<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" decoding="async" fetchpriority="high" 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>Microsoft is making it easier to expand Google PMax campaigns into Microsoft while gaining more visibility and control over performance.

<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" 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>Microsoft Advertising is rolling out a slate of updates aimed at making Performance Max campaigns easier to manage, measure, and migrate — especially for advertisers already using Google Ads.</p>



<p><strong>Driving the news.</strong> Microsoft now lets advertisers import Google PMax campaigns that use new customer acquisition (NCA) goals, a feature that has been generally available in Microsoft since early this year.</p>



<p>The update is now live for all advertisers.</p>



<p>That means marketers can more easily port over campaigns designed to prioritize first-time buyers without rebuilding them from scratch.</p>



<p><strong>What’s new</strong>. Microsoft says imported Google PMax campaigns with NCA goals will carry over if they don’t already exist in the advertiser’s account. Existing Microsoft NCA settings won’t be overwritten.</p>



<p>For audience lists:</p>



<ul class="wp-block-list">
<li>Google website visitor segments will convert into Microsoft remarketing lists.</li>



<li>Google’s “all visitors” and “all converters” lists will map to Microsoft equivalents.</li>



<li>Unsupported lists, like Customer Match, will prompt advertisers to use fallback options.</li>
</ul>



<p>Microsoft also says it takes a more conservative approach to “unknown” customers, classifying them as existing customers to avoid overcounting new customer conversions.</p>



<p><strong>Why we care.</strong> This could make cross-platform campaign expansion faster and lower the friction of testing Microsoft’s PMax inventory removing the need of rebuilding campaigns from scratch. The added landing page reporting and search term visibility also give marketers better insight into what’s driving performance, which can help improve optimization and budget decisions.</p>



<p><strong>More visbility for PMax</strong>. Microsoft is also adding landing page (Final URL) reporting for PMax campaigns. Advertisers can now see spend, clicks, impressions, conversion value, and ROAS by landing page.</p>



<p>They can also segment by campaign, asset group, and other dimensions.</p>



<p>Microsoft also said search term reporting is becoming more visible by default, with more transparency updates — including auction insights and added publisher URL metrics — planned later.</p>



<p><strong>Other key updates:</strong>



<ul class="wp-block-list">
<li><strong>Seasonality adjustments</strong> now support portfolio bid strategies, expanding a tool advertisers use for short-term events like promotions.</li>



<li><strong>Campaign name limits</strong> are increasing from 128 to 400 characters, helping agencies and enterprise teams manage naming conventions at scale.</li>



<li><strong>Autogenerated assets</strong> are expanding to underbuilt Responsive Search Ads to improve ad relevance and performance.</li>



<li><strong>Merchant Center</strong> users can now update store names and domains directly without contacting support.</li>
</ul>



<p><strong>The bottom line</strong>. <a href="https://about.ads.microsoft.com/en/blog/post/april-2026/performance-max-updates-and-other-product-news-for-april-2026">These updates</a> make it easier to scale across platforms, save time on campaign setup, and get better visibility into what’s actually driving performance — giving advertisers more control over both efficiency and results.</p>


Microsoft Advertising is rolling out a slate of updates aimed at making Performance Max campaigns easier to manage, measure, and migrate — especially for advertisers already using Google Ads.
Driving the news. Microsoft now lets advertisers import Google PMax campaigns that use new customer acquisition (NCA) goals, a feature that has been generally available in Microsoft since early this year.
The update is now live for all advertisers.
That means marketers can more easily port over campaigns designed to prioritize first-time buyers without rebuilding them from scratch.
What’s new. Microsoft says imported Google PMax campaigns with NCA goals will carry over if they don’t already exist in the advertiser’s account. Existing Microsoft NCA settings won’t be overwritten.
For audience lists:
Google website visitor segments will convert into Microsoft remarketing lists.
Google’s “all visitors” and “all converters” lists will map to Microsoft equivalents.
Unsupported lists, like Customer Match, will prompt advertisers to use fallback options.
Microsoft also says it takes a more conservative approach to “unknown” customers, classifying them as existing customers to avoid overcounting new customer conversions.
Why we care. This could make cross-platform campaign expansion faster and lower the friction of testing Microsoft’s PMax inventory removing the need of rebuilding campaigns from scratch. The added landing page reporting and search term visibility also give marketers better insight into what’s driving performance, which can help improve optimization and budget decisions.
More visbility for PMax. Microsoft is also adding landing page (Final URL) reporting for PMax campaigns. Advertisers can now see spend, clicks, impressions, conversion value, and ROAS by landing page.
They can also segment by campaign, asset group, and other dimensions.
Microsoft also said search term reporting is becoming more visible by default, with more transparency updates — including auction insights and added publisher URL metrics — planned later.
Other key updates:




Seasonality adjustments now support portfolio bid strategies, expanding a tool advertisers use for short-term events like promotions.
Campaign name limits are increasing from 128 to 400 characters, helping agencies and enterprise teams manage naming conventions at scale.
Autogenerated assets are expanding to underbuilt Responsive Search Ads to improve ad relevance and performance.
Merchant Center users can now update store names and domains directly without contacting support.
The bottom line. These updates make it easier to scale across platforms, save time on campaign setup, and get better visibility into what’s actually driving performance — giving advertisers more control over both efficiency and results.

Microsoft is making it easier to expand Google PMax campaigns into Microsoft while gaining more visibility and control over performance.

Microsoft makes it easier to import Google PMax campaigns

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations.png" class="attachment-large size-large wp-post-image" alt="ChatGPT citations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Heading alignment and narrow answers drive citations, while long, broad content underperforms, study finds.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations.png" class="attachment-large size-large wp-post-image" alt="ChatGPT citations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/chatgpt-citations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>ChatGPT citations favor pages that rank well, match the query in their headings, and stay tightly focused, according to an AirOps study of 16,851 queries. The top retrieval result was cited 58% of the time, and pages that answered the main query more narrowly outperformed broader, more comprehensive guides.</p>



<p><strong>Why we care</strong>. This study clarifies how to earn ChatGPT citations: win retrieval, mirror the query in your headings, and answer one question extremely well. In this study, that mattered more than breadth.</p>



<p><strong>The findings.</strong> Retrieval rank was the strongest signal. Pages in the top search position were cited 58.4% of the time, versus 14.2% for pages in position 10.</p>



<ul class="wp-block-list">
<li>Heading relevance was the strongest on-page factor. Pages with the strongest heading-query match were cited 41.0% of the time, compared with roughly 30% for weaker matches.</li>



<li>Focused pages also beat comprehensive ones. Pages that answered the main query more narrowly outperformed broader, more comprehensive guides, undercutting the usual “ultimate guide” approach.</li>
</ul>



<p><strong>What drove ChatGPT citations</strong>. In this study, pages that won citations usually ranked well, used headings that closely matched the query, and stayed focused on answering it.</p>



<ul class="wp-block-list">
<li><strong>Structure helped, but only slightly:</strong> Pages with JSON-LD markup posted a 38.5% citation rate versus 32.0% for pages without it, and articles with 4 to 10 subheadings performed best.</li>



<li><strong>Beyond a certain point, length hurt performance:</strong> Pages between 500 and 2,000 words performed best, but pages longer than 5,000 words were cited less often than pages under 500 words.</li>
</ul>



<p><strong>Freshness helps, up to a point. </strong>Pages published 30 to 89 days earlier performed best, while pages newer than 30 days performed worse. This suggests new content may need time to build retrieval signals.</p>



<ul class="wp-block-list">
<li>Pages more than 2 years old were cited less often, which suggests that content refreshes could help if you&#8217;re already ranking for the right queries.</li>
</ul>



<p><strong>About the data</strong>. AirOps said it scraped ChatGPT’s interface, not the API, and analyzed 50,553 responses generated from 16,851 unique queries run three times each. The dataset included 353,799 pages and more than 1.5 million fan-out detail rows across 10 verticals and four query types.</p>



<p><strong>The study.</strong> <a href="https://www.airops.com/report/the-fan-out-effect-what-happens-between-a-query-and-a-citation" target="_blank" rel="noopener">The Fan-Out Effect: What Happens Between a Query and a Citation</a>


ChatGPT citations favor pages that rank well, match the query in their headings, and stay tightly focused, according to an AirOps study of 16,851 queries. The top retrieval result was cited 58% of the time, and pages that answered the main query more narrowly outperformed broader, more comprehensive guides.
Why we care. This study clarifies how to earn ChatGPT citations: win retrieval, mirror the query in your headings, and answer one question extremely well. In this study, that mattered more than breadth.
The findings. Retrieval rank was the strongest signal. Pages in the top search position were cited 58.4% of the time, versus 14.2% for pages in position 10.
Heading relevance was the strongest on-page factor. Pages with the strongest heading-query match were cited 41.0% of the time, compared with roughly 30% for weaker matches.
Focused pages also beat comprehensive ones. Pages that answered the main query more narrowly outperformed broader, more comprehensive guides, undercutting the usual “ultimate guide” approach.
What drove ChatGPT citations. In this study, pages that won citations usually ranked well, used headings that closely matched the query, and stayed focused on answering it.
Structure helped, but only slightly: Pages with JSON-LD markup posted a 38.5% citation rate versus 32.0% for pages without it, and articles with 4 to 10 subheadings performed best.
Beyond a certain point, length hurt performance: Pages between 500 and 2,000 words performed best, but pages longer than 5,000 words were cited less often than pages under 500 words.
Freshness helps, up to a point. Pages published 30 to 89 days earlier performed best, while pages newer than 30 days performed worse. This suggests new content may need time to build retrieval signals.
Pages more than 2 years old were cited less often, which suggests that content refreshes could help if you’re already ranking for the right queries.
About the data. AirOps said it scraped ChatGPT’s interface, not the API, and analyzed 50,553 responses generated from 16,851 unique queries run three times each. The dataset included 353,799 pages and more than 1.5 million fan-out detail rows across 10 verticals and four query types.
The study. The Fan-Out Effect: What Happens Between a Query and a Citation

Heading alignment and narrow answers drive citations, while long, broad content underperforms, study finds.

ChatGPT citations reward ranking and precision over length: Study

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Chrome now has a new side-by-side mode, search across tabs, and multi-input tools.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/05/google-ai-mode-head-1920-e1748875083240-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google announced Chrome updates that let searchers use AI Mode in a more engaging, deeper way. Chrome lets you do it all without switching tabs and potentially losing your place.</p>



<p><strong>What&#8217;s new. </strong>Chrome added three new features:</p>



<ul class="wp-block-list">
<li><strong>Search side-by-side: </strong>In AI Mode on Chrome desktop, clicking a link opens the webpage next to AI Mode. That makes it easier to visit relevant sites, compare details, and ask follow-up questions without losing the context of your search. Here’s what it looks like:</li>
</ul>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/04/AI-Mode-in-Chrome-Ninja-Coffee.mp4"></video></figure>



<ul class="wp-block-list">
<li><strong>Search across your tabs:</strong> On Chrome desktop or mobile, you can tap the new “plus” menu on the New Tab page, or the existing plus menu in AI Mode, to add recent tabs to your search. That lets AI Mode deliver more tailored responses and suggest more sites to explore.</li>



<li><strong>Multi-input and easy tool access</strong>: You can also mix and match multiple tabs, images, or files like PDFs and bring that context into AI Mode. Tools like <a href="https://blog.google/products-and-platforms/products/search/ai-mode-canvas-writing-coding/">Canvas</a> and <a href="https://support.google.com/websearch/answer/16649374">image creation</a> are also available wherever you see the new plus menu in Chrome.</li>
</ul>



<p><strong>Why we care. </strong>These new Chrome-specific features for U.S. users unlock more AI Mode capabilities. Again, they’re limited to Chrome users for now, but they show the direction Google is taking AI Mode.</p>


Google announced Chrome updates that let searchers use AI Mode in a more engaging, deeper way. Chrome lets you do it all without switching tabs and potentially losing your place.
What’s new. Chrome added three new features:
Search side-by-side: In AI Mode on Chrome desktop, clicking a link opens the webpage next to AI Mode. That makes it easier to visit relevant sites, compare details, and ask follow-up questions without losing the context of your search. Here’s what it looks like:





Search across your tabs: On Chrome desktop or mobile, you can tap the new “plus” menu on the New Tab page, or the existing plus menu in AI Mode, to add recent tabs to your search. That lets AI Mode deliver more tailored responses and suggest more sites to explore.
Multi-input and easy tool access: You can also mix and match multiple tabs, images, or files like PDFs and bring that context into AI Mode. Tools like Canvas and image creation are also available wherever you see the new plus menu in Chrome.
Why we care. These new Chrome-specific features for U.S. users unlock more AI Mode capabilities. Again, they’re limited to Chrome users for now, but they show the direction Google is taking AI Mode.

