<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/toxic-link.png" class="attachment-large size-large wp-post-image" alt="Toxic link" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/08/toxic-link.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The case could test whether businesses can use false advertising law to challenge harmful backlink campaigns.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/toxic-link.png" class="attachment-large size-large wp-post-image" alt="Toxic link" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/toxic-link.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/toxic-link-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">A federal judge refused to dismiss a lawsuit alleging an auto transport company used toxic backlinks to hurt a competitor&#8217;s Google rankings.</p>



<p class="wp-block-paragraph"><strong>Catch up quick. </strong>The June 2 ruling came at the motion-to-dismiss stage:</p>



<ul class="wp-block-list">
<li>The court didn&#8217;t decide whether the allegations are true. Instead, it found the plaintiffs had plausibly alleged a false advertising claim under the federal <a href="https://www.law.cornell.edu/wex/lanham_act">Lanham Act,</a> along with trademark and related Illinois consumer protection claims. </li>



<li>The judge dismissed only the plaintiffs&#8217; California unfair competition claims.</li>
</ul>



<p class="wp-block-paragraph" id="h-alleged-toxic-backlink-campaign"><strong>Alleged toxic backlink campaign. </strong>Montway&#8217;s verified complaint alleges competitor Nexus AT LLC created more than 2,350 toxic backlinks between April and October 2025. The links pointed to Montway&#8217;s website from spam-filled sites using anchor text such as &#8220;buy steroids online,&#8221; &#8220;Payday loan services,&#8221; &#8220;illegal betting sites,&#8221; &#8220;Cocaine powder online,&#8221; and &#8220;unlicensed firearms.&#8221;</p>



<ul class="wp-block-list">
<li>Montway alleges the campaign aimed to lower its Google rankings and falsely associate its brand with illegal or unsavory products and services.</li>



<li>The complaint also alleges a former Nexus manager told Montway executives that Nexus CEO George Arkin directed an SEO contractor to carry out the campaign. </li>



<li>Montway further alleges it sent a cease-and-desist letter in October 2025 and that the backlink campaign intensified afterward. Those allegations have not been proven in court.</li>
</ul>



<p class="wp-block-paragraph" id="h-false-advertising-claim-survives"><strong>False advertising claim survives</strong>. Judge Matthew Kennelly found that the plaintiffs had plausibly alleged that the anchor text was literally false because it appeared to promise one destination but sent users elsewhere. He also found the alleged backlink campaign could qualify as &#8220;commercial advertising or promotion&#8221; under the Lanham Act. That allowed the false advertising claim to move forward.</p>



<p class="wp-block-paragraph" id="h-why-this-ruling-is-interesting"><strong>Why this ruling is interesting. </strong>The decision focuses on whether an alleged toxic backlink campaign can fall under existing false advertising law. It doesn&#8217;t decide whether the defendants are liable.</p>



<ul class="wp-block-list">
<li>Rebecca Tushnet, a Harvard Law professor who writes about trademark law, <a href="https://tushnet.blogspot.com/2026/06/court-allows-tm-and-false-advertising.html">analyzed the decision on her 43(B)log</a>, questioning parts of the court&#8217;s trademark analysis while examining its approach to the false advertising claim.</li>
</ul>



<p class="wp-block-paragraph" id="h-why-we-care"><strong>Why we care. </strong>Companies that believe competitors are trying to manipulate their search visibility have traditionally had few options beyond reporting the activity to search engines. If this legal theory survives, it could provide another legal avenue to challenge SEO sabotage.</p>



<p class="wp-block-paragraph" id="h-why-we-care"><strong>The case. </strong>You can read more about it on <a href="https://www.courtlistener.com/docket/71776095/montway-llc-v-nexus-at-llc/" target="_blank" rel="noopener">Court Listener.</a>


A federal judge refused to dismiss a lawsuit alleging an auto transport company used toxic backlinks to hurt a competitor’s Google rankings.
Catch up quick. The June 2 ruling came at the motion-to-dismiss stage:
The court didn’t decide whether the allegations are true. Instead, it found the plaintiffs had plausibly alleged a false advertising claim under the federal Lanham Act, along with trademark and related Illinois consumer protection claims. 
The judge dismissed only the plaintiffs’ California unfair competition claims.
Alleged toxic backlink campaign. Montway’s verified complaint alleges competitor Nexus AT LLC created more than 2,350 toxic backlinks between April and October 2025. The links pointed to Montway’s website from spam-filled sites using anchor text such as “buy steroids online,” “Payday loan services,” “illegal betting sites,” “Cocaine powder online,” and “unlicensed firearms.”
Montway alleges the campaign aimed to lower its Google rankings and falsely associate its brand with illegal or unsavory products and services.
The complaint also alleges a former Nexus manager told Montway executives that Nexus CEO George Arkin directed an SEO contractor to carry out the campaign. 
Montway further alleges it sent a cease-and-desist letter in October 2025 and that the backlink campaign intensified afterward. Those allegations have not been proven in court.
False advertising claim survives. Judge Matthew Kennelly found that the plaintiffs had plausibly alleged that the anchor text was literally false because it appeared to promise one destination but sent users elsewhere. He also found the alleged backlink campaign could qualify as “commercial advertising or promotion” under the Lanham Act. That allowed the false advertising claim to move forward.
Why this ruling is interesting. The decision focuses on whether an alleged toxic backlink campaign can fall under existing false advertising law. It doesn’t decide whether the defendants are liable.
Rebecca Tushnet, a Harvard Law professor who writes about trademark law, analyzed the decision on her 43(B)log, questioning parts of the court’s trademark analysis while examining its approach to the false advertising claim.
Why we care. Companies that believe competitors are trying to manipulate their search visibility have traditionally had few options beyond reporting the activity to search engines. If this legal theory survives, it could provide another legal avenue to challenge SEO sabotage.
The case. You can read more about it on Court Listener.

The case could test whether businesses can use false advertising law to challenge harmful backlink campaigns.

Judge lets SEO sabotage lawsuit over toxic backlinks move forward

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Developers can now retrieve Campaign Manager 360 reporting data in real time with a single API request.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-adds-real-time-reporting-endpoint-to-Campaign-Manager-360-API-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google introduced a new <code>reportData.query</code> endpoint for the Campaign Manager 360 API, making it easier for developers to retrieve campaign performance data without generating downloadable reports.</p>



<p class="wp-block-paragraph">The new endpoint is designed for real-time reporting, dashboards and ad-hoc analysis.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening:</strong> The <code>reportData.query</code> endpoint allows developers to synchronously query campaign performance data and receive structured JSON directly in the API response.</p>



<p class="wp-block-paragraph">Unlike the existing reporting workflow, developers no longer need to create a Report resource before retrieving data. Instead, they can define dimensions, metrics and filters directly in the request body.</p>



<p class="wp-block-paragraph">Queries can run for up to 60 seconds, making the endpoint better suited for interactive reporting and real-time applications.</p>



<p class="wp-block-paragraph"><strong>The existing reporting API remains.</strong> Google says the traditional Reports service is still the preferred option for large datasets, scheduled reporting jobs and applications that rely on downloadable CSV or Excel files.</p>



<p class="wp-block-paragraph">That workflow requires creating report configurations, running reports, polling for completion and downloading the generated files.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The new endpoint significantly simplifies reporting for developers building dashboards or custom analytics tools. By eliminating report configuration and file management, it reduces implementation complexity and speeds up access to campaign data.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://ads-developers.googleblog.com/2026/08/query-report-data-with-campaign-manager.html">Google&#8217;s new <code>reportData.query</code> endpoint</a> offers a faster, simpler way to retrieve Campaign Manager 360 reporting data, while the existing Reports API remains the best choice for large-scale and scheduled reporting.</p>


Google introduced a new reportData.query endpoint for the Campaign Manager 360 API, making it easier for developers to retrieve campaign performance data without generating downloadable reports.
The new endpoint is designed for real-time reporting, dashboards and ad-hoc analysis.
What’s happening: The reportData.query endpoint allows developers to synchronously query campaign performance data and receive structured JSON directly in the API response.
Unlike the existing reporting workflow, developers no longer need to create a Report resource before retrieving data. Instead, they can define dimensions, metrics and filters directly in the request body.
Queries can run for up to 60 seconds, making the endpoint better suited for interactive reporting and real-time applications.
The existing reporting API remains. Google says the traditional Reports service is still the preferred option for large datasets, scheduled reporting jobs and applications that rely on downloadable CSV or Excel files.
That workflow requires creating report configurations, running reports, polling for completion and downloading the generated files.
Why we care. The new endpoint significantly simplifies reporting for developers building dashboards or custom analytics tools. By eliminating report configuration and file management, it reduces implementation complexity and speeds up access to campaign data.
Bottom line. Google’s new reportData.query endpoint offers a faster, simpler way to retrieve Campaign Manager 360 reporting data, while the existing Reports API remains the best choice for large-scale and scheduled reporting.

