<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>ChatGPT ads now allows for conversion-optimized product feed campaigns, expanded measurement integrations and carousel ads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">OpenAI is expanding ChatGPT Ads&#8217; conversion capabilities with new campaign types, broader measurement integrations and enhanced optimization tools, while preparing to launch the platform in two new markets.</p>



<p class="wp-block-paragraph">The latest updates are aimed at helping advertisers improve conversion tracking, automate campaign creation and scale ecommerce advertising.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. OpenAI has rolled out several new features centered on conversion optimization.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="722" height="1520" src="https://searchengineland.com/wp-content/seloads/2026/08/OpenAI-updates.png" alt="" class="wp-image-484495"/></figure>



<p class="wp-block-paragraph">Product feed campaigns now support <strong>conversion-optimized cost-per-click (oCPC)</strong> campaigns in beta, allowing advertisers to optimize toward conversions while continuing to pay per click. Advertisers can also clone existing CPC campaigns into oCPC campaigns or create them in bulk, simplifying campaign migration.</p>



<p class="wp-block-paragraph">The platform is also introducing dynamic URL parameters, enabling advertisers to automatically append campaign, ad group and ad IDs to landing page URLs for easier attribution and analytics.</p>


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<p class="wp-block-paragraph"><strong>Measurement gets a boost</strong>. OpenAI continues to expand its measurement ecosystem with new integrations.</p>



<p class="wp-block-paragraph">Advertisers can now connect Triple Whale to measure ChatGPT Ads performance alongside other marketing channels, while Sonar Optimize can send stronger conversion signals back to OpenAI. Hightouch now supports sending conversion events directly into ChatGPT Ads for measurement and optimization.</p>



<p class="wp-block-paragraph">Ads Manager has also gained more detailed Pixel validation diagnostics, helping advertisers identify why conversion events were rejected and providing recommendations for fixing implementation issues.</p>



<p class="wp-block-paragraph">Meanwhile, Automatic Advanced Matching (AAM) will become the default for all new web pixels immediately and will automatically be enabled for existing pixels on August 17, unless advertisers choose to opt out beforehand.</p>



<p class="wp-block-paragraph"><strong>New markets and ad formats</strong>. OpenAI says ChatGPT Ads will launch in Brazil and Mexico in the coming week, expanding advertiser access in Latin America.</p>



<p class="wp-block-paragraph">The company has also begun testing a multi-product carousel format for product feed campaigns, allowing multiple products to appear within a single ad unit.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The updates givies advertisers better tools to optimize for conversions, improve measurement, and scale campaigns more efficiently. New integrations with platforms like Triple Whale and Hightouch, enhanced pixel diagnostics, and Automatic Advanced Matching should lead to more accurate attribution and stronger optimization signals.</p>



<p class="wp-block-paragraph"><strong>Bottom line:</strong> OpenAI is doubling down on performance advertising with expanded conversion optimization, richer measurement integrations, new ecommerce formats and continued international expansion for ChatGPT Ads.</p>


OpenAI is expanding ChatGPT Ads’ conversion capabilities with new campaign types, broader measurement integrations and enhanced optimization tools, while preparing to launch the platform in two new markets.
The latest updates are aimed at helping advertisers improve conversion tracking, automate campaign creation and scale ecommerce advertising.
What’s happening. OpenAI has rolled out several new features centered on conversion optimization.




Product feed campaigns now support conversion-optimized cost-per-click (oCPC) campaigns in beta, allowing advertisers to optimize toward conversions while continuing to pay per click. Advertisers can also clone existing CPC campaigns into oCPC campaigns or create them in bulk, simplifying campaign migration.
The platform is also introducing dynamic URL parameters, enabling advertisers to automatically append campaign, ad group and ad IDs to landing page URLs for easier attribution and analytics.
AI recommends.
      
See your AI visibility
    
Measurement gets a boost. OpenAI continues to expand its measurement ecosystem with new integrations.
Advertisers can now connect Triple Whale to measure ChatGPT Ads performance alongside other marketing channels, while Sonar Optimize can send stronger conversion signals back to OpenAI. Hightouch now supports sending conversion events directly into ChatGPT Ads for measurement and optimization.
Ads Manager has also gained more detailed Pixel validation diagnostics, helping advertisers identify why conversion events were rejected and providing recommendations for fixing implementation issues.
Meanwhile, Automatic Advanced Matching (AAM) will become the default for all new web pixels immediately and will automatically be enabled for existing pixels on August 17, unless advertisers choose to opt out beforehand.
New markets and ad formats. OpenAI says ChatGPT Ads will launch in Brazil and Mexico in the coming week, expanding advertiser access in Latin America.
The company has also begun testing a multi-product carousel format for product feed campaigns, allowing multiple products to appear within a single ad unit.
Why we care. The updates givies advertisers better tools to optimize for conversions, improve measurement, and scale campaigns more efficiently. New integrations with platforms like Triple Whale and Hightouch, enhanced pixel diagnostics, and Automatic Advanced Matching should lead to more accurate attribution and stronger optimization signals.
Bottom line: OpenAI is doubling down on performance advertising with expanded conversion optimization, richer measurement integrations, new ecommerce formats and continued international expansion for ChatGPT Ads.

ChatGPT ads now allows for conversion-optimized product feed campaigns, expanded measurement integrations and carousel ads

ChatGPT Ads rolls out oCPC campaigns, AAM and product carousels

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google is introducing new qualification criteria based on trust signals, verification and account history.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is expanding its Limited Ad Serving policy to cover all Google Ads, giving qualified advertisers unrestricted impressions while limiting ad delivery for accounts it considers higher risk.</p>



<p class="wp-block-paragraph">The updated policy begins rolling out in August and will be implemented gradually through 2028.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s changing</strong>. Under the revised policy, Google will limit impressions—not disapprove ads—for advertisers it determines are unqualified in certain ad-serving scenarios that are more likely to result in poor user experiences.</p>



<p class="wp-block-paragraph">Google says qualification is based on a range of signals, including account maturity, advertiser verification status, policy compliance history, user reports, ad format usage, industry and other account attributes. Advertisers with strong trust signals won&#8217;t be affected by impression limits.</p>



<p class="wp-block-paragraph">Accounts that are limited will receive an in-account notification and can appeal the decision through Google&#8217;s Limited Ad Serving Appeals Form.</p>



<p class="wp-block-paragraph"><strong>What advertisers should do</strong>. Google is encouraging advertisers to build trust by completing advertiser verification, complying with advertising policies and maintaining clear branding across ads and landing pages.</p>



<p class="wp-block-paragraph">For Search campaigns, Google also recommends avoiding generic ad copy, clearly identifying your business and, where available, pinning your domain to the first headline position to reinforce brand identity.</p>



<p class="wp-block-paragraph">On YouTube, Gmail, Discover and the Play Store, advertisers are advised to continue building campaigns that generate positive user engagement while Google evaluates account quality.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The update formalises how Google determines which advertisers can serve ads without restrictions. Rather than focusing solely on policy violations, Google is placing greater emphasis on trust, account history and user experience when deciding how broadly ads can be shown.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://support.google.com/adspolicy/answer/17344822?hl=en">Google&#8217;s expanded Limited Ad Serving policy</a> gives trusted advertisers unrestricted delivery while encouraging newer or less-established advertisers to build credibility through verification, policy compliance and consistent branding before gaining full access to inventory.</p>


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Google is expanding its Limited Ad Serving policy to cover all Google Ads, giving qualified advertisers unrestricted impressions while limiting ad delivery for accounts it considers higher risk.
The updated policy begins rolling out in August and will be implemented gradually through 2028.
What’s changing. Under the revised policy, Google will limit impressions—not disapprove ads—for advertisers it determines are unqualified in certain ad-serving scenarios that are more likely to result in poor user experiences.
Google says qualification is based on a range of signals, including account maturity, advertiser verification status, policy compliance history, user reports, ad format usage, industry and other account attributes. Advertisers with strong trust signals won’t be affected by impression limits.
Accounts that are limited will receive an in-account notification and can appeal the decision through Google’s Limited Ad Serving Appeals Form.
What advertisers should do. Google is encouraging advertisers to build trust by completing advertiser verification, complying with advertising policies and maintaining clear branding across ads and landing pages.
For Search campaigns, Google also recommends avoiding generic ad copy, clearly identifying your business and, where available, pinning your domain to the first headline position to reinforce brand identity.
On YouTube, Gmail, Discover and the Play Store, advertisers are advised to continue building campaigns that generate positive user engagement while Google evaluates account quality.
Why we care. The update formalises how Google determines which advertisers can serve ads without restrictions. Rather than focusing solely on policy violations, Google is placing greater emphasis on trust, account history and user experience when deciding how broadly ads can be shown.
Bottom line. Google’s expanded Limited Ad Serving policy gives trusted advertisers unrestricted delivery while encouraging newer or less-established advertisers to build credibility through verification, policy compliance and consistent branding before gaining full access to inventory.
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Google is introducing new qualification criteria based on trust signals, verification and account history.

Google expands Limited Ad Serving policy across all Ads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Microsoft's now lets advertisers appeal multiple disapproved text &#038; image assets at once, reducing time spent resolving policy issues.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Microsoft Advertising launched bulk editing and appeals for disapproved assets, making it faster for advertisers to resolve policy issues without updating assets one at a time.</p>



<p class="wp-block-paragraph">The feature is now available in all accounts and supports both text and image assets.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Announced by Microsoft Ads Product Liaison Navah Hopkins, the new tool lets advertisers bulk edit or appeal disapproved assets directly within Microsoft Advertising.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="961" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit.jpeg" alt="" class="wp-image-484484" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit.jpeg 2048w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit-768x360.jpeg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit-1536x721.jpeg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p class="wp-block-paragraph">There are a few important limitations. Because Microsoft reviews assets individually, appeals must be submitted for all disapproved assets within an ad. This allows approved assets to continue serving during the review process, provided the ad&#8217;s final URL remains approved.</p>



<p class="wp-block-paragraph">For image assets, advertisers can&#8217;t simply edit an existing creative—they&#8217;ll need to upload a replacement image. In some cases, Microsoft also recommends requesting a policy exception instead of modifying the asset. Advertisers can submit up to 5,000 ad exception requests.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Bulk editing removes one of the more time-consuming parts of campaign management, especially for advertisers managing large numbers of assets. Instead of reviewing and appealing each disapproval individually, teams can resolve policy issues much more efficiently.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. Microsoft continues to invest in workflow improvements alongside new AI-powered campaign features. While not a headline-grabbing launch, updates like this reduce operational friction and make it easier for advertisers and agencies to manage campaigns at scale.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://www.linkedin.com/posts/navahhopkins_thrilled-to-share-that-microsoft-advertising-share-7491122041186566144-s7A4/">Microsoft Advertising&#8217;s new bulk edit and appeal tool</a> simplifies policy management by allowing advertisers to update or challenge multiple disapproved assets at once.</p>


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Microsoft Advertising launched bulk editing and appeals for disapproved assets, making it faster for advertisers to resolve policy issues without updating assets one at a time.
The feature is now available in all accounts and supports both text and image assets.
What’s happening. Announced by Microsoft Ads Product Liaison Navah Hopkins, the new tool lets advertisers bulk edit or appeal disapproved assets directly within Microsoft Advertising.




