<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The update will take a few days to roll out.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/09/google-spam-header-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Google has released the August 2026 spam update and said this update will take a few days to roll out. This update applies globally and to all languages, Google added.</p>



<p class="wp-block-paragraph"><strong>More details. </strong>Google posted about the update on its <a href="https://status.search.google.com/incidents/LEubPCm2octf2uMqCFKE">incident dashboard</a> and wrote:</p>



<ul class="wp-block-list">
<li>Released the August 2026 spam update, which applies globally and to all languages. The rollout may take a few days to complete.</li>
</ul>



<p class="wp-block-paragraph">You can learn more about Google spam updates in <a href="https://developers.google.com/search/docs/appearance/spam-updates">this Google help document</a>.</p>



<p class="wp-block-paragraph"><strong>Why we care. </strong>This is the third Google spam update announced in 2026, the last one was the <a href="https://searchengineland.com/google-releases-june-2026-spam-update-481002">June 2026 spam update</a>. If your site was not impacted, then you are good to go – at least for now.</p>



<p class="wp-block-paragraph">There will always be cases of sites not spamming Google that get hit by a spam update but hopefully that won’t be one of your sites.</p>



<p class="wp-block-paragraph">


Google has released the August 2026 spam update and said this update will take a few days to roll out. This update applies globally and to all languages, Google added.
More details. Google posted about the update on its incident dashboard and wrote:
Released the August 2026 spam update, which applies globally and to all languages. The rollout may take a few days to complete.
You can learn more about Google spam updates in this Google help document.
Why we care. This is the third Google spam update announced in 2026, the last one was the June 2026 spam update. If your site was not impacted, then you are good to go – at least for now.
There will always be cases of sites not spamming Google that get hit by a spam update but hopefully that won’t be one of your sites.

The update will take a few days to roll out.

Google releases August 2026 spam update

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal.png" class="attachment-large size-large wp-post-image" alt="What 9 months of AI Overview data and 51,000+ tracked events reveal" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Traffic swings, attribution gaps, and unexpected citation patterns offer a clearer picture of how AI Overviews affect organic search.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal.png" class="attachment-large size-large wp-post-image" alt="What 9 months of AI Overview data and 51,000+ tracked events reveal" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/What-9-months-of-AI-Overview-data-and-51000-tracked-events-reveal-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Most brands still don&#8217;t have a clear picture of how much traffic <a href="https://searchengineland.com/guide/google-ai-overviews">AI Overviews</a> are sending them. Google hasn&#8217;t given us a clean signal for AI Overview traffic in Search Console, making it difficult to know how much organic traffic is coming from AI Overviews, which content is driving it, and how accurately that traffic is being reported.</p>



<p class="wp-block-paragraph">So we built our own tracking.</p>



<p class="wp-block-paragraph">Since September 2025, I&#8217;ve been capturing AI Overview referral data for one of the brands I manage in the transportation industry. From September 2025 to June 2026, we recorded 51,200 tracked events across 1,661 cited snippets.</p>



<p class="wp-block-paragraph">The data shows that AI Overview prominence in the SERP isn&#8217;t stable. It also reveals clear patterns in the types of content Google cites, how those citations change over time, and how much of that traffic gets misattributed in analytics.</p>



<p class="wp-block-paragraph">Here&#8217;s what nine months of tracking revealed — and what it means for SEO reporting, content prioritization, and GEO.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="812" src="https://searchengineland.com/wp-content/seloads/2026/08/image-61.png" alt="" class="wp-image-485082" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-61.png 2048w, https://searchengineland.com/wp-content/seloads/2026/08/image-61-768x305.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-61-1536x609.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<h2 id="h-the-tracking-setup-and-why-it-works" class="wp-block-heading">The tracking setup — and why it works</h2>



<p class="wp-block-paragraph">The methodology is straightforward, but most teams haven&#8217;t implemented it.</p>



<p class="wp-block-paragraph">When a user clicks on a cited snippet inside a Google AI Overview, Google sometimes appends a <code>#:~:text=</code> fragment to the destination URL. We created a custom dimension in GA4 that fires whenever a session lands with that fragment present.</p>



<p class="wp-block-paragraph">It&#8217;s not a perfect signal, but it&#8217;s the most reliable one available without waiting for Google to expose this natively in Search Console. The fragment is already sitting in your GA4 data. You just need to surface it.</p>



<p class="wp-block-paragraph">Once we had it captured, we grouped snippets into thematic categories and started analyzing patterns. A few things stood out immediately.</p>



<ul class="wp-block-list">
<li><strong>Concentration is high:</strong> The top-performing snippet alone drove 2,276 events. The average across all 1,661 snippets is 31. Like most things in SEO, a small number of pages are doing the bulk of the work.</li>



<li><strong>Snippets have lifecycles:</strong> Some peak during a specific period and then fade — usually when query intent shifts seasonally or when the content becomes stale relative to what Google is now preferring to cite. Others emerge months after publication and keep climbing. This makes freshness and specificity more important than you&#8217;d initially assume.</li>