Google Chrome now has a new side-by-side mode, search across tabs, and multi-input tools.

Google AI Mode in Chrome now lets you search deeper with fewer tabs

<div><img width="800" height="457" src="https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-800x457.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-800x457.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-592x338.jpg 592w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-198x113.jpg 198w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-1536x878.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>602 million scam ads were removed, and 24.9 million accounts were suspended, according to Google's 2025 Ads Safety Report.

<div><img width="800" height="457" src="https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-800x457.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-800x457.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-592x338.jpg 592w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-198x113.jpg 198w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security-1536x878.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/04/google-server-security.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google is making Gemini a core part of ad enforcement, saying the AI upgrade helped catch more scams while sharply reducing mistaken suspensions of legitimate advertisers. The move shows how quickly ad safety is turning into an AI fight over speed, scale, and accuracy.</p>



<p><strong>The details.</strong> In its 2025 Ads Safety Report, Google said it blocked or removed 8.3 billion ads and suspended 24.9 million advertiser accounts last year. It said more than 99% of policy-violating ads were stopped before they ran.</p>



<ul class="wp-block-list">
<li>Google credited Gemini with cutting incorrect advertiser suspensions by 80%, processing 4x more user reports than the year before, and spotting scam signals faster by better understanding ad intent.</li>



<li>Scams were a major focus. Google said it removed 602 million scam-related ads and suspended 4 million scam-linked accounts.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="390" height="390" src="https://searchengineland.com/wp-content/seloads/2026/04/AI-detection-1.png" alt="" class="wp-image-474488" srcset="https://searchengineland.com/wp-content/seloads/2026/04/AI-detection-1.png 390w, https://searchengineland.com/wp-content/seloads/2026/04/AI-detection-1-95x95.png 95w" sizes="(max-width: 390px) 100vw, 390px" /></figure>
</div>


<p><strong>By the numbers:</strong>



<ul class="wp-block-list">
<li><strong>602 million</strong> scam-related ads removed</li>



<li><strong>4 million</strong> scam-linked accounts suspended</li>



<li><strong>4.8 billion</strong> ads restricted</li>



<li><strong>480 million</strong> web pages blocked or restricted</li>



<li><strong>245,000+</strong> publisher sites actioned</li>



<li><strong>35</strong> policy updates made in 2025</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="788" height="212" src="https://searchengineland.com/wp-content/seloads/2026/04/Google-Ad-safety-numbers.png" alt="" class="wp-image-474485" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Google-Ad-safety-numbers.png 788w, https://searchengineland.com/wp-content/seloads/2026/04/Google-Ad-safety-numbers-768x207.png 768w" sizes="(max-width: 788px) 100vw, 788px" /></figure>



<p><strong>The U.S. picture:</strong> Google said it removed 1.7 billion ads and suspended 3.3 million advertiser accounts in the U.S. in 2025. The most common violations included abuse of the ad network, misrepresentation, sexual content, personalization violations, and dating and companionship ads.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="805" height="500" src="https://searchengineland.com/wp-content/seloads/2026/04/Policy-vioilations.png" alt="" class="wp-image-474486" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Policy-vioilations.png 805w, https://searchengineland.com/wp-content/seloads/2026/04/Policy-vioilations-768x477.png 768w" sizes="(max-width: 805px) 100vw, 805px" /></figure>



<p><strong>Why we care.</strong> This directly affects whether campaigns launch, stay live, or get flagged. Google is signaling that AI will play a bigger role in deciding which ads run and which accounts get stopped. For advertisers, that raises the stakes on policy compliance while also promising fewer costly false suspensions.</p>



<p><strong>How it works:</strong> Google said Gemini analyzes hundreds of billions of signals, including account age, behavior patterns, and campaign activity, to detect malicious intent earlier than older systems built more heavily around keywords and rule matching.</p>



<p>The company also said that by the end of 2025, most Responsive Search Ads would be reviewed instantly at submission, blocking harmful ads before launch. It plans to expand that capability to more formats this year.</p>



<p><strong>Yes, but.</strong> Faster automated enforcement does not always mean smoother enforcement. Some advertisers in the U.K. and U.S. have recently <a href="https://searchengineland.com/google-ads-advertisers-report-wave-of-unexplained-ad-disapprovals-474287">reported bulk ad disapproval alerts despite finding no actual policy issues</a>. That adds pressure on Google to prove tighter AI enforcement will not create new disruptions for legitimate brands.</p>



<p><strong>Bottom line:</strong> Google wants advertisers to see Gemini as both shield and filter — tougher on scams, but more precise with legitimate accounts. The real test is whether that balance holds as enforcement gets faster and more automated.</p>



<p><strong>Google&#8217;s blog post.</strong> <a href="https://blog.google/products/ads-commerce/2025-ads-safety-report/" target="_blank" rel="noopener">Gemini is stopping harmful ads before people ever see them</a>


Google is making Gemini a core part of ad enforcement, saying the AI upgrade helped catch more scams while sharply reducing mistaken suspensions of legitimate advertisers. The move shows how quickly ad safety is turning into an AI fight over speed, scale, and accuracy.
The details. In its 2025 Ads Safety Report, Google said it blocked or removed 8.3 billion ads and suspended 24.9 million advertiser accounts last year. It said more than 99% of policy-violating ads were stopped before they ran.
Google credited Gemini with cutting incorrect advertiser suspensions by 80%, processing 4x more user reports than the year before, and spotting scam signals faster by better understanding ad intent.
Scams were a major focus. Google said it removed 602 million scam-related ads and suspended 4 million scam-linked accounts.




By the numbers:




602 million scam-related ads removed
4 million scam-linked accounts suspended
4.8 billion ads restricted
480 million web pages blocked or restricted
245,000+ publisher sites actioned
35 policy updates made in 2025




The U.S. picture: Google said it removed 1.7 billion ads and suspended 3.3 million advertiser accounts in the U.S. in 2025. The most common violations included abuse of the ad network, misrepresentation, sexual content, personalization violations, and dating and companionship ads.




Why we care. This directly affects whether campaigns launch, stay live, or get flagged. Google is signaling that AI will play a bigger role in deciding which ads run and which accounts get stopped. For advertisers, that raises the stakes on policy compliance while also promising fewer costly false suspensions.
How it works: Google said Gemini analyzes hundreds of billions of signals, including account age, behavior patterns, and campaign activity, to detect malicious intent earlier than older systems built more heavily around keywords and rule matching.
The company also said that by the end of 2025, most Responsive Search Ads would be reviewed instantly at submission, blocking harmful ads before launch. It plans to expand that capability to more formats this year.
Yes, but. Faster automated enforcement does not always mean smoother enforcement. Some advertisers in the U.K. and U.S. have recently reported bulk ad disapproval alerts despite finding no actual policy issues. That adds pressure on Google to prove tighter AI enforcement will not create new disruptions for legitimate brands.
Bottom line: Google wants advertisers to see Gemini as both shield and filter — tougher on scams, but more precise with legitimate accounts. The real test is whether that balance holds as enforcement gets faster and more automated.
Google’s blog post. Gemini is stopping harmful ads before people ever see them

602 million scam ads were removed, and 24.9 million accounts were suspended, according to Google's 2025 Ads Safety Report.

Gemini helped Google block more than 99% of bad ads before they ran

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search.png" class="attachment-large size-large wp-post-image" alt="Why your website is now the source of truth in local AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI may surface your business, but your website is where decisions happen. Learn how to structure content for visibility, trust, and action.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search.png" class="attachment-large size-large wp-post-image" alt="Why your website is now the source of truth in local AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-website-is-now-the-source-of-truth-in-local-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Open ChatGPT, then search for a local business you know has a strong online presence. Ask for a recommendation in that category. Chances are, it comes up. If you check what the AI cites as sources, you’ll almost certainly find the business’s own website in the mix.</p>



<p>That tells you something important: AI doesn’t conjure answers out of thin air. It pulls from whatever it can find. If your website isn’t the best, most complete, most authoritative source of information about your business, the AI will assemble its answer from scraps. You lose control of your own narrative.</p>



<p>That’s what’s driving a growing question among business owners and marketers: “Do I even need a website anymore? If AI answers everything, why does it matter?”</p>



<p>Your website isn’t just a marketing tool anymore. It’s a source document. AI treats it as an authoritative input. The real question is who gets to define your business: you or someone else. Here’s what’s changing, where conventional wisdom falls short, and what to do about it.</p>



<h2 class="wp-block-heading" id="h-zero-click-doesn-t-mean-zero-opportunity">Zero-click doesn’t mean zero opportunity</h2>



<p>A lot of marketers are seeing the same thing right now: impressions holding steady or rising, but clicks dropping. People get what they need without ever landing on a page, leading some to declare websites obsolete. That’s the wrong read.</p>



<p>Fewer clicks don’t mean less importance. They mean the nature of the click has changed. Look at where AI Overviews actually appear.</p>



<p>According to our analysis of Ahrefs data, of the 46 million+ keywords that trigger an AI Overview, nearly 99% are informational. Navigational keywords account for just 0.13%. Someone wanted a quick fact, got it, and moved on. Those were never high-intent visits anyway.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1489" height="245" src="https://searchengineland.com/wp-content/seloads/2026/04/AI-Overviews-99-are-informational.png" alt="AI Overviews - 99% are informational" class="wp-image-474393" srcset="https://searchengineland.com/wp-content/seloads/2026/04/AI-Overviews-99-are-informational.png 1489w, https://searchengineland.com/wp-content/seloads/2026/04/AI-Overviews-99-are-informational-768x126.png 768w" sizes="(max-width: 1489px) 100vw, 1489px" /></figure>
</div>


<p>The clicks that drive revenue, the ones tied to bookings, calls, purchases, and consultations, still happen. Commercial and transactional keywords make up just 12.5% and 3.5% of AI Overview triggers, respectively.&nbsp;</p>



<p>(<strong>Note:</strong> These percentages exceed 100% in total because keywords can carry multiple intent classifications, a single keyword can be both informational and commercial, for example.)&nbsp;</p>



<p>Those are exactly the queries where people are closest to a decision. They just happen further down the funnel, after a recommendation has already been made. When someone is ready to decide, they validate and check the website.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/homepage-matters-seo-474314">Your homepage matters again for SEO — here’s why</a></em></strong>



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<h2 class="wp-block-heading" id="h-ai-recommends-your-customer-decides-know-the-difference">AI recommends, your customer decides. Know the difference.</h2>



<p>When someone asks an AI assistant, “Who’s the best plumber near me?”, the AI might surface a few names. It’s pattern-matching based on reviews, location signals, website content, and business profile data. It’s offering a starting point, not a final verdict.</p>



<p>The AI isn’t picking up the phone or handing over a credit card. Especially for high-stakes local decisions, a contractor in your home, a doctor for your kid, a mechanic for your car, most people aren’t going to act on an algorithm’s suggestion without doing their own digging first.</p>



<p>What actually happens after the AI recommends? The customer:&nbsp;</p>



<ul class="wp-block-list">
<li>Googles the business. </li>



<li>Reads the reviews. </li>



<li>Looks at photos. </li>



<li>Checks the website to see if you offer exactly what they need, and at a price they can stomach.</li>
</ul>



<p>That validation phase is where decisions are made. And your website is at the center of it. AI might have gotten you in the door, but your website is what closes it.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/problem-brand-solves-ai-473427">If you can’t say what problem your brand solves, AI won’t either</a></em></strong>



<h2 class="wp-block-heading" id="h-ai-is-actually-making-your-website-more-valuable">AI is actually making your website more valuable</h2>



<p>AI systems are reading your content to determine what you do, who you serve, and how you help. They’re cross-referencing your site with your Google Business Profile, directory listings, and reviews to ensure consistency. </p>



<p>When everything lines up, they gain confidence recommending you. When it doesn’t, you get skipped. This means your website is now effectively a source document for AI. </p>



<p>Either it provides clear, structured information, or AI fills the gaps with third-party content — a stale Yelp review from 2019, an outdated directory listing with the wrong hours, or a competitor’s blog post that happens to rank well.</p>



<p>I know which one I’d rather have the AI pulling from.</p>



<p><strong><em>Dig deeper: </em></strong><a href="https://searchengineland.com/local-seo-ai-search-462083"><strong><em>Why local SEO is thriving in the AI-first search era</em></strong></a>



