume they are ours to control.&nbsp;</p>



<p>But without search engines, their reach is limited.&nbsp;</p>



<p>That tension sits at the heart of a debate that has split SEO opinion.</p>



<p>On one side is the “Google doesn’t owe you anything” camp.&nbsp;</p>



<ul class="wp-block-list">
<li>Many SEOs argue that the web is open by default, and that allowing search engines to crawl a site implicitly grants permission for content use without any guaranteed return.&nbsp;</li>



<li>Google enables discovery, the argument goes, but no one is promised clicks or backlinks in exchange.</li>
</ul>



<p>On the other side is the “It’s not their content” perspective.&nbsp;</p>



<ul class="wp-block-list">
<li>Publishers argue that:
<ul class="wp-block-list">
<li>Training large language models is fundamentally different from indexing pages.</li>



<li>Generating answers from proprietary content without attribution or compensation breaks the long-standing balance between platforms and publishers.&nbsp;</li>
</ul>
</li>



<li>When visibility is absorbed into AI summaries with no clear recourse or reward, the long-term implications for publishers, brands, and SEO are significant.</li>
</ul>



<p>This debate plays out daily across social media, Reddit threads, and Quora discussions. </p>



<p>Some point to generative engine optimization, or <a href="https://searchengineland.com/what-is-generative-engine-optimization-geo-444418">GEO</a>, as a potential survival path, where being quoted in AI answers replaces traditional rankings.&nbsp;</p>



<p>But that approach still leaves publishers dependent on Google’s decisions about linking and on users choosing to click through.</p>



<p>In practice, both sides have valid arguments.&nbsp;</p>



<p>Still, the broader direction appears clear.&nbsp;</p>



<p>Even if Google faces penalties from this investigation, search is unlikely to revert to a blue-links-only model.&nbsp;</p>



<p>The shift toward a zero-click experience is already underway.</p>



<h3 class="wp-block-heading" id="h-the-dark-future-of-a-web-without-unique-content">The dark future of a web without unique content</h3>



<p>Before examining the potential outcomes of the complaint and what they may mean for SEOs, it is worth considering the consequences for information itself.</p>



<p>As creators feel their work is being reused without permission or reward, the incentive to produce original, high-quality content diminishes.&nbsp;</p>



<p>At the same time, the volume of AI-generated content created with minimal human input continues to grow. This trend is not marginal.&nbsp;</p>



<p>Entire websites now exist with thousands of pages produced almost entirely by generative systems.</p>



<p>Much of this material is derived from existing text that has been reworked, combined, or lightly altered, often with occasional hallucinations or inaccuracies.&nbsp;</p>



<p>That content, in turn, feeds new AI answers and additional AI-generated material, creating a cycle of content reuse, error propagation, and declining informational quality due to a lack of genuinely new inputs.</p>



<p>From that perspective, the debate over AI training and content rights is not only about traffic or monetization.</p>



<p>It also raises fundamental questions about how the web sustains original knowledge creation – and why protecting publishers may be necessary to prevent long-term degradation of information quality.</p>



<h2 class="wp-block-heading" id="h-what-can-happen-if-google-loses">What can happen if Google loses</h2>



<p>For years, the contract between Google and publishers was simple: “I let you crawl, you give me clicks.”&nbsp;</p>



<p>Generative AI has broken that contract.&nbsp;</p>



<p>If the EU finds Google’s practices anticompetitive, we could see three major shifts in the search landscape:</p>



<ul class="wp-block-list">
<li><strong>Mandatory opt-out mechanisms:</strong> Currently, blocking Google-Extended stops training but does not necessarily protect you from being summarized in real time. A regulatory win could force a granular “opt out of AI summaries without losing search rankings” mechanism.</li>



<li><strong>The licensing economy:</strong> Much like the music industry, we may see the rise of collective licensing. If Google is forced to pay for the training value of content, organic search may eventually split into free search and premium, licensed AI search.</li>



<li><strong>AEO formalization:</strong> If attribution becomes a legal requirement, citing the source may become a ranking factor. SEOs would need to optimize for entity citations rather than only traditional backlinks.</li>
</ul>



<h2 class="wp-block-heading" id="h-ads-and-the-shifting-economics-of-visibility">Ads and the shifting economics of visibility</h2>



<p>While this is primarily a story about AI, content rights, and SEO, ads remain the elephant in the SERP.</p>