<li><strong>Content prioritization gets sharper:</strong> The most useful output of having this data is that it makes decisions more grounded. When you map snippet volume and growth trajectory against your current content investment, the gaps become visible.</li>
</ul>


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<h2 id="h-certain-topic-types-got-cited" class="wp-block-heading">Certain topic types got cited</h2>



<p class="wp-block-paragraph">In our case:</p>



<ul class="wp-block-list">
<li><strong>Transfer time content</strong> and <strong>pricing content</strong> are already being cited frequently with clear upward momentum. The play there is to refresh and expand the existing content.</li>



<li><strong>Destination guides</strong> are underperforming relative to what the data suggests they could be driving.</li>



<li><strong>Structured transport comparison tables, formatted as actual HTML tables,</strong> are punching well above their weight in terms of citation frequency — which tells you something about how AI Overviews are selecting content to surface.</li>
</ul>



<p class="wp-block-paragraph">The broader pattern is consistent with what most people working in GEO are finding: AI Overview citations favor content that is specific, structured, and directly answers a well-defined question. Times, prices, named routes, comparison formats. Not vague editorial.</p>



<h2 id="h-22-4-of-ai-overview-traffic-is-being-misattributed-to-direct" class="wp-block-heading">22.4% of AI Overview traffic is being misattributed to Direct</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1155" src="https://searchengineland.com/wp-content/seloads/2026/08/image-63.png" alt="" class="wp-image-485083" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-63.png 2048w, https://searchengineland.com/wp-content/seloads/2026/08/image-63-768x433.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-63-1536x866.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p class="wp-block-paragraph">This was the most striking finding.</p>



<p class="wp-block-paragraph">When we started plotting the dataset on a GA4 exploration report, we noticed that a meaningful portion of traffic arriving via AI Overviews was being attributed to the Direct channel rather than Organic Search.</p>



<p class="wp-block-paragraph">We know AI Overviews only exist within Google Search. Traffic from there should be attributed to organic. So we built misattribution tracking into our AI Overview dashboard and started measuring it on a monthly and weekly basis.</p>



<p class="wp-block-paragraph">Across the full dataset — more than 50,000 AI Overview events over nine months — the average misattribution rate was 22.4%.</p>



<p class="wp-block-paragraph">That&#8217;s 11,468 AI Overview events attributed to Direct instead of Organic. The range varied by month:</p>



<ul class="wp-block-list">
<li><strong>Worst month:</strong> May 2026 – 29.3% of AI Overview sessions were misattributed to Direct.</li>



<li><strong>Best month:</strong> April 2026 – 16.8% were misattributed.</li>
</ul>



<p class="wp-block-paragraph">The implications for SEO reporting are significant. Depending on your total organic traffic volume and how much AI Overview referral traffic you&#8217;re generating, you could be materially underreporting organic performance without realizing it.</p>



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<h2 id="h-ai-overviews-are-driving-7-53-of-organic-sessions-but-it-s-volatile" class="wp-block-heading">AI Overviews are driving 7.53% of organic sessions — but it&#8217;s volatile</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="989" src="https://searchengineland.com/wp-content/seloads/2026/08/image-62.png" alt="" class="wp-image-485081" srcset="https://searchengineland.com/wp-content/seloads/2026/08/image-62.png 2048w, https://searchengineland.com/wp-content/seloads/2026/08/image-62-768x371.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/image-62-1536x742.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p class="wp-block-paragraph">Using the same first-party dataset, we built a percentage metric to track what share of our total organic sessions came from AI Overviews each period.</p>



<p class="wp-block-paragraph">From September 2025 to June 2026, 7.53% of organic sessions came from AI Overviews.</p>



<p class="wp-block-paragraph">But the distribution is not flat:</p>



<ul class="wp-block-list">
<li>At its peak in February-March 2026, it reached 16-17% — meaning nearly one in six organic visitors arrived via an AI Overview.</li>



<li>More recently (as of writing), it has trended down to around 2-4%.</li>
</ul>



<p class="wp-block-paragraph">That volatility is notable. It suggests AI Overview prominence in the SERP is not stable — it fluctuates based on query type, Google&#8217;s confidence in available content, and possibly broader algorithmic changes. Brands treating AI Overview traffic as a fixed percentage of organic are likely miscalibrating their models.</p>



<h2 id="h-the-caveats-you-should-know" class="wp-block-heading">The caveats you should know</h2>



<p class="wp-block-paragraph">Two important limitations with this approach:</p>



<h3 id="h-the-text-identifier-isn-t-exclusive-to-ai-overviews" class="wp-block-heading">The #:~:text= identifier isn&#8217;t exclusive to AI Overviews</h3>



<p class="wp-block-paragraph">The same fragment is used by Featured Snippets and People Also Ask results. So some portion of what we&#8217;re capturing may bleed from those formats.&nbsp;</p>



<p class="wp-block-paragraph">We did run the exercise in Ahrefs to check our Featured Snippet exposure, and at the time of checking, we were included in fewer than 30 — largely because we don&#8217;t target terms that typically trigger Featured Snippets.&nbsp;</p>