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<h2 class="wp-block-heading" id="h-the-visibility-gap-between-traditional-search-and-ai-is-enormous">The visibility gap between traditional search and AI is enormous</h2>



<p>If you want a sense of how selective AI is compared to traditional search, <a href="https://searchengineland.com/ai-local-visibility-report-2026-468085">SOCi’s 2026 Local Visibility Index</a>, which analyzed nearly 350,000 locations across 2,751 multi-location brands, puts it starkly:</p>



<ul class="wp-block-list">
<li>Only 1.2% of locations were recommended by ChatGPT.</li>



<li>11% by Gemini.</li>



<li>7.4% by Perplexity.</li>



<li>35.9% appeared in Google’s traditional local 3-pack.</li>
</ul>



<p>AI is up to 30 times more selective than traditional local search. Here’s the kicker: strong performance in the local pack doesn’t guarantee AI visibility.&nbsp;</p>



<p>SOCi found that in retail, only 45% of brands leading in traditional local search also appeared in AI recommendations. More than half were invisible to AI entirely.</p>



<p>The brands making it into AI recommendations?&nbsp;</p>



<p>The ones with accurate, consistent information across platforms, strong review volume and sentiment, and well-structured website content. That last one is where most local businesses are leaving the most value on the table.</p>



<h2 class="wp-block-heading" id="h-your-website-is-the-only-place-you-control-the-narrative">Your website is the only place you control the narrative</h2>



<p>Everywhere else — Google, Yelp, review sites, social media, and AI summaries — you’re at the mercy of other people’s opinions and platform algorithms. You don’t get to decide what gets shown or how it’s framed.</p>



<p>Your website is different. You decide what to highlight, the story to tell, and the objections to address. You can showcase what makes you different and guide visitors exactly where you want them to go.</p>



<p>More importantly, you can feed AI the narrative you want it to use. If your site has well-structured service pages, detailed FAQs, and content that answers real questions your customers ask, AI can pull directly from that when generating responses. You’re essentially writing your own introduction.</p>



<p>On the flip side, if your site is thin or generic, AI fills in the blanks with whatever else it can find. You lose the ability to define yourself.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/website-matters-ai-age-458829">Your website still matters in the age of AI</a></em></strong>



<h2 class="wp-block-heading" id="h-what-to-actually-do-about-it">What to actually do about it</h2>



<p>This doesn’t require a rebuild, just more intentional structure and content. Here’s where to focus.</p>



<h3 class="wp-block-heading" id="h-treat-your-website-as-a-source-of-truth">Treat your website as a source of truth</h3>



<p>Stop writing vague claims like “we’re the best in the business.” AI doesn’t know what to do with that. Write specific, factual, helpful content about what you do, who you serve, and what results you deliver.</p>



<p>Every piece of information on your website — your services, hours, location, and pricing approach — should align with what’s on your Google Business Profile and across your directory listings.</p>



<p>As Search Engine Land contributor Will Scott <a href="https://searchengineland.com/ai-local-search-visibility-roi-456272#:~:text=%E2%80%9CToday%2C%20LLMs%20can%20give%20you%20wrong%20information.%20Disambiguation%20through%20context%20is%20critical.%20So%20when%20they%20are%20building%20their%20ontologies%20%E2%80%93%20their%20map%20of%20relationships%20of%20knowledge%20%E2%80%93%20consistency%20matters%20a%20lot.%E2%80%9D">notes</a>: </p>



<ul class="wp-block-list">
<li>&#8220;Disambiguation through context is critical. When they&#8217;re building their ontologies, their map of relationships of knowledge, consistency matters a lot.&#8221;</li>
</ul>



<h3 class="wp-block-heading" id="h-structure-your-content-so-ai-can-actually-read-it">Structure your content so AI can actually read it</h3>



<p>AI reads for structure, not just keywords. An AirOps analysis of 217,508 retrieved pages found that only <a href="https://www.airops.com/report/from-retrieved-to-cited-how-commercial-content-earns-citations-in-ai-search" target="_blank" rel="noopener">15% of the pages</a> ChatGPT retrieves actually earn a citation in the response. </p>



<p>Being crawled isn’t enough. How your content is organized determines whether it gets used. That means:</p>



<ul class="wp-block-list">
<li><strong>Schema markup:</strong> Specifically LocalBusiness, FAQPage, and Service schemas. This cheat sheet tells AI and search engines exactly what your business is, what it offers, and where it’s located.</li>



<li><strong>Clear headings and short sentences: </strong>Use H2s and H3s to break content into scannable sections, and keep your sentences tight. The AirOps research found that pages averaging 11 to 14 words per sentence had roughly a 7% higher likelihood of being cited, likely because shorter sentences are easier for AI to parse and extract cleanly. Don’t bury critical information in long paragraphs.</li>



<li><strong>An FAQ section:</strong> Built around the actual questions you hear in emails, calls, and consultations. Write answers in natural language. This directly mirrors how people search conversationally, and AI loves it. The same research found that pages with 7 to 26 list sections were 6% to 15% more likely to earn a citation.</li>



<li><strong>Individual service pages: </strong>Not one catch-all “Services” page. Separate pages for each service with details about what’s included, who it’s for, and what to expect. Pages with 5 to 7 statistics supporting their claims had a 20% higher likelihood of being cited, so don’t just describe your services, back them up with specific, concrete details AI can confidently pull from.</li>
</ul>



<h3 class="wp-block-heading" id="h-write-for-your-customer-s-questions">Write for your customer&#8217;s questions</h3>



<p>Most business websites are written for the business, not the customer. Corporate speak, vague value propositions, and industry jargon nobody searched for. Customers don’t search for buzzwords. They search for questions:</p>



<ul class="wp-block-list">
<li>“Do you take my insurance?”</li>



<li>“How long does the repair take?”</li>



<li>“What’s the difference between [service A] and [service B]?”</li>



<li>“Can you help with [specific problem]?”</li>
</ul>



<p>If your website answers those questions directly and clearly, you become the best answer AI can find when someone asks. Not sure what questions your customers are actually asking?&nbsp;</p>



<p>Check your Google Business Profile Q&amp;A section, your customer service emails, transcripts of your calls or meetings, and your reviews. The questions are already in front of you.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-ai-visibility-they-ask-you-answer-469387">How to apply ‘They Ask, You Answer’ to SEO and AI visibility</a></em></strong>



<h3 class="wp-block-heading" id="h-do-an-ai-audit-of-your-own-business-right-now">Do an AI audit of your own business right now</h3>



<p>Here’s an exercise worth doing today: open ChatGPT, Perplexity, and Google AI Mode, and ask each one about your business. Ask contextual questions a real customer might ask, such as:&nbsp;</p>



<ul class="wp-block-list">
<li>“What do people say about [your business]?”</li>



<li>“Is [your business] good for [specific service]?”</li>
</ul>



<p>This is actually the first thing we do when onboarding a new client. We build a brand interpretation document.&nbsp;</p>



<p>It’s a snapshot of what AI systems currently know about a brand, pulled from the most important third-party sources in that industry. It tells us whether what’s being said about the brand is accurate, current, and coming from the right places, or whether it’s outdated, wrong, and sourced from somewhere you’d never choose yourself.</p>



<p>Ask your preferred AI what it knows about your business, then have it summarize consensus from key industry sources. Pay close attention to what comes back and where it came from. </p>



<ul class="wp-block-list">
<li>Is it citing your website? </li>



<li>Your Google Business Profile? </li>



<li>A review platform? </li>



<li>A third-party directory? </li>



<li>Is any of it inaccurate or out of date?</li>
</ul>



<p>That audit tells you exactly where your information gaps are and how to fix them.</p>



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<h2 class="wp-block-heading" id="h-what-s-at-stake-if-you-let-your-site-go-stale">What’s at stake if you let your site go stale</h2>



<p>If your website is thin, outdated, or poorly structured, AI fills the gaps with whatever it can find. That content may be inaccurate, negative, or just plain wrong. Maybe an old review mentions a service you no longer offer, or a directory has the wrong phone number. AI doesn’t fact-check. It aggregates.</p>



<p>Beyond accuracy, there’s the positioning problem. Without a strong website, what you’re known for and what makes you different gets shaped by third-party sources. Your expertise gets undersold. Your unique value gets lost in the noise.</p>



<p>AI might surface your name, but your website builds the trust that turns a recommendation into a call, a booking, or a sale. That’s where the decision happens.</p>



<p><strong><em>Dig deeper: </em></strong><a href="https://searchengineland.com/local-search-ai-enterprises-468255"><strong><em>How AI is reshaping local search and what enterprises must do now</em></strong></a>

Open ChatGPT, then search for a local business you know has a strong online presence. Ask for a recommendation in that category. Chances are, it comes up. If you check what the AI cites as sources, you’ll almost certainly find the business’s own website in the mix.
That tells you something important: AI doesn’t conjure answers out of thin air. It pulls from whatever it can find. If your website isn’t the best, most complete, most authoritative source of information about your business, the AI will assemble its answer from scraps. You lose control of your own narrative.
That’s what’s driving a growing question among business owners and marketers: “Do I even need a website anymore? If AI answers everything, why does it matter?”
Your website isn’t just a marketing tool anymore. It’s a source document. AI treats it as an authoritative input. The real question is who gets to define your business: you or someone else. Here’s what’s changing, where conventional wisdom falls short, and what to do about it.
Zero-click doesn’t mean zero opportunity
A lot of marketers are seeing the same thing right now: impressions holding steady or rising, but clicks dropping. People get what they need without ever landing on a page, leading some to declare websites obsolete. That’s the wrong read.
Fewer clicks don’t mean less importance. They mean the nature of the click has changed. Look at where AI Overviews actually appear.
According to our analysis of Ahrefs data, of the 46 million+ keywords that trigger an AI Overview, nearly 99% are informational. Navigational keywords account for just 0.13%. Someone wanted a quick fact, got it, and moved on. Those were never high-intent visits anyway.




The clicks that drive revenue, the ones tied to bookings, calls, purchases, and consultations, still happen. Commercial and transactional keywords make up just 12.5% and 3.5% of AI Overview triggers, respectively. 
(Note: These percentages exceed 100% in total because keywords can carry multiple intent classifications, a single keyword can be both informational and commercial, for example.) 
Those are exactly the queries where people are closest to a decision. They just happen further down the funnel, after a recommendation has already been made. When someone is ready to decide, they validate and check the website.
Dig deeper: Your homepage matters again for SEO — here’s why




  
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AI recommends, your customer decides. Know the difference.
When someone asks an AI assistant, “Who’s the best plumber near me?”, the AI might surface a few names. It’s pattern-matching based on reviews, location signals, website content, and business profile data. It’s offering a starting point, not a final verdict.
The AI isn’t picking up the phone or handing over a credit card. Especially for high-stakes local decisions, a contractor in your home, a doctor for your kid, a mechanic for your car, most people aren’t going to act on an algorithm’s suggestion without doing their own digging first.
What actually happens after the AI recommends? The customer: 
Googles the business. 
Reads the reviews. 
Looks at photos. 
Checks the website to see if you offer exactly what they need, and at a price they can stomach.
That validation phase is where decisions are made. And your website is at the center of it. AI might have gotten you in the door, but your website is what closes it.
Dig deeper: If you can’t say what problem your brand solves, AI won’t either



AI is actually making your website more valuable
AI systems are reading your content to determine what you do, who you serve, and how you help. They’re cross-referencing your site with your Google Business Profile, directory listings, and reviews to ensure consistency. 
When everything lines up, they gain confidence recommending you. When it doesn’t, you get skipped. This means your website is now effectively a source document for AI. 
Either it provides clear, structured information, or AI fills the gaps with third-party content — a stale Yelp review from 2019, an outdated directory listing with the wrong hours, or a competitor’s blog post that happens to rank well.
I know which one I’d rather have the AI pulling from.
Dig deeper: Why local SEO is thriving in the AI-first search era




	
	
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See terms.
		