<p>As more organic real estate is consumed by AI-generated summaries and assistive chat, the last predictable lever for visibility remains paid ads.&nbsp;</p>



<p>Even if the EU forces Google to rein in its AI answers or improve attribution, the total space left for traditional blue links is unlikely to expand significantly.&nbsp;</p>



<p>The available space will continue to favor Google’s revenue-generating products.</p>



<p>If AI Overviews dominate above the fold and organic links are pushed further down, CPCs will likely rise, whether inside or outside AI answers.&nbsp;</p>



<p>Advertisers will compete more aggressively for the remaining clickable positions.&nbsp;</p>



<p>Regardless of how the AI future plays out for Google, the direction is clear: the price of visibility is increasing.</p>



<h2 class="wp-block-heading" id="h-how-to-adapt-your-seo-and-content-strategy">How to adapt your SEO and content strategy</h2>



<p>Even before any formal EU decision, leading teams are shifting from “rank for the keyword” to “be the primary entity answer wherever the model looks.”&nbsp;</p>



<p>That involves:</p>



<ul class="wp-block-list">
<li>Strengthening entity clarity with schema, consistent NAP, and structured data so AI systems can associate queries, topics, and attributes with your brand.</li>



<li>Auditing how your brand appears in AI Overviews, major chatbots, and vertical AI tools, then tracking inclusion, sentiment, and factual accuracy as emerging visibility KPIs.</li>



<li>Reviewing robots.txt. Blocking may protect IP but reduce exposure, while remaining open may increase AI visibility while raising licensing and valuation questions.</li>



<li>Educating leadership that traffic is no longer the only outcome of visibility. Being cited, summarized, or used as a grounding source in AI outputs has value, but that value must be defined and measured internally.</li>
</ul>



<p>As legal and technical frameworks evolve, the strategic challenge is to remain machine-readable and rights-aware, asserting control over how content is used while ensuring the brand remains present wherever AI answers are trusted most.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-build-a-helpful-content-strategy-for-2023-391074">How to build an effective content strategy for 2026</a></em></strong></p>