There are a few important limitations. Because Microsoft reviews assets individually, appeals must be submitted for all disapproved assets within an ad. This allows approved assets to continue serving during the review process, provided the ad’s final URL remains approved.
For image assets, advertisers can’t simply edit an existing creative—they’ll need to upload a replacement image. In some cases, Microsoft also recommends requesting a policy exception instead of modifying the asset. Advertisers can submit up to 5,000 ad exception requests.
Why we care. Bulk editing removes one of the more time-consuming parts of campaign management, especially for advertisers managing large numbers of assets. Instead of reviewing and appealing each disapproval individually, teams can resolve policy issues much more efficiently.
The bigger picture. Microsoft continues to invest in workflow improvements alongside new AI-powered campaign features. While not a headline-grabbing launch, updates like this reduce operational friction and make it easier for advertisers and agencies to manage campaigns at scale.
Bottom line. Microsoft Advertising’s new bulk edit and appeal tool simplifies policy management by allowing advertisers to update or challenge multiple disapproved assets at once.
a customer you lose.
      
See who’s stealing your traffic

Microsoft's now lets advertisers appeal multiple disapproved text & image assets at once, reducing time spent resolving policy issues.

Microsoft Advertising adds bulk editing for disapproved assets

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>YouTube is overlaying static image ads during landscape mobile videos, potentially giving advertisers a new placement.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/youTube-image-ads-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">YouTube appears to be testing a new mobile ad format that displays static image ads during horizontal video playback, potentially creating an additional inventory option for advertisers without fully interrupting the viewing experience.</p>



<p class="wp-block-paragraph">If rolled out more broadly, the format could increase ad frequency while changing how users consume long-form content on mobile.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. The experiment overlays a sponsored image ad on part of the screen while a video continues playing in landscape mode. Unlike traditional pre-roll or mid-roll video ads, the image doesn&#8217;t pause or replace the content being watched.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2026/08/youtube-image-ads-mobile-video.jpg" alt="" class="wp-image-484480" srcset="https://searchengineland.com/wp-content/seloads/2026/08/youtube-image-ads-mobile-video.jpg 1280w, https://searchengineland.com/wp-content/seloads/2026/08/youtube-image-ads-mobile-video-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/youtube-image-ads-mobile-video-1200x675.jpg 1200w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<p class="wp-block-paragraph">According to early observations, these image ads appear roughly every three minutes during playback, making them more frequent than YouTube&#8217;s standard video ad breaks.</p>



<p class="wp-block-paragraph">Google has not confirmed whether the feature is part of a limited test or planned for a wider rollout.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. For advertisers, the format could introduce another way to reach viewers without requiring video creative. For users, however, more frequent on-screen ads could change the viewing experience, even if the content itself isn&#8217;t interrupted.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. YouTube continues experimenting with new ad placements as it looks to expand monetisation opportunities across devices and formats. Rather than relying solely on traditional video ads, the platform is increasingly testing formats that integrate advertising more seamlessly into the viewing experience.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://ppcnewsfeed.com/ppc-news/2026-08/youtube-tests-image-ads-horizontal-mobile-playback/">YouTube is testing image ads during horizontal mobile playback</a>, a new format that could expand ad inventory while reshaping how advertising appears alongside video content.</p>



<p class="wp-block-paragraph"><strong>First spotted.</strong> This update was spotted by PPC News Feed founder Hana Kobzova. </p>


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YouTube appears to be testing a new mobile ad format that displays static image ads during horizontal video playback, potentially creating an additional inventory option for advertisers without fully interrupting the viewing experience.
If rolled out more broadly, the format could increase ad frequency while changing how users consume long-form content on mobile.
What’s happening. The experiment overlays a sponsored image ad on part of the screen while a video continues playing in landscape mode. Unlike traditional pre-roll or mid-roll video ads, the image doesn’t pause or replace the content being watched.




According to early observations, these image ads appear roughly every three minutes during playback, making them more frequent than YouTube’s standard video ad breaks.
Google has not confirmed whether the feature is part of a limited test or planned for a wider rollout.
Why we care. For advertisers, the format could introduce another way to reach viewers without requiring video creative. For users, however, more frequent on-screen ads could change the viewing experience, even if the content itself isn’t interrupted.
The bigger picture. YouTube continues experimenting with new ad placements as it looks to expand monetisation opportunities across devices and formats. Rather than relying solely on traditional video ads, the platform is increasingly testing formats that integrate advertising more seamlessly into the viewing experience.
Bottom line. YouTube is testing image ads during horizontal mobile playback, a new format that could expand ad inventory while reshaping how advertising appears alongside video content.
First spotted. This update was spotted by PPC News Feed founder Hana Kobzova. 
a customer you lose.
      
See who’s stealing your traffic

YouTube is overlaying static image ads during landscape mobile videos, potentially giving advertisers a new placement.

YouTube tests image ads during horizontal mobile playback

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google now lets advertisers measure new customer acquisition without affecting bidding, replacing a reporting workaround.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Ads-customer-acquisition-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google Ads introduced a new &#8220;Report on new customers acquired&#8221; option within Customer Acquisition, making it easier for advertisers to measure new customer performance without influencing campaign bidding.</p>



<p class="wp-block-paragraph">The update removes the need for a widely used workaround that many advertisers relied on to access new-versus-existing customer reporting.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Customer Acquisition now includes a third option alongside the existing bidding settings. By selecting &#8220;Report on new customers acquired,&#8221; advertisers can measure new customer performance without applying any bidding adjustments.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="563" height="348" src="https://searchengineland.com/wp-content/seloads/2026/08/New-customer-acquisition.png" alt="" class="wp-image-484474"/></figure>



<p class="wp-block-paragraph">Enabling the setting unlocks the New customers and New customer value columns, giving advertisers a clearer view of acquisition performance while leaving Google&#8217;s bidding algorithms unchanged.</p>



<p class="wp-block-paragraph">Previously, advertisers wanting this reporting often selected &#8220;Bid higher for new customers&#8221; and assigned a token value of 0.01. While the setting technically modified bidding, the value was so small that it had virtually no practical impact. The workaround, first highlighted by Vasant Chaudhary, became a common way to access new customer reporting.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The new reporting option separates measurement from optimisation. Advertisers who want visibility into new customer acquisition—but don&#8217;t want Google&#8217;s bidding strategy to prioritise those users—can now do so without relying on a workaround.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. Google continues to expand reporting controls as advertisers place greater emphasis on customer lifetime value and acquisition efficiency. Giving advertisers cleaner measurement options also reflects a broader push to make campaign settings more transparent and reduce the need for unofficial hacks.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. Google&#8217;s new Customer Acquisition reporting option gives advertisers a straightforward way to track new customer performance without affecting bidding, replacing the long-standing 0.01 workaround.</p>



<p class="wp-block-paragraph"><strong>First spotted. </strong>Shared by Paid Search expert Thomas Eccel on <a href="https://www.linkedin.com/posts/thomaseccel_ppc-googleads-share-7490707193697161216-kp_m/?utm_source=share&amp;utm_medium=member_ios&amp;rcm=ACoAAAAOXwgBGvKJ5PG5kuwaTmFUJWimyBar5pw">LinkedIn</a>.</p>


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Google Ads introduced a new “Report on new customers acquired” option within Customer Acquisition, making it easier for advertisers to measure new customer performance without influencing campaign bidding.
The update removes the need for a widely used workaround that many advertisers relied on to access new-versus-existing customer reporting.
What’s happening. Customer Acquisition now includes a third option alongside the existing bidding settings. By selecting “Report on new customers acquired,” advertisers can measure new customer performance without applying any bidding adjustments.




Enabling the setting unlocks the New customers and New customer value columns, giving advertisers a clearer view of acquisition performance while leaving Google’s bidding algorithms unchanged.
Previously, advertisers wanting this reporting often selected “Bid higher for new customers” and assigned a token value of 0.01. While the setting technically modified bidding, the value was so small that it had virtually no practical impact. The workaround, first highlighted by Vasant Chaudhary, became a common way to access new customer reporting.
Why we care. The new reporting option separates measurement from optimisation. Advertisers who want visibility into new customer acquisition—but don’t want Google’s bidding strategy to prioritise those users—can now do so without relying on a workaround.
The bigger picture. Google continues to expand reporting controls as advertisers place greater emphasis on customer lifetime value and acquisition efficiency. Giving advertisers cleaner measurement options also reflects a broader push to make campaign settings more transparent and reduce the need for unofficial hacks.
Bottom line. Google’s new Customer Acquisition reporting option gives advertisers a straightforward way to track new customer performance without affecting bidding, replacing the long-standing 0.01 workaround.
First spotted. Shared by Paid Search expert Thomas Eccel on LinkedIn.
a customer you lose.
      
See who’s stealing your traffic

Google now lets advertisers measure new customer acquisition without affecting bidding, replacing a reporting workaround.

Google Ads adds dedicated reporting for new customer acquisition

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations.png" class="attachment-large size-large wp-post-image" alt="How business context changes AI recommendations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>See how three AI models responded as business context became progressively richer for the same strategic challenge.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations.png" class="attachment-large size-large wp-post-image" alt="How business context changes AI recommendations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-business-context-changes-AI-recommendations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Every AI success story seems to end the same way. Someone shares a remarkable output, and almost immediately someone asks, &#8220;Will you share the prompt?&#8221;</p>



<p class="wp-block-paragraph">It&#8217;s a reasonable request. We often give prompts too much credit. By the time someone writes a prompt, they&#8217;ve already defined objectives, gathered context, weighed tradeoffs, and decided what success looks like. </p>



<p class="wp-block-paragraph">Prompts capture the result of conversations, assumptions, revisions, and editorial judgments that came long before anyone started typing.</p>



<p class="wp-block-paragraph">To see how much that process matters, I gave the same strategic assignment to ChatGPT, Claude, and Gemini, changing only the information that came before the prompt.</p>



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



<p class="wp-block-paragraph">The assignment was straightforward. A company had invested in SEO for years, and its website was well established. Leadership knew search behavior was changing as AI-generated answers became more common, but no one knew what, if anything, should change about the marketing strategy.</p>



<p class="wp-block-paragraph">I gave the same assignment to ChatGPT, Claude, and Gemini. The goal was to create a strategic roadmap identifying:</p>



<ul class="wp-block-list">
<li>What information should be gathered.</li>



<li>Which opportunities deserved attention.</li>



<li>Which assumptions required validation.</li>



<li>What should happen before content creation began.</li>
</ul>



<p class="wp-block-paragraph">I wasn&#8217;t trying to identify the &#8220;winning&#8221; model. I wanted to see how the responses changed as the assignment evolved.</p>


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<h2 id="h-first-run-the-models-filled-in-the-missing-intent" class="wp-block-heading">First run: The models filled in the missing intent</h2>