The visibility gap between traditional search and AI is enormous
If you want a sense of how selective AI is compared to traditional search, SOCi’s 2026 Local Visibility Index, which analyzed nearly 350,000 locations across 2,751 multi-location brands, puts it starkly:
Only 1.2% of locations were recommended by ChatGPT.
11% by Gemini.
7.4% by Perplexity.
35.9% appeared in Google’s traditional local 3-pack.
AI is up to 30 times more selective than traditional local search. Here’s the kicker: strong performance in the local pack doesn’t guarantee AI visibility. 
SOCi found that in retail, only 45% of brands leading in traditional local search also appeared in AI recommendations. More than half were invisible to AI entirely.
The brands making it into AI recommendations? 
The ones with accurate, consistent information across platforms, strong review volume and sentiment, and well-structured website content. That last one is where most local businesses are leaving the most value on the table.
Your website is the only place you control the narrative
Everywhere else — Google, Yelp, review sites, social media, and AI summaries — you’re at the mercy of other people’s opinions and platform algorithms. You don’t get to decide what gets shown or how it’s framed.
Your website is different. You decide what to highlight, the story to tell, and the objections to address. You can showcase what makes you different and guide visitors exactly where you want them to go.
More importantly, you can feed AI the narrative you want it to use. If your site has well-structured service pages, detailed FAQs, and content that answers real questions your customers ask, AI can pull directly from that when generating responses. You’re essentially writing your own introduction.
On the flip side, if your site is thin or generic, AI fills in the blanks with whatever else it can find. You lose the ability to define yourself.
Dig deeper: Your website still matters in the age of AI



What to actually do about it
This doesn’t require a rebuild, just more intentional structure and content. Here’s where to focus.
Treat your website as a source of truth
Stop writing vague claims like “we’re the best in the business.” AI doesn’t know what to do with that. Write specific, factual, helpful content about what you do, who you serve, and what results you deliver.
Every piece of information on your website — your services, hours, location, and pricing approach — should align with what’s on your Google Business Profile and across your directory listings.
As Search Engine Land contributor Will Scott notes: 
“Disambiguation through context is critical. When they’re building their ontologies, their map of relationships of knowledge, consistency matters a lot.”
Structure your content so AI can actually read it
AI reads for structure, not just keywords. An AirOps analysis of 217,508 retrieved pages found that only 15% of the pages ChatGPT retrieves actually earn a citation in the response. 
Being crawled isn’t enough. How your content is organized determines whether it gets used. That means:
Schema markup: Specifically LocalBusiness, FAQPage, and Service schemas. This cheat sheet tells AI and search engines exactly what your business is, what it offers, and where it’s located.
Clear headings and short sentences: Use H2s and H3s to break content into scannable sections, and keep your sentences tight. The AirOps research found that pages averaging 11 to 14 words per sentence had roughly a 7% higher likelihood of being cited, likely because shorter sentences are easier for AI to parse and extract cleanly. Don’t bury critical information in long paragraphs.
An FAQ section: Built around the actual questions you hear in emails, calls, and consultations. Write answers in natural language. This directly mirrors how people search conversationally, and AI loves it. The same research found that pages with 7 to 26 list sections were 6% to 15% more likely to earn a citation.
Individual service pages: Not one catch-all “Services” page. Separate pages for each service with details about what’s included, who it’s for, and what to expect. Pages with 5 to 7 statistics supporting their claims had a 20% higher likelihood of being cited, so don’t just describe your services, back them up with specific, concrete details AI can confidently pull from.
Write for your customer’s questions
Most business websites are written for the business, not the customer. Corporate speak, vague value propositions, and industry jargon nobody searched for. Customers don’t search for buzzwords. They search for questions:
“Do you take my insurance?”
“How long does the repair take?”
“What’s the difference between [service A] and [service B]?”
“Can you help with [specific problem]?”
If your website answers those questions directly and clearly, you become the best answer AI can find when someone asks. Not sure what questions your customers are actually asking? 
Check your Google Business Profile Q&A section, your customer service emails, transcripts of your calls or meetings, and your reviews. The questions are already in front of you.
Dig deeper: How to apply ‘They Ask, You Answer’ to SEO and AI visibility



Do an AI audit of your own business right now
Here’s an exercise worth doing today: open ChatGPT, Perplexity, and Google AI Mode, and ask each one about your business. Ask contextual questions a real customer might ask, such as: 
“What do people say about [your business]?”
“Is [your business] good for [specific service]?”
This is actually the first thing we do when onboarding a new client. We build a brand interpretation document. 
It’s a snapshot of what AI systems currently know about a brand, pulled from the most important third-party sources in that industry. It tells us whether what’s being said about the brand is accurate, current, and coming from the right places, or whether it’s outdated, wrong, and sourced from somewhere you’d never choose yourself.
Ask your preferred AI what it knows about your business, then have it summarize consensus from key industry sources. Pay close attention to what comes back and where it came from. 
Is it citing your website? 
Your Google Business Profile? 
A review platform? 
A third-party directory? 
Is any of it inaccurate or out of date?
That audit tells you exactly where your information gaps are and how to fix them.
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What’s at stake if you let your site go stale
If your website is thin, outdated, or poorly structured, AI fills the gaps with whatever it can find. That content may be inaccurate, negative, or just plain wrong. Maybe an old review mentions a service you no longer offer, or a directory has the wrong phone number. AI doesn’t fact-check. It aggregates.
Beyond accuracy, there’s the positioning problem. Without a strong website, what you’re known for and what makes you different gets shaped by third-party sources. Your expertise gets undersold. Your unique value gets lost in the noise.
AI might surface your name, but your website builds the trust that turns a recommendation into a call, a booking, or a sale. That’s where the decision happens.
Dig deeper: How AI is reshaping local search and what enterprises must do now

AI may surface your business, but your website is where decisions happen. Learn how to structure content for visibility, trust, and action.

Why your website is now the source of truth in local AI search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/How-to-fix-a-suspended-Google-Merchant-Center-account.png" class="attachment-large size-large wp-post-image" alt="How to fix a suspended Google Merchant Center account" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/How-to-fix-a-suspended-Google-Merchant-Center-account.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/How-to-fix-a-suspended-Google-Merchant-Center-account-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/How-to-fix-a-suspended-Google-Merchant-Center-account-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/How-to-fix-a-suspended-Google-Merchant-Center-account-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Identify why your Merchant Center was flagged, audit your site and feed, and fix issues before requesting a review.

Google has unique policies for Google Shopping that are stricter than its general advertising policies. If Google thinks you’ve violated any of them, it can suspend your Merchant Center.
That cuts off access to Google Shopping, Local Inventory Ads, product feeds in Performance Max and dynamic remarketing, and free listings for products. That means losing your highest-ROI channel overnight.
Here’s how Google’s system works — and what you can do to fix suspensions and get back online.
Case study: How we reinstated a suspended Merchant Center
A UK-based ecommerce retailer came to us after their Google Merchant Center account was suspended for “Misrepresentation,” cutting off their Shopping ads entirely.
Like many legitimate merchants, they were blindsided. Their store was real, their products were accurate, and they had no idea what Google’s specific objection was.
We started with a full compliance audit of their website and Merchant Center account, working through every area Google scrutinizes.
What we found wasn’t one big violation. It was a long list of smaller gaps that, in combination, signaled untrustworthiness to Google’s systems.
The website’s Contact Us page lacked a physical address, a domain-based email address, and clear customer service hours, all of which Google expects from a legitimate business.
Their policy pages (shipping, returns, refunds, and payment) either didn’t exist or lacked the specific detail Google looks for. Missing elements included cancellation windows, defective item procedures, and accepted payment methods.
Beyond policies, their site lacked an order tracking feature and a cookie consent mechanism (required under UK law). A bot blocker was preventing Google’s automated crawlers from crawling the site.
Inside Google Merchant Center itself, Shopify’s automatic shipping sync was creating conflicting data. 
We documented every required change in detail and handed the client a clear, prioritized action list. Once they made all the changes, we requested a review from Google.
Google approved the appeal and reinstated the account.
Key takeaway: Google evaluates the totality of your website and feed, not just individual policy pages. A successful reinstatement almost always requires fixing multiple issues across your site before submitting an appeal.
Dig deeper: Google Ads account suspensions: What advertisers need to know




  
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Step 1: Identify the type of suspension
Google will email you the policy they believe you’ve violated.




You can also find this information on the Needs attention tab in your Merchant Center.




Read the suspension notice carefully because Google’s description, vague as it often is, will be your starting point for the following audit steps.
Misrepresentation
Misrepresentation is the most common policy we see cited for Google Merchant Center suspensions.
This policy covers a wide range of problems, from inaccurate information in Merchant Center, to missing policy pages on your website, to bad reviews about your business on third-party websites.
Follow the steps outlined in this guide to focus on improving four key areas:
Your Merchant Center settings.
Your product feed.
Your website.
Your online reputation.
Counterfeit products
You’re most likely to see this suspension reason if you’re reselling products from other brands (such as Pokémon cards, Prada bags, or Nike sneakers).
Helpful actions to take:
Say on your website whether you have a relationship with the manufacturer.

Are you an authorized reseller?
Do you purchase directly from the manufacturer?
Do you purchase from third parties?
Explain your authentication process.
Don’t list prices significantly lower than the manufacturer’s suggested retail price (MSRP).
Website needs improvement
Rather than citing a specific policy violation, Google is flagging that your website doesn’t appear sufficiently complete or functional.




Use incognito mode and multiple devices to check your website for:
Placeholder images or text.
Missing policy pages.
Problems adding products to cart or finishing the checkout process.
Unsupported shopping content
Google has a list of things that can be advertised via “regular” Google ads, but not via Google Shopping.
Services as a whole may not be advertised, which is why you won’t see ads for lawyers, doctors, or consultants on Google Shopping.
It gets tricky when services are bundled with products (you can advertise car tires, but you can’t advertise the labor to replace the tires on your car).
Google tends to aggressively flag things as services, or unsupported digital goods, that don’t actually fall within those policies.
What to do:
Separate services from physical products on your website.
Add explanation text to product pages clearly stating that what you’re selling is a physical good and not a service.
Avoid keywords like ebook and PDF that could trigger Google to think you’re selling disallowed digital goods.
Healthcare and medicines
Google restricts advertising healthcare-related products. The policies are country-specific, so be sure to carefully read the policy for the country, or countries, you’re targeting.
To sell prescription and over-the-counter drugs in the U.S., advertisers must undergo third-party certification through a company such as LegitScript and a separate certification process with Google.
Google explicitly lists pharmaceuticals and supplements that aren’t allowed to be advertised. Unfortunately, this list is not comprehensive. We’ve had cases where Google support informed us that products not on this list are not allowed to be advertised.
What to do:
Get certified (if you meet the certification requirements).
Avoid making claims about the benefits of what you sell that can’t be directly verified by linking to studies from your product pages.
Add appropriate disclaimers to your product pages and customer testimonials.
Dig deeper: A guide to Google Ads for regulated and sensitive categories



DMCA violation
If someone reports your website for content that violates the Digital Millennium Copyright Act (DMCA), Google will suspend your Merchant Center. These reports are filed in the Lumen database, where you can see what content has been flagged and when the report was made.
What to do:
If you’re violating copyright, remove the content from your website.
If you’re not violating copyright, document how this content is original to your website and why you believe the report was wrong.
After requesting a review of your suspension, you will probably have to engage in back-and-forth with Google support to argue why you should be allowed back on their platform.
Step 2: Audit your Merchant Center settings
Merchant Center settings are misconfigured in almost every suspension case we work on.
Go through every single page in your Merchant Center to make sure you’ve entered as much information as possible and that everything you’ve entered is accurate and matches what’s on your website.
Business info





Your store name must comply with Google’s policies.
Your physical address needs to be exactly right (no misplaced words or numbers) and should match the physical address on your website’s Contact page.
You should have accurate contact information, and a link to your Contact page, and relevant social media profiles.
Shipping and returns





Every product in your feed needs to be covered by at least one shipping rule and a return policy.
The shipping methods, handling and shipping times, cost structure, return timeline, refund process, exceptions, and restocking fees need to exactly match the information on the Shipping and Returns policy pages on your website.
Step 3: Audit your product feed data quality
Think of your product feed as your ads. Just as saying inaccurate things in your ads can lead to disapprovals, providing inaccurate or insufficient product data to Google can result in item disapprovals and account suspensions.




Item disapprovals
In addition to account-level suspensions, Google often disapproves specific products for product-level violations.