Developers can now retrieve Campaign Manager 360 reporting data in real time with a single API request.

Google adds real-time reporting endpoint to Campaign Manager 360 API

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Advertisers can now use PMax store-goal campaigns to prioritize nearby, high-intent visitors across Google Maps, Waze and Search.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-Local-customisation-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google published a new help document detailing <a href="https://searchengineland.com/local-services-ads-come-to-google-ads-via-performance-max-482692">Local customer optimization for Performance Max campaigns with store goals</a>, a feature designed to prioritize ads for people who are nearby and ready to visit or contact a business.</p>



<p class="wp-block-paragraph">The migration of serving ads to people who are nearby to Performance Max was announced last month. </p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening.</strong> Local customer optimization helps Performance Max campaigns reach users who are actively planning trips, navigating or searching for nearby businesses across Google Maps, Waze and local formats on Google Search.</p>



<p class="wp-block-paragraph">According to Google, the feature aims to capture high-intent local customers at the moment they&#8217;re most likely to visit a store, request directions or make contact.</p>



<p class="wp-block-paragraph"><strong>Merchant Center isn&#8217;t supported</strong>. One key limitation is that Local customer optimization isn&#8217;t compatible with Merchant Center.</p>



<p class="wp-block-paragraph">Performance Max campaigns using products from Merchant Center or campaigns with online conversion goals can&#8217;t use the feature. Advertisers must remove Merchant Center product feeds or create a separate store-goals campaign to enable Local customer optimization.</p>



<p class="wp-block-paragraph"><strong>How to enable it</strong>. Advertisers creating a new Performance Max campaign for store goals will see a new Local customer optimization toggle during campaign setup after selecting offline conversion goals such as store visits, directions or store sales.</p>



<p class="wp-block-paragraph">For existing campaigns, the setting can be found under Budget and bidding optimization within campaign settings. Once enabled and saved, Google will begin optimizing delivery toward nearby, high-intent users. The feature can also be turned off at any time to return the campaign to standard Performance Max behavior.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Until recently, advertisers couldn&#8217;t specifically optimize Performance Max campaigns for people who were actively navigating, trip-planning or searching nearby with immediate local intent. Local customer optimization brings those placements into Performance Max for store-goal campaigns, giving brick-and-mortar businesses a new way to reach high-intent customers across Google Maps, Waze and local Search formats from within a single campaign.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://support.google.com/google-ads/answer/17198659">Google&#8217;s new Local customer optimization feature helps Performance Max campaigns</a> prioritize nearby customers with strong local intent—but only for store-goal campaigns that don&#8217;t use Merchant Center product feeds.</p>


Google published a new help document detailing Local customer optimization for Performance Max campaigns with store goals, a feature designed to prioritize ads for people who are nearby and ready to visit or contact a business.
The migration of serving ads to people who are nearby to Performance Max was announced last month. 
What’s happening. Local customer optimization helps Performance Max campaigns reach users who are actively planning trips, navigating or searching for nearby businesses across Google Maps, Waze and local formats on Google Search.
According to Google, the feature aims to capture high-intent local customers at the moment they’re most likely to visit a store, request directions or make contact.
Merchant Center isn’t supported. One key limitation is that Local customer optimization isn’t compatible with Merchant Center.
Performance Max campaigns using products from Merchant Center or campaigns with online conversion goals can’t use the feature. Advertisers must remove Merchant Center product feeds or create a separate store-goals campaign to enable Local customer optimization.
How to enable it. Advertisers creating a new Performance Max campaign for store goals will see a new Local customer optimization toggle during campaign setup after selecting offline conversion goals such as store visits, directions or store sales.
For existing campaigns, the setting can be found under Budget and bidding optimization within campaign settings. Once enabled and saved, Google will begin optimizing delivery toward nearby, high-intent users. The feature can also be turned off at any time to return the campaign to standard Performance Max behavior.
Why we care. Until recently, advertisers couldn’t specifically optimize Performance Max campaigns for people who were actively navigating, trip-planning or searching nearby with immediate local intent. Local customer optimization brings those placements into Performance Max for store-goal campaigns, giving brick-and-mortar businesses a new way to reach high-intent customers across Google Maps, Waze and local Search formats from within a single campaign.
Bottom line. Google’s new Local customer optimization feature helps Performance Max campaigns prioritize nearby customers with strong local intent—but only for store-goal campaigns that don’t use Merchant Center product feeds.

Advertisers can now use PMax store-goal campaigns to prioritize nearby, high-intent visitors across Google Maps, Waze and Search.

Google adds Local customer optimization to Performance Max

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google says the update improves the clarity and readability of its YouTube and Discover Feed ad requirements

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/YouTube-and-Discover-Feed-ad-requirements-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google updated the YouTube and Discover Feed ad requirements to make the policy easier for advertisers to understand.</p>



<p class="wp-block-paragraph">The company says the changes are editorial only and do not affect how the policy is enforced.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Google revised the language and formatting of the YouTube and Discover Feed ad requirements this month to improve clarity and readability.</p>



<p class="wp-block-paragraph">According to Google, the update is intended to provide clearer guidance for advertisers and does <strong>not</strong> introduce any new requirements or enforcement changes.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Advertisers don&#8217;t need to take action, but the refreshed documentation may make it easier to interpret the policy and ensure ads comply with existing requirements.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://support.google.com/adspolicy/answer/17455694?hl=en">Google&#8217;s latest policy update improves the wording</a>, not the rules, for YouTube and Discover Feed ads.</p>


Google updated the YouTube and Discover Feed ad requirements to make the policy easier for advertisers to understand.
The company says the changes are editorial only and do not affect how the policy is enforced.
What’s happening. Google revised the language and formatting of the YouTube and Discover Feed ad requirements this month to improve clarity and readability.
According to Google, the update is intended to provide clearer guidance for advertisers and does not introduce any new requirements or enforcement changes.
Why we care. Advertisers don’t need to take action, but the refreshed documentation may make it easier to interpret the policy and ensure ads comply with existing requirements.
Bottom line. Google’s latest policy update improves the wording, not the rules, for YouTube and Discover Feed ads.

Google says the update improves the clarity and readability of its YouTube and Discover Feed ad requirements

Google updates YouTube and Discover Feed ad requirements

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Merchant Center is updating its reporting with new YouTube traffic classifications and expanded product-level performance insights.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/merchant-centre-cross-platform-reporting-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is updating Merchant Center performance reporting to align metrics more closely with Google Ads and YouTube, giving merchants a more consistent view of how products perform across Google&#8217;s platforms.</p>



<p class="wp-block-paragraph">The changes, which begin rolling out on August 24, include new traffic classifications, expanded product-level reporting and future segmentation tools.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. One of the biggest changes is the separation of YouTube affiliate traffic from standard organic traffic.</p>



<p class="wp-block-paragraph">Traffic generated through YouTube creators participating in Google&#8217;s affiliate program will now appear under a new &#8220;YouTube affiliate&#8221; traffic category instead of &#8220;Organic.&#8221; Google says the change will provide a clearer picture of free listings performance, although advertisers may see a one-time drop in reported organic traffic when the update takes effect. Historical data dating back to July 1st will also be updated.</p>



<p class="wp-block-paragraph">Google is also revising how organic YouTube clicks and impressions are measured to better align with YouTube&#8217;s reporting definitions, another change that could reduce reported organic traffic.</p>



<p class="wp-block-paragraph"><strong>Reporting expands</strong>. Merchant Center&#8217;s product-level reporting is also getting broader coverage.</p>