In one of the most consequential regulatory moves yet for the future of search, the European Commission has launched a formal antitrust investigation into Google. 
At the center of the complaint is Google’s use of publisher content to train and power AI Overviews and other generative AI features – while potentially diverting traffic away from original sources.
For anyone working in SEO, content strategy, or brand visibility, the implications are immediate. 
Is Google crossing a line by repurposing publisher content for AI-generated answers, or is this simply the cost of participating in an open, crawlable web?
With regulators now stepping in, the industry is being compelled to reassess how machine-readable content is used, managed, and valued – and what it may cost brands, publishers, and agencies if regulation fails to keep pace with innovation.
Here’s what’s happening, why it matters, and how the industry is already responding.
What’s actually happening: Core allegations in the complaint
This EU move comes amid a growing wave of lawsuits and policy disputes over AI training data, from high-profile publisher cases against OpenAI and others to Penske Media’s recent antitrust suit targeting Google’s AI products. 
Publishers increasingly describe Google’s approach as a forced choice: accept unlicensed use of their content for AI training and answers, or risk losing critical search traffic.
At the same time, technical controls such as robots.txt directives, Google-Extended, and emerging noai and nopreview meta conventions reflect an industry trying to regain control over a web that was never designed for large language model training. 
The core dispute is whether AI training and answer generation are extensions of traditional indexing and snippet creation, or a distinct use that requires licensing, attribution, or both.
Dig deeper: New web standards could redefine how AI models use your content
What does the complaint target
With publishers reporting traffic drops of 20–50% on informational queries, the complaint – led by a coalition of European news and specialist publishers – targets three practices:
Google’s scraping of publisher content to train and ground models such as Gemini for AI Overviews and AI Mode.
A lack of meaningful opt-out options that preserve search visibility.
AI summaries that capture user attention above organic links, reducing clicks to original publishers.
Regulators are being asked to examine three core questions:
How Google trains and grounds its models on publisher content.
Whether publishers have meaningful ways to opt out without sacrificing search visibility.
Whether AI Overviews reinforce Google’s dominance by keeping users inside Google’s own interface.
Zero-click search evolution: Is the market ready?
For the SEO community, this probe marks what may be the start of the post-click era, where the battle for visibility shifts from the SERP to the LLM context window. 
The open question is whether Google is ready for that shift.
The zero-click search experience is often discussed, but for it to work for all parties, three conditions need to be met:
Users must be able to get what they need within the SERP, AI Overviews, or AI Mode.
Google must seamlessly blend content types – text, images, video, products, services, and even checkout – into a coherent, useful experience.
Publishers must be fairly compensated for participating in this ecosystem.
At present, Google appears eager to move toward a fully zero-click experience, but is not yet able to support it end to end:
Users still encounter hallucinated or outdated answers.
Assistive chats remain fragmented and cannot support full discovery or purchase flows.
Publishers remain unclear about how, or whether, they are compensated when their content is quoted.
What is the opt-out version, and how effective is it?
In its defense around content repurposing, Google points to opt-out mechanisms such as Google-Extended in robots.txt. 
While Google-Extended can block Gemini training, it does not prevent AI-generated answers from fetching live data from publishers’ websites.
In practice, blocking LLM training has several limitations:
It does not prevent content from appearing in AI Overviews. If Google has indexed a page, it can still summarize or rephrase that content in AI answers, even when Google-Extended is blocked.
It is opt-out, not opt-in. Content is used by default, and publishers must be aware of Google-Extended and actively implement it to stop training.
It does not provide granular control. Publishers cannot allow traditional snippets while blocking LLM training, or vice versa.
Why opting out may be a bad idea
Many publishers want to opt out of crawling or having their content used in AI-generated answers. 
However, if AI answers become the default interface as search moves further toward a zero-click experience, relying solely on direct or organic traffic may become increasingly risky.
In practice, this creates a lose-lose dynamic. 
Blocking usage may protect intellectual property but reduce visibility, while staying open preserves presence at the cost of control. 
Without regulatory protections in place, publishers are largely left to play within the system as it exists today.
Dig deeper: How AI answers are disrupting publisher revenue and advertising
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See terms.
The big debate: ‘Google doesn’t owe you’ vs. ‘it’s not their content’
Since websites exist, we tend to assume they are ours to control. 
But without search engines, their reach is limited. 
That tension sits at the heart of a debate that has split SEO opinion.
On one side is the “Google doesn’t owe you anything” camp. 
Many SEOs argue that the web is open by default, and that allowing search engines to crawl a site implicitly grants permission for content use without any guaranteed return. 
Google enables discovery, the argument goes, but no one is promised clicks or backlinks in exchange.
On the other side is the “It’s not their content” perspective. 
Publishers argue that:

Training large language models is fundamentally different from indexing pages.
Generating answers from proprietary content without attribution or compensation breaks the long-standing balance between platforms and publishers. 
When visibility is absorbed into AI summaries with no clear recourse or reward, the long-term implications for publishers, brands, and SEO are significant.
This debate plays out daily across social media, Reddit threads, and Quora discussions. 
Some point to generative engine optimization, or GEO, as a potential survival path, where being quoted in AI answers replaces traditional rankings. 
But that approach still leaves publishers dependent on Google’s decisions about linking and on users choosing to click through.
In practice, both sides have valid arguments. 
Still, the broader direction appears clear. 
Even if Google faces penalties from this investigation, search is unlikely to revert to a blue-links-only model. 
The shift toward a zero-click experience is already underway.
The dark future of a web without unique content
Before examining the potential outcomes of the complaint and what they may mean for SEOs, it is worth considering the consequences for information itself.
As creators feel their work is being reused without permission or reward, the incentive to produce original, high-quality content diminishes. 
At the same time, the volume of AI-generated content created with minimal human input continues to grow. This trend is not marginal. 
Entire websites now exist with thousands of pages produced almost entirely by generative systems.
Much of this material is derived from existing text that has been reworked, combined, or lightly altered, often with occasional hallucinations or inaccuracies. 
That content, in turn, feeds new AI answers and additional AI-generated material, creating a cycle of content reuse, error propagation, and declining informational quality due to a lack of genuinely new inputs.
From that perspective, the debate over AI training and content rights is not only about traffic or monetization.
It also raises fundamental questions about how the web sustains original knowledge creation – and why protecting publishers may be necessary to prevent long-term degradation of information quality.
What can happen if Google loses
For years, the contract between Google and publishers was simple: “I let you crawl, you give me clicks.” 
Generative AI has broken that contract. 
If the EU finds Google’s practices anticompetitive, we could see three major shifts in the search landscape:
Mandatory opt-out mechanisms: Currently, blocking Google-Extended stops training but does not necessarily protect you from being summarized in real time. A regulatory win could force a granular “opt out of AI summaries without losing search rankings” mechanism.
The licensing economy: Much like the music industry, we may see the rise of collective licensing. If Google is forced to pay for the training value of content, organic search may eventually split into free search and premium, licensed AI search.
AEO formalization: If attribution becomes a legal requirement, citing the source may become a ranking factor. SEOs would need to optimize for entity citations rather than only traditional backlinks.
Ads and the shifting economics of visibility
While this is primarily a story about AI, content rights, and SEO, ads remain the elephant in the SERP.
As more organic real estate is consumed by AI-generated summaries and assistive chat, the last predictable lever for visibility remains paid ads. 
Even if the EU forces Google to rein in its AI answers or improve attribution, the total space left for traditional blue links is unlikely to expand significantly. 
The available space will continue to favor Google’s revenue-generating products.
If AI Overviews dominate above the fold and organic links are pushed further down, CPCs will likely rise, whether inside or outside AI answers. 
Advertisers will compete more aggressively for the remaining clickable positions. 
Regardless of how the AI future plays out for Google, the direction is clear: the price of visibility is increasing.
How to adapt your SEO and content strategy
Even before any formal EU decision, leading teams are shifting from “rank for the keyword” to “be the primary entity answer wherever the model looks.” 
That involves:
Strengthening entity clarity with schema, consistent NAP, and structured data so AI systems can associate queries, topics, and attributes with your brand.
Auditing how your brand appears in AI Overviews, major chatbots, and vertical AI tools, then tracking inclusion, sentiment, and factual accuracy as emerging visibility KPIs.
Reviewing robots.txt. Blocking may protect IP but reduce exposure, while remaining open may increase AI visibility while raising licensing and valuation questions.
Educating leadership that traffic is no longer the only outcome of visibility. Being cited, summarized, or used as a grounding source in AI outputs has value, but that value must be defined and measured internally.
As legal and technical frameworks evolve, the strategic challenge is to remain machine-readable and rights-aware, asserting control over how content is used while ensuring the brand remains present wherever AI answers are trusted most.
Dig deeper: How to build an effective content strategy for 2026

An antitrust case puts AI Overviews, opt-outs, and zero-click visibility under scrutiny amid growing debate over content use and attribution.

Google vs. publishers: What the EU probe means for SEO, AI answers, and content rights

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Here are four ways to evolve your SEO strategy and boost visibility in AI-powered search.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png" alt="" class="wp-image-466427" srcset="https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature.png 1920w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/12/Contentful-20251219-feature-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure></div>


<p>Does it feel like your organic traffic is disappearing? You aren&#8217;t imagining it. AI Overviews and answer engines are sidelining classic SEO results.&nbsp;</p>



<p>To stay visible, brands need to adapt –&nbsp;fast.</p>



<p>The good news: you don’t need to rewrite your entire SEO playbook. With a few smart tweaks, you can shift from SEO to GEO and reclaim your share of search in the age of generative AI.</p>



<p>GEO, or generative engine optimization, focuses on entities –&nbsp;not just pages. That means your brand, products, services, and experts. By strengthening these signals, you increase the chances your business is cited, referenced, and recommended inside AI-generated answers and conversational search results.</p>



<p>This shift to GEO matters because AI search tools work differently from traditional engines. Instead of a list of blue links, AI delivers answers that anticipate follow-up questions and add context. Users get what they need faster, but brands get fewer clicks.</p>



<p>Organic search demand isn’t disappearing, but traffic is drifting away from it. As clicks decline, visibility inside AI-generated responses becomes more critical than ever.</p>



<h2 class="wp-block-heading" id="h-what-you-need-to-do-now">What you need to do now</h2>



<p>You don’t need to reinvent your strategy to move from SEO to GEO. GEO builds on the principles you already use, with added focus on structure, clarity, and consistency.</p>



<h3 class="wp-block-heading" id="h-1-prioritize-e-e-a-t-experience-expertise-authoritativeness-and-trustworthiness">1. Prioritize E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness)</h3>



<p>AI engines reward clear, authoritative content that signals real expertise. When your content aligns with established quality guidelines, it’s more likely to be used in generative answers.</p>