There are many things that can cause item disapprovals. Top issues include:
Links or images that don’t load.
Mismatches between pricing or availability.
Missing weight or shipping information.
Invalid GTINs.
Unsupported product categories like weapons, digital goods, or services.
These problems don’t necessarily cause account suspensions, but you should fix as many as possible before requesting a review. You want Google to see you as committed to sending high-quality data and not violating any of their policies.
Wrong prices and URLs
The price in your product feed must match the price shown when someone lands on that product’s page. Two common mistakes:
Using a parent product URL with a product variant’s price, which causes a mismatch between the price in the ad and the price on the product page.
Putting a sale price in the feed that is not on the product page, or vice versa.
GTINs
Global Trade Identification Numbers (GTINs) are the numbers, such as UPCs and ISBNs, that manufacturers assign to their products.
If your products don’t have GTINs, you can set the value of the field identifier_exists in your feed to FALSE.
If your products have GTINs and you have access to them, send those numbers to Google in your feed.
You don’t have to send a GTIN, but if you do, it must be accurate.
We’ve seen cases where advertisers created fake GTINs, thinking it would help their products perform better. Instead, Google suspended the entire account.
Copied product photos and descriptions
Resellers who copy product images and descriptions from manufacturers may run into problems, especially if you don’t provide the product GTINs in the feed.
Ideally, you should take your own product images and write your own product descriptions, so that everything on your website is original.
Dig deeper: Google Ads’ three-strikes system: Managing warnings, strikes, and suspension




	
	
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Step 4: Audit your website
Even if your Merchant Center settings and product feed are clean, your website itself can be the reason you’re suspended.
Crawl issues
Google will suspend your account if they’re not able to crawl your website.
For example, we’ve seen clients block visits from countries from which a high volume of spam traffic was originating. This accidentally blocked Google’s robots from accessing the website and caused a suspension.
We’ve also seen mistakes with the robots.txt file accidentally excluding Google’s bots from accessing key pages, which looks to Google like you’re trying to hide something.
Missing information
You need clear and distinct policy pages on your website, including:
Privacy.
Shipping.
Refund and return.
Terms of service.
Order tracking.
Payment.
You also need accurate contact information on your Contact page and a comprehensive About page.
Inaccurate or inconsistent information
Any claims you make on your website must be true. For example, if you say you offer free shipping on orders over $25, then you have to actually give free shipping when a cart value is greater than $25.
We often see inconsistencies on websites, such as:
Different return windows mentioned on the Return policy page than in the Return policy pop-up on the Shopify checkout page.
Old phone numbers that no longer work and haven’t been removed.
Template language referencing other businesses or products you don’t sell that you never removed from policy pages.
Badges and awards
Adding badges and awards (such as the Better Business Bureau badge and Trustpilot review widgets) to your website is a way to demonstrate credibility.
When you add badges, awards, or “As seen on” logos to your website, make sure to hyperlink them to supporting pages, or else Google may think you’re making unsupported claims.
Step 5: Audit your digital footprint
Google wants only trusted businesses to run Google Shopping ads, so they look beyond your website and Merchant Center at your digital footprint as a whole.
Reviews
If you don’t have reviews on third-party websites like Trustpilot and BBB, or worse, if there are many negative reviews about your business, Google will view you with more suspicion.
Make a focused effort to ask your customers for reviews and respond professionally to all reviews (positive or negative), so that Google sees you’re an active, engaged business.
Social media
Google expects websites to have profiles on social media platforms like Facebook and Instagram.
There is even a place in your Merchant Center where you can directly link to your social profiles.
It can be helpful to claim profiles for your business and make sure that your business info in those profiles (domain, phone number, physical and email addresses) match what’s on your website.
Authorized resellers
If you’re an authorized reseller for another brand, establish as much of a connection to that brand online as possible. For example:
Ask the brand to link to your website from their social media profiles and website.
Post any information you’re legally allowed to share about your contract on your website so that Google sees you’re being transparent.
Create an authentication guide that details how you authenticate the products you sell.
Step 6: Request a review
After you have followed steps 1-5 to identify and fix as many potential problems as possible, you are ready to ask Google to review your suspension.
To request a review:
Log in to your Google Merchant Center account.
Click Products & store.
Click Products.
Click Needs attention.
In the box that says “Suspended account for policy violation,” click Fix.
Click the button labeled “I disagree with the issue.”




Google sometimes makes the button unclickable until you go through identity verification, and in some cases, it also requires a video verification process.
Google doesn’t let you write any context when you request a review. Clicking the button is your only option.
Google limits how many reviews you may request. The limit varies per account, but often is three or less. Once you’ve reached that limit, Google will tell you that it will no longer accept additional review requests, and the button will no longer be clickable.
Google will not review your appeal unless there is at least one product in your Merchant Center.
What if I’m suspended for multiple things?
Google sometimes flags Merchant Centers with multiple policy violations at the same time. Fix everything possible on your website and in your account, and then appeal the suspensions one at a time.
Start with the suspension that looks the most comprehensive. For example, misrepresentation is a more “egregious” suspension in Google’s eyes than sale of service, so start by appealing the former.
If one policy issue is a suspension and another is a warning (suspended for misrepresentation and warned for website needs improvement), appeal the warning first.
Common questions about Google Merchant Center suspensions
Why is my Google Merchant Center suspended?
Google will tell you what policy it believes you’ve violated via email, and in a notification in the “Needs Attention” tab in your Merchant Center.
These policies are usually quite broad, and narrowing down exactly why you were suspended can be difficult, which is why it’s vital that you fix as many potential problems as possible before appealing your suspension.
How long does a Google Merchant Center suspension last?
In most cases, it lasts forever unless you successfully appeal the suspension.
That said, we’ve seen cases where Google re-crawled a website after changes were made and automatically reinstated an account prior to the advertiser requesting a review (but don’t count on this happening).
Can Google Merchant Center support help me?
Sometimes, if you know how to ask the right questions, Google Merchant Center support will provide some ideas about what went wrong, or will point to specific data issues with your products.
What happens if Google rejects my appeal?
Typically, Google will put your Merchant Center into a cool-down period during which you can’t request another review.
The first cool-down period is usually seven days, and the timeline gets longer with subsequent rejections.
How many times can I appeal a Google Merchant Center suspension?
Google typically limits appeals to between one and three attempts, though exceptions exist.
Why does Google keep suspending my Merchant Center account?
It’s not uncommon for Google to accept an appeal of a Merchant Center suspension and then suspend that account again for the same policy.
This could be due to Google’s automated systems re-flagging you for something that its manual reviewers decided was not a violation.
It could also be because Google is unfortunately inconsistent with how it flags policy violations and enforces its policies.
Can I ask customers to write reviews of my business online?
You can. If you’re sending product reviews to Merchant Center, you must disclose to Google if you incentivize customers to leave reviews.
Dig deeper: Dealing with Google Ads frustrations: Poor support, suspensions, rising costs




  
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Preventing Google Merchant Center suspensions
All of the steps outlined in this guide to fix suspensions are things you should proactively do to help prevent suspensions from happening.
Doing these things before you’re suspended can potentially save you tremendous time, frustration, and opportunity cost.
Here are a few more ideas to help stop suspensions:
Check your website weekly via incognito mode on mobile and desktop devices to make sure your website functions properly.
Get a real physical business address, and feature that address on your Contact page and in your website footer.
Regularly ask your clients to write reviews about you, and respond professionally to every single review.
Consistently read the policies on your website to make sure they are still accurate, and update them immediately if you change your processes.
Monitor your Merchant Center daily for disapprovals, and quickly fix anything that Google says needs attention.
Google has policies in place because it wants to protect consumers.
By following Google’s policies and showing that you’re a legitimate advertiser, you can protect your ability to use one of the most important channels available for growing an ecommerce brand.

Identify why your Merchant Center was flagged, audit your site and feed, and fix issues before requesting a review.

How to fix a suspended Google Merchant Center account

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/Why-log-file-analysis-matters-for-AI-crawlers-and-search-visibility.png" class="attachment-large size-large wp-post-image" alt="Why log file analysis matters for AI crawlers and search visibility" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Why-log-file-analysis-matters-for-AI-crawlers-and-search-visibility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/Why-log-file-analysis-matters-for-AI-crawlers-and-search-visibility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/Why-log-file-analysis-matters-for-AI-crawlers-and-search-visibility-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/Why-log-file-analysis-matters-for-AI-crawlers-and-search-visibility-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Track how AI crawlers access your site, identify crawl gaps, and understand what content gets missed using log file data.

One of the biggest challenges in AI search is that visibility is being shaped by systems you can’t directly observe.
Nothing like Google Search Console exists for ChatGPT, Claude, or Perplexity. No reporting layer showing what’s crawled, how often, or whether your content is considered at all.
Yet these systems are actively crawling the web, building datasets, powering retrieval, and generating answers that shape discovery — often without sending traffic back to the source.
This creates a gap. In traditional SEO, performance and behavior are connected. You can see impressions, clicks, indexing, and some level of crawl data. In AI search, that feedback loop doesn’t exist.
Log files are the closest thing to that missing layer. They don’t summarize or interpret activity. They record it — every request, every URL, every crawler. 
For AI systems, that raw data is often the only way to understand how your site is actually being accessed.
Some visibility is emerging — just not from AI platforms
That lack of visibility hasn’t gone entirely unaddressed. 
Bing is one of the first platforms to introduce this natively. Through Bing Webmaster Tools, Copilot-related insights are beginning to show how AI-driven systems interact with websites. It’s still early, but it’s a meaningful shift — and the first real example of an AI system exposing even part of its behavior to site owners.
Beyond that, a new category of tools is emerging. Platforms like Scrunch, Profound, and others focus on AI visibility, tracking how content appears in AI-generated responses and how different agents interact with a site. 
In some cases, they connect directly to sources like Cloudflare or other traffic layers, making it easier to monitor crawler activity without manually exporting and analyzing raw logs.
That visibility is useful, especially as AI systems evolve quickly. But it isn’t complete. 
Most of these tools operate within a defined window. Some only surface a limited timeframe of agent activity, making them effective for near-term monitoring, but less useful for understanding longer-term patterns or changes in crawl behavior.
AI crawler activity isn’t consistent. Unlike Googlebot, which crawls continuously, many AI agents appear sporadically or in bursts. Without historical data, it’s difficult to determine whether a change in activity is meaningful or normal variation.
Log files solve for that. They provide a complete, unfiltered record of crawler behavior — every request, every URL, every user agent. With continuous retention, they enable analysis of patterns over time and revisiting data when something changes.
Dig deeper: Log file analysis for SEO: Find crawl issues & fix them fast