<p class="wp-block-paragraph">Performance reports will now include data from all Google Ads channels and formats, including Performance Max, Video, App and Demand Gen campaigns. As a result, advertisers may notice a one-time increase in metrics such as impressions and clicks as more campaign data becomes available.</p>



<p class="wp-block-paragraph">Google also confirmed it plans to introduce a new Network reporting dimension in the future, allowing merchants to segment performance by Google network in a way that&#8217;s similar to Google Ads.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. While some merchants may initially see shifts in their reporting, the updates should make it easier to understand where product performance is coming from and compare results across Google&#8217;s advertising and organic surfaces.</p>



<p class="wp-block-paragraph">The expanded product reporting also gives retailers a more complete view of how products perform across different campaign types without switching between platforms.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://support.google.com/merchants/answer/17103877">Merchant Center reporting is becoming more consistent with Google Ads and YouTube</a>, giving advertisers richer cross-channel insights while introducing new traffic classifications that may temporarily change reported performance metrics.</p>


Google is updating Merchant Center performance reporting to align metrics more closely with Google Ads and YouTube, giving merchants a more consistent view of how products perform across Google’s platforms.
The changes, which begin rolling out on August 24, include new traffic classifications, expanded product-level reporting and future segmentation tools.
What’s happening. One of the biggest changes is the separation of YouTube affiliate traffic from standard organic traffic.
Traffic generated through YouTube creators participating in Google’s affiliate program will now appear under a new “YouTube affiliate” traffic category instead of “Organic.” Google says the change will provide a clearer picture of free listings performance, although advertisers may see a one-time drop in reported organic traffic when the update takes effect. Historical data dating back to July 1st will also be updated.
Google is also revising how organic YouTube clicks and impressions are measured to better align with YouTube’s reporting definitions, another change that could reduce reported organic traffic.
Reporting expands. Merchant Center’s product-level reporting is also getting broader coverage.
Performance reports will now include data from all Google Ads channels and formats, including Performance Max, Video, App and Demand Gen campaigns. As a result, advertisers may notice a one-time increase in metrics such as impressions and clicks as more campaign data becomes available.
Google also confirmed it plans to introduce a new Network reporting dimension in the future, allowing merchants to segment performance by Google network in a way that’s similar to Google Ads.
Why we care. While some merchants may initially see shifts in their reporting, the updates should make it easier to understand where product performance is coming from and compare results across Google’s advertising and organic surfaces.
The expanded product reporting also gives retailers a more complete view of how products perform across different campaign types without switching between platforms.
Bottom line. Merchant Center reporting is becoming more consistent with Google Ads and YouTube, giving advertisers richer cross-channel insights while introducing new traffic classifications that may temporarily change reported performance metrics.

Merchant Center is updating its reporting with new YouTube traffic classifications and expanded product-level performance insights.

Google updates Merchant Center with cross-platform reporting

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google will auto-transition Travel campaigns to Search campaigns for Travel starting in Q3 2026, which can also be done manually.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-travel-campaigns-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google will begin migrating Travel campaigns to <a href="https://searchengineland.com/google-ai-max-gets-new-controls-shopping-rollout-and-travel-consolidation-476025">Search campaigns for Travel</a> starting in Q3 2026, automatically moving advertisers to the new campaign type while preserving existing settings where possible.</p>



<p class="wp-block-paragraph">The migration is part of Google&#8217;s broader effort to consolidate travel advertising into a single Search-based campaign experience with AI-powered bidding, reporting and campaign management. </p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Existing Travel campaigns will be automatically replaced with new Search campaigns for Travel, with Google creating new campaigns that mirror the closest equivalent settings from the originals. Advertisers can also choose to migrate manually before their scheduled transition date. </p>



<p class="wp-block-paragraph">Google says advertisers should monitor their account notifications and email for their specific migration timeline.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Automatic migrations can save time, but they also give advertisers an opportunity to review campaign settings, bidding strategies and reporting before the switch takes place. Brands that prefer greater control may want to migrate manually and validate performance before Google performs the transition automatically.</p>



<p class="wp-block-paragraph"><strong>The bigger picture.</strong> Search campaigns for Travel were introduced earlier this year to bring travel feeds and formats into a unified Search campaign experience. The new campaign type combines AI Max capabilities, advanced bidding, search term reporting and travel-specific formats into a single workflow, replacing the fragmented approach of managing multiple travel campaign types. </p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. Travel advertisers don&#8217;t need to take immediate action, but they should watch for migration notices and prepare for their campaigns to<a href="https://support.google.com/hotelprices/answer/14116724?hl=en"> move to Search campaigns for Travel</a> over the coming months.</p>


Google will begin migrating Travel campaigns to Search campaigns for Travel starting in Q3 2026, automatically moving advertisers to the new campaign type while preserving existing settings where possible.
The migration is part of Google’s broader effort to consolidate travel advertising into a single Search-based campaign experience with AI-powered bidding, reporting and campaign management. 
What’s happening. Existing Travel campaigns will be automatically replaced with new Search campaigns for Travel, with Google creating new campaigns that mirror the closest equivalent settings from the originals. Advertisers can also choose to migrate manually before their scheduled transition date. 
Google says advertisers should monitor their account notifications and email for their specific migration timeline.
Why we care. Automatic migrations can save time, but they also give advertisers an opportunity to review campaign settings, bidding strategies and reporting before the switch takes place. Brands that prefer greater control may want to migrate manually and validate performance before Google performs the transition automatically.
The bigger picture. Search campaigns for Travel were introduced earlier this year to bring travel feeds and formats into a unified Search campaign experience. The new campaign type combines AI Max capabilities, advanced bidding, search term reporting and travel-specific formats into a single workflow, replacing the fragmented approach of managing multiple travel campaign types. 
Bottom line. Travel advertisers don’t need to take immediate action, but they should watch for migration notices and prepare for their campaigns to move to Search campaigns for Travel over the coming months.

Google will auto-transition Travel campaigns to Search campaigns for Travel starting in Q3 2026, which can also be done manually.

Google to migrate Travel campaigns to Search campaigns for Travel

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Query-templates-Expanding-the-scope-of-topical-authority.png" class="attachment-large size-large wp-post-image" alt="Query templates- Expanding the scope of topical authority" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Query-templates-Expanding-the-scope-of-topical-authority.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Query-templates-Expanding-the-scope-of-topical-authority-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Query-templates-Expanding-the-scope-of-topical-authority-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Query-templates-Expanding-the-scope-of-topical-authority-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>A single query can sit inside thousands of variations. Mapping those patterns can build topical authority across an entire search network.

A single query can sit inside thousands of variations. Mapping those patterns can build topical authority across an entire search network.

Query templates: Expanding the scope of topical authority

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-to-use-MCP-to-get-more-data-from-the-tools-you-already-use.png" class="attachment-large size-large wp-post-image" alt="How to use MCP to get more data from the tools you already use" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-to-use-MCP-to-get-more-data-from-the-tools-you-already-use.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-use-MCP-to-get-more-data-from-the-tools-you-already-use-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-use-MCP-to-get-more-data-from-the-tools-you-already-use-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-use-MCP-to-get-more-data-from-the-tools-you-already-use-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Your SEO tools already contain the answers. MCP makes it easier to ask questions your dashboards weren't built to handle.


Model Context Protocol (MCP) makes it easier to work with the data already sitting inside your SEO and marketing tools. Instead of digging through reports, exporting data, and stitching spreadsheets together, you can ask an AI assistant questions that would otherwise take hours to answer.
That makes an MCP server useful for analysis that requires finding patterns across pages, keywords, traffic, rankings, and other data points. 
Here’s how I’ve been using MCP servers to get more out of tools like Ahrefs, Google Analytics, and Google Search Console.
Using MCP to uncover what’s driving competitor growth
A few months ago, I set out to learn why a client’s competitor was growing so fast. Ahrefs showed me their winning pages and keywords, but not the underlying trend or how the pieces fit together. 
Had those pages climbed steadily for months or spiked suddenly? 
Did the growth track to a page type or subdirectory, or did the whole site benefit from an algorithm update?




I connected Claude to the Ahrefs MCP server and asked it to dig in. Minutes later, I had a breakdown of which pages were new in the last six months, their estimated traffic, the keywords driving it, and how key pages had grown month over month.