<p class="wp-block-paragraph">At first, I believed I&#8217;d crafted a perfectly reasonable prompt. Then I realized what I&#8217;d actually written was a perfectly reasonable assignment. Rather than reproduce it line by line, here&#8217;s what it included:</p>



<ul class="wp-block-list">
<li>A request for strategic guidance rather than marketing copy.</li>



<li>An explanation that it was for an established business concerned about its visibility in AI-generated search.</li>



<li>Instructions to identify missing information to prevent hallucinations and invented facts.</li>



<li>An expectation that the response would prioritize planning over execution.</li>
</ul>



<p class="wp-block-paragraph">The complete opening assignment is shown in Figure 1.</p>


<div class="wp-block-image">
<figure data-wp-context="{&quot;imageId&quot;:&quot;6a7670255a39f&quot;}" data-wp-interactive="core/image" data-wp-key="6a7670255a39f" class="aligncenter size-full wp-lightbox-container"><img decoding="async" width="626" height="317" data-wp-class--hide="state.isContentHidden" data-wp-class--show="state.isContentVisible" data-wp-init="callbacks.setButtonStyles" data-wp-on--click="actions.showLightbox" data-wp-on--load="callbacks.setButtonStyles" data-wp-on--pointerdown="actions.preloadImage" data-wp-on--pointerenter="actions.preloadImageWithDelay" data-wp-on--pointerleave="actions.cancelPreload" data-wp-on-window--resize="callbacks.setButtonStyles" src="https://searchengineland.com/wp-content/seloads/2026/08/image-4.jpeg" alt="" class="wp-image-484460"/><button
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			data-wp-on--click="actions.showLightbox"
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		>
			<svg xmlns="http://www.w3.org/2000/svg" width="12" height="12" fill="none" viewBox="0 0 12 12">
				<path fill="#fff" d="M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z" />
			</svg>
		</button></figure>
</div>


<p class="wp-block-paragraph">It defined the problem, established the type of help I needed, and discouraged unsupported assumptions. It also left room for interpretation.</p>



<p class="wp-block-paragraph">Then I ran the assignment through all three models. The responses came back quickly. They were thoughtful, well-organized, and complete.&nbsp;</p>



<p class="wp-block-paragraph">Each would have seemed reasonable on its own. Side by side, however, they revealed something important: They weren&#8217;t really answering the same question.</p>



<ul class="wp-block-list">
<li>Claude treated the assignment as the beginning of a discovery project. </li>



<li>Gemini interpreted it primarily as an AI search optimization project. </li>



<li>ChatGPT expanded it into a formal consulting framework with governance, measurement, and phased implementation.</li>
</ul>



<p class="wp-block-paragraph">None of the interpretations were unreasonable. The issue was that the models hadn&#8217;t been told which business problem mattered most.</p>



<p class="wp-block-paragraph">Was the problem declining traffic? Brand visibility? AI citations? Lead generation? Competitive pressure? Future readiness? Each requires a different strategy.&nbsp;</p>



<p class="wp-block-paragraph">Without enough information to understand the underlying intent, each model supplied its own interpretation. When an assignment leaves room for interpretation, models don&#8217;t simply fill in missing facts. They fill in the missing intent.</p>



<p class="wp-block-paragraph">I stopped thinking about how to improve a prompt and started thinking about how to improve the brief.</p>



<h2 id="h-second-run-better-context-better-recommendations" class="wp-block-heading">Second run: Better context, better recommendations</h2>



<p class="wp-block-paragraph">Experienced marketers begin with conversations. They learn what success looks like, which customers matter most, where the business makes its money, what constraints exist, and which compromises are acceptable. Then they turn that information into a functional brief.</p>



<p class="wp-block-paragraph">That&#8217;s what my process intentionally skipped for the experiment.</p>



<p class="wp-block-paragraph">For the second run, I kept the original assignment largely intact and added the information that would normally emerge during those conversations.</p>



<p class="wp-block-paragraph">The revised brief established the client as a regional HVAC company with a mature website, a limited budget, and a preference for improving existing assets before creating significant new content. It also clarified the objective of increasing qualified service inquiries during the upcoming season, with maintenance agreements representing the highest-value long-term outcome.</p>



<p class="wp-block-paragraph">The revised brief is shown in Figure 2.</p>


<div class="wp-block-image">
<figure data-wp-context="{&quot;imageId&quot;:&quot;6a7670255a95c&quot;}" data-wp-interactive="core/image" data-wp-key="6a7670255a95c" class="aligncenter size-full wp-lightbox-container"><img decoding="async" width="626" height="578" data-wp-class--hide="state.isContentHidden" data-wp-class--show="state.isContentVisible" data-wp-init="callbacks.setButtonStyles" data-wp-on--click="actions.showLightbox" data-wp-on--load="callbacks.setButtonStyles" data-wp-on--pointerdown="actions.preloadImage" data-wp-on--pointerenter="actions.preloadImageWithDelay" data-wp-on--pointerleave="actions.cancelPreload" data-wp-on-window--resize="callbacks.setButtonStyles" src="https://searchengineland.com/wp-content/seloads/2026/08/image-3.jpeg" alt="" class="wp-image-484461"/><button
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				<path fill="#fff" d="M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z" />
			</svg>
		</button></figure>
</div>


<p class="wp-block-paragraph">I didn&#8217;t add an elaborate prompting formula or ask the models to reason in a particular way. I supplied the information a strategist would ordinarily gather before recommending a course of action.</p>



<p class="wp-block-paragraph">The difference was immediate. All three models retained their original approaches, but their recommendations were grounded in the same business.</p>



<ul class="wp-block-list">
<li>Claude remained discovery-oriented, focusing on seasonal demand, maintenance agreements, existing assets, and budget prioritization.</li>



<li>Gemini remained more technical, tying its recommendations more closely to local service questions and commercial constraints.</li>



<li>ChatGPT retained its framework-driven approach, prioritizing repair-versus-replacement decisions, maintenance-plan development, and protecting the company&#8217;s existing SEO environment.</li>
</ul>



<p class="wp-block-paragraph">Additional business context transformed the assignment into a brief. The responses became more detailed, more commercially relevant, and more closely aligned with the same business challenge.</p>



<p class="wp-block-paragraph">The quality of the response depended less on the sophistication of the prompt than on the quality of the business context behind it.</p>



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<h2 id="h-final-run-where-human-judgment-still-matters" class="wp-block-heading">Final run: Where human judgment still matters</h2>



<p class="wp-block-paragraph">A better brief brought the models closer together. It didn&#8217;t automatically make their recommendations useful.</p>



<p class="wp-block-paragraph">All three generated more possibilities than a regional business with a limited budget could reasonably pursue before the upcoming season. They identified opportunities, organized them, and explained why each might matter. Choosing among them still required strategic judgment.</p>



<p class="wp-block-paragraph">Choosing among the recommendations required strategic judgment. I evaluated them by a different standard:</p>



<ul class="wp-block-list">
<li>Would I present this to a client? </li>



<li>Could they act on it? </li>



<li>Was it supported by available evidence? </li>



<li>Did it align with the objectives, or was it simply a reasonable SEO activity?</li>
</ul>



<p class="wp-block-paragraph">Any recommendation could be technically valid and still be a poor investment. A content opportunity might appear useful but lack evidence of customer interest or demand. A measurement framework could be thorough but unrealistic, given available staffing or systems.</p>



<p class="wp-block-paragraph">A few priorities consistently survived across model revisions:</p>



<ul class="wp-block-list">
<li>Establishing a baseline for how the company appears in commercially significant AI-generated answers.</li>



<li>Measuring qualified leads, booked work, and maintenance agreement growth alongside citations and AI referrals.</li>



<li>Defining what counts as a qualified inquiry before treating visibility as a success.</li>



<li>Auditing existing service pages, local business information, and conversion paths before commissioning substantial new content.</li>



<li>Creating new assets only when existing pages couldn&#8217;t address a validated information gap.</li>



<li>Emphasizing urgent seasonal decisions and maintenance agreement opportunities rather than a sitewide transformation.</li>
</ul>



<p class="wp-block-paragraph">The models expanded the field of possibilities, but strategic judgment still needed to narrow it.</p>


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<h2 id="h-prompts-are-evidence-not-explanations" class="wp-block-heading">Prompts are evidence, not explanations</h2>



<p class="wp-block-paragraph">A prompt screenshot typically conceals how the assignment framed the task, how the brief added business context, and how human judgment established priorities.</p>



<p class="wp-block-paragraph">Exact prompts are useful because they show how a task was framed and what information the model received. They don&#8217;t reveal what the user already knew, what the first run exposed, what assumptions were rejected, or why the next revision changed.</p>



<p class="wp-block-paragraph">That’s why a prompt that produced an impressive result in one situation delivers something merely adequate in another. The words are the same, but the thinking behind them isn&#8217;t.</p>



<p class="wp-block-paragraph">A prompt makes discovery, research, business judgment, and editorial review visible to the model. It doesn&#8217;t replace them.</p>



<h2 id="h-what-the-prompt-leaves-out" class="wp-block-heading">What the prompt leaves out</h2>



<p class="wp-block-paragraph">The experiment started with an assignment. It evolved into a brief. Human judgment established the priorities.</p>



<p class="wp-block-paragraph">A prompt is the first visible artifact of that workflow. We ask others for prompts because they&#8217;re easy to share. They fit into a screenshot, a social post, or a slide. </p>



<p class="wp-block-paragraph">The conversations, changing assumptions, false starts, and judgment calls behind them are harder to package. They&#8217;re also far more instructive.</p>



<p class="wp-block-paragraph">The next time someone shares an impressive AI output, asking for the prompt may still be worthwhile. Just don&#8217;t mistake it for the full explanation. The more useful question is how they got there.</p>

Every AI success story seems to end the same way. Someone shares a remarkable output, and almost immediately someone asks, “Will you share the prompt?”
It’s a reasonable request. We often give prompts too much credit. By the time someone writes a prompt, they’ve already defined objectives, gathered context, weighed tradeoffs, and decided what success looks like. 
Prompts capture the result of conversations, assumptions, revisions, and editorial judgments that came long before anyone started typing.
To see how much that process matters, I gave the same strategic assignment to ChatGPT, Claude, and Gemini, changing only the information that came before the prompt.
The experiment
The assignment was straightforward. A company had invested in SEO for years, and its website was well established. Leadership knew search behavior was changing as AI-generated answers became more common, but no one knew what, if anything, should change about the marketing strategy.
I gave the same assignment to ChatGPT, Claude, and Gemini. The goal was to create a strategic roadmap identifying:
What information should be gathered.
Which opportunities deserved attention.
Which assumptions required validation.
What should happen before content creation began.
I wasn’t trying to identify the “winning” model. I wanted to see how the responses changed as the assignment evolved.
customers find first.
      