<p class="wp-block-paragraph">In practice, we believe AI Overviews are the dominant driver given the volume and the period of data collection, but it&#8217;s not a perfectly clean signal.</p>



<h3 id="h-the-metric-compares-events-to-sessions" class="wp-block-heading">The metric compares events to sessions</h3>



<p class="wp-block-paragraph">Our custom dimension in GA4 is event-scoped, not session-scoped. The AI Overview share percentage therefore compares events against sessions, which isn&#8217;t an ideal comparison.&nbsp;</p>



<p class="wp-block-paragraph">It&#8217;s better than nothing — and it&#8217;s directionally accurate — but worth knowing if you replicate this.</p>


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<h2 id="h-what-this-means-practically" class="wp-block-heading">What this means practically</h2>



<p class="wp-block-paragraph">If you&#8217;re not tracking this yet, start. The setup isn&#8217;t complex, and the signal — imperfect as it is — is the best first-party data you&#8217;ll get until Google decides to surface this natively.</p>



<p class="wp-block-paragraph">A few things to take away from nine months of data:</p>



<ul class="wp-block-list">
<li><strong>Structured, specific content wins.</strong> Times, prices, routes, named comparisons. Not editorial padding.</li>



<li><strong>Freshness matters more than you think.</strong> Snippets have lifecycles. Stale content loses citation share.</li>



<li><strong>Your organic traffic is likely underreported.</strong> If ~22% of AI Overview events are going to Direct, your channel reporting has a systematic gap.</li>



<li><strong>The share is volatile.</strong> Don&#8217;t treat a peak month as a new baseline.</li>
</ul>



<p class="wp-block-paragraph">The <code>#:~:text=</code> fragment is sitting there in your GA4 data right now. You just need to surface it.</p>



<p class="wp-block-paragraph"><em>Special thanks to Simant Sah for helping collate the data and put together the report where the screenshots come from.</em>

Most brands still don’t have a clear picture of how much traffic AI Overviews are sending them. Google hasn’t given us a clean signal for AI Overview traffic in Search Console, making it difficult to know how much organic traffic is coming from AI Overviews, which content is driving it, and how accurately that traffic is being reported.
So we built our own tracking.
Since September 2025, I’ve been capturing AI Overview referral data for one of the brands I manage in the transportation industry. From September 2025 to June 2026, we recorded 51,200 tracked events across 1,661 cited snippets.
The data shows that AI Overview prominence in the SERP isn’t stable. It also reveals clear patterns in the types of content Google cites, how those citations change over time, and how much of that traffic gets misattributed in analytics.
Here’s what nine months of tracking revealed — and what it means for SEO reporting, content prioritization, and GEO.




The tracking setup — and why it works
The methodology is straightforward, but most teams haven’t implemented it.
When a user clicks on a cited snippet inside a Google AI Overview, Google sometimes appends a #:~:text= fragment to the destination URL. We created a custom dimension in GA4 that fires whenever a session lands with that fragment present.
It’s not a perfect signal, but it’s the most reliable one available without waiting for Google to expose this natively in Search Console. The fragment is already sitting in your GA4 data. You just need to surface it.
Once we had it captured, we grouped snippets into thematic categories and started analyzing patterns. A few things stood out immediately.
Concentration is high: The top-performing snippet alone drove 2,276 events. The average across all 1,661 snippets is 31. Like most things in SEO, a small number of pages are doing the bulk of the work.
Snippets have lifecycles: Some peak during a specific period and then fade — usually when query intent shifts seasonally or when the content becomes stale relative to what Google is now preferring to cite. Others emerge months after publication and keep climbing. This makes freshness and specificity more important than you’d initially assume.
Content prioritization gets sharper: The most useful output of having this data is that it makes decisions more grounded. When you map snippet volume and growth trajectory against your current content investment, the gaps become visible.
customers find first.
      
Start your free trial
    
Certain topic types got cited
In our case:
Transfer time content and pricing content are already being cited frequently with clear upward momentum. The play there is to refresh and expand the existing content.
Destination guides are underperforming relative to what the data suggests they could be driving.
Structured transport comparison tables, formatted as actual HTML tables, are punching well above their weight in terms of citation frequency — which tells you something about how AI Overviews are selecting content to surface.
The broader pattern is consistent with what most people working in GEO are finding: AI Overview citations favor content that is specific, structured, and directly answers a well-defined question. Times, prices, named routes, comparison formats. Not vague editorial.
22.4% of AI Overview traffic is being misattributed to Direct




This was the most striking finding.
When we started plotting the dataset on a GA4 exploration report, we noticed that a meaningful portion of traffic arriving via AI Overviews was being attributed to the Direct channel rather than Organic Search.
We know AI Overviews only exist within Google Search. Traffic from there should be attributed to organic. So we built misattribution tracking into our AI Overview dashboard and started measuring it on a monthly and weekly basis.
Across the full dataset — more than 50,000 AI Overview events over nine months — the average misattribution rate was 22.4%.
That’s 11,468 AI Overview events attributed to Direct instead of Organic. The range varied by month:
Worst month: May 2026 – 29.3% of AI Overview sessions were misattributed to Direct.
Best month: April 2026 – 16.8% were misattributed.
The implications for SEO reporting are significant. Depending on your total organic traffic volume and how much AI Overview referral traffic you’re generating, you could be materially underreporting organic performance without realizing it.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
AI Overviews are driving 7.53% of organic sessions — but it’s volatile