  
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Not all AI crawlers behave the same way
In log files, everything appears as a user agent string. On the surface, it’s easy to treat them the same, but they represent different systems with different objectives. That distinction matters, because it directly affects how they access and interact with your site.
AI-related crawlers generally fall into two groups: training and retrieval.
Training crawlers
Training crawlers, such as GPTBot, ClaudeBot, CCBot, and Google-Extended, collect content for large-scale datasets and model development. 
Their activity isn’t tied to real-time queries, and they don’t behave like traditional search crawlers. You’ll typically see them less frequently, and when they do appear, their crawl patterns are broader and less targeted.
Because of that, their presence – or absence – carries a different implication. If these crawlers don’t appear in your logs at all, it’s not just a crawl issue. It raises the question of whether your content is included in the datasets that influence how AI systems understand topics over time.
At the same time, it’s important to consider how much data you’re analyzing. Training crawlers don’t operate on a continuous crawl cycle like Googlebot. 
Their activity is often sporadic, which means a short log window (a few hours, or even a single day) can be misleading. You may not see them simply because they haven’t crawled within that timeframe.
That’s why analyzing log data over a longer period matters. It helps distinguish between true absence and normal variation in how these systems crawl.
Retrieval and answer crawlers
Retrieval crawlers operate differently. Agents like ChatGPT-User and PerplexityBot are more closely tied to live, or near-real-time, responses. Their activity tends to be event-driven and more targeted, often limited to a small number of URLs.
That makes their behavior less predictable and easier to misinterpret. You won’t see the same volume or consistency you would from Googlebot, but patterns still matter. 
If these crawlers never reach deeper content, or consistently stop at top-level pages, it can indicate limitations in how your site is discovered or accessed.
Traditional crawlers still matter, but they’re no longer the full picture
Googlebot and Bingbot still provide the baseline. Their crawl behavior is consistent and typically gives a reliable view of how well your site can be discovered and indexed.
The difference is that AI crawlers don’t always follow the same paths. It’s common to see strong, deep crawl coverage from Googlebot alongside much lighter, or more shallow, interaction from AI systems. That gap doesn’t show up in Search Console, but becomes clear in log files.
What AI crawler behavior actually tells you
Once you isolate AI crawlers in your log files, the goal isn’t just to confirm they exist. It’s to understand how they interact with your site – and what that behavior implies about visibility.
AI systems crawl the web to train models, build retrieval indexes, and support generative answers. But unlike Googlebot, there’s very little direct visibility into how that activity plays out.
Log files make that behavior observable. There are a few key patterns to focus on.
Discovery: Are you being accessed at all?
Start by checking whether AI crawlers appear in your logs.
In many cases, they don’t — or appear far less frequently than traditional search crawlers. That doesn’t always indicate a technical issue, but highlights how differently these systems discover and access content.
If AI crawlers are completely absent, they may be blocked in robots.txt, rate-limited at the server or CDN level, or simply not discovering your site.
Presence alone is a signal. Absence is one too.
Crawl depth: How far into your site do they go?
When AI crawlers do appear, the next question is how far they get.
It’s common to see them limited to top-level pages – the homepage, primary navigation, and a small number of high-level URLs. Deeper content, including long-tail pages, or location-specific content, is often untouched.
If crawlers aren’t reaching those sections, they’re not seeing the full structure of your site. That limits how much context they can build and reduces the likelihood that deeper content is surfaced in AI-generated responses.
Crawl paths: How AI systems actually see your site
When AI crawlers access a site, they don’t build a comprehensive map the way traditional search engines do. 
Their behavior is more selective and influenced by what’s immediately accessible, which means your site structure plays a larger role in what they reach.
In log files, this appears as concentrated activity around a small set of URLs. 
Requests are typically clustered around the homepage, primary navigation, and pages that are directly linked, or easy to discover. 
As you move deeper into the site, crawl activity often drops off, sometimes sharply, even when those pages are important from a business, or SEO, perspective.
The practical implication: pages buried behind JavaScript-heavy navigation, or weak internal linking, are significantly less likely to be accessed.
As a result, the version of your site AI systems interact with is often incomplete. Entire sections can be effectively invisible because they sit outside the paths these crawlers can follow. 
This is where log file analysis becomes particularly useful, because it exposes the difference between what exists and what’s actually accessed.
Crawl friction: Where access breaks down
Log files also surface where crawlers encounter issues. This includes:
403 responses (blocked requests).
429 responses (rate limiting).
Redirects and redirect chains.
Unexpected status codes.
For AI crawlers, these issues can have an outsized impact. Their activity is already limited, and failed requests reduce the likelihood they continue deeper into the site.
Cross-system comparison: How does this differ from Googlebot?
Comparing AI crawler behavior to Googlebot provides useful context.
Googlebot typically shows consistent, deep crawl coverage across a site. AI crawlers often behave differently – appearing less frequently, accessing fewer pages, and stopping at shallower levels.
That difference highlights where your site is accessible for traditional search, but not necessarily for AI-driven systems. As those systems become more influential in discovery, crawl accessibility becomes a multi-system concern – not just a Google one.
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How to analyze AI crawler behavior with log files
You don’t need a complex setup to start getting value from log files. Most hosting platforms retain access logs by default, even if only for a short window.
You’ll find that retention varies across hosting providers, but it’s often limited to anywhere from a few hours to a few days. Kinsta, for example, typically retains logs for a short rolling window, which is enough to get started but not for long-term analysis.
Start with the logs you already have
The first step is simply to export access logs from your hosting environment.
Even a small dataset can surface useful patterns, particularly when you’re looking for presence, crawl paths, and obvious gaps. At this stage, you’re not trying to build a complete picture over time. You’re looking for directional insight into how different crawlers are interacting with your site right now.
Use a log analysis tool to make the data usable
Raw log files are difficult to work with directly, especially at scale.
Tools like Screaming Frog Log File Analyzer make it possible to process that data quickly. Logs can be uploaded in their raw format and broken down by user agent, URL, and response code, allowing you to move from raw requests to structured analysis without additional preprocessing.
This is where the data becomes usable.




Segment by crawler type
Once the logs are loaded, segmentation becomes the priority. Start by isolating user agents so you can compare AI crawlers, Googlebot, and Bingbot.
This is critical, because behavior varies significantly across systems. Without segmentation, everything blends together. With it, patterns start to emerge.
To filter your views by bot, select your bot at the top right of the Log File Analyser. This will update all subsequent analysis to the bot you’ve selected.
You can begin to see:
Whether AI crawlers appear at all.
How their activity compares to traditional search.
Whether their behavior aligns or diverges.
Analyze crawl behavior against your site structure
From there, shift from presence to behavior.
Look at which URLs are being accessed, how frequently they appear, and how that maps to your site structure. This is where the earlier analysis becomes practical.
You’re not just asking what was crawled. You’re asking:
Are crawlers reaching deeper content?
Which sections of the site are being skipped entirely?
Does this align with how your site is structured and linked?
This is where crawl paths, accessibility, and prioritization start to surface as real, observable patterns.
Use response codes to identify friction
Filtering by response code adds another layer of insight.
This helps surface where crawlers are encountering issues, including:
Blocked requests.
Rate limiting.
Redirect chains.
Unexpected responses.
For AI crawlers, these issues can have a greater impact. Their activity is already limited, so failed requests reduce the likelihood that they continue further into the site.
Cross-reference crawlable vs. crawled
One of the most valuable steps is comparing what can be crawled with what is actually being crawled.
Running a standard crawl alongside your log analysis allows you to identify this gap directly. Pages that are accessible in theory, but never appear in logs, represent missed opportunities for discovery.
Understand what your logs don’t show
As you work through log data, it’s also important to understand its limitations.
Server-level logs only capture requests that reach your origin. In environments that include a CDN, or security layer like Cloudflare, some requests may be filtered before they ever reach the site. That means certain crawler activity, particularly blocked, or rate-limited, requests, won’t appear in your logs at all.
This becomes relevant when interpreting absence. If specific AI crawlers don’t appear in your data, it doesn’t always mean they aren’t attempting to access the site. In some cases, they may be getting filtered upstream.
How to scale: Continuous log retention
Log file analysis breaks down quickly if you’re only looking at short timeframes.
A few hours of data, or even a single day, can show you what happened. It can also make it look like nothing is happening at all. With AI crawlers, that distinction matters.
Their activity isn’t continuous. Training crawlers may appear intermittently, and retrieval agents are often tied to specific events or queries. 
A short log window can easily lead you to the wrong conclusion. A crawler that doesn’t appear in your data may still be active. It just hasn’t shown up within that window.
This is where retention changes the analysis. Once you’re working with a longer dataset, you’ll see how often it appears, where it shows up, and whether that behavior is consistent over time. What looked like absence starts to resolve into patterns.
Moving beyond your hosting limits
At that point, the limitation isn’t analysis. It’s access to data over time.
Most hosting environments aren’t designed for long-term log retention. Even when logs are available, they’re typically tied to a short rolling window. That makes it difficult to revisit behavior, compare time periods, or understand how crawler activity evolves.
To get beyond that, you need to store logs outside of your hosting environment. Log storage options include: 
Amazon S3 is one of the most common approaches. It provides flexible, low-cost storage that allows you to retain logs continuously and query them when needed. If the goal is to build a historical view of crawler behavior, it’s a practical and widely supported option.
Cloudflare R2 serves a similar purpose and can be a better fit for sites already using Cloudflare. It keeps storage within the same ecosystem and simplifies how log data is handled, particularly when edge-level logging is part of the setup.
The specific platform matters less than the shift itself. You’re moving from whatever your host happened to keep to a dataset you control.
Bridging the gap with automation
Not every setup supports continuous streaming, and most teams aren’t going to build that infrastructure upfront.
If your retention window is limited, automation becomes the practical way to extend it.
Instead of manually downloading logs, you can schedule the process. Many hosting providers expose logs over SFTP, which makes it possible to pull them at regular intervals before they expire.
A scheduled SFTP job – whether built in a workflow tool like n8n, or scripted – is enough to turn a short retention window into something you can actually analyze over time. That’s often the difference between one-off analysis and something repeatable.

  
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Getting closer to a complete view
As your dataset grows, so does the need to understand its boundaries. Log files show you what reached your site. They don’t always show you what tried to.
In environments that include a CDN, or security layer, some requests may be filtered before they reach your origin. That becomes more noticeable over time, particularly when certain crawlers appear less frequently than expected.
At that point, edge-level logging becomes a useful addition. It provides visibility into requests that are blocked or filtered upstream and helps explain gaps in origin-level data.
It’s not required to get value from log analysis, but it becomes relevant once you’re trying to build a more complete picture of crawler behavior across systems.
Log files show you what reached your site. They don’t show everything, but they’re the only place this interaction becomes visible at all.
You’re not optimizing for one crawler anymore. And the teams that start measuring this now won’t be guessing later.

Track how AI crawlers access your site, identify crawl gaps, and understand what content gets missed using log file data.

Why log file analysis matters for AI crawlers and search visibility

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes.png" class="attachment-large size-large wp-post-image" alt="Why your Google Ads results keep repeating the same outcomes" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Ads is trained by what you reinforce over time. That’s why results repeat — it learns what gets funded and sustained.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes.png" class="attachment-large size-large wp-post-image" alt="Why your Google Ads results keep repeating the same outcomes" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/Why-your-Google-Ads-results-keep-repeating-the-same-outcomes-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Paid search success used to be driven by optimizations. You adjusted bids, restructured campaigns, refined match types, and added negatives. Performance moved accordingly.</p>



<p>That’s still how many accounts are managed. When I audit them, they often look “well optimized”: active management, no glaring structural deficiencies, and targets that match achieved ROAS. On paper, everything checks out. But performance is quietly stuck.</p>



<p>Google Ads no longer responds to isolated optimizations. It builds on what you’ve been rewarding. So when I hear, “That didn’t work,” it usually means the change didn’t override months of prior signals.</p>



<p>What most advertisers still call optimization is actually training. They’re teaching the system the wrong lessons.</p>



<h2 class="wp-block-heading" id="h-why-isolated-optimizations-don-t-move-the-needle-anymore">Why isolated optimizations don’t move the needle anymore</h2>



<p>Today’s Google Ads environment is dominated by Smart Bidding, Performance Max, broad match expansion/AI Max, and modeled conversions. These systems don’t reset when you make a change. They learn cumulatively.</p>



<p>If you raise a ROAS target this week, that action doesn’t override six months of reinforced signals. If you launch a new campaign but shut it down after 10 days, the system doesn’t “forget” that volatility was punished. If brand revenue consistently carries the account, Google learns that safe, predictable demand is the highest priority.</p>



<p>The platform continuously optimizes toward the behaviors that survive, get funded, hit targets, and avoid being paused.</p>



<p>When accounts plateau despite strong management, it’s rarely because bids are wrong. It’s because the system has been trained to avoid uncertainty, but uncertainty is where growth lives.</p>



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<h2 class="wp-block-heading" id="h-what-training-looks-like-in-a-google-ads-account">What training looks like in a Google Ads account</h2>



<p>On the back end, Google Ads is constantly answering one question: What does success look like here?</p>



<p>It infers the answer from:</p>



<ul class="wp-block-list">
<li>Which conversions you include.</li>



<li>How you value them.</li>



<li>Which campaigns are protected during volatility.</li>



<li>How quickly you react to performance swings.</li>
</ul>



<p>Over time, those signals shape the system’s behavior:</p>



<ul class="wp-block-list">
<li>Which queries it expands into.</li>



<li>Which audiences it prioritizes.</li>



<li>How aggressively it competes in auctions.</li>



<li>Whether it explores new demand or recycles existing buyers.</li>
</ul>



<p>Training is about the direction you reinforce over months. If repeat customers hit your ROAS target easily and prospecting campaigns fluctuate, which one do you think the system will prioritize over time?</p>



<p>Here’s a pattern I’ve seen more than once.</p>



<ul class="wp-block-list">
<li>Month 1: Non-brand drives 52% of revenue.</li>



<li>Month 6: Non-brand drives 36%.</li>
</ul>



<p>ROAS improves, and everyone’s happy. Except new customer growth flattens. The system has simply learned that predictable revenue is more important than incremental revenue. That’s training.</p>



<h2 class="wp-block-heading" id="h-how-you-might-be-training-google-ads-wrong">How you might be training Google Ads wrong</h2>



<p>These mistakes are subtle and are often framed as good management. That’s what makes them dangerous.</p>



<h3 class="wp-block-heading" id="h-mistake-1-training-on-the-easiest-revenue">Mistake 1: Training on the easiest revenue</h3>



<p>Branded search converts well, returning customers convert well, and promo periods convert very well — so we lean in. We scale budgets behind what works and protect it.</p>