Start your free trial
    
First run: The models filled in the missing intent
At first, I believed I’d crafted a perfectly reasonable prompt. Then I realized what I’d actually written was a perfectly reasonable assignment. Rather than reproduce it line by line, here’s what it included:
A request for strategic guidance rather than marketing copy.
An explanation that it was for an established business concerned about its visibility in AI-generated search.
Instructions to identify missing information to prevent hallucinations and invented facts.
An expectation that the response would prioritize planning over execution.
The complete opening assignment is shown in Figure 1.

			
				




It defined the problem, established the type of help I needed, and discouraged unsupported assumptions. It also left room for interpretation.
Then I ran the assignment through all three models. The responses came back quickly. They were thoughtful, well-organized, and complete. 
Each would have seemed reasonable on its own. Side by side, however, they revealed something important: They weren’t really answering the same question.
Claude treated the assignment as the beginning of a discovery project. 
Gemini interpreted it primarily as an AI search optimization project. 
ChatGPT expanded it into a formal consulting framework with governance, measurement, and phased implementation.
None of the interpretations were unreasonable. The issue was that the models hadn’t been told which business problem mattered most.
Was the problem declining traffic? Brand visibility? AI citations? Lead generation? Competitive pressure? Future readiness? Each requires a different strategy. 
Without enough information to understand the underlying intent, each model supplied its own interpretation. When an assignment leaves room for interpretation, models don’t simply fill in missing facts. They fill in the missing intent.
I stopped thinking about how to improve a prompt and started thinking about how to improve the brief.
Second run: Better context, better recommendations
Experienced marketers begin with conversations. They learn what success looks like, which customers matter most, where the business makes its money, what constraints exist, and which compromises are acceptable. Then they turn that information into a functional brief.
That’s what my process intentionally skipped for the experiment.
For the second run, I kept the original assignment largely intact and added the information that would normally emerge during those conversations.
The revised brief established the client as a regional HVAC company with a mature website, a limited budget, and a preference for improving existing assets before creating significant new content. It also clarified the objective of increasing qualified service inquiries during the upcoming season, with maintenance agreements representing the highest-value long-term outcome.
The revised brief is shown in Figure 2.

			
				




I didn’t add an elaborate prompting formula or ask the models to reason in a particular way. I supplied the information a strategist would ordinarily gather before recommending a course of action.
The difference was immediate. All three models retained their original approaches, but their recommendations were grounded in the same business.
Claude remained discovery-oriented, focusing on seasonal demand, maintenance agreements, existing assets, and budget prioritization.
Gemini remained more technical, tying its recommendations more closely to local service questions and commercial constraints.
ChatGPT retained its framework-driven approach, prioritizing repair-versus-replacement decisions, maintenance-plan development, and protecting the company’s existing SEO environment.
Additional business context transformed the assignment into a brief. The responses became more detailed, more commercially relevant, and more closely aligned with the same business challenge.
The quality of the response depended less on the sophistication of the prompt than on the quality of the business context behind it.
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Final run: Where human judgment still matters
A better brief brought the models closer together. It didn’t automatically make their recommendations useful.
All three generated more possibilities than a regional business with a limited budget could reasonably pursue before the upcoming season. They identified opportunities, organized them, and explained why each might matter. Choosing among them still required strategic judgment.
Choosing among the recommendations required strategic judgment. I evaluated them by a different standard:
Would I present this to a client? 
Could they act on it? 
Was it supported by available evidence? 
Did it align with the objectives, or was it simply a reasonable SEO activity?
Any recommendation could be technically valid and still be a poor investment. A content opportunity might appear useful but lack evidence of customer interest or demand. A measurement framework could be thorough but unrealistic, given available staffing or systems.
A few priorities consistently survived across model revisions:
Establishing a baseline for how the company appears in commercially significant AI-generated answers.
Measuring qualified leads, booked work, and maintenance agreement growth alongside citations and AI referrals.
Defining what counts as a qualified inquiry before treating visibility as a success.
Auditing existing service pages, local business information, and conversion paths before commissioning substantial new content.
Creating new assets only when existing pages couldn’t address a validated information gap.
Emphasizing urgent seasonal decisions and maintenance agreement opportunities rather than a sitewide transformation.
The models expanded the field of possibilities, but strategic judgment still needed to narrow it.
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Prompts are evidence, not explanations
A prompt screenshot typically conceals how the assignment framed the task, how the brief added business context, and how human judgment established priorities.
Exact prompts are useful because they show how a task was framed and what information the model received. They don’t reveal what the user already knew, what the first run exposed, what assumptions were rejected, or why the next revision changed.
That’s why a prompt that produced an impressive result in one situation delivers something merely adequate in another. The words are the same, but the thinking behind them isn’t.
A prompt makes discovery, research, business judgment, and editorial review visible to the model. It doesn’t replace them.
What the prompt leaves out
The experiment started with an assignment. It evolved into a brief. Human judgment established the priorities.
A prompt is the first visible artifact of that workflow. We ask others for prompts because they’re easy to share. They fit into a screenshot, a social post, or a slide. 
The conversations, changing assumptions, false starts, and judgment calls behind them are harder to package. They’re also far more instructive.
The next time someone shares an impressive AI output, asking for the prompt may still be worthwhile. Just don’t mistake it for the full explanation. The more useful question is how they got there.

See how three AI models responded as business context became progressively richer for the same strategic challenge.

How business context changes AI recommendations

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/What-six-perspectives-reveal-about-demand-generation-in-AI-search.png" class="attachment-large size-large wp-post-image" alt="What six perspectives reveal about demand generation in AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/What-six-perspectives-reveal-about-demand-generation-in-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/What-six-perspectives-reveal-about-demand-generation-in-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/What-six-perspectives-reveal-about-demand-generation-in-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/What-six-perspectives-reveal-about-demand-generation-in-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>SEO, PR, analyst relations, and publishers are solving the same AI measurement problem from different angles. Here's what they agree on.

Over the past few months, six organizations have published new research, models, and perspectives on measuring marketing performance. They come from different disciplines, including SEO, PR, analyst relations, and media measurement, and they don’t always agree. Together, though, they point to a broader shift: marketing success can no longer be measured through website traffic alone.
Rather than competing ideas, these perspectives describe different dimensions of the same problem. Comparing them side by side reveals where they overlap, where they diverge, and what marketers can learn from each as they rethink demand generation in an AI-driven, zero-click world.
Six perspectives on the same problem
According to an ancient Indian parable, a group of blind men who had never encountered an elephant decided to learn what it was like by touch.
Each touched a different part of the animal and came away with a different conclusion:
The side was a wall.
The tusk was a spear.
The trunk was a snake.
The leg was a tree.
The ear was a fan.
The tail was a rope.
Because each believed only his own experience, they argued rather than recognizing that they were describing the same animal.
The six perspectives in this article work much the same way. Each captures a different aspect of measuring marketing performance in AI-driven search. Together, they offer a more complete picture of how AI is changing marketing measurement.
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1. Zero-click marketing
Most Search Engine Land readers have already seen Rand Fishkin’s SparkToro post, “In 2026, Less than One Third of Google Searches Still Send a Click.” In the first four months of 2026, 68.01% of Google searches ended without a click — up from 60.45% in 2024 — and Fishkin attributes much of that acceleration to AI Overviews, now present on over 20% of searches and cutting CTR by nearly 60% when they appear.
Fishkin’s recommendations boil down to six points: 
Replace traffic with a correlation dashboard tracking brand and demand signals over time.
Do audience research to find where your ICP (Ideal Customer Profile) actually pays attention.
Invest in channels you don’t own without obsessing over traffic back to your site.
Keep publishing on-site content anyway, since it still shapes AI Overviews.
Build short-form storytelling skills for the platforms where attention now lives.
Remember that SEO still pays off for branded, local, and high-intent transactional searches — territory Cyrus Shepard recently mapped in “The Websites Still Winning In Google.”
SparkToro’s perspective naturally emphasizes where audience attention has shifted. That becomes important when compared with the perspectives that follow.
2. GEO tactics for AI visibility
The second perspective comes from research Fractl conducted with Search Engine Land, presented by cofounder Kelsey Libert at SMX Advanced in Boston on June 4. I covered the key findings for Search Engine Land.
One of the study’s most notable findings is a collapse in trust. In 2025, 82% of consumers found AI search more helpful than traditional search; by 2026, that had fallen to 54%, a 28-point drop in a year. 
More useful, though, is the GEO tactic hierarchy Libert presented: high risk, table stakes, and the moat.
FAQ optimization (49% adoption) is high risk because it’s trivially replicable. Brand mentions, topical authority, and structured data are table stakes.
The moat is original data, proprietary research, and digital PR — the kind of content AI systems need but can’t replicate.
The hierarchy reflects the broader shift away from traffic-based metrics and toward influence, authority, and original information.
Fractl and Search Engine Land’s data give a tactical answer to which content actually travels. Branded web mentions and YouTube impressions correlate with AI visibility at 0.50-0.74, while backlink count and ad spend sit below 0.30 — a reallocation signal away from link building and paid tactics and toward earned placements and original research.
Additionally, the research found that buyers check an average of 2.4 platforms before validating a purchase. That’s a concrete, surveyable proxy for the “influence” Fishkin says should replace traffic as a KPI.
3. AI measurement through upstream evidence
On May 20, AMEC — the body behind the Barcelona Principles that have shaped PR measurement for over a decade — released its seven GEO Principles and a companion Practitioner’s Guide to GEO Measurement, developed with practitioners from FleishmanHillard, Ketchum, Hotwire Global, Converseon, Big Valley Marketing, and PR Agency One.
If that sounds like a PR trade story rather than an SEO one, that’s part of the problem. Many marketers have treated AI citations as the new rankings. AMEC takes a different view, arguing that visibility is only one part of a broader measurement model that connects AI discovery to awareness, trust, behavior, and business impact.
Although the SEO and PR/comms communities have operated in separate silos for years, both now depend on the same upstream content to shape what AI engines say.
AMEC organizes GEO measurement into three evidence domains:
Upstream reputation (the earned, shared, and owned content AI models draw on).
Search and content readiness (whether that information is structured and discoverable).
Downstream AI output tracking (what stakeholders actually see — presence, framing, citations, accuracy).
Map this against Fishkin’s point that your site’s influence on AI Overviews persists even as clicks disappear, and the connection is clear. AMEC’s upstream and readiness domains are essentially a measurement protocol for the work Fishkin says still matters.
Where it gets more useful for demand gen is Principle 5: GEO measurement should distinguish visibility from outcomes and connect AI discovery to awareness, trust, behavior, and impact. 
Appearing in an AI Overview is an output. Whether that appearance moved someone toward a purchase decision is an outcome — and AMEC is explicit that no single tool or score proves that connection. 
The guide is candid that connecting any of it to pipeline requires “combined evidence” — a comfort with directional, triangulated evidence rather than a dashboard number that maps cleanly to MQLs (marketing-qualified leads).
For practitioners, the takeaway is a new minimum evidence bar: a governed query library tied to actual buyer questions, documented prompts and platforms, repeat testing with variation disclosed, and saved outputs as evidence.
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4. Credibility and AI trust
The fourth perspective comes from Burson, one of the world’s largest PR and communications agencies, which released “The Credibility Paradox: Advancing Generative Engine Optimization from Visibility to Reputation” in June. While AMEC focuses on measuring AI visibility and its business impact, Burson shifts the conversation to whether audiences believe what AI says about a brand.
Burson partnered with AI marketing platform Profound to run thousands of reputation-related prompts across seven AI platforms, covering 85 companies in 10 industries against eight “reputation levers.” The agency’s Decipher tool then generated more than 55,000 “believability forecasts” for the resulting answers.
Interestingly, the headline finding sharpens AMEC’s fifth principle: A brand can be cited by an AI engine and still lose the reputation opportunity if the audience doesn’t believe what the AI says about it. Burson calls this the Credibility Paradox — seen, but not believed.
The most useful finding for demand gen is the proof-versus-posture divide. Levers backed by observable evidence — innovation, creativity, workplace, products — outperformed levers that depend on institutional self-description, like leadership, governance, and citizenship, by roughly a two-to-one margin. 
AI engines are more willing to vouch for what your product does and what it’s like to work at your company than for what your leadership says about its own values — a direct signal for content prioritization.
Regarding the methodology, those 55,000 believability forecasts come from an AI system that predicts how human audiences would judge AI-generated answers — AI assessing AI at scale. That makes treating it as directional rather than definitive. 
But on the underlying question of whether “credibility” can even be measured, my colleague Katie Paine — a measurement standards veteran who reviewed an earlier draft of this article — makes a useful point: Credibility isn’t as unmeasurable as it sounds, because for goals like this, you can define proxies. 
If someone doesn’t find an AI-generated answer about your brand credible, they probably won’t follow you, share your content, or click through when a link is offered. Believability may be a precursor metric to behaviors GEO tools can already track.
Burson naturally emphasizes the credibility layer because reputation measurement is central to its work.
5. Analyst influence in B2B AI discovery
The fifth perspective comes from a different direction entirely. In a LinkedIn post, Jamin Spitzer — a former Microsoft communications insights leader now running his own measurement consultancy — argues that GEO belongs on the analyst relations desk, not the SEO desk.
Spitzer’s case: When a B2B buyer asks an AI platform who leads a category or what their shortlist should be, the answer is frequently a synthesis of analyst content — Gartner, Forrester, IDC, independent analysts — because that content is exactly the authoritative, comparative, taxonomy-rich material generative engines are built to reach for. 
AR teams have spent decades trying to trace influence that “shapes a buyer’s mental model” long before it surfaces in a deal. Spitzer argues GEO tools now make that influence newly observable, such as:
Which analysts’ framing a model is reproducing.
Whether a brand is described using current or outdated positioning.
Where gaps exist between a company’s priority analysts and what the AI is actually citing.
This is the B2B hand on the elephant that the first three perspectives largely miss. AMEC, Burson, and Fractl all gravitate toward consumer-facing or brand-reputation signals — workplace, innovation, earned media, and YouTube mentions. 
None of them addresses the specific mechanism Spitzer describes: a multi-month enterprise sales cycle in which an AI-generated “consideration set,” built partly from analyst reports, can shape outcomes before a buyer ever opens a Magic Quadrant.
For B2B demand gen specifically, Spitzer’s perspective suggests the upstream content that matters most isn’t earned media or product pages, it’s analyst relationships and the content those relationships produce.
And the pattern repeats once more: An AR-focused measurement consultant is naturally positioned to see the analyst-influence layer of this problem, for the same reason a PR agency sees credibility and a digital PR agency sees entity authority. 
Spitzer’s framing doesn’t compete with AMEC, Burson, or Fractl so much as identify a category of upstream source — analyst content that the others’ perspectives don’t name.
6. The credibility gap in AI citations
The sixth perspective connects to research from Angela Dwyer at Full Intel, which Paine also flagged. 
Dwyer’s analysis of AI media citations and credible journalism examined which news sources AI platforms cite most often when answering questions. She found a gap between citation frequency and the outlets that audiences rate as most trustworthy. 
That’s a publisher-side mirror of Burson’s brand-side paradox: Just as a brand can be visible but not believed, a publication can be heavily cited by AI engines while its own readers hold it in lower regard than less-cited competitors. 
For demand gen, it’s a reminder that the upstream sources AMEC and Burson both point to aren’t a neutral pool. Some of the outlets AI leans on most are themselves fighting a credibility gap, which complicates the idea that “getting cited by a major publication” is a clean proxy for credibility transfer.
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Here’s the elephant
Read side by side, these perspectives resemble six different hands on the same elephant:
SparkToro sees attention and correlation.
Fractl sees entity authority and earned mentions.
AMEC sees upstream evidence domains.
Burson sees credibility and believability.
Spitzer sees analyst influence in B2B buying cycles.
Dwyer’s research highlights the credibility of the news sources AI relies on.
None of these perspectives replaces the others. Each measures a different dimension of how AI influences discovery, trust, and buying decisions. Together, they suggest marketing measurement is becoming multidimensional rather than website-centric.
Rather than searching for a single model, marketers may need to combine multiple perspectives. No single perspective captures the whole picture, but together they offer a more complete view of how AI shapes visibility, influence, and demand.