Here’s what I learned about this competitor:
They built a new section of their site with highly focused service pages.
International content they’ve been building for the last three years started to take off.
They flipped the switch on domain redirects for 10+ firms they acquired years ago.
Ahrefs doesn’t hide this data, but it’s scattered across reports and different filters. Normally, you’d export dozens of reports and combine the data with pivot tables. For monthly, weekly, or daily comparisons, that process is slow and frustrating.
MCP lets you pull and reshape data that already lives in the tools you pay for, but is a pain to reach through the normal interface. Developers who work with APIs won’t find this new. For everyone else, it opens up a whole new world of data analysis.
AI recommends.
      
See your AI visibility
    
How MCP connects AI to your tools
MCP is an open standard that lets AI assistants connect to external tools and data sources. Anthropic open-sourced it in November 2024, and support has since expanded across major AI platforms.
An MCP server connects an AI assistant to a specific tool or service, letting you query its data in plain language. For example, Semrush offers several MCP servers.




Many other AI platforms and tools support MCP as well, including N8N and Copilot Studio.
Dig deeper: WebMCP explained: Inside Chrome 146’s agent-ready web preview



The questions your marketing dashboards can’t easily answer




This is where MCP can earn its place in your workflow. The everyday stuff — what a page ranks for, how many backlinks it has — is easy to look up anywhere. The hard questions are the ones where the answer is hidden in the data, and you have to dig for it.
Here are the kinds of prompts I’ve used:
“Using the Ahrefs MCP server, help me understand why this site is doing so well, especially in the last 12 months. Is it specific pages or keywords?”
“Using Ahrefs data, can you tell which pages are new in the last six months and what their estimated traffic is?”
“Compare the backlink profiles and growth trends for these five sites, and tell me which one is picking up referring domains the fastest and how.”
“Across these 20 keywords in my niche, which sites rank most often and in the best positions?”
These are the questions that often come up in analysis work, such as competitor research and post-algorithm reviews. You can do this manually, but it takes hours of busywork to piece everything together.
MCP works across your marketing stack
Many marketing platforms now ship MCP servers, including Semrush, DataForSEO, Serpstat, Buffer, and VidIQ. 
What you can pull depends on what each tool exposes through its API, but once it’s connected, all you have to do is ask it questions.




Google Analytics is one of the most useful MCP servers I’ve used. GA4 is powerful but hard to navigate. Half the time, you know the answer is in there, but don’t want to build another exploration report to find it. 
The Google Analytics MCP server connects to the GA4 Data API, so you can just ask. A few examples:
Diagnosing a drop: 

“Organic traffic fell about 20% last week. Which pages lost the most, and is it concentrated in a specific country or device type?”
Finding the mismatch: 

“Which pages have high engagement time but a low conversion rate?”
“Can you give me traffic for the last 30 minutes, by the minute?”
If you manage multiple accounts, you can run queries across several properties at once:
“Across all my properties, what are their respective data retention settings (2 months vs. 14 months)?”
“What is the combined traffic for [site 1] and [site 2] for the last week, broken down by Organic, Direct, and Referral?”
“Which web data streams in my account do not have Enhanced Measurement enabled?”
One of my go-to uses for this MCP server is analyzing traffic after algorithm updates and trying to understand what the impact might be, such as which pages have declined or improved. I’ve also used it to review traffic across a client’s entire site to find opportunities for content refreshes and identify actual anomalies that stand out against normal fluctuations.
Querying the API directly also bypasses the 5,000-row export limit of the GA4 interface. The biggest drawback to the Analytics MCP is that it’s quite complicated to set up: it requires a Google Cloud project and an OAuth client.
Google Search Console MCP
Ahrefs gives you third-party estimates, and GA4 shows what people did after they landed. To complete the stack, add Google Search Console to get queries, impressions, clicks, CTR, and average position.
Google has an official GA4 MCP server, but not an official Search Console MCP server. Several community-built GSC MCP servers are available on GitHub. If you’re connecting to a client’s property, check what access the MCP server requests before installing it. 
I use one from Suganthan Mohanadasan, which is open-source and lets you run the MCP server locally from your own computer. The setup is the same as the Google Cloud project and OAuth process for the GA4 MCP server, so set aside some time to get it going.
Once it’s connected, it handles the questions the Search Console interface makes difficult. Here are a couple of examples I like:
“Give me a health check across my GSC properties.” One prompt covers every property at once, instead of opening each account to check.
“What topics is [site] missing content for based on adjacent query data?” This has given me some excellent topics that don’t exist in my GSC account but are related to the query data.




Like the other MCP servers I’ve talked about, the data is there, but MCP lets you get it out easily and in a way the GSC dashboard can’t.
Get the newsletter search marketers rely on.
 
				
				
			
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Tracking how AI talks about your brand
If you care about GEO, MCP can also monitor your AI search visibility. Both Ahrefs and Semrush offer AI metrics accessible through their MCP servers.




For example, Ahrefs’ Brand Radar (an expensive paid upgrade, unfortunately) tracks how brands appear in AI answers across major surfaces like Google’s AI Overviews and AI Mode, ChatGPT, Perplexity, Gemini, and Copilot. It tracks share of voice against competitors, shows brand mentions and citations, and identifies which pages and domains those platforms cite most in your space.
Semrush offers an MCP server that includes access to useful AI metrics, too. You can ask it to summarize where competitors are seeing shifts in AI traffic and how your site compares.
Many other AI tools are building MCP servers, too. For example, Waikay.io, an awesome AI brand monitoring tool from Dixon Jones, just released an MCP server for customers on Level 2 accounts.
Chaining tools and speeding up reporting
You can speed up analysis by connecting multiple sources. Because the AI holds context across tools, you can ask a question that would normally mean three logins and a spreadsheet to reconcile.
For example: Which blog posts lost traffic last month, what keywords do they rank for, and which are worth refreshing first? One source has the traffic, another has the rankings, and the assistant pulls both into a single answer.
Reporting is the obvious use. People wire up MCP servers through connectors like N8N and platforms like HubSpot to pull the week’s data, summarize it, and drop it into a doc or email on a schedule. You still want a human reading the output, but the grunt work of gathering and formatting becomes much easier.
Dig deeper: AI agents in SEO: A practical workflow walkthrough



What to know before using MCP
None of this is new to developers. Anyone comfortable with an API could pull and reshape this data long before MCP existed.
But the data is now more accessible, and we can ask LLMs questions about it. MCP exposes capabilities that lived behind code and makes them available to people with zero developer skills.
Even for developers, being able to talk to an LLM about the data can help them understand its meaning or inspire ideas they would never have come up with on their own.
A few limitations are worth knowing:
These MCP servers run on the tool’s API, so big requests eat into your API credits and plan limits. Heavy queries add up.
The AI only sees what the API exposes. If a data point isn’t available through the tool’s API, you can’t use it in analysis.
Verify the output. The data is correct, but the AI can still misread it or oversimplify. Sanity-check anything you’ll act on or put in front of a client.
Tell it to use the MCP. Assistants don’t always know whether to call the connected tool or just search the web, so I start prompts with “Using the Analytics MCP” to ensure the right route is taken.
Be patient with big requests. A project spanning many keywords or several sites can take a while to come back and, depending on your LLM plan, may burn through credits and require daily pauses until they replenish.
customers won’t either.
      
See your AI visibility
    
Where to start
Pick one tool you already pay for and one question its dashboard makes annoying. Connect the MCP server to your LLM of choice, ask, and compare the answer to doing it by hand. 
That first query is likely to open your eyes to the possibilities. After that, you’ll see how many of your data-pull tasks are a single prompt away.

Your SEO tools already contain the answers. MCP makes it easier to ask questions your dashboards weren't built to handle.