<p>Over time, Google learns that predictable revenue is the safest path to success.</p>



<p>Here’s a simplified example (replace with real data if available):</p>



<figure class="wp-block-table"><table><tbody><tr><td><strong>Month</strong></td><td><strong>Branded cost %</strong></td><td><strong>Account ROAS</strong></td></tr><tr><td>1</td><td>33%</td><td>$5.44</td></tr><tr><td>2</td><td>35%</td><td>$5.03</td></tr><tr><td>3</td><td>40%</td><td>$6.10</td></tr><tr><td>4</td><td>38%</td><td>$6.69</td></tr><tr><td>5</td><td>42%</td><td>$7.06</td></tr><tr><td>6</td><td>46%</td><td>$7.39</td></tr></tbody></table></figure>



<p>ROAS improved during this period, but incremental demand declined due to the account’s conservative training. This is one of the most common ceilings we see.</p>



<h3 class="wp-block-heading" id="h-mistake-2-punishing-volatility">Mistake 2: Punishing volatility</h3>



<p>This one hits close to home for most teams. Short-term inefficiency is part of prospecting, but most advertisers respond to it immediately:</p>



<ul class="wp-block-list">
<li>Tightening ROAS targets after one soft week.</li>



<li>Pulling budget during learning phases.</li>



<li>Pausing campaigns that explore new or expanded audiences.</li>
</ul>



<p>From a human perspective, this feels responsible, but from a training perspective, it sends a clear message: exploration (uncertainty) is unacceptable.</p>



<p>The system adapts by prioritizing stability over expansion. It narrows the query mix. It leans harder into repeat purchasers. It becomes increasingly efficient, and increasingly stagnant. If everything in your account feels equally clean, you’re probably recycling demand.</p>



<p>Even if ROAS fluctuates, a prospecting or awareness campaign can still drive meaningful new customer lift if given time to mature, as in the example below:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="957" height="452" src="https://searchengineland.com/wp-content/seloads/2026/04/image-85.png" alt="" class="wp-image-474442" srcset="https://searchengineland.com/wp-content/seloads/2026/04/image-85.png 957w, https://searchengineland.com/wp-content/seloads/2026/04/image-85-768x363.png 768w" sizes="(max-width: 957px) 100vw, 957px" /></figure>



<p>The difference between plateaued accounts and growing accounts is rarely skill. It’s tolerance for controlled volatility.</p>



<h3 class="wp-block-heading" id="h-mistake-3-pretending-all-purchases-are-equal">Mistake 3: Pretending all purchases are equal</h3>



<p>In most DTC setups, every purchase is treated equally, but a first-time, full-price buyer, a repeat customer, and a promo-driven order aren’t equal signals.</p>



<p>When every purchase sends the same signal, Google will favor the one that’s easiest to reproduce. That’s usually repeat behavior. Then we wonder why new customer acquisition gets harder.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1450" height="1360" src="https://searchengineland.com/wp-content/seloads/2026/04/image-87.png" alt="" class="wp-image-474444" title="Chart" srcset="https://searchengineland.com/wp-content/seloads/2026/04/image-87.png 1450w, https://searchengineland.com/wp-content/seloads/2026/04/image-87-768x720.png 768w" sizes="(max-width: 1450px) 100vw, 1450px" /></figure>



<p>For the client above, the implementation of lapsed customer targeting and valuation led to a 53% YoY increase in orders vs. a 12% YoY increase the three months prior.</p>



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



<p>This is where many teams get uncomfortable, because it requires letting go of short-term ROAS obsession in favor of aligning Google Ads with the actual business model.</p>



<p>If a client’s business depends on new customer growth, but you’re optimizing purely to blended ROAS, you’ve misaligned the system from the start. If mis-training is cumulative, so is intentional training. Here’s what that looks like in practice:</p>



<h3 class="wp-block-heading" id="h-maintain-efficiency-lanes">Maintain efficiency lanes</h3>



<p>Efficiency lanes exist to protect baseline revenue. They’re tightly managed. They often include brand campaigns and high-intent non-brand terms with predictable performance.</p>



<p>These campaigns can carry stricter ROAS or CPA targets. They stabilize cash flow. They help CEOs sleep at night. They are not your growth engine.</p>



<h3 class="wp-block-heading" id="h-build-growth-lanes">Build growth lanes</h3>



<p>Growth lanes are structured differently. They often include broader match types, category expansion, new audience layering, or creative angles that introduce new use cases. They have looser yet realistic targets.</p>



<p>If your efficiency campaigns run at a 500% ROAS target, your growth campaigns might operate at 350%, with the explicit understanding that they exist to expand demand and acquire new customers.</p>



<p>Here’s the key: you don’t tighten the growth lane every time it fluctuates. You let it learn.</p>



<p>In one DTC account, separating these lanes and holding growth campaigns to a slightly lower ROAS threshold led to a 43% lift in YoY new customers in Q4, while blended ROAS actually improved 10%.</p>



<p>You can see the spend and order relationship below, where an increased investment in new drove measurable change, and the reduction on returning customers didn’t harm the bottom line.&nbsp;</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1200" height="630" src="https://searchengineland.com/wp-content/seloads/2026/04/image-88.png" alt="" class="wp-image-474445" title="Chart" srcset="https://searchengineland.com/wp-content/seloads/2026/04/image-88.png 1200w, https://searchengineland.com/wp-content/seloads/2026/04/image-88-768x403.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /></figure>
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<div class="wp-block-image">
<figure class="alignleft size-full"><img decoding="async" width="1200" height="630" src="https://searchengineland.com/wp-content/seloads/2026/04/image-89.png" alt="" class="wp-image-474451" title="Chart" srcset="https://searchengineland.com/wp-content/seloads/2026/04/image-89.png 1200w, https://searchengineland.com/wp-content/seloads/2026/04/image-89-768x403.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /></figure>
</div>


<p>This controlled asymmetry is how you scale smarter.</p>



<h3 class="wp-block-heading" id="h-change-signals-slowly">Change signals slowly</h3>



<p>If you adjust ROAS targets every two weeks, you’re resetting the system constantly.</p>



<p>Targets shouldn’t be adjusted weekly in response to noise. Campaigns shouldn’t pause during early learning unless structurally broken. Creative testing should be protected long enough to produce a clear signal.</p>



<p>Give it time and let data compound. In one account, simply holding ROAS targets steady for 60 days — instead of tightening them after minor dips — resulted in broader query expansion and improved non-brand impression share without increasing spend.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1200" height="742" src="https://searchengineland.com/wp-content/seloads/2026/04/image-86.png" alt="" class="wp-image-474443" title="Chart" srcset="https://searchengineland.com/wp-content/seloads/2026/04/image-86.png 1200w, https://searchengineland.com/wp-content/seloads/2026/04/image-86-768x475.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /></figure>
</div>


<p>The performance didn’t spike overnight. It grew gradually — that’s training working.</p>



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<h2 class="wp-block-heading" id="h-what-it-means-to-manage-a-trained-system">What it means to manage a trained system</h2>



<p>If any of the mistakes feel familiar, ask yourself:</p>



<ul class="wp-block-list">
<li>Do we tighten targets faster than we loosen them?</li>



<li>Has our revenue mix shifted toward brand and repeat customers over time?</li>



<li>Do we pause exploratory campaigns within the first 2–3 weeks?</li>



<li>Have our core conversion definitions changed multiple times in the last 60 days?</li>



<li>Is query expansion flat despite budget headroom?</li>
</ul>



<p>If the answer is often “yes,” the system isn’t failing you. It’s doing exactly what you trained it to do.</p>



<p>That’s the shift. Paid search used to be about making better decisions than the auction in real time. Now it’s about designing the environment the auction learns from. That’s a different job.</p>



<p>Automation doesn’t reward who moves fastest. It reflects what you’ve been teaching it.</p>



<p>Once you see the account as something you’re training, the question changes. It’s no longer “Why isn’t this working?” It’s “What have we been rewarding?”</p>

Paid search success used to be driven by optimizations. You adjusted bids, restructured campaigns, refined match types, and added negatives. Performance moved accordingly.
That’s still how many accounts are managed. When I audit them, they often look “well optimized”: active management, no glaring structural deficiencies, and targets that match achieved ROAS. On paper, everything checks out. But performance is quietly stuck.
Google Ads no longer responds to isolated optimizations. It builds on what you’ve been rewarding. So when I hear, “That didn’t work,” it usually means the change didn’t override months of prior signals.
What most advertisers still call optimization is actually training. They’re teaching the system the wrong lessons.
Why isolated optimizations don’t move the needle anymore
Today’s Google Ads environment is dominated by Smart Bidding, Performance Max, broad match expansion/AI Max, and modeled conversions. These systems don’t reset when you make a change. They learn cumulatively.
If you raise a ROAS target this week, that action doesn’t override six months of reinforced signals. If you launch a new campaign but shut it down after 10 days, the system doesn’t “forget” that volatility was punished. If brand revenue consistently carries the account, Google learns that safe, predictable demand is the highest priority.
The platform continuously optimizes toward the behaviors that survive, get funded, hit targets, and avoid being paused.
When accounts plateau despite strong management, it’s rarely because bids are wrong. It’s because the system has been trained to avoid uncertainty, but uncertainty is where growth lives.

  
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What training looks like in a Google Ads account
On the back end, Google Ads is constantly answering one question: What does success look like here?
It infers the answer from:
Which conversions you include.
How you value them.
Which campaigns are protected during volatility.
How quickly you react to performance swings.
Over time, those signals shape the system’s behavior:
Which queries it expands into.
Which audiences it prioritizes.
How aggressively it competes in auctions.
Whether it explores new demand or recycles existing buyers.
Training is about the direction you reinforce over months. If repeat customers hit your ROAS target easily and prospecting campaigns fluctuate, which one do you think the system will prioritize over time?
Here’s a pattern I’ve seen more than once.
Month 1: Non-brand drives 52% of revenue.
Month 6: Non-brand drives 36%.
ROAS improves, and everyone’s happy. Except new customer growth flattens. The system has simply learned that predictable revenue is more important than incremental revenue. That’s training.
How you might be training Google Ads wrong
These mistakes are subtle and are often framed as good management. That’s what makes them dangerous.
Mistake 1: Training on the easiest revenue
Branded search converts well, returning customers convert well, and promo periods convert very well — so we lean in. We scale budgets behind what works and protect it.
Over time, Google learns that predictable revenue is the safest path to success.
Here’s a simplified example (replace with real data if available):

MonthBranded cost %Account ROAS
133%$5.44
235%$5.03
340%$6.10
438%$6.69
542%$7.06
646%$7.39





ROAS improved during this period, but incremental demand declined due to the account’s conservative training. This is one of the most common ceilings we see.
Mistake 2: Punishing volatility
This one hits close to home for most teams. Short-term inefficiency is part of prospecting, but most advertisers respond to it immediately:
Tightening ROAS targets after one soft week.
Pulling budget during learning phases.
Pausing campaigns that explore new or expanded audiences.
From a human perspective, this feels responsible, but from a training perspective, it sends a clear message: exploration (uncertainty) is unacceptable.
The system adapts by prioritizing stability over expansion. It narrows the query mix. It leans harder into repeat purchasers. It becomes increasingly efficient, and increasingly stagnant. If everything in your account feels equally clean, you’re probably recycling demand.
Even if ROAS fluctuates, a prospecting or awareness campaign can still drive meaningful new customer lift if given time to mature, as in the example below:




The difference between plateaued accounts and growing accounts is rarely skill. It’s tolerance for controlled volatility.
Mistake 3: Pretending all purchases are equal
In most DTC setups, every purchase is treated equally, but a first-time, full-price buyer, a repeat customer, and a promo-driven order aren’t equal signals.
When every purchase sends the same signal, Google will favor the one that’s easiest to reproduce. That’s usually repeat behavior. Then we wonder why new customer acquisition gets harder.