SEO, PR, analyst relations, and publishers are solving the same AI measurement problem from different angles. Here's what they agree on.

What six perspectives reveal about demand generation in AI search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see.png" class="attachment-large size-large wp-post-image" alt="Your rankings aren&#039;t telling you what your customers see" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Customers don't search in the controlled environment your SEO tools measure. That gap changes how you should interpret rankings.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see.png" class="attachment-large size-large wp-post-image" alt="Your rankings aren&#039;t telling you what your customers see" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Your-rankings-arent-telling-you-what-your-customers-see-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">&#8220;We&#8217;re number one now, so why hasn&#8217;t traffic gone up?&#8221; I still get versions of that question almost every week.</p>



<p class="wp-block-paragraph">For years, <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> has been built around rankings. Clients wanted to know where they ranked on Google, agencies proudly reported monthly position improvements, and SEO software became increasingly sophisticated at tracking every movement.</p>



<p class="wp-block-paragraph">There&#8217;s nothing wrong with that. I still monitor rankings every day. The problem is that ranking first no longer means being seen first.</p>



<p class="wp-block-paragraph">Search for almost any commercial keyword today, and before you reach the first organic listing, you&#8217;ll probably see paid ads, an AI Overview, shopping results, local businesses, videos, People Also Ask, images, or Reddit discussions. By the time customers reach what we used to call Position 1, they&#8217;ve already seen much of the page.</p>



<p class="wp-block-paragraph">Technically, you may still rank first organically. Practically, you might be halfway down the page before anyone even has the chance to click your website.</p>



<p class="wp-block-paragraph">On mobile, where most searches now take place, the challenge is even greater. Screen space is limited. Users often have to scroll through multiple Google-owned features before they reach a traditional organic result. In some cases, they never do.</p>



<h2 id="h-there-isn-t-one-version-of-google-anymore" class="wp-block-heading">There isn&#8217;t one version of Google anymore</h2>



<p class="wp-block-paragraph">Clients often compare what they&#8217;re seeing with what someone else sees.</p>



<ul class="wp-block-list">
<li>&#8220;I can see us at number two.&#8221;</li>



<li>&#8220;I&#8217;m seeing us at number five.&#8221;</li>



<li>&#8220;My colleague can&#8217;t see us at all.&#8221;</li>
</ul>



<p class="wp-block-paragraph">Usually, they&#8217;re all right.</p>



<p class="wp-block-paragraph">Google has personalized search results for years, but it&#8217;s become much more noticeable. Location, device, search history, and intent all influence what Google shows. Even the way someone phrases a search can completely change what appears.</p>



<p class="wp-block-paragraph">When we produce ranking reports, we&#8217;re measuring one version of Google&#8217;s results under controlled conditions. That&#8217;s useful. It helps us spot trends, identify technical problems, and monitor progress over time.</p>



<p class="wp-block-paragraph">But it isn&#8217;t showing exactly what every potential customer sees.</p>



<p class="wp-block-paragraph">That&#8217;s an important distinction because too many businesses still assume rankings are an absolute measure of visibility. They&#8217;re not.</p>



<p class="wp-block-paragraph">That&#8217;s one reason SEO can feel so confusing for business owners. They search for their own company, don&#8217;t see what they expected, and assume something is wrong. In reality, Google may simply be showing them a different version of the results than it shows someone else.</p>


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<h2 id="h-why-clients-still-fixate-on-rankings" class="wp-block-heading">Why clients still fixate on rankings</h2>



<p class="wp-block-paragraph">This might be slightly controversial, but the SEO industry has created part of this problem.</p>



<p class="wp-block-paragraph">For years, we&#8217;ve led with rankings because they&#8217;re easy to measure and explain. It&#8217;s much simpler to tell a client they&#8217;ve moved from position seven to position three than it is to explain changes in search visibility across multiple search features.</p>



<p class="wp-block-paragraph">The downside is we&#8217;ve conditioned businesses to judge SEO almost entirely on rankings. That becomes a problem when a client drops two positions and immediately thinks something has gone wrong, even though inquiries have increased.</p>



<p class="wp-block-paragraph">I&#8217;ve had exactly that conversation. The ranking report suggested performance had slipped. The business&#8217;s phone certainly didn&#8217;t.</p>



<p class="wp-block-paragraph">That&#8217;s when you realize rankings don&#8217;t always reflect what&#8217;s really happening.</p>



<p class="wp-block-paragraph">I&#8217;ve also had the opposite conversation, where rankings improved across dozens of keywords, but leads barely changed. On paper, the campaign looked fantastic. From the client&#8217;s perspective, nothing meaningful had happened because the business hadn&#8217;t grown.</p>



<p class="wp-block-paragraph">That was a useful reminder that SEO reports should never become more important than business results.</p>



<h2 id="h-ai-didn-t-start-this-shift-it-accelerated-it" class="wp-block-heading">AI didn&#8217;t start this shift. It accelerated it.</h2>



<p class="wp-block-paragraph">There&#8217;s a lot of discussion around AI Overviews, and understandably so. They&#8217;re changing how people search and how information is presented.</p>



<p class="wp-block-paragraph">Google had already been moving away from 10 blue links for years. Featured snippets, Local Packs, shopping results, videos, image packs, and knowledge panels had already transformed the search results long before AI entered the conversation.</p>



<p class="wp-block-paragraph">AI has simply made the gap between rankings and visibility even wider. We&#8217;re optimizing for a search experience, not a predictable page of results.</p>



<p class="wp-block-paragraph">What&#8217;s different now is that Google is becoming much better at answering questions without requiring users to visit a website at all.&nbsp;</p>



<p class="wp-block-paragraph">For informational searches, an AI Overview can often provide enough information for someone to move on without clicking anything.</p>



<p class="wp-block-paragraph">That doesn&#8217;t necessarily mean SEO is becoming less valuable. It means the role of SEO is evolving. We&#8217;re no longer competing only against other websites. Increasingly, we&#8217;re competing for attention within Google&#8217;s own search experience.</p>