Using the same first-party dataset, we built a percentage metric to track what share of our total organic sessions came from AI Overviews each period.
From September 2025 to June 2026, 7.53% of organic sessions came from AI Overviews.
But the distribution is not flat:
At its peak in February-March 2026, it reached 16-17% — meaning nearly one in six organic visitors arrived via an AI Overview.
More recently (as of writing), it has trended down to around 2-4%.
That volatility is notable. It suggests AI Overview prominence in the SERP is not stable — it fluctuates based on query type, Google’s confidence in available content, and possibly broader algorithmic changes. Brands treating AI Overview traffic as a fixed percentage of organic are likely miscalibrating their models.
The caveats you should know
Two important limitations with this approach:
The #:~:text= identifier isn’t exclusive to AI Overviews
The same fragment is used by Featured Snippets and People Also Ask results. So some portion of what we’re capturing may bleed from those formats. 
We did run the exercise in Ahrefs to check our Featured Snippet exposure, and at the time of checking, we were included in fewer than 30 — largely because we don’t target terms that typically trigger Featured Snippets. 
In practice, we believe AI Overviews are the dominant driver given the volume and the period of data collection, but it’s not a perfectly clean signal.
The metric compares events to sessions
Our custom dimension in GA4 is event-scoped, not session-scoped. The AI Overview share percentage therefore compares events against sessions, which isn’t an ideal comparison. 
It’s better than nothing — and it’s directionally accurate — but worth knowing if you replicate this.
customers won’t either.
      
See your AI visibility
    
What this means practically
If you’re not tracking this yet, start. The setup isn’t complex, and the signal — imperfect as it is — is the best first-party data you’ll get until Google decides to surface this natively.
A few things to take away from nine months of data:
Structured, specific content wins. Times, prices, routes, named comparisons. Not editorial padding.
Freshness matters more than you think. Snippets have lifecycles. Stale content loses citation share.
Your organic traffic is likely underreported. If ~22% of AI Overview events are going to Direct, your channel reporting has a systematic gap.
The share is volatile. Don’t treat a peak month as a new baseline.
The #:~:text= fragment is sitting there in your GA4 data right now. You just need to surface it.
Special thanks to Simant Sah for helping collate the data and put together the report where the screenshots come from.

Traffic swings, attribution gaps, and unexpected citation patterns offer a clearer picture of how AI Overviews affect organic search.

What 9 months of AI Overview data and 51,000+ tracked events reveal

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Microsoft shared documentation for its beta Conversions API, as a server-side option for sending data directly to the platform.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-Adv-conversion-API-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Microsoft is giving advertisers a new server-side option for sending conversion data directly to its advertising platform, reducing their dependence on browser-based tracking.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Microsoft Advertising has published new documentation for its Conversions API (CAPI), a server-side measurement solution currently in beta.</p>



<p class="wp-block-paragraph">CAPI lets advertisers send conversion and customer interaction data directly from their own systems to Microsoft Advertising through a single connection.</p>



<p class="wp-block-paragraph"><strong>The details</strong>. Microsoft says the Conversions API can support multiple measurement scenarios, including online and offline events.</p>



<p class="wp-block-paragraph">The potential benefits include:</p>



<ul class="wp-block-list">
<li>Improving conversion measurement accuracy.</li>



<li>Increasing attribution coverage.</li>



<li>Sending both online and offline conversion events.</li>



<li>Reducing reliance on browser-only tracking methods.</li>



<li>Supporting multiple measurement use cases through one server-side integration.</li>
</ul>



<p class="wp-block-paragraph"><strong>How it works</strong>. Microsoft recommends using CAPI alongside Universal Event Tracking (UET) rather than treating it as a replacement.</p>



<p class="wp-block-paragraph">UET continues to capture activity in the browser, while CAPI provides a server-to-server connection for sending event data directly to Microsoft Advertising.</p>



<p class="wp-block-paragraph">Using the two together can give advertisers more complete measurement coverage when browser signals are unavailable or limited.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. CAPI gives Microsoft advertisers another way to preserve conversion signals and connect online advertising with actions that happen outside the browser, including offline events. For advertisers already investing in server-side measurement across other ad platforms, Microsoft&#8217;s solution could also make it easier to build a more consistent measurement strategy across channels.</p>



<p class="wp-block-paragraph"><strong>Yes, but</strong>. CAPI remains in beta and isn&#8217;t available to every Microsoft Advertising account yet.</p>



<p class="wp-block-paragraph">Advertisers will also need the technical resources to establish and maintain a server-side integration, making implementation more involved than simply installing a browser tag.</p>