How to use MCP to get more data from the tools you already use

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work.png" class="attachment-large size-large wp-post-image" alt="The new search journey changes how SEO and PPC should work" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The first search is rarely the whole journey. See how AI answers, paid ads, organic results and follow-up queries shape conversion.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work.png" class="attachment-large size-large wp-post-image" alt="The new search journey changes how SEO and PPC should work" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/The-new-search-journey-changes-how-SEO-and-PPC-should-work-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph"><a href="https://searchengineland.com/guide/what-is-seo">SEO</a> and <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> have traditionally been managed as two channels that share a results page. The coordination questions were about overlap: Should paid bid on terms the site already ranks for? Where is that overlap wasting budget? Which channel gets credit for the conversion?</p>



<p class="wp-block-paragraph">That model no longer fits the search experience. </p>



<p class="wp-block-paragraph">An AI Overview answers the query and cites sources, ads compete for the remaining attention, and organic results appear alongside Reddit threads and related searches. Searchers can move between those surfaces, refine their query, and repeat the process until they know enough to act.</p>



<p class="wp-block-paragraph">Search is now a loop: an AI answer shapes the shortlist, ads capture filtered demand, organic reinforces the decision, and a follow-up query starts the process again. What happens on one surface can change the outcome on another.</p>



<p class="wp-block-paragraph">The challenge for SEO and PPC teams is to measure and optimize that loop rather than individual queries or channels.</p>



<h2 id="h-the-journey-is-now-a-loop-not-a-line" class="wp-block-heading">The journey is now a loop, not a line</h2>



<p class="wp-block-paragraph"><a href="https://searchengineland.com/google-zero-click-searches-2026-study-479717">SparkToro&#8217;s 2026 analysis</a> found that 68% of Google searches now end without a click. More importantly, the share of searches that led to another Google query rose 7.2 percentage points.</p>



<p class="wp-block-paragraph">Refining and re-querying isn&#8217;t new. Searchers have chained one query to the next since the search began. What changed is the answer layer now sitting at the top of each step. It absorbs clicks that used to happen along the way and influences which brands get seen.</p>



<p class="wp-block-paragraph">Consider a familiar journey. In 2023, a search for “best project management software for remote teams” might have driven clicks to comparison articles and vendor sites, with conversions occurring a week or two later.</p>



<p class="wp-block-paragraph">The same search plays out differently today. An AI Overview names three tools, and the user doesn&#8217;t click. Instead, they search “asana vs monday for agencies,” see another AI Overview and ads from both brands, and click one. </p>



<p class="wp-block-paragraph">Then, they search “monday.com implementation problems” and read an organic article before starting a trial. That&#8217;s three queries inside a single loop, with each stage creating a different opportunity for visibility.</p>



<p class="wp-block-paragraph">The loop has four stages: an AI answer shapes the consideration set, paid ads capture filtered demand, organic results reinforce the decision, and a follow-up query restarts the loop.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-vs-ppc-debate-finally-over-482366">Why the SEO vs. PPC debate is finally over</a></em></strong>



<h2 id="h-stage-1-ai-answers-shape-the-consideration-set" class="wp-block-heading">Stage 1: AI answers shape the consideration set</h2>



<p class="wp-block-paragraph">AI Overviews show up most often at the start of a search, when someone runs broad questions before they know enough to get specific. </p>



<p class="wp-block-paragraph">In <a href="https://searchengineland.com/google-ai-overviews-ctr-recovery-study-475566" target="_blank" rel="noopener">Seer Interactive&#8217;s 2026 study</a> of 53 brands and 5.47 million queries, comparison queries triggered an AI Overview 95.4% of the time, and question-format queries 85.9%. SparkToro puts the overall AI Overview presence above 20% of searches, and when one appears, the click-through rate drops nearly 60%.</p>



<p class="wp-block-paragraph">Search was never where interest was created. That still happens in social feeds, video, communities, word of mouth, and brand marketing. What the AI answer changed is the next step. Once someone starts searching, the AI Overview narrows a broad topic down to a few named sources or options. </p>



<p class="wp-block-paragraph">A searcher arrives with a general question and leaves the first query with two or three specific names in mind. That narrowing used to happen across articles, listings, and ads. Now it happens inside the AI answer.</p>



<p class="wp-block-paragraph">A brand can still buy an ad on that page, but it can&#8217;t buy its way into the AI answer itself. The overview either cites it as a source or it doesn&#8217;t. That citation is the asset the entire system depends on.</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">
  <div>
    
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        Be the brand <span>AI recommends</span>.
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        See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.
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      <span id="semrush-one-cta">See your AI visibility</span>
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<h2 id="h-stage-2-ads-capture-the-filtered-demand" class="wp-block-heading">Stage 2: Ads capture the filtered demand</h2>



<p class="wp-block-paragraph">Most advertisers assume the AI layer is bad for paid search. The data says otherwise.</p>



<p class="wp-block-paragraph">Seer&#8217;s September 2025 numbers looked alarming at first, with paid click-through rate on AI Overview queries down 68%. The 2026 update told a different story. </p>



<p class="wp-block-paragraph">When an AI Overview appears, paid CTR actually rose from 14.6% to 16.2%. On queries without one, it fell from 26% to 21.8%. So, paid isn&#8217;t being hurt by the AI answer. It&#8217;s capturing the demand that answer filters and passes along.</p>



<p class="wp-block-paragraph">The same pattern shows up in click share. Similarweb <a href="https://searchengineland.com/paid-search-clicks-double-organic-clicks-fall-study-469519">compared January 2025 to January 2026</a> and found organic losing share in every category it tracked. In headphones, organic went from 73% of clicks down to 50%. Text ads were the only surface to gain share.&nbsp;</p>



<p class="wp-block-paragraph">Amazon grew paid clicks 35% in headphones even as its organic volume fell. As the AI answer takes the early clicks, the paid slots below it become where the remaining demand converts to a click.</p>



<p class="wp-block-paragraph">One stage feeds the next. The brand the AI answer cited shows up here with a trust signal the competitor bidding next to it doesn&#8217;t have. The next stage measures what that is worth.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-ppc-trust-across-search-case-study-484383">How SEO and PPC build trust across search: Case study</a></em></strong>



<h2 id="h-stage-3-organic-reinforces-the-decision" class="wp-block-heading">Stage 3: Organic reinforces the decision</h2>



<p class="wp-block-paragraph">Stage 2 ended with paid absorbing the clicks near the AI answer. So who&#8217;s left to click an organic result? The searcher who didn&#8217;t stop at the AI answer and who is now deeper in the loop.</p>



<p class="wp-block-paragraph">Two things keep clicks in organic&#8217;s column. The first is the set of queries where no AI Overview appears at all, which is where organic is actually gaining. Seer found organic CTR on those queries rose from 2.93% to 3.97% in 2025. </p>



<p class="wp-block-paragraph">Fewer people click overall, but the ones who do are past the quick-answer stage and want real depth. The second is the moment of decision. By now, the AI answer has built the shortlist and the ads have shown the options, so the organic click confirms a choice rather than discovering one.</p>



<p class="wp-block-paragraph">The citation is what ties this back to paid. Seer found that brands cited inside an AI Overview earned 35% more organic clicks and 91% more paid clicks than uncited brands on the same queries.&nbsp;</p>



<p class="wp-block-paragraph">Seer couldn&#8217;t prove the citation caused the lift, and the paid sample was small, but the effect points in the same direction. The citation acts as a trust signal and lifts both the listing and the ad to the same page.</p>



<p class="wp-block-paragraph">That is where the two disciplines fuse. The citation is earned through SEO work, yet much of its payoff shows up in the paid account as a CTR lift. Sharing query reports across teams is coordination, and good teams have done it for years. One asset that moves both channels&#8217; numbers, on the same page, at the same time is new.</p>



<p class="wp-block-paragraph">What earns a citation is narrower than most content plans assume. A <a href="https://searchengineland.com/seo-geo-gap-ai-search-traffic-organic-traffic-478731">case study by Search Engine Land contributor Adam Gnuse</a>, covering 10 domains and roughly 150,000 pages, found that generic how-to content underperforms in AI citations because models can already write it themselves.</p>



<p class="wp-block-paragraph">What gets cited is original data and proprietary research. That leaves the “what is” library that anchored a decade of content strategy mismatched to the job organic now does.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-ppc-alignment-483407">SEO and PPC alignment starts with your org chart</a></em></strong>



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			<p class="text-center mb-0"><a class="nl-terms" href="https://searchengineland.com/termsofuse" target="_blank" aria-label="opens in a new tab">See terms.</a>
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<hr class="wp-block-separator has-text-color has-cyan-bluish-gray-color has-css-opacity has-cyan-bluish-gray-background-color has-background"/>