<p class="wp-block-paragraph">That&#8217;s also why rankings have become a less reliable way to measure SEO performance. They still tell us something useful, but they no longer tell us everything we need to know.</p>



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<h2 id="h-click-through-rate-deserves-more-attention" class="wp-block-heading">Click-through rate deserves more attention</h2>



<p class="wp-block-paragraph">One place to start is click-through rate. If rankings were the whole story, we&#8217;d expect every number one ranking to deliver the highest percentage of clicks.</p>



<p class="wp-block-paragraph">We know that isn&#8217;t always true. The title tag, the meta description, brand recognition, review stars, search intent, and the surrounding search features all influence whether someone chooses to click.</p>



<p class="wp-block-paragraph">I&#8217;ve seen pages ranked third outperform pages ranked first simply because the listing was more compelling.</p>



<p class="wp-block-paragraph">Equally, I&#8217;ve seen strong rankings produce disappointing traffic because the page was buried beneath paid ads, AI Overviews, and other Google features. That&#8217;s why rankings should always be viewed alongside impressions, click-through rates, and conversions.&nbsp;</p>



<p class="wp-block-paragraph">Looking at one metric in isolation rarely tells the full story.</p>



<h2 id="h-the-question-clients-care-about" class="wp-block-heading">The question clients care about</h2>



<p class="wp-block-paragraph">When I meet a new client, they rarely say they want better rankings.</p>



<p class="wp-block-paragraph">What they really want is more inquiries. More sales. More leads. More customers.</p>



<p class="wp-block-paragraph">Rankings only matter if they help deliver those outcomes.</p>



<p class="wp-block-paragraph">I&#8217;ve seen websites sitting in second or third position consistently outperform competitors ranked above them because their titles were more compelling, their content answered the user&#8217;s question better, or their brand had built more trust.</p>



<p class="wp-block-paragraph">Equally, I&#8217;ve seen businesses celebrate reaching number one while inquiries barely moved because hardly anyone was clicking that listing anymore.</p>



<p class="wp-block-paragraph">That&#8217;s why we need to stop treating rankings as the finish line. They&#8217;re a useful indicator. They&#8217;re not the objective.</p>



<p class="wp-block-paragraph">The businesses that succeed online aren&#8217;t usually the ones obsessed with a single keyword. They&#8217;re the ones creating genuinely useful content, building trust with their audience, and making it easy for customers to take the next step.</p>



<p class="wp-block-paragraph">That&#8217;s much harder to measure than rankings, but it&#8217;s ultimately what drives long-term growth.</p>



<h2 id="h-so-what-should-we-be-measuring" class="wp-block-heading">So what should we be measuring?</h2>



<p class="wp-block-paragraph">Rankings deserve a place in every SEO report. But they shouldn’t dominate the conversation.</p>



<p class="wp-block-paragraph">Instead, ask questions like these:</p>



<ul class="wp-block-list">
<li>Are we attracting the right visitors?</li>



<li>Are more people making contact?</li>



<li>Has organic traffic become more qualified?</li>



<li>Are we visible in the places our customers are actually searching?</li>



<li>Is SEO contributing to business growth?</li>



<li>Are branded searches increasing?</li>



<li>Are users returning to the website?</li>



<li>Is organic search generating revenue rather than simply visits?</li>
</ul>



<p class="wp-block-paragraph">Those are the conversations clients care about because they&#8217;re the ones that affect their business. The best SEO campaigns I&#8217;ve worked on haven&#8217;t always been the ones with the biggest ranking improvements.</p>



<p class="wp-block-paragraph">They&#8217;ve been the ones where SEO became an important contributor to the company&#8217;s overall growth. That&#8217;s a much more meaningful achievement.</p>


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<h2 id="h-seo-has-always-evolved-and-so-should-the-way-we-measure-it" class="wp-block-heading">SEO has always evolved, and so should the way we measure it</h2>



<p class="wp-block-paragraph">I&#8217;ve worked in SEO for nearly 20 years. During that time, we&#8217;ve adapted to countless algorithm updates, mobile-first indexing, Core Web Vitals, Helpful Content updates, and now AI-driven search.</p>



<p class="wp-block-paragraph">Every few years, something changes the way we work. This is one of those moments.</p>



<p class="wp-block-paragraph">If a client&#8217;s inquiries have doubled, revenue has increased, and they&#8217;re winning more customers, moving from Position 1 to Position 3 for a handful of keywords isn&#8217;t the story that matters. That&#8217;s not how businesses measure success, and it shouldn&#8217;t be how SEO professionals measure it, either.</p>



<p class="wp-block-paragraph">Google isn&#8217;t one fixed search engine anymore. It&#8217;s a constantly changing experience that&#8217;s different for every user.</p>



<p class="wp-block-paragraph">Today, the question isn&#8217;t simply, &#8220;Where do we rank?&#8221; It&#8217;s, &#8220;Can our customers actually see us when they&#8217;re searching?&#8221;</p>



<p class="wp-block-paragraph">The sooner we stop treating rankings as the ultimate KPI, the sooner we&#8217;ll have better conversations with clients, produce more meaningful reports, and measure SEO in ways that reflect how Google works today.</p>

“We’re number one now, so why hasn’t traffic gone up?” I still get versions of that question almost every week.
For years, SEO has been built around rankings. Clients wanted to know where they ranked on Google, agencies proudly reported monthly position improvements, and SEO software became increasingly sophisticated at tracking every movement.
There’s nothing wrong with that. I still monitor rankings every day. The problem is that ranking first no longer means being seen first.
Search for almost any commercial keyword today, and before you reach the first organic listing, you’ll probably see paid ads, an AI Overview, shopping results, local businesses, videos, People Also Ask, images, or Reddit discussions. By the time customers reach what we used to call Position 1, they’ve already seen much of the page.
Technically, you may still rank first organically. Practically, you might be halfway down the page before anyone even has the chance to click your website.
On mobile, where most searches now take place, the challenge is even greater. Screen space is limited. Users often have to scroll through multiple Google-owned features before they reach a traditional organic result. In some cases, they never do.
There isn’t one version of Google anymore
Clients often compare what they’re seeing with what someone else sees.
“I can see us at number two.”
“I’m seeing us at number five.”
“My colleague can’t see us at all.”
Usually, they’re all right.
Google has personalized search results for years, but it’s become much more noticeable. Location, device, search history, and intent all influence what Google shows. Even the way someone phrases a search can completely change what appears.
When we produce ranking reports, we’re measuring one version of Google’s results under controlled conditions. That’s useful. It helps us spot trends, identify technical problems, and monitor progress over time.
But it isn’t showing exactly what every potential customer sees.
That’s an important distinction because too many businesses still assume rankings are an absolute measure of visibility. They’re not.
That’s one reason SEO can feel so confusing for business owners. They search for their own company, don’t see what they expected, and assume something is wrong. In reality, Google may simply be showing them a different version of the results than it shows someone else.
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Why clients still fixate on rankings
This might be slightly controversial, but the SEO industry has created part of this problem.
For years, we’ve led with rankings because they’re easy to measure and explain. It’s much simpler to tell a client they’ve moved from position seven to position three than it is to explain changes in search visibility across multiple search features.
The downside is we’ve conditioned businesses to judge SEO almost entirely on rankings. That becomes a problem when a client drops two positions and immediately thinks something has gone wrong, even though inquiries have increased.
I’ve had exactly that conversation. The ranking report suggested performance had slipped. The business’s phone certainly didn’t.
That’s when you realize rankings don’t always reflect what’s really happening.
I’ve also had the opposite conversation, where rankings improved across dozens of keywords, but leads barely changed. On paper, the campaign looked fantastic. From the client’s perspective, nothing meaningful had happened because the business hadn’t grown.
That was a useful reminder that SEO reports should never become more important than business results.
AI didn’t start this shift. It accelerated it.
There’s a lot of discussion around AI Overviews, and understandably so. They’re changing how people search and how information is presented.
Google had already been moving away from 10 blue links for years. Featured snippets, Local Packs, shopping results, videos, image packs, and knowledge panels had already transformed the search results long before AI entered the conversation.
AI has simply made the gap between rankings and visibility even wider. We’re optimizing for a search experience, not a predictable page of results.
What’s different now is that Google is becoming much better at answering questions without requiring users to visit a website at all. 
For informational searches, an AI Overview can often provide enough information for someone to move on without clicking anything.
That doesn’t necessarily mean SEO is becoming less valuable. It means the role of SEO is evolving. We’re no longer competing only against other websites. Increasingly, we’re competing for attention within Google’s own search experience.
That’s also why rankings have become a less reliable way to measure SEO performance. They still tell us something useful, but they no longer tell us everything we need to know.
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Click-through rate deserves more attention
One place to start is click-through rate. If rankings were the whole story, we’d expect every number one ranking to deliver the highest percentage of clicks.
We know that isn’t always true. The title tag, the meta description, brand recognition, review stars, search intent, and the surrounding search features all influence whether someone chooses to click.
I’ve seen pages ranked third outperform pages ranked first simply because the listing was more compelling.
Equally, I’ve seen strong rankings produce disappointing traffic because the page was buried beneath paid ads, AI Overviews, and other Google features. That’s why rankings should always be viewed alongside impressions, click-through rates, and conversions. 
Looking at one metric in isolation rarely tells the full story.
The question clients care about
When I meet a new client, they rarely say they want better rankings.
What they really want is more inquiries. More sales. More leads. More customers.
Rankings only matter if they help deliver those outcomes.
I’ve seen websites sitting in second or third position consistently outperform competitors ranked above them because their titles were more compelling, their content answered the user’s question better, or their brand had built more trust.
Equally, I’ve seen businesses celebrate reaching number one while inquiries barely moved because hardly anyone was clicking that listing anymore.
That’s why we need to stop treating rankings as the finish line. They’re a useful indicator. They’re not the objective.
The businesses that succeed online aren’t usually the ones obsessed with a single keyword. They’re the ones creating genuinely useful content, building trust with their audience, and making it easy for customers to take the next step.
That’s much harder to measure than rankings, but it’s ultimately what drives long-term growth.
So what should we be measuring?
Rankings deserve a place in every SEO report. But they shouldn’t dominate the conversation.
Instead, ask questions like these:
Are we attracting the right visitors?
Are more people making contact?
Has organic traffic become more qualified?
Are we visible in the places our customers are actually searching?
Is SEO contributing to business growth?
Are branded searches increasing?
Are users returning to the website?
Is organic search generating revenue rather than simply visits?
Those are the conversations clients care about because they’re the ones that affect their business. The best SEO campaigns I’ve worked on haven’t always been the ones with the biggest ranking improvements.
They’ve been the ones where SEO became an important contributor to the company’s overall growth. That’s a much more meaningful achievement.
before your competitors.
      