<h3 class="wp-block-heading" id="h-2-make-your-content-easy-for-ai-crawlers-to-read">2. Make your content easy for AI crawlers to read</h3>



<p>While Googlebot handles JavaScript well, many AI crawlers don’t. Fully rendered HTML, clean structure, and predictable layouts make it easier for AI systems to understand your content and reference it accurately.</p>



<h3 class="wp-block-heading" id="h-3-invest-in-structured-data">3. Invest in structured data</h3>



<p>Schema markup, complete metadata, descriptive alt text, and transcripts help AI models understand your content and connect it to the right entities. These behind-the-scenes signals make it more likely your content appears in AI-generated conversations.</p>



<h3 class="wp-block-heading" id="h-4-rethink-measurement">4. Rethink measurement</h3>



<p>Traffic is no longer the north star. Focus instead on conversions, deeper funnel impact, sentiment, and your brand’s visibility inside generative results.</p>



<h2 class="wp-block-heading" id="h-want-to-go-deeper">Want to go deeper?</h2>



<p>If you&#8217;re ready to pivot from SEO to GEO with confidence, explore proven best practices, frameworks, and real-world examples on <strong><a href="https://www.contentful.com/resources/geo/?utm_source=search-engine-land&amp;utm_medium=media-sponsorship&amp;utm_campaign=fy26-q4-global-great_content_collapse" target="_blank" rel="noopener sponsored nofollow">Contentful’s GEO Hub</a></strong>. It’s your go-to resource for understanding the shift – and staying ahead.</p>



<p></p>


Does it feel like your organic traffic is disappearing? You aren’t imagining it. AI Overviews and answer engines are sidelining classic SEO results. 
To stay visible, brands need to adapt – fast.
The good news: you don’t need to rewrite your entire SEO playbook. With a few smart tweaks, you can shift from SEO to GEO and reclaim your share of search in the age of generative AI.
GEO, or generative engine optimization, focuses on entities – not just pages. That means your brand, products, services, and experts. By strengthening these signals, you increase the chances your business is cited, referenced, and recommended inside AI-generated answers and conversational search results.
This shift to GEO matters because AI search tools work differently from traditional engines. Instead of a list of blue links, AI delivers answers that anticipate follow-up questions and add context. Users get what they need faster, but brands get fewer clicks.
Organic search demand isn’t disappearing, but traffic is drifting away from it. As clicks decline, visibility inside AI-generated responses becomes more critical than ever.
What you need to do now
You don’t need to reinvent your strategy to move from SEO to GEO. GEO builds on the principles you already use, with added focus on structure, clarity, and consistency.
1. Prioritize E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness)
AI engines reward clear, authoritative content that signals real expertise. When your content aligns with established quality guidelines, it’s more likely to be used in generative answers.
2. Make your content easy for AI crawlers to read
While Googlebot handles JavaScript well, many AI crawlers don’t. Fully rendered HTML, clean structure, and predictable layouts make it easier for AI systems to understand your content and reference it accurately.
3. Invest in structured data
Schema markup, complete metadata, descriptive alt text, and transcripts help AI models understand your content and connect it to the right entities. These behind-the-scenes signals make it more likely your content appears in AI-generated conversations.
4. Rethink measurement
Traffic is no longer the north star. Focus instead on conversions, deeper funnel impact, sentiment, and your brand’s visibility inside generative results.
Want to go deeper?
If you’re ready to pivot from SEO to GEO with confidence, explore proven best practices, frameworks, and real-world examples on Contentful’s GEO Hub. It’s your go-to resource for understanding the shift – and staying ahead.

Here are four ways to evolve your SEO strategy and boost visibility in AI-powered search.

From SEO to GEO: How marketing leaders stay visible in AI-driven search by Contentful

<div><img width="1920" height="1085" src="https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards.webp" class="attachment-large size-large wp-post-image" alt="Semrush AI Visibility Awards" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards.webp 1920w, https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards-768x434.webp 768w, https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards-1536x868.webp 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Semrush’s new AI Visibility Awards reveal which brands are winning trust — and share of voice — in AI-generated search results.