<h2 id="h-stage-4-follow-up-queries-restart-the-loop" class="wp-block-heading">Stage 4: Follow-up queries restart the loop</h2>



<p class="wp-block-paragraph">The stage most strategies ignore is the one growing fastest. That 7.2-point rise in searches leading to another search means people cycle back through the system again and again before they act.</p>



<p class="wp-block-paragraph">Each new search resets the board. The follow-up query can pull up a different AI Overview, a different set of ads, and a different list of organic results. A brand can win the first search and disappear from the next. Ranking first for “best project management software” counts for nothing if a competitor owns “asana vs monday for agencies” and the complaint threads behind “monday.com implementation problems.”</p>



<p class="wp-block-paragraph">This is why tracking one query at a time hides how much is actually moving. Rank reports and cost per click both measure a single query in isolation. What competes now is the whole chain of searches, not the first one. Showing up across that chain matters more than owning the term at the top.</p>



<p class="wp-block-paragraph">A caveat before the tactics. This loop describes considered searches where people compare and evaluate before acting. It doesn&#8217;t govern everything. Navigational queries, local searches, and strong branded terms still resolve in a single click.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/paid-search-ai-search-advantage-484301">Why paid search could be your AI search advantage</a></em></strong>



<h2 id="h-key-adjustments-for-running-the-loop" class="wp-block-heading">Key adjustments for running the loop</h2>



<p class="wp-block-paragraph">The key is connecting what happens across the journey before making channel-level decisions.</p>



<h3 id="h-build-one-view-organized-by-query-path" class="wp-block-heading">Build one view, organized by query path</h3>



<p class="wp-block-paragraph">Start with 90 days of Google Ads query data. Layer in AI Overview presence from a third-party tracker like Semrush, Ahrefs, or ZipTie, since Search Console doesn&#8217;t flag which queries trigger them.&nbsp;</p>



<p class="wp-block-paragraph">For each priority journey, record five facts side by side across the head query and its follow-ups: AI Overview presence, citation status, organic position, paid position, and combined click share. Separate channel reports can&#8217;t describe interactions that happen on a single page. Those are now the interactions that matter most.</p>



<h3 id="h-use-the-new-search-console-ai-reports-but-know-their-limits" class="wp-block-heading">Use the new Search Console AI reports, but know their limits</h3>



<p class="wp-block-paragraph">In June, Google <a href="https://searchengineland.com/google-search-console-gains-reporting-on-social-and-video-platforms-481696">launched dedicated Search Console reports</a> for generative AI features covering AI Overviews and AI Mode. They report impressions by page, country, device, and date, but not clicks or queries, and they&#8217;re rolling out gradually. Pair them with query-level tracking to understand where AI visibility translates into performance.</p>



<h3 id="h-segment-comparison-and-question-queries-by-citation-status-before-cutting-them" class="wp-block-heading">Segment comparison and question queries by citation status before cutting them</h3>



<p class="wp-block-paragraph">These formats trigger AI Overviews more than 85% of the time and sit at the loop&#8217;s entry point.&nbsp;</p>



<ul class="wp-block-list">
<li>For uncited queries under 1% CTR and below half the account average conversion rate, the standard playbook applies: sharper creative, lower bids, or reallocation toward transactional terms.&nbsp;</li>



<li>For cited queries, the instinct reverses. Those are where organic and paid perform best together, and they warrant maintained or increased investment.</li>
</ul>



<h3 id="h-fund-original-data-as-a-system-asset-with-a-named-owner" class="wp-block-heading">Fund original data as a system asset with a named owner</h3>



<p class="wp-block-paragraph">If citation drives presence at Stage 1 and reinforcement at Stage 3, original research is the infrastructure for the whole loop. It scales to the business. </p>



<p class="wp-block-paragraph">A national SaaS brand needs proprietary research, while a regional service company may just need genuinely useful local expertise that a model can&#8217;t generate.&nbsp;</p>



<p class="wp-block-paragraph">The obstacle is organizational. Work that benefits every stage and is measured by none loses every budget conversation to last-click attribution. </p>



<p class="wp-block-paragraph">Citation share belongs in the same reporting view as CPA and average position, with one owner across both channels.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/guide/beat-commodity-content">AI made content a commodity, but you can harness expertise to stand out</a></em></strong>



<h2 id="h-search-optimization-now-spans-multiple-queries" class="wp-block-heading">Search optimization now spans multiple queries</h2>



<p class="wp-block-paragraph">SEO and PPC are now stages in one system that searchers loop through: an AI answer that shapes the shortlist, ads that capture the filtered demand, organic that reinforces the decision, and follow-up queries that restart it. </p>



<p class="wp-block-paragraph">The response is to map priority journeys across all four stages instead of tracking two channels separately, to check citation status before cutting a comparison query, and to fund the original insight that feeds the loop.</p>



<p class="wp-block-paragraph">Plenty of searches still work the old way, but on research-heavy journeys, no channel operates independently anymore. A team that keeps budgeting, measuring, and staffing around individual channels will keep optimizing isolated pieces of a journey that now operates as a single connected system. The advertisers winning in 2026 will be those who restructured around the loop rather than the line.</p>

SEO and PPC have traditionally been managed as two channels that share a results page. The coordination questions were about overlap: Should paid bid on terms the site already ranks for? Where is that overlap wasting budget? Which channel gets credit for the conversion?
That model no longer fits the search experience. 
An AI Overview answers the query and cites sources, ads compete for the remaining attention, and organic results appear alongside Reddit threads and related searches. Searchers can move between those surfaces, refine their query, and repeat the process until they know enough to act.
Search is now a loop: an AI answer shapes the shortlist, ads capture filtered demand, organic reinforces the decision, and a follow-up query starts the process again. What happens on one surface can change the outcome on another.
The challenge for SEO and PPC teams is to measure and optimize that loop rather than individual queries or channels.
The journey is now a loop, not a line
SparkToro’s 2026 analysis found that 68% of Google searches now end without a click. More importantly, the share of searches that led to another Google query rose 7.2 percentage points.
Refining and re-querying isn’t new. Searchers have chained one query to the next since the search began. What changed is the answer layer now sitting at the top of each step. It absorbs clicks that used to happen along the way and influences which brands get seen.
Consider a familiar journey. In 2023, a search for “best project management software for remote teams” might have driven clicks to comparison articles and vendor sites, with conversions occurring a week or two later.
The same search plays out differently today. An AI Overview names three tools, and the user doesn’t click. Instead, they search “asana vs monday for agencies,” see another AI Overview and ads from both brands, and click one. 
Then, they search “monday.com implementation problems” and read an organic article before starting a trial. That’s three queries inside a single loop, with each stage creating a different opportunity for visibility.
The loop has four stages: an AI answer shapes the consideration set, paid ads capture filtered demand, organic results reinforce the decision, and a follow-up query restarts the loop.
Dig deeper: Why the SEO vs. PPC debate is finally over



Stage 1: AI answers shape the consideration set
AI Overviews show up most often at the start of a search, when someone runs broad questions before they know enough to get specific. 
In Seer Interactive’s 2026 study of 53 brands and 5.47 million queries, comparison queries triggered an AI Overview 95.4% of the time, and question-format queries 85.9%. SparkToro puts the overall AI Overview presence above 20% of searches, and when one appears, the click-through rate drops nearly 60%.
Search was never where interest was created. That still happens in social feeds, video, communities, word of mouth, and brand marketing. What the AI answer changed is the next step. Once someone starts searching, the AI Overview narrows a broad topic down to a few named sources or options. 
A searcher arrives with a general question and leaves the first query with two or three specific names in mind. That narrowing used to happen across articles, listings, and ads. Now it happens inside the AI answer.
A brand can still buy an ad on that page, but it can’t buy its way into the AI answer itself. The overview either cites it as a source or it doesn’t. That citation is the asset the entire system depends on.
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Stage 2: Ads capture the filtered demand
Most advertisers assume the AI layer is bad for paid search. The data says otherwise.
Seer’s September 2025 numbers looked alarming at first, with paid click-through rate on AI Overview queries down 68%. The 2026 update told a different story. 
When an AI Overview appears, paid CTR actually rose from 14.6% to 16.2%. On queries without one, it fell from 26% to 21.8%. So, paid isn’t being hurt by the AI answer. It’s capturing the demand that answer filters and passes along.
The same pattern shows up in click share. Similarweb compared January 2025 to January 2026 and found organic losing share in every category it tracked. In headphones, organic went from 73% of clicks down to 50%. Text ads were the only surface to gain share. 
Amazon grew paid clicks 35% in headphones even as its organic volume fell. As the AI answer takes the early clicks, the paid slots below it become where the remaining demand converts to a click.
One stage feeds the next. The brand the AI answer cited shows up here with a trust signal the competitor bidding next to it doesn’t have. The next stage measures what that is worth.
Dig deeper: How SEO and PPC build trust across search: Case study