<p class="wp-block-paragraph"><strong>The big picture</strong>. Microsoft is following the broader advertising industry&#8217;s shift toward combining browser and server-side signals rather than relying exclusively on tracking pixels.</p>



<p class="wp-block-paragraph"><a href="https://learn.microsoft.com/en-us/advertising/guides/uet-conversion-api-integration?view=bingads-13">The new documentation</a> shows that server-side measurement is moving from an advanced implementation option toward a standard part of advertisers&#8217; measurement stacks.</p>


Microsoft is giving advertisers a new server-side option for sending conversion data directly to its advertising platform, reducing their dependence on browser-based tracking.
What’s happening. Microsoft Advertising has published new documentation for its Conversions API (CAPI), a server-side measurement solution currently in beta.
CAPI lets advertisers send conversion and customer interaction data directly from their own systems to Microsoft Advertising through a single connection.
The details. Microsoft says the Conversions API can support multiple measurement scenarios, including online and offline events.
The potential benefits include:
Improving conversion measurement accuracy.
Increasing attribution coverage.
Sending both online and offline conversion events.
Reducing reliance on browser-only tracking methods.
Supporting multiple measurement use cases through one server-side integration.
How it works. Microsoft recommends using CAPI alongside Universal Event Tracking (UET) rather than treating it as a replacement.
UET continues to capture activity in the browser, while CAPI provides a server-to-server connection for sending event data directly to Microsoft Advertising.
Using the two together can give advertisers more complete measurement coverage when browser signals are unavailable or limited.
Why we care. CAPI gives Microsoft advertisers another way to preserve conversion signals and connect online advertising with actions that happen outside the browser, including offline events. For advertisers already investing in server-side measurement across other ad platforms, Microsoft’s solution could also make it easier to build a more consistent measurement strategy across channels.
Yes, but. CAPI remains in beta and isn’t available to every Microsoft Advertising account yet.
Advertisers will also need the technical resources to establish and maintain a server-side integration, making implementation more involved than simply installing a browser tag.
The big picture. Microsoft is following the broader advertising industry’s shift toward combining browser and server-side signals rather than relying exclusively on tracking pixels.
The new documentation shows that server-side measurement is moving from an advanced implementation option toward a standard part of advertisers’ measurement stacks.

Microsoft shared documentation for its beta Conversions API, as a server-side option for sending data directly to the platform.

Microsoft Advertising publishes Conversions API documentation

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google has updated its Branded Searches documentation, with PMax notably no longer listed among supported campaign types.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-updates-Branded-Searches-conversion-measurement-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is giving advertisers clearer rules for measuring whether YouTube and Demand Gen ads prompt people to search for their brands — while making several notable changes from the metric&#8217;s original rollout.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Google has updated its documentation for Branded Searches, a conversion type that measures when someone searches for an advertiser&#8217;s brand on Google or YouTube after seeing an ad.</p>



<p class="wp-block-paragraph">The conversion type itself isn&#8217;t new. <a href="https://searchengineland.com/google-ads-branded-searches-conversion-metric-459382">Google introduced Branded Searches in 2025</a> as an always-on alternative to running Search Lift experiments.</p>



<p class="wp-block-paragraph">What&#8217;s changed is how Google now defines its availability, attribution and reporting.</p>



<p class="wp-block-paragraph"><strong>The details:</strong> Google&#8217;s updated guidance introduces or clarifies several important points:</p>



<ul class="wp-block-list">
<li><strong>7-day default window:</strong> Branded Searches now uses a seven-day default conversion window, compared with the 30-day view-through window described when the feature originally launched. Advertisers can adjust the window between one and 30 days.</li>



<li><strong>YouTube and Demand Gen:</strong> Google&#8217;s current documentation lists YouTube and Demand Gen as eligible campaign types. Performance Max, which was included when Branded Searches was announced in 2025, is no longer listed.</li>



<li><strong>Consideration goal:</strong> Google now formally categorizes Branded Searches under the Consideration goal.</li>



<li><strong>Reporting, not bidding:</strong> Branded Searches is treated as a primary conversion action but isn&#8217;t available as a bidding optimization goal. The data appears in Results and All Conversions rather than the standard Conversions column.</li>



<li><strong>Brand mapping still matters:</strong> Advertisers don&#8217;t need to set up a Search Lift experiment, but Google says brand mapping must be configured for measurement to work.</li>
</ul>



<p class="wp-block-paragraph">Google&#8217;s documentation says Branded Searches can be viewed at the campaign, ad group and asset levels, as well as through Report Editor.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Branded search behavior can provide advertisers with a useful signal between an ad impression and a traditional conversion.</p>



<p class="wp-block-paragraph">Someone may see a YouTube ad, remember the company and search for the brand days later without clicking the original ad. Branded Searches is designed to make that influence more visible inside Google Ads.</p>



<p class="wp-block-paragraph">That can help advertisers assess whether upper-funnel campaigns are generating genuine brand interest instead of evaluating them solely on clicks and direct conversions.</p>