<div><img width="1920" height="1085" src="https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards.webp" class="attachment-large size-large wp-post-image" alt="Semrush AI Visibility Awards" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards.webp 1920w, https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards-768x434.webp 768w, https://searchengineland.com/wp-content/seloads/2025/12/AI-brain-search-awards-1536x868.webp 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>As AI chatbots become the go-to tools for travel planning, product recommendations, and more, marketers face a growing challenge: how do you make sure your brand appears in the answers?</p>



<p>Semrush believes it has the answer – and it’s launching an award program to spotlight the brands leading the way.</p>



<p>The newly announced AI Visibility Awards recognize the companies most often cited, recommended, and surfaced in AI-generated responses, using Semrush’s AI Visibility Index, a dataset built from more than 2,500 real prompts run through ChatGPT and Google’s AI Mode.</p>



<p>Andrew Warden, CMO at Semrush, said:</p>



<ul class="wp-block-list">
<li>“This year marks a turning point in how brands earn visibility. It’s not about submissions or panels – it’s about real user behavior. These awards recognize the marketers cracking the AI code and earning trust where it counts: inside the answers.”</li>
</ul>



<h2 class="wp-block-heading" id="h-what-the-ai-visibility-awards-measure">What the AI Visibility Awards measure</h2>



<p>The awards highlight three types of performers across four major verticals:</p>



<ul class="wp-block-list">
<li><strong>Category Leaders:</strong> Brands with the largest footprint in AI search</li>



<li><strong>Growth Engines:</strong> Fastest gainers in visibility</li>



<li><strong>Challengers:</strong> Up-and-comers gaining traction in AI results</li>
</ul>



<p>For example, Google topped the Business &amp; Professional Services category, while Rippling was recognized as a Challenger brand. In Consumer Electronics, Samsung led the pack, with Logitech and Nothing Technology earning Growth Engine and Challenger honors, respectively.</p>



<p>Other notable winners:</p>



<ul class="wp-block-list">
<li><strong>Microsoft</strong>, Category Leader for Digital Tech &amp; Software</li>



<li><strong>UNIQLO</strong>, Growth Engine in Fashion &amp; Apparel</li>



<li><strong>Anthropic</strong>, Challenger in Digital Tech &amp; Software</li>
</ul>



<h2 class="wp-block-heading" id="h-ai-search-trends-marketers-should-watch">AI search trends marketers should watch</h2>



<p>The award data reveals a few emerging truths about AI-driven discovery:</p>



<ul class="wp-block-list">
<li><strong>Stability among leaders:</strong> Top brands showed less than 20% monthly volatility in AI share-of-voice, suggesting AI engines “lock in” trusted names.</li>



<li><strong>Niches break through:</strong> Brands with clear topical relevance — like Patagonia in ethical fashion or Logitech in gaming accessories — punch above their weight.</li>



<li><strong>Challengers can compete:</strong> Newer players like Nuuly and Anthropic are finding traction with strong positioning and momentum.</li>



<li><strong>Verticals behave differently:</strong> Some, like Business &amp; Professional Services, remain highly competitive, while others reward consistency or focus.</li>
</ul>



<p>These awards underscore what many marketers are only starting to confront: AI visibility is now part of the competitive equation. For some brands, it’s already shaping strategy.</p>


As AI chatbots become the go-to tools for travel planning, product recommendations, and more, marketers face a growing challenge: how do you make sure your brand appears in the answers?
Semrush believes it has the answer – and it’s launching an award program to spotlight the brands leading the way.
The newly announced AI Visibility Awards recognize the companies most often cited, recommended, and surfaced in AI-generated responses, using Semrush’s AI Visibility Index, a dataset built from more than 2,500 real prompts run through ChatGPT and Google’s AI Mode.
Andrew Warden, CMO at Semrush, said:
“This year marks a turning point in how brands earn visibility. It’s not about submissions or panels – it’s about real user behavior. These awards recognize the marketers cracking the AI code and earning trust where it counts: inside the answers.”
What the AI Visibility Awards measure
The awards highlight three types of performers across four major verticals:
Category Leaders: Brands with the largest footprint in AI search
Growth Engines: Fastest gainers in visibility
Challengers: Up-and-comers gaining traction in AI results
For example, Google topped the Business & Professional Services category, while Rippling was recognized as a Challenger brand. In Consumer Electronics, Samsung led the pack, with Logitech and Nothing Technology earning Growth Engine and Challenger honors, respectively.
Other notable winners:
Microsoft, Category Leader for Digital Tech & Software
UNIQLO, Growth Engine in Fashion & Apparel
Anthropic, Challenger in Digital Tech & Software
AI search trends marketers should watch
The award data reveals a few emerging truths about AI-driven discovery:
Stability among leaders: Top brands showed less than 20% monthly volatility in AI share-of-voice, suggesting AI engines “lock in” trusted names.
Niches break through: Brands with clear topical relevance — like Patagonia in ethical fashion or Logitech in gaming accessories — punch above their weight.
Challengers can compete: Newer players like Nuuly and Anthropic are finding traction with strong positioning and momentum.
Verticals behave differently: Some, like Business & Professional Services, remain highly competitive, while others reward consistency or focus.
These awards underscore what many marketers are only starting to confront: AI visibility is now part of the competitive equation. For some brands, it’s already shaping strategy.