Stage 3: Organic reinforces the decision
Stage 2 ended with paid absorbing the clicks near the AI answer. So who’s left to click an organic result? The searcher who didn’t stop at the AI answer and who is now deeper in the loop.
Two things keep clicks in organic’s column. The first is the set of queries where no AI Overview appears at all, which is where organic is actually gaining. Seer found organic CTR on those queries rose from 2.93% to 3.97% in 2025. 
Fewer people click overall, but the ones who do are past the quick-answer stage and want real depth. The second is the moment of decision. By now, the AI answer has built the shortlist and the ads have shown the options, so the organic click confirms a choice rather than discovering one.
The citation is what ties this back to paid. Seer found that brands cited inside an AI Overview earned 35% more organic clicks and 91% more paid clicks than uncited brands on the same queries. 
Seer couldn’t prove the citation caused the lift, and the paid sample was small, but the effect points in the same direction. The citation acts as a trust signal and lifts both the listing and the ad to the same page.
That is where the two disciplines fuse. The citation is earned through SEO work, yet much of its payoff shows up in the paid account as a CTR lift. Sharing query reports across teams is coordination, and good teams have done it for years. One asset that moves both channels’ numbers, on the same page, at the same time is new.
What earns a citation is narrower than most content plans assume. A case study by Search Engine Land contributor Adam Gnuse, covering 10 domains and roughly 150,000 pages, found that generic how-to content underperforms in AI citations because models can already write it themselves.
What gets cited is original data and proprietary research. That leaves the “what is” library that anchored a decade of content strategy mismatched to the job organic now does.
Dig deeper: SEO and PPC alignment starts with your org chart




	
	
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Stage 4: Follow-up queries restart the loop
The stage most strategies ignore is the one growing fastest. That 7.2-point rise in searches leading to another search means people cycle back through the system again and again before they act.
Each new search resets the board. The follow-up query can pull up a different AI Overview, a different set of ads, and a different list of organic results. A brand can win the first search and disappear from the next. Ranking first for “best project management software” counts for nothing if a competitor owns “asana vs monday for agencies” and the complaint threads behind “monday.com implementation problems.”
This is why tracking one query at a time hides how much is actually moving. Rank reports and cost per click both measure a single query in isolation. What competes now is the whole chain of searches, not the first one. Showing up across that chain matters more than owning the term at the top.
A caveat before the tactics. This loop describes considered searches where people compare and evaluate before acting. It doesn’t govern everything. Navigational queries, local searches, and strong branded terms still resolve in a single click.
Dig deeper: Why paid search could be your AI search advantage



Key adjustments for running the loop
The key is connecting what happens across the journey before making channel-level decisions.
Build one view, organized by query path
Start with 90 days of Google Ads query data. Layer in AI Overview presence from a third-party tracker like Semrush, Ahrefs, or ZipTie, since Search Console doesn’t flag which queries trigger them. 
For each priority journey, record five facts side by side across the head query and its follow-ups: AI Overview presence, citation status, organic position, paid position, and combined click share. Separate channel reports can’t describe interactions that happen on a single page. Those are now the interactions that matter most.
Use the new Search Console AI reports, but know their limits
In June, Google launched dedicated Search Console reports for generative AI features covering AI Overviews and AI Mode. They report impressions by page, country, device, and date, but not clicks or queries, and they’re rolling out gradually. Pair them with query-level tracking to understand where AI visibility translates into performance.
Segment comparison and question queries by citation status before cutting them
These formats trigger AI Overviews more than 85% of the time and sit at the loop’s entry point. 
For uncited queries under 1% CTR and below half the account average conversion rate, the standard playbook applies: sharper creative, lower bids, or reallocation toward transactional terms. 
For cited queries, the instinct reverses. Those are where organic and paid perform best together, and they warrant maintained or increased investment.
Fund original data as a system asset with a named owner
If citation drives presence at Stage 1 and reinforcement at Stage 3, original research is the infrastructure for the whole loop. It scales to the business. 
A national SaaS brand needs proprietary research, while a regional service company may just need genuinely useful local expertise that a model can’t generate. 
The obstacle is organizational. Work that benefits every stage and is measured by none loses every budget conversation to last-click attribution. 
Citation share belongs in the same reporting view as CPA and average position, with one owner across both channels.
Dig deeper: AI made content a commodity, but you can harness expertise to stand out



Search optimization now spans multiple queries
SEO and PPC are now stages in one system that searchers loop through: an AI answer that shapes the shortlist, ads that capture the filtered demand, organic that reinforces the decision, and follow-up queries that restart it. 
The response is to map priority journeys across all four stages instead of tracking two channels separately, to check citation status before cutting a comparison query, and to fund the original insight that feeds the loop.
Plenty of searches still work the old way, but on research-heavy journeys, no channel operates independently anymore. A team that keeps budgeting, measuring, and staffing around individual channels will keep optimizing isolated pieces of a journey that now operates as a single connected system. The advertisers winning in 2026 will be those who restructured around the loop rather than the line.

The first search is rarely the whole journey. See how AI answers, paid ads, organic results and follow-up queries shape conversion.

The new search journey changes how SEO and PPC should work

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/featured-image.png" class="attachment-large size-large wp-post-image" alt="Community signals are AI&#039;s largest third-party source" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>UGC platforms out-cite review sites at every stage of the buyer journey. Here’s what you need to know about organic authority multiplication.


Across a sample of 35,000 ChatGPT citations, user-generated content (UGC) platforms hold more of the cited-domain share for SaaS-related prompts than review sites and publishers combined. They hold it at the top of the journey, at the bottom, and at every point between. There is no stage where they’re skipped.
So how do you build authority in a source you don’t control?
Let’s talk brand authority multiplication. Part 1 covered third-party citation signals. Parts 2 and 3 covered proprietary data and what makes it citable. Both of those are levers you can pull on your own.
This one — UGC — is not.
The uncomfortable part: The UGC pattern is bigger than expected. Problem is, this is the authority layer you can seed, prompt, and participate in, but never truly own. While some platforms, like Reddit, are really, really challenging to influence.
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Method and limitations
The data comes from an analysis I ran for G2 in February 2026.
Source: ~35,000 citation URLs captured in Profound.
Coverage: US only, ChatGPT only, month of December 2025.
Each SaaS vendor-related prompt was classified into one journey step: discovery (376 prompts), exploration (1,179), evaluation (1,367), or focused evaluation (255).
Each citation URL was reduced to a root domain and classified as review_platform, ugc_platform, publisher, or vendor_or_other.
Records were de-duplicated to one per run, intent, and domain, so a single answer citing 6 Reddit threads counts once.
The evaluation stage was the largest journey step covered in this prompt set. 




And for reference, more than half of the SaaS-related prompts in this study use commercial language. But only 1.5% actually name a vendor brand. 




What this analysis doesn’t do:
The UGC set is wide. It groups Reddit, Wikipedia, Quora, YouTube, and LinkedIn. These UGC platforms have different uses and audiences. We report on the UGC set in aggregate for the stage analysis and break out composition later (in section 3).
The analysis measures share of unique cited domains, not share of citation volume. Part 1 measured citation rows and put Video and Social at ~6.5%. Different denominator, different bucket, different dataset. 
One engine, one market, one month. There are limitations with this data set. Given the consensus gap, where 91% of citations appear in only 1 engine, don’t read ChatGPT results as overall AI search results.
The prompts for this analysis were software vendor-seeking by design, which is why vendor domains hold 66.7% to 71.8% of citations at every stage. 
1. UGC is the largest third-party source class in SaaS-related AI answers
Strip out the vendor domains included in this analysis, and look at what is left: UGC platforms hold 17.1% of cited domains overall, more than 4x publishers at 4.0%.