<p class="wp-block-paragraph"><strong>The bottom line.</strong> This isn&#8217;t a new conversion type or a new seven-day attribution window. The noteworthy update is that Google&#8217;s current Branded Searches documentation lists YouTube and Demand Gen — but no longer Performance Max.</p>



<p class="wp-block-paragraph"><strong>First spotted.</strong> This update was spotted by Hana Kobzova, founder of <a href="https://ppcnewsfeed.com/ppc-news/2026-08/branded-searches-conversion-type-added-google-ads/">PPC News Feed</a>. </p>


Google is giving advertisers clearer rules for measuring whether YouTube and Demand Gen ads prompt people to search for their brands — while making several notable changes from the metric’s original rollout.
What’s happening. Google has updated its documentation for Branded Searches, a conversion type that measures when someone searches for an advertiser’s brand on Google or YouTube after seeing an ad.
The conversion type itself isn’t new. Google introduced Branded Searches in 2025 as an always-on alternative to running Search Lift experiments.
What’s changed is how Google now defines its availability, attribution and reporting.
The details: Google’s updated guidance introduces or clarifies several important points:
7-day default window: Branded Searches now uses a seven-day default conversion window, compared with the 30-day view-through window described when the feature originally launched. Advertisers can adjust the window between one and 30 days.
YouTube and Demand Gen: Google’s current documentation lists YouTube and Demand Gen as eligible campaign types. Performance Max, which was included when Branded Searches was announced in 2025, is no longer listed.
Consideration goal: Google now formally categorizes Branded Searches under the Consideration goal.
Reporting, not bidding: Branded Searches is treated as a primary conversion action but isn’t available as a bidding optimization goal. The data appears in Results and All Conversions rather than the standard Conversions column.
Brand mapping still matters: Advertisers don’t need to set up a Search Lift experiment, but Google says brand mapping must be configured for measurement to work.
Google’s documentation says Branded Searches can be viewed at the campaign, ad group and asset levels, as well as through Report Editor.
Why we care. Branded search behavior can provide advertisers with a useful signal between an ad impression and a traditional conversion.
Someone may see a YouTube ad, remember the company and search for the brand days later without clicking the original ad. Branded Searches is designed to make that influence more visible inside Google Ads.
That can help advertisers assess whether upper-funnel campaigns are generating genuine brand interest instead of evaluating them solely on clicks and direct conversions.
The bottom line. This isn’t a new conversion type or a new seven-day attribution window. The noteworthy update is that Google’s current Branded Searches documentation lists YouTube and Demand Gen — but no longer Performance Max.
First spotted. This update was spotted by Hana Kobzova, founder of PPC News Feed.

Google has updated its Branded Searches documentation, with PMax notably no longer listed among supported campaign types.

Google updates Branded Searches conversion measurement

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand.png" class="attachment-large size-large wp-post-image" alt="Google Search Console now connects social content to search demand" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>See how query data can reveal content gaps, guide creator partnerships, compare formats, and shape what you create next.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand.png" class="attachment-large size-large wp-post-image" alt="Google Search Console now connects social content to search demand" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Search-Console-now-connects-social-content-to-search-demand-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">For the entirety of Google Search Console’s life, it has spoken one simple language: your website. Pages, queries, clicks, impressions, all tied to a domain you own and verify.</p>



<p class="wp-block-paragraph">On July 7, that changed. Google <a href="https://searchengineland.com/google-search-console-gains-reporting-on-social-and-video-platforms-481696">shipped Platform properties</a>, a new property type that lets you verify a social or video account and get the same first-party search performance data GSC has always given website owners. Think clicks, impressions, CTR, average position, and the actual queries behind them — just pointed at your social presence instead.</p>



<p class="wp-block-paragraph">Worth noting up front: This covers Search, Discover, and News. So a TikTok clip or a YouTube Short can now be tracked across all three surfaces the same way you&#8217;d track a blog post.</p>



<p class="wp-block-paragraph">The mechanics of the launch — which platforms are supported, how verification works, and how this differs from Google&#8217;s separate Search profiles feature — are already well covered.</p>



<p class="wp-block-paragraph">However, one detail deserves repeating because it&#8217;s time-sensitive: there&#8217;s no historical backfill. Data collection starts the moment you verify. That means every week you spend deciding whether this is useful is a week of query data you can&#8217;t get back.</p>



<p class="wp-block-paragraph">Let’s take a look at what this means for brands and SEOs, some examples of what it looks like in practice, and what it means for marketing going forward.</p>



<h2 id="h-what-gsc-platform-properties-actually-changes-for-brands" class="wp-block-heading">What GSC Platform properties actually changes for brands</h2>



<p class="wp-block-paragraph">The obvious win is a single first-party lens that gives brands access to both owned and earned content, instead of having to stitch together GA4 and native platform dashboards with a hefty dollop of guesswork.</p>



<p class="wp-block-paragraph">But Google&#8217;s own guidance points at something more specific than better reporting. It points at a workflow. Three parts of it are worth knowing about:</p>