Semrush’s new AI Visibility Awards reveal which brands are winning trust — and share of voice — in AI-generated search results.

New AI Visibility Awards spotlight brands thriving in AI-generated search results

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-800x450.png" class="attachment-large size-large wp-post-image" alt="Microsoft Ads: How it compares to Google Ads and tips for getting started" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google added native location targeting controls to Demand Gen campaigns, giving advertisers more precise geo-targeting.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-800x450.png" class="attachment-large size-large wp-post-image" alt="Microsoft Ads: How it compares to Google Ads and tips for getting started" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2024/11/Microsoft-Ads-How-it-compares-to-Google-Ads-and-tips-for-getting-started.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google Ads is rolling out new location targeting options for Demand Gen campaigns, matching the controls already available in Search.</p>



<p><strong>What’s new</strong>. You can choose between <em>Presence or interest</em> and <em>Presence </em>when setting up Demand Gen campaigns. </p>



<ul class="wp-block-list">
<li>The option appears directly in the campaign interface, removing the need for manual exclusions.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2025/12/demand-gen-location-language.jpg" alt="" class="wp-image-466437" srcset="https://searchengineland.com/wp-content/seloads/2025/12/demand-gen-location-language.jpg 1280w, https://searchengineland.com/wp-content/seloads/2025/12/demand-gen-location-language-768x432.jpg 768w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<p><strong>Why we care.</strong> Until now, Demand Gen advertisers had limited control over geotargeting. By making <em>presence </em>targeting native to campaign setup, Google removes a common workaround and reduces the risk of accidental geo-leakage. The result is cleaner traffic, more accurate measurement, and greater confidence in upper-funnel Demand Gen performance.</p>



<p><strong>The big picture</strong>. Demand Gen is designed for upper- and mid-funnel reach across YouTube, Discover, and Gmail. Adding clearer location controls gives advertisers more confidence that impressions and clicks are coming from users actually located in their target markets.</p>



<p><strong>Bottom line</strong>. With proper location targeting now built in, Demand Gen campaigns are easier to set up, easier to control, and less likely to waste budget outside intended geographies.</p>



<p><strong>First seen.</strong> This update was spotted by Google Ads specialist Marcin Wsół on <a href="https://www.linkedin.com/posts/marcinwsol_nowo%C5%9B%C4%87-nowe-opcje-lokalizacji-w-activity-7406995228265517056-mopG/?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAABU5RtAB1yM61HMd6Ska99csDVjiJlgRo6A" target="_blank" rel="noopener">LinkedIn</a>.</p>


Google Ads is rolling out new location targeting options for Demand Gen campaigns, matching the controls already available in Search.
What’s new. You can choose between Presence or interest and Presence when setting up Demand Gen campaigns. 
The option appears directly in the campaign interface, removing the need for manual exclusions.




Why we care. Until now, Demand Gen advertisers had limited control over geotargeting. By making presence targeting native to campaign setup, Google removes a common workaround and reduces the risk of accidental geo-leakage. The result is cleaner traffic, more accurate measurement, and greater confidence in upper-funnel Demand Gen performance.
The big picture. Demand Gen is designed for upper- and mid-funnel reach across YouTube, Discover, and Gmail. Adding clearer location controls gives advertisers more confidence that impressions and clicks are coming from users actually located in their target markets.
Bottom line. With proper location targeting now built in, Demand Gen campaigns are easier to set up, easier to control, and less likely to waste budget outside intended geographies.
First seen. This update was spotted by Google Ads specialist Marcin Wsół on LinkedIn.

Google added native location targeting controls to Demand Gen campaigns, giving advertisers more precise geo-targeting.

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