Sit with the ratio for a second, because most authority-building budgets are aimed at the 2 smaller buckets: Digital PR targets publishers. Review campaigns target review platforms.
But the largest outside-source class in the sample, for this particular set of prompts, receives the least deliberate investment. Mostly because most marketing pros aren’t sure what a plan for it even looks like.
Even more importantly, excluding the vendor, UGC is the most common third-party source to show up in the AI Answer (not just the citation set) in this SaaS prompt data. 




2. Review sites move with purchase intent. UGC doesn’t.
Read the table by column instead of by row and a second pattern shows up.
UGC dips slightly in the Evaluation journey step, passing its share over to publishers and review platforms. (Confirming that, yes, investment in Digital PR and review campaigns does matter.)
But review platforms swing. They sit at 7.4% in discovery and climb to 13.2% at evaluation, roughly 1.8x, then fall back to 8.4% in focused evaluation. A 5.8-point range.
UGC barely moves. 17.8%, 18.2%, 15.1%, 17.2%. A 3.1-point range across the stages.




Review platforms are a reliable bottom-of-funnel lever, while UGC is a floor.



That distinction can help decide where the money goes and when. A review campaign can be scheduled against a quarter because its payoff concentrates at a known stage. In other analyses, I found that (software) reviews increase a vendor’s AI visibility and shape AI answers.
But community presence has no such stage, unfortunately. Much like classic organic search visibility, it involves doing work to gain visibility in the answer when someone is learning what their needs are, and it still requires work to earn visibility when they are choosing between 2 finalists.
The review platform shares peaks at evaluation and falls to 8.4% in focused evaluation. Review platforms do their work while a buyer is building a shortlist, less once they are comparing 2 finalists. UGC holds at 17.2% through that same step.
Even at the narrowest gap between UGC and the review platforms (at the evaluation step), the point where peer proof is supposedly most concentrated on review sites, UGC still leads in citation amount.
3. Platform concentration isn’t platform stability
A floor that holds at 17% doesn’t mean the platforms underneath it hold.
Break the UGC bucket into its parts: Wikipedia, Reddit, and LinkedIn account for 99% of UGC citations in this sample. Everything else splits the remaining 1%.




Wikipedia alone runs 10.1 to 14.0 points of that 17-point floor depending on the stage. It’s the single largest third-party source in the dataset… larger than the entire review platform class at every journey step except evaluation. That means the biggest slice of the biggest third-party source class is the one where deliberate action is least available to you.
Despite their hold across the AI citations and answers in this set, these platforms are volatile in their visibility. 
In GIB #20, Reddit declined on both dimensions for the first time since I started tracking AI mentions in February: visibility down 11.7% and AI mentions down 10.9% in the 28 days to June 8, 2026.
Three weeks later the bucket moved the other way. In the 28 days to June 29 (GIB #21):
LinkedIn +43.3% SEO visibility (289.4 to 414.7)
X +38.6%
Instagram +21.4%
Facebook +20.1%
Reddit +18.1% (2,297.6 to 2,765.7)
YouTube at the bottom of the range: 11%
All UGC. The 2 windows overlap by a week, so treat these as adjacent reads on a moving bucket rather than a before and after.
Every one of those platforms lost AI Overview citations in the same 28 days it gained organic visibility. Google rewarded them in search and cited them less in AI answers, on the same properties, in the same window. A platform can concentrate share in one surface while losing it in the other.
So treat UGC as a portfolio and give each platform a job.
The aggregate is the number to defend. The composition is what you rebalance. And the platforms doing the work here aren’t interchangeable:
Wikipedia is the largest and least actionable. You don’t campaign here. You make sure the sources Wikipedia editors are required to rely on (things like trade press, original research, primary documentation) exist and are accurate. 
Reddit is the most volatile, but presence here is worth it.
LinkedIn is where a named person outperforms a brand account. 
YouTube offers durability as a Google-owned property where you have some control, and it’s your hedge.
Focus on the platforms where your audience actually lives. An audience research tool like Sparktoro will tell you where. What you don’t do is bet the whole community effort on one platform and then check the box that you’re “doing UGC.”
4. How to produce community signals on purpose
None of this is an argument for buying reviews or astroturfing threads. That’s a short-term tactic that can hurt your brand in the long-term. But there is an argument here for showing up where the answers are already being assembled.
Find which UGC platforms your category feeds
Run your highest-intent prompts and record which UGC domains appear, mostly across citations. In some categories, it will be Reddit and YouTube. In others, it’s a Discord, a Stack Exchange, or a single trade forum. The bucket is 17% on average and the composition is local to your topic. Part 1’s finding applies here: The source set AI trusts is rebuilt per topic.
Highlight people in the places that matter to your audience, not just the brand account
In Topics matter for third-party signals, we reported that a named author with a byline appears to outperform the same content under a brand, and LinkedIn’s own testing pointed the same way. A community treats a person as a participant… and a logo as an advertiser. This can be something as simple as your best sales rep making a YouTube shorts series about tips and tricks with your product.
Answer the questions your support queue already sees on repeat
Ticket logs, sales call transcripts, and in-app search queries hold the exact phrasing buyers use. Why proprietary data is your most defensible asset made this case for owned content. It applies even harder in community, where a question is sitting there already asked.
Make your customers’ words retrievable on your own pages
Pull real third-party review quotes, with links to the source, into the top of your highest-cited pages. The science of how AI pays attention found 44.2% of citations come from the first 30% of a page. 
Whether the presence of positive third-party proof in that top third band changes how AI describes your brand is untested (outside of first-hand experience), so run it as a test with a stated hypothesis and a control set rather than as a tactic.
Measure the aggregate, rebalance the mix
Track UGC-sourced citations as 1 number, and platform composition as a second. The first tells you whether the floor is holding, and the second tells you where to move next quarter.
Mine communities for questions and terminology
Extract questions your audience asks on Reddit & Co. and track what words they use to describe your category, features, and brands. Then, use this information to inform your prompts and copy.
Correct the record that’s already sitting there
A 2023 thread claiming you lack a feature you shipped last year stays retrievable and keeps feeding answers. Reply in-thread with a dated correction and a link to the change. Removal requests rarely land, and deleting a thread deletes the context AI is reading from. 
Set alerts on brand plus category terms (F5Bot for Reddit and HN, Syften if you need Discord and Slack coverage), so you catch it in weeks instead of quarters.
The strongest community signal isn’t written by you
Give customers and power users something worth posting on their own: early access to your data, a free tool, a number they can quote in an argument. That is as close to ownership as this bucket gets.
If a finding from this week changes a decision for your brand, the Growth Memo Premium Resource Library has 45+ (and growing) checklists, light tools, AI workflows, and stakeholder slide decks to put it to work.



5. Google started measuring social, and left out the platforms that matter most here
On July 7, Google introduced platform properties in Search Console, a property type that reports clicks, impressions, CTR, average position, and queries for Instagram, TikTok, X, and YouTube. You must link owned accounts to view, so this isn’t the same as brand mention monitoring across the web.
But Reddit isn’t on the list. Neither is LinkedIn, the two platforms doing the most work in the UGC bucket above are the two you still can’t measure natively. 
Plus, this new feature reports visibility in Google Search and Discover, not AI answers. A team that connects these properties and calls the output AI visibility measurement will be measuring the wrong surface with real numbers, which is worse than measuring nothing.
Use it for what it is: 
The first native read on how your off-site content performs in classic Google. (The community signals feeding AI answers stay unmeasured for now.)
An important signal of how crucial multichannel brand visibility is for AI search.
Out of the factors in the brand multiplication series (we examined topics, proprietary data, and original first-party research), community proof is the only one that keeps working while you sleep. 
Third-party authority takes a quarter to move. Proprietary data takes a research cycle. Community presence takes a year, and once it takes off organically, then holds a floor that doesn’t care which stage of the journey your buyer is in.
Fund it as a standing line rather than a single campaign, because there is no stage where turning it off is safe when you want to maintain or grow organic AI search visibility.
This post first appeared on the author’s website and is republished here with permission.

UGC platforms out-cite review sites at every stage of the buyer journey. Here’s what you need to know about organic authority multiplication.

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