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SEO has always evolved, and so should the way we measure it
I’ve worked in SEO for nearly 20 years. During that time, we’ve adapted to countless algorithm updates, mobile-first indexing, Core Web Vitals, Helpful Content updates, and now AI-driven search.
Every few years, something changes the way we work. This is one of those moments.
If a client’s inquiries have doubled, revenue has increased, and they’re winning more customers, moving from Position 1 to Position 3 for a handful of keywords isn’t the story that matters. That’s not how businesses measure success, and it shouldn’t be how SEO professionals measure it, either.
Google isn’t one fixed search engine anymore. It’s a constantly changing experience that’s different for every user.
Today, the question isn’t simply, “Where do we rank?” It’s, “Can our customers actually see us when they’re searching?”
The sooner we stop treating rankings as the ultimate KPI, the sooner we’ll have better conversations with clients, produce more meaningful reports, and measure SEO in ways that reflect how Google works today.

Customers don't search in the controlled environment your SEO tools measure. That gap changes how you should interpret rankings.

Your rankings aren’t telling you what your customers see

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image.png" class="attachment-large size-large wp-post-image" alt="You Can’t Demand the Click If You Won’t Give the Link - featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Publishers demanding citations and traffic from AI platforms should give the same credit to the data, research, and reporting they use.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image.png" class="attachment-large size-large wp-post-image" alt="You Can’t Demand the Click If You Won’t Give the Link - featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/You-Cant-Demand-the-Click-If-You-Wont-Give-the-Link-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Raise your hand if you’re frustrated by how much traffic Google has clawed back with the launch of AI Overviews and AI Mode.</p>



<p class="wp-block-paragraph">Admittedly, both of these can be crazy helpful for users. <em>(I know – it pains me to type it.)</em>



<p class="wp-block-paragraph">But across various industries, the response has been overwhelmingly negative. Publishers argue that Google is using their content without sending enough traffic in return. Some question the <a href="https://www.seoforlunch.com/p/what-if-you-were-held-accountable" target="_blank" rel="noopener">legal responsibility of AI answers</a>. Others are pursuing legal action or considering <a href="https://www.seroundtable.com/publishers-blocking-google-search-41735.html" target="_blank" rel="noopener">opting out of Google altogether</a>.</p>



<p class="wp-block-paragraph">Fine. To avoid a 6,000-word detour, I’ll concede the point: it doesn’t feel fair.</p>



<p class="wp-block-paragraph">But many of the same businesses demanding citations, links, and traffic from Google routinely reference another company’s data, reporting, or expertise without providing a clickable link. Sometimes they even write out the source’s domain while deliberately leaving it unlinked — all because someone is afraid of “giving away” link equity.</p>



<p class="wp-block-paragraph"><strong>You can’t demand that AI platforms support the open web while refusing to participate in it yourself.</strong>



<p><a href="https://www.seoforlunch.com/embed" rel="noopener noreferrer">View embedded content</a>



<h2 id="h-it-was-worth-mentioning-it-was-worth-linking" class="wp-block-heading">It was worth mentioning, it was worth linking</h2>



<p class="wp-block-paragraph">A citation isn’t a favor, and it isn’t an SEO handout. It allows readers to verify the claim, review the original research, understand its context, and discover the people or organizations responsible for the work.</p>



<p class="wp-block-paragraph">Take the example below. SEOJobs.com’s data was valuable enough to reference directly, but apparently not valuable enough to link to.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1328" height="317" src="https://searchengineland.com/wp-content/seloads/2026/08/image-1.jpeg" alt="" class="wp-image-484378" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-1.jpeg 1328w, https://searchengineland.com/wp-content/seloads/2026/08/image-1-768x183.jpeg 768w" sizes="(max-width: 1328px) 100vw, 1328px" /></figure>
</div>


<p class="wp-block-paragraph">SEOJobs.com is named as a resource — but isn’t linked.</p>



<p class="wp-block-paragraph">I notice these examples because I own the site and monitor brand mentions. But don’t confuse <a href="https://www.seojobs.com/" target="_blank" rel="noopener">SEOJobs.com</a> as a unique target. This happens every day to researchers, creators, small businesses, newsletters, podcasts, and independent publishers.</p>



<p class="wp-block-paragraph">If someone’s work helped strengthen your content, helping readers find the original source <em>should</em> be the default.</p>



<h2 id="h-why-publishers-withhold-links" class="wp-block-heading">Why publishers withhold links</h2>



<p class="wp-block-paragraph">Publishers usually justify withholding links in one of three ways. Two are based on misguided SEO thinking. The third can be legitimate, but often exposes another contradiction.</p>



<h3 id="h-we-don-t-want-to-lose-link-equity" class="wp-block-heading">‘We don’t want to lose link equity’</h3>



<p class="wp-block-paragraph">Linking to a relevant source does not drain your website’s authority like water leaking from a bucket. <em>(I desperately wanted to write that in all caps. I didn’t. You’re welcome.)</em>



<p class="wp-block-paragraph">You aren’t protecting your rankings by trapping readers on your domain or omitting citations that would make your content more useful.</p>



<p class="wp-block-paragraph">Refusing legitimate citations isn’t an SEO strategy. It puts a spotlight on a business that doesn’t understand how search works.</p>



<h3 id="h-we-don-t-want-to-help-their-seo" class="wp-block-heading">‘We don’t want to help their SEO’</h3>



<p class="wp-block-paragraph">This is where the justification gets uglier.</p>



<p class="wp-block-paragraph">Some publishers will reference a business, use its data, and even awkwardly write out its domain, just without making it clickable.</p>



<p class="wp-block-paragraph">I once contacted a publisher that referenced <a href="https://www.seojobs.com/blog/seo-job-report/">SEOJobs.com’s 2025 job data</a> and asked whether they would add a link so readers could view the full dataset. They declined. Instead, they offered to publish an “exclusive blog post” about SEOJobs.com for $500.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1020" height="415" src="https://searchengineland.com/wp-content/seloads/2026/08/image.jpeg" alt="" class="wp-image-484379" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image.jpeg 1020w, https://searchengineland.com/wp-content/seloads/2026/08/image-768x312.jpeg 768w" sizes="(max-width: 1020px) 100vw, 1020px" /><figcaption class="wp-element-caption"><em>Yes, I could buy ”coverage” — for $500.</em></figcaption></figure>
</div>


<p class="wp-block-paragraph">To be clear, I wasn’t asking them to sell me coverage. I was asking them to properly cite a source they had already chosen to mention.</p>



<p class="wp-block-paragraph">If the link was withheld so its value could be packaged into something they could sell me, that wasn’t an editorial decision. It was a sales strategy disguised as editorial policy.</p>



<h3 id="h-we-don-t-want-to-endorse-the-website" class="wp-block-heading">‘We don’t want to endorse the website’</h3>



<p class="wp-block-paragraph">This can be legitimate. Nobody should be expected to send readers to an unsafe website or lend credibility to misinformation. Paid placements and user-generated content also require different considerations.</p>



<p class="wp-block-paragraph">But for a standard editorial citation, the contradiction remains:</p>



<p class="wp-block-paragraph">If you didn’t consider the source credible enough for readers to visit, why was its information credible enough to use in your article?</p>



<h2 id="h-nofollow-is-not-an-editorial-safety-blanket" class="wp-block-heading">Nofollow is not an editorial safety blanket</h2>



<p class="wp-block-paragraph">Even when publishers provide a clickable link, many automatically apply a nofollow attribute as if it protects them from some undefined SEO risk. <em>(Someone, think of the </em><em><s>children</s></em><em> link juice!!!)</em>



<p class="wp-block-paragraph">But nofollow isn’t a generic disclaimer for every external website.</p>



<p class="wp-block-paragraph">Google already provides attributes for specific types of links. Sponsored is intended for advertisements, sponsorships, affiliate links, and other paid relationships. ugc applies to links added through user-generated content, such as comments or forum posts. nofollow can be used when a publisher genuinely does not want to associate its website with the destination.</p>



<p class="wp-block-paragraph">A normal, unpaid editorial citation doesn’t automatically fall into any of those categories.</p>



<p class="wp-block-paragraph">In the example below, SEOJobs.com was mentioned organically within an editorial article and linked as the source. There was no payment, sponsorship, affiliate relationship, or user-generated content. Yet the link was still tagged nofollow.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1456" height="322" src="https://searchengineland.com/wp-content/seloads/2026/08/image-2.jpeg" alt="" class="wp-image-484380" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-2.jpeg 1456w, https://searchengineland.com/wp-content/seloads/2026/08/image-2-768x170.jpeg 768w" sizes="(max-width: 1456px) 100vw, 1456px" /></figure>
</div>


<p class="wp-block-paragraph">The text is linked but contains a nofollow attribute</p>



<p class="wp-block-paragraph">Why?</p>



<p class="wp-block-paragraph">If the publication trusted the source enough to mention it, considered the destination safe enough to send readers to, and received no compensation for including it, <strong>what exactly was the attribute protecting them from?</strong>



<p class="wp-block-paragraph">This isn’t about obsessing over a tiny piece of HTML. It’s about the editorial mindset behind it.</p>



<p class="wp-block-paragraph">Automatically applying nofollow to every external link says:</p>



<ul class="wp-block-list">
<li>“<em>We’ll use your work, and we may even send readers to it — but we’ll make damn sure you receive as little value as possible…”</em></li>
</ul>



<p class="wp-block-paragraph">Sound familiar?</p>



<h2 id="h-publishers-are-recreating-the-same-problem" class="wp-block-heading">Publishers are recreating the same problem</h2>



<p class="wp-block-paragraph">Publishers are understandably frustrated: someone invests time and money creating original data, another platform uses it to improve its own product, and the original creator receives little (or nothing) in return.</p>



<p class="wp-block-paragraph"><strong>That is the fundamental complaint about AI Overviews.</strong>



<p class="wp-block-paragraph">But when a publisher uses another website’s research, reporting, examples, or ideas without linking to the original source, it creates the same problem on a smaller scale. The publisher strengthens its article, keeps the reader’s attention, and denies the creator even the opportunity to earn a visit.</p>



<p class="wp-block-paragraph">To be clear, publishers doing it doesn’t excuse Google and vice versa. Two wrongs don’t make a right. <em>(At least that’s what my Momma told me growing up)</em>



<p class="wp-block-paragraph">But if publishers expect AI companies to properly credit and support the sources behind their answers, they should hold themselves to the same standard.</p>



<h2 id="h-a-simple-standard-for-editorial-links" class="wp-block-heading">A simple standard for editorial links</h2>



<p class="wp-block-paragraph">This doesn’t need to be complicated. Before publishing, ask:</p>



<ul class="wp-block-list">
<li>Did this source contribute information, data, reporting, or an original idea?</li>



<li>Would visiting it help readers verify the claim or better understand the context?</li>



<li>Is the destination relevant, trustworthy, and safe?</li>



<li>Was the mention unpaid and editorially chosen?</li>
</ul>



<p class="wp-block-paragraph">If the answers are yes, <strong>provide a normal clickable link.</strong>



<ul class="wp-block-list">
<li>No need for a blanket nofollow policy.</li>



<li>No imaginary concern about leaking “link juice.”</li>
</ul>



<p class="wp-block-paragraph">Just give readers access to the source that helped make your content better.</p>



<h2 id="h-give-what-you-re-demanding" class="wp-block-heading">Give what you’re demanding</h2>



<p class="wp-block-paragraph">The open web cannot function when everyone wants attribution, but nobody wants to provide it. Links allow readers to inspect claims, recognize original work, and discover the people and businesses contributing real value.</p>



<p class="wp-block-paragraph">This isn’t about generously handing out SEO credit. It’s about giving readers the transparency they deserve and sources the recognition they earned.</p>



<p class="wp-block-paragraph">If you want Google and AI platforms to cite their sources, start by making sure you cite yours.</p>



<p class="wp-block-paragraph"><em>This post first appeared on the author’s website and is republished here with permission.</em>


<div class="wp-block-image">
<figure class="aligncenter"><a href="https://seoforlunch.com/?utm_source=searchengineland.com&amp;utm_medium=social"><img decoding="async" width="1774" height="887" src="https://searchengineland.com/wp-content/seloads/2026/05/leroy2.jpg.webp" alt="Leroy2" class="wp-image-476987" srcset="https://searchengineland.com/wp-content/seloads/2026/05/leroy2.jpg 1774w, https://searchengineland.com/wp-content/seloads/2026/05/leroy2-768x384.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/leroy2-1536x768.jpg 1536w" sizes="(max-width: 1774px) 100vw, 1774px" /></a></figure>
</div>

Raise your hand if you’re frustrated by how much traffic Google has clawed back with the launch of AI Overviews and AI Mode.
Admittedly, both of these can be crazy helpful for users. (I know – it pains me to type it.)