For the client above, the implementation of lapsed customer targeting and valuation led to a 53% YoY increase in orders vs. a 12% YoY increase the three months prior.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
What intentional training actually looks like
This is where many teams get uncomfortable, because it requires letting go of short-term ROAS obsession in favor of aligning Google Ads with the actual business model.
If a client’s business depends on new customer growth, but you’re optimizing purely to blended ROAS, you’ve misaligned the system from the start. If mis-training is cumulative, so is intentional training. Here’s what that looks like in practice:
Maintain efficiency lanes
Efficiency lanes exist to protect baseline revenue. They’re tightly managed. They often include brand campaigns and high-intent non-brand terms with predictable performance.
These campaigns can carry stricter ROAS or CPA targets. They stabilize cash flow. They help CEOs sleep at night. They are not your growth engine.
Build growth lanes
Growth lanes are structured differently. They often include broader match types, category expansion, new audience layering, or creative angles that introduce new use cases. They have looser yet realistic targets.
If your efficiency campaigns run at a 500% ROAS target, your growth campaigns might operate at 350%, with the explicit understanding that they exist to expand demand and acquire new customers.
Here’s the key: you don’t tighten the growth lane every time it fluctuates. You let it learn.
In one DTC account, separating these lanes and holding growth campaigns to a slightly lower ROAS threshold led to a 43% lift in YoY new customers in Q4, while blended ROAS actually improved 10%.
You can see the spend and order relationship below, where an increased investment in new drove measurable change, and the reduction on returning customers didn’t harm the bottom line. 








This controlled asymmetry is how you scale smarter.
Change signals slowly
If you adjust ROAS targets every two weeks, you’re resetting the system constantly.
Targets shouldn’t be adjusted weekly in response to noise. Campaigns shouldn’t pause during early learning unless structurally broken. Creative testing should be protected long enough to produce a clear signal.
Give it time and let data compound. In one account, simply holding ROAS targets steady for 60 days — instead of tightening them after minor dips — resulted in broader query expansion and improved non-brand impression share without increasing spend.




The performance didn’t spike overnight. It grew gradually — that’s training working.

  
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Get started with
What it means to manage a trained system
If any of the mistakes feel familiar, ask yourself:
Do we tighten targets faster than we loosen them?
Has our revenue mix shifted toward brand and repeat customers over time?
Do we pause exploratory campaigns within the first 2–3 weeks?
Have our core conversion definitions changed multiple times in the last 60 days?
Is query expansion flat despite budget headroom?
If the answer is often “yes,” the system isn’t failing you. It’s doing exactly what you trained it to do.
That’s the shift. Paid search used to be about making better decisions than the auction in real time. Now it’s about designing the environment the auction learns from. That’s a different job.
Automation doesn’t reward who moves fastest. It reflects what you’ve been teaching it.
Once you see the account as something you’re training, the question changes. It’s no longer “Why isn’t this working?” It’s “What have we been rewarding?”

Google Ads is trained by what you reinforce over time. That’s why results repeat — it learns what gets funded and sustained.

Why your Google Ads results keep repeating the same outcomes

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility.png" class="attachment-large size-large wp-post-image" alt="Google core update-volatility" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Nearly 80% of top results shifted as Google’s latest update hit aggregators and boosted brands, official sites, and data-rich sources.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility.png" class="attachment-large size-large wp-post-image" alt="Google core update-volatility" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/google-core-update-volatility-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The <a href="https://searchengineland.com/google-march-2026-core-update-rolling-out-now-472759">March 2026 Google core update</a> drove far higher ranking volatility than the <a href="https://searchengineland.com/google-december-2025-core-update-rollout-is-now-complete-466362">December 2025 core update</a>. Nearly 80% of top-three results shifted, and almost one in four top-10 pages fell out of the top 100, according to SE Ranking data shared exclusively with Search Engine Land.</p>



<p><strong>The data</strong>. Volatility increased across every ranking tier.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1974" height="1257" src="https://searchengineland.com/wp-content/seloads/2026/04/serp-volatility-december-2025-vs-march-2026-core-update.png" alt="" class="wp-image-474400" srcset="https://searchengineland.com/wp-content/seloads/2026/04/serp-volatility-december-2025-vs-march-2026-core-update.png 1974w, https://searchengineland.com/wp-content/seloads/2026/04/serp-volatility-december-2025-vs-march-2026-core-update-768x489.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/serp-volatility-december-2025-vs-march-2026-core-update-1536x978.png 1536w" sizes="(max-width: 1974px) 100vw, 1974px" /></figure>



<ul class="wp-block-list">
<li>In the top 3, 79.5% of URLs changed positions, up from 66.8% in December. In the top 10, 90.7% shifted, compared to 83.1%.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1974" height="1257" src="https://searchengineland.com/wp-content/seloads/2026/04/ranking-stability-urls-position.png" alt="" class="wp-image-474401" srcset="https://searchengineland.com/wp-content/seloads/2026/04/ranking-stability-urls-position.png 1974w, https://searchengineland.com/wp-content/seloads/2026/04/ranking-stability-urls-position-768x489.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/ranking-stability-urls-position-1536x978.png 1536w" sizes="(max-width: 1974px) 100vw, 1974px" /></figure>



<ul class="wp-block-list">
<li>Stability dropped sharply. Only 20.5% of top 3 URLs held their exact position, down from 33.1%. In the top 10, that fell to 9.3%, from 16.9%.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1374" height="1261" src="https://searchengineland.com/wp-content/seloads/2026/04/top-10-pages-disappeared-top-100.png" alt="" class="wp-image-474402" srcset="https://searchengineland.com/wp-content/seloads/2026/04/top-10-pages-disappeared-top-100.png 1374w, https://searchengineland.com/wp-content/seloads/2026/04/top-10-pages-disappeared-top-100-768x705.png 768w" sizes="(max-width: 1374px) 100vw, 1374px" /></figure>



<ul class="wp-block-list">
<li>Churn intensified at the top. About 24.1% of pages ranking in the top 10 fell out of the top 100 entirely, versus 14.7% after the December update.</li>
</ul>



<p><strong>It&#8217;s (sort of) complicated. </strong>The <a href="https://searchengineland.com/google-march-2026-core-update-rolling-out-now-472759">March 2026 core update began rolling out</a> a day after the <a href="https://searchengineland.com/google-march-2026-spam-update-done-rolling-out-472455">March 2026 spam update completed</a>. This complicated attribution, according to SE Ranking:</p>



<ul class="wp-block-list">
<li>Based on historical patterns and the scale of movement, most volatility was likely driven by the core update, with the spam update amplifying disruption.</li>



<li>That overlap likely skews direct comparisons to December, though March still appeared more volatile.</li>
</ul>



<p><strong>More core update analysis.</strong> Meanwhile, <a href="https://www.aleydasolis.com/en/search-engine-optimization/google-march-core-update-2026/" target="_blank" rel="noopener">independent analysis by Aleyda Solis</a>, using Sistrix data from March 26 to April 11, found a consistent shift in where visibility concentrates. Rankings appeared to move from intermediary sites toward stronger destination sources. Website types gaining search visibility:</p>



<ul class="wp-block-list">
<li>Official and institutional.</li>



<li>Specialist and niche.</li>



<li>Established brands.</li>



<li>Dominant platforms.</li>
</ul>



<p>Losses were more common among aggregators, directories, and comparison-driven sites.</p>



<p><strong>Winners and losers.</strong> Among the vertical shifts Solis highlighted:</p>



<ul class="wp-block-list">
<li>Dictionary and language reference sites declined, while larger reference platforms and major destinations gained visibility.</li>



<li>Job aggregators like ZipRecruiter and Glassdoor lost ground, while employer sites and specialized platforms like USAJobs and Amazon.jobs surged.</li>



<li>Government and institutional domains, including Census.gov and BLS.gov, saw strong gains on fact-driven queries.</li>



<li>Travel and real estate visibility shifted away from broad discovery platforms toward stronger brands and primary destinations.</li>



<li>Health results were re-sorted. Broad consumer health sites declined, while clinical, research-driven, and specialist sources gained.</li>



<li><strong>One exception:</strong> YouTube had the largest visibility loss in the dataset.</li>
</ul>



<p><strong>Why we care</strong>. The data suggests Google&#8217;s March 2026 core update raised the bar for ranking. Strong brands, owned data, and direct query value won. Intermediaries now look increasingly exposed.</p>


The March 2026 Google core update drove far higher ranking volatility than the December 2025 core update. Nearly 80% of top-three results shifted, and almost one in four top-10 pages fell out of the top 100, according to SE Ranking data shared exclusively with Search Engine Land.
The data. Volatility increased across every ranking tier.





In the top 3, 79.5% of URLs changed positions, up from 66.8% in December. In the top 10, 90.7% shifted, compared to 83.1%.





Stability dropped sharply. Only 20.5% of top 3 URLs held their exact position, down from 33.1%. In the top 10, that fell to 9.3%, from 16.9%.





Churn intensified at the top. About 24.1% of pages ranking in the top 10 fell out of the top 100 entirely, versus 14.7% after the December update.
It’s (sort of) complicated. The March 2026 core update began rolling out a day after the March 2026 spam update completed. This complicated attribution, according to SE Ranking:
Based on historical patterns and the scale of movement, most volatility was likely driven by the core update, with the spam update amplifying disruption.
That overlap likely skews direct comparisons to December, though March still appeared more volatile.
More core update analysis. Meanwhile, independent analysis by Aleyda Solis, using Sistrix data from March 26 to April 11, found a consistent shift in where visibility concentrates. Rankings appeared to move from intermediary sites toward stronger destination sources. Website types gaining search visibility:
Official and institutional.
Specialist and niche.
Established brands.
Dominant platforms.
Losses were more common among aggregators, directories, and comparison-driven sites.
Winners and losers. Among the vertical shifts Solis highlighted:
Dictionary and language reference sites declined, while larger reference platforms and major destinations gained visibility.
Job aggregators like ZipRecruiter and Glassdoor lost ground, while employer sites and specialized platforms like USAJobs and Amazon.jobs surged.
Government and institutional domains, including Census.gov and BLS.gov, saw strong gains on fact-driven queries.
Travel and real estate visibility shifted away from broad discovery platforms toward stronger brands and primary destinations.
Health results were re-sorted. Broad consumer health sites declined, while clinical, research-driven, and specialist sources gained.
One exception: YouTube had the largest visibility loss in the dataset.
Why we care. The data suggests Google’s March 2026 core update raised the bar for ranking. Strong brands, owned data, and direct query value won. Intermediaries now look increasingly exposed.

Nearly 80% of top results shifted as Google’s latest update hit aggregators and boosted brands, official sites, and data-rich sources.

March 2026 Google core update more volatile than December — here’s what changed

<div><img width="360" height="200" src="https://searchengineland.com/wp-content/seloads/2026/04/mt_360x200_smxnow_april.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" /></div>Join us May 6 for the second SMX Now, featuring Ameet Khabra on how to spot and stop PPC drift before it hurts performance.

<div><img width="360" height="200" src="https://searchengineland.com/wp-content/seloads/2026/04/mt_360x200_smxnow_april.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" /></div>
<p>Automation doesn’t fail on its own — it does exactly what it’s trained to do. The problem is that when Google Ads is fed incomplete, misaligned, or overly broad signals, it can optimize toward the wrong outcome faster than most advertisers realize.</p>



<p>In our second installment of SMX Now, our new monthly series, Ameet Khabra of Hop Skip Media will break down a real account where a 417% jump in conversions turned out to be the wrong kind of success. She’ll use that case study to explain the four key ways automation drift enters an account: signal drift, query drift, inventory drift, and creative drift.</p>



<p>You’ll leave with a practical framework for diagnosing drift early, understanding where human oversight matters most, and managing automation more deliberately so it works toward real business goals — not just platform-reported wins.</p>



<p>Join us May 6 at noon ET.</p>



<p class="has-text-align-center"><a href="https://www.bigmarker.com/third-door-media/the-automation-drift-and-how-to-correct-course?utm_bmcr_source=Editorial" type="link" id="https://www.bigmarker.com/third-door-media/the-automation-drift-and-how-to-correct-course?utm_bmcr_source=Editorial" target="_blank" rel="noopener"><strong>Save your spot</strong></a>


Automation doesn’t fail on its own — it does exactly what it’s trained to do. The problem is that when Google Ads is fed incomplete, misaligned, or overly broad signals, it can optimize toward the wrong outcome faster than most advertisers realize.
In our second installment of SMX Now, our new monthly series, Ameet Khabra of Hop Skip Media will break down a real account where a 417% jump in conversions turned out to be the wrong kind of success. She’ll use that case study to explain the four key ways automation drift enters an account: signal drift, query drift, inventory drift, and creative drift.
You’ll leave with a practical framework for diagnosing drift early, understanding where human oversight matters most, and managing automation more deliberately so it works toward real business goals — not just platform-reported wins.
Join us May 6 at noon ET.
Save your spot

Join us May 6 for the second SMX Now, featuring Ameet Khabra on how to spot and stop PPC drift before it hurts performance.

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Read the Latest Trends and Headlines in Digital Marketing.

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

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