<ul class="wp-block-list">
<li><strong>Query groups:</strong> The Insights report clusters the search terms driving traffic into top, trending-up, and trending-down groups. That&#8217;s a real input for planning captions, hashtags and next topics. Ultimately, you&#8217;re working from demand that already exists rather than guessing at it.</li>



<li><strong>The 24-hour filter:</strong> If a post starts picking up search traffic within a day of going live, you can catch it while it&#8217;s still live and act by cross-promoting to another platform or timing a follow-up.</li>



<li><strong>Format comparisons:</strong> Using URL-based comparison filters, you can put Shorts against long-form, or Reels against static posts, and get an actual answer to “should we be putting more into short-form?”</li>
</ul>



<p class="wp-block-paragraph">These same three mechanics also change how you should work with creators. None of those three workflow parts are limited to owned content decisions, despite the signals coming from owned data. </p>


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<h2 id="h-how-gsc-platform-properties-can-reshape-creator-partnerships" class="wp-block-heading">How GSC Platform properties can reshape creator partnerships</h2>



<p class="wp-block-paragraph">Smart brands could already be considering running them through a creator program to answer the questions brands have historically had to take on faith.</p>



<p class="wp-block-paragraph">Query groups show you which conversations you already have traction in, but that also means, by omission, they tell you which conversations you don&#8217;t have a presence in. These insights become the foundations of an honest brief for creator activity. </p>



<p class="wp-block-paragraph">Rather than simply picking creators based on reach and hoping the relevance follows, you can point to specific query territory you&#8217;re absent from and brief against it — developing your presence within new conversations. Alternatively, you could double down within a conversation by partnering with creators who can champion your brand, further developing your presence and preference.</p>



<p class="wp-block-paragraph">This thinking reframes creator spend as buying coverage of conversations you don&#8217;t own yet or want to show up more within, rather than taking a risk on buying an audience you <em>hope</em> overlaps with yours.</p>



<p class="wp-block-paragraph">Format comparisons can also feed straight into the brief itself. For example, if your own data shows Shorts consistently earning search visibility while long-form doesn&#8217;t for your category, that&#8217;s a concrete production instruction for a creator rather than a stylistic preference.</p>



<p class="wp-block-paragraph">And the 24-hour filter gives campaign measurement a dimension it didn&#8217;t have before. During a live campaign, you can see whether <a href="https://searchengineland.com/creator-content-ai-search-strategy-483616">creator content</a> is earning genuine search visibility or just in-app impressions. This could provide a better read on whether the work is generating durable discovery or a spike that vanishes with feed changes.</p>



<p class="wp-block-paragraph">There&#8217;s a neat symmetry here, too. This data lets creators show that their content genuinely ranks for specific searches, rather than simply racking up views. Platform properties give both sides of the negotiation the same evidence base and metrics.</p>



<p class="wp-block-paragraph">Creator conversations that once centered on follower counts can now focus on which queries each party actually shows up for. That&#8217;s a far stronger basis for partnerships and can strengthen search marketing across the social-search landscape.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/creator-content-ai-search-strategy-483616">Why creator-led content marketing is the new standard in search</a></em></strong>



<h2 id="h-an-example-of-how-gsc-platform-properties-could-work-in-the-wild" class="wp-block-heading">An example of how GSC Platform properties could work in the wild</h2>



<p class="wp-block-paragraph">Picture a hypothetical running shoe brand called Tiger Feet. They connect their Instagram and YouTube properties to the GSC Platform properties, and a few weeks later, the <em>Performance</em> report shows something nobody expected: A Reel about lacing techniques for wide feet is pulling steady clicks from Google for variations of &#8220;how to lace running shoes wide feet,&#8221; while the website has no page targeting that query.</p>



<p class="wp-block-paragraph">That&#8217;s three decisions in one data point:</p>



<ul class="wp-block-list">
<li><strong>There&#8217;s proven demand:</strong> You&#8217;re seeing real-world results for a topic nobody on the Tiger Feet content team had previously flagged, and you know it&#8217;s real because people are searching it and landing on your content.</li>



<li><strong>You&#8217;re capturing it in the wrong format for conversion.</strong> A Reel earns the click but sells nothing. A product-linked guide on your site, with the video embedded, could.</li>



<li><strong>You now know what to write and roughly how to angle it.</strong> Because Platform properties give you the exact query language, rather than a keyword tool&#8217;s approximation of it, you have a road map to where to focus your content next.</li>
</ul>



<p class="wp-block-paragraph">Run the same logic in reverse, and it&#8217;s just as useful: If a social post is already ranking well for a query, that&#8217;s a case for <strong>not</strong> commissioning a page that could end up competing with it.&nbsp;</p>



<p class="wp-block-paragraph">That&#8217;s the shift. Social content stops being measured purely on engagement and starts being measured on demand, which is a completely different question and a much more commercially useful one.</p>



<h2 id="h-platform-properties-give-you-first-party-data-not-competitive-visibility" class="wp-block-heading">Platform properties give you first-party data, not competitive visibility</h2>



<p class="wp-block-paragraph">Platform properties only work on accounts you can verify, which means you get your own data and nothing else. No competitor view. No share of voice. No category benchmark.</p>