But across various industries, the response has been overwhelmingly negative. Publishers argue that Google is using their content without sending enough traffic in return. Some question the legal responsibility of AI answers. Others are pursuing legal action or considering opting out of Google altogether.
Fine. To avoid a 6,000-word detour, I’ll concede the point: it doesn’t feel fair.
But many of the same businesses demanding citations, links, and traffic from Google routinely reference another company’s data, reporting, or expertise without providing a clickable link. Sometimes they even write out the source’s domain while deliberately leaving it unlinked — all because someone is afraid of “giving away” link equity.
You can’t demand that AI platforms support the open web while refusing to participate in it yourself.



View embedded content



It was worth mentioning, it was worth linking
A citation isn’t a favor, and it isn’t an SEO handout. It allows readers to verify the claim, review the original research, understand its context, and discover the people or organizations responsible for the work.
Take the example below. SEOJobs.com’s data was valuable enough to reference directly, but apparently not valuable enough to link to.




SEOJobs.com is named as a resource — but isn’t linked.
I notice these examples because I own the site and monitor brand mentions. But don’t confuse SEOJobs.com as a unique target. This happens every day to researchers, creators, small businesses, newsletters, podcasts, and independent publishers.
If someone’s work helped strengthen your content, helping readers find the original source should be the default.
Why publishers withhold links
Publishers usually justify withholding links in one of three ways. Two are based on misguided SEO thinking. The third can be legitimate, but often exposes another contradiction.
‘We don’t want to lose link equity’
Linking to a relevant source does not drain your website’s authority like water leaking from a bucket. (I desperately wanted to write that in all caps. I didn’t. You’re welcome.)



You aren’t protecting your rankings by trapping readers on your domain or omitting citations that would make your content more useful.
Refusing legitimate citations isn’t an SEO strategy. It puts a spotlight on a business that doesn’t understand how search works.
‘We don’t want to help their SEO’
This is where the justification gets uglier.
Some publishers will reference a business, use its data, and even awkwardly write out its domain, just without making it clickable.
I once contacted a publisher that referenced SEOJobs.com’s 2025 job data and asked whether they would add a link so readers could view the full dataset. They declined. Instead, they offered to publish an “exclusive blog post” about SEOJobs.com for $500.
Yes, I could buy ”coverage” — for $500.



To be clear, I wasn’t asking them to sell me coverage. I was asking them to properly cite a source they had already chosen to mention.
If the link was withheld so its value could be packaged into something they could sell me, that wasn’t an editorial decision. It was a sales strategy disguised as editorial policy.
‘We don’t want to endorse the website’
This can be legitimate. Nobody should be expected to send readers to an unsafe website or lend credibility to misinformation. Paid placements and user-generated content also require different considerations.
But for a standard editorial citation, the contradiction remains:
If you didn’t consider the source credible enough for readers to visit, why was its information credible enough to use in your article?
Nofollow is not an editorial safety blanket
Even when publishers provide a clickable link, many automatically apply a nofollow attribute as if it protects them from some undefined SEO risk. (Someone, think of the children link juice!!!)



But nofollow isn’t a generic disclaimer for every external website.
Google already provides attributes for specific types of links. Sponsored is intended for advertisements, sponsorships, affiliate links, and other paid relationships. ugc applies to links added through user-generated content, such as comments or forum posts. nofollow can be used when a publisher genuinely does not want to associate its website with the destination.
A normal, unpaid editorial citation doesn’t automatically fall into any of those categories.
In the example below, SEOJobs.com was mentioned organically within an editorial article and linked as the source. There was no payment, sponsorship, affiliate relationship, or user-generated content. Yet the link was still tagged nofollow.




The text is linked but contains a nofollow attribute
Why?
If the publication trusted the source enough to mention it, considered the destination safe enough to send readers to, and received no compensation for including it, what exactly was the attribute protecting them from?



This isn’t about obsessing over a tiny piece of HTML. It’s about the editorial mindset behind it.
Automatically applying nofollow to every external link says:
“We’ll use your work, and we may even send readers to it — but we’ll make damn sure you receive as little value as possible…”
Sound familiar?
Publishers are recreating the same problem
Publishers are understandably frustrated: someone invests time and money creating original data, another platform uses it to improve its own product, and the original creator receives little (or nothing) in return.
That is the fundamental complaint about AI Overviews.



But when a publisher uses another website’s research, reporting, examples, or ideas without linking to the original source, it creates the same problem on a smaller scale. The publisher strengthens its article, keeps the reader’s attention, and denies the creator even the opportunity to earn a visit.
To be clear, publishers doing it doesn’t excuse Google and vice versa. Two wrongs don’t make a right. (At least that’s what my Momma told me growing up)



But if publishers expect AI companies to properly credit and support the sources behind their answers, they should hold themselves to the same standard.
A simple standard for editorial links
This doesn’t need to be complicated. Before publishing, ask:
Did this source contribute information, data, reporting, or an original idea?
Would visiting it help readers verify the claim or better understand the context?
Is the destination relevant, trustworthy, and safe?
Was the mention unpaid and editorially chosen?
If the answers are yes, provide a normal clickable link.




No need for a blanket nofollow policy.
No imaginary concern about leaking “link juice.”
Just give readers access to the source that helped make your content better.
Give what you’re demanding
The open web cannot function when everyone wants attribution, but nobody wants to provide it. Links allow readers to inspect claims, recognize original work, and discover the people and businesses contributing real value.
This isn’t about generously handing out SEO credit. It’s about giving readers the transparency they deserve and sources the recognition they earned.
If you want Google and AI platforms to cite their sources, start by making sure you cite yours.
This post first appeared on the author’s website and is republished here with permission.

Publishers demanding citations and traffic from AI platforms should give the same credit to the data, research, and reporting they use.

You can’t demand the click if you won’t give the link

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google will upgrade eligible Search campaigns to AI Max from Sept. 1, enabling search term matching and text customization.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-to-auto-upgrade-some-Search-campaigns-to-AI-Max-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is automatically migrating eligible Search campaigns to AI Max, expanding adoption of its AI-powered campaign features without requiring advertisers to opt in manually.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Advertisers are receiving emails notifying them that, beginning Sept. 1st, Search campaigns using Automatically Created Assets (ACA) and/or the campaign-level broad match setting will be automatically upgraded to AI Max for Search campaigns.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1700" height="1808" src="https://searchengineland.com/wp-content/seloads/2026/08/Automatically-created-Assets-AI-Max.jpeg" alt="" class="wp-image-484429" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Automatically-created-Assets-AI-Max.jpeg 1700w, https://searchengineland.com/wp-content/seloads/2026/08/Automatically-created-Assets-AI-Max-768x817.jpeg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Automatically-created-Assets-AI-Max-1444x1536.jpeg 1444w" sizes="(max-width: 1700px) 100vw, 1700px" /></figure>



<p class="wp-block-paragraph">The rollout will preserve existing campaign behavior as closely as possible by applying AI Max settings that mirror advertisers&#8217; current configurations.</p>



<p class="wp-block-paragraph"><strong>Auto upgrade</strong>. Campaigns using Automatically Created Assets will be upgraded with search term matching and text customization enabled by default. Campaigns using the campaign-level broad match setting will receive AI Max with search term matching enabled.</p>



<p class="wp-block-paragraph">Google says the goal is to make the transition seamless by carrying forward the functionality advertisers already rely on, while moving campaigns onto its newer AI-powered framework.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Advertisers currently using Automatically Created Assets or campaign-level broad match won&#8217;t need to manually migrate to AI Max. However, they should review campaign settings after the upgrade to understand which AI features have been enabled and how they could affect query matching, ad creative and overall campaign performance.</p>



<p class="wp-block-paragraph"><strong>The bottom line</strong>. Google is making AI Max the default experience for more Search campaigns, signaling its continued shift away from legacy campaign controls and toward AI-driven automation.</p>



<p class="wp-block-paragraph"><strong>First spotted. </strong>This update was shared on <a href="https://x.com/MenachemAni/status/2085125059237097819/photo/1">X</a> by Menachem Ani, Founder of JXT Group. </p>


<a href="https://www.semrush.com/ai-seo/overview?utm_campaign=ic_sel_0101ai&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
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Google is automatically migrating eligible Search campaigns to AI Max, expanding adoption of its AI-powered campaign features without requiring advertisers to opt in manually.
What’s happening. Advertisers are receiving emails notifying them that, beginning Sept. 1st, Search campaigns using Automatically Created Assets (ACA) and/or the campaign-level broad match setting will be automatically upgraded to AI Max for Search campaigns.




The rollout will preserve existing campaign behavior as closely as possible by applying AI Max settings that mirror advertisers’ current configurations.
Auto upgrade. Campaigns using Automatically Created Assets will be upgraded with search term matching and text customization enabled by default. Campaigns using the campaign-level broad match setting will receive AI Max with search term matching enabled.
Google says the goal is to make the transition seamless by carrying forward the functionality advertisers already rely on, while moving campaigns onto its newer AI-powered framework.
Why we care. Advertisers currently using Automatically Created Assets or campaign-level broad match won’t need to manually migrate to AI Max. However, they should review campaign settings after the upgrade to understand which AI features have been enabled and how they could affect query matching, ad creative and overall campaign performance.
The bottom line. Google is making AI Max the default experience for more Search campaigns, signaling its continued shift away from legacy campaign controls and toward AI-driven automation.
First spotted. This update was shared on X by Menachem Ani, Founder of JXT Group. 
AI recommends.
      
See your AI visibility

Google will upgrade eligible Search campaigns to AI Max from Sept. 1, enabling search term matching and text customization.

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