<p class="wp-block-paragraph">Every other discipline in search has some form of competitive visibility. You can see who&#8217;s outranking you organically, estimate what competitors are bidding on, audit their backlinks, and track their positions. </p>



<p class="wp-block-paragraph">Here, you get a perfectly clear view of your own performance and no visibility elsewhere — so this data should be combined with SERP analysis and manual research rather than relying on it in isolation.</p>



<p class="wp-block-paragraph">What are the practical consequences of this limitation? It means:</p>



<ul class="wp-block-list">
<li><strong>You can&#8217;t tell good from great.</strong> If an article pulls 400 clicks from Google in a month, is that strong for your category or embarrassing? There&#8217;s no external reference point, so you&#8217;re benchmarking against your own history and nothing more.</li>



<li><strong>You&#8217;ll spot demand, not competition:</strong> Query groups will tell you people are searching a topic and finding you. They won&#8217;t tell you that three competitors are already better positioned for it, or that the space is wide open. That still needs conventional keyword and SERP research alongside it.</li>



<li><strong>Absence of data isn&#8217;t absence of opportunity:</strong> A query showing nothing in your reports might mean no demand, or it might mean healthy demand that&#8217;s all going to someone else. The report can&#8217;t distinguish between the two, and it&#8217;s an easy mistake to make.</li>
</ul>



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<h2 id="h-what-platform-properties-change-for-seos" class="wp-block-heading">What Platform properties change for SEOs</h2>



<p class="wp-block-paragraph">The useful framing here isn&#8217;t that it’s a new report for SEOs to get lost within. The way to approach this development is as if it&#8217;s a new content inventory that behaves like your existing one.</p>



<p class="wp-block-paragraph">That’s because Platform properties speak the vocabulary SEOs already work in, which means social content can easily fold into existing workflows instead of sitting in a silo owned by another team — further affording brands the opportunity to break down silos at a time when discovery of brands relies on collaboration across organic media strategies.</p>



<p class="wp-block-paragraph">What can you do as an SEO with Platform properties? Turns out, a lot:</p>



<ul class="wp-block-list">
<li><strong>Gap and overlap analysis:</strong> You can check whether a query is already being answered by the brand&#8217;s own social content (or ask creator partners to share insights on their answers on your behalf) before commissioning a page for it. You can also spot cases where a page and an article are quietly competing and determine whether or not this is a good or bad thing.</li>



<li><strong>Test captions and titles like meta titles:</strong> You can annotate the date that you rewrote a TikTok caption or YouTube title and then compare performance on either side of it. Same discipline you&#8217;d apply to standard optimizations.</li>



<li><strong>Apply structural thinking off-site:</strong> Comparing things like playlist performance or formats within a platform allows you to think about grouping and cannibalization for content that doesn&#8217;t even live on your domain at all.</li>
</ul>



<p class="wp-block-paragraph">There are two caveats worth bringing up with clients before this lands in a report.&nbsp;</p>



<ul class="wp-block-list">
<li>Reporting carries the usual Search Console delays, so this isn&#8217;t a real-time dashboard despite the 24-hour view.&nbsp;</li>



<li>Coverage will vary by platform and content type while the rollout matures, so early numbers need to be treated as directional rather than definitive.</li>
</ul>



<p class="wp-block-paragraph">Social strategy has traditionally sat with the social team and been judged on engagement. Platform properties give SEOs a legitimate reason to be in that conversation. The content is now visible in the same tool, in the same terms they already report in and understand, and that they can develop effective strategies around.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/optimize-influencer-content-search-everywhere-472382">How to optimize influencer content for search everywhere</a></em></strong>



<h2 id="h-what-gsc-platform-properties-change-for-search-marketing-generally" class="wp-block-heading">What GSC Platform properties change for search marketing, generally</h2>



<p class="wp-block-paragraph">If you step back and look at this new rollout, it confirms something Google has been building toward for years: The results page stopped being a list of blue links a long time ago.</p>



<p class="wp-block-paragraph">Google&#8217;s own documentation shows exactly where this content appears — short-video carousels, &#8220;latest posts&#8221; carousels, and &#8220;what people are saying&#8221; SERP features — all within Search and Discover results.</p>



<p class="wp-block-paragraph">Platform properties are Google handing marketers an instrument for a part of the SERP that was already there and simply going unmeasured. This points to three things worth thinking about:</p>



<ul class="wp-block-list">
<li><strong>The search universe is expanding, and the SEO/social divide keeps dissolving:</strong> When both are measured in the same tool with the same metrics, it gets harder to defend treating them as separate disciplines with separate owners and separate budgets.</li>



<li><strong>Feed-based discovery is becoming as strategically important as query-based search:</strong> In terms of the role search plays in a brand&#8217;s discovery, that shift has been visible for a while, and this is the first proper measurement tool for it.</li>



<li><strong>Google is now building on the assumption that search behavior is cross-platform:</strong> Google isn&#8217;t just tolerating the fact that people search for things they saw on TikTok anymore. Instead, it&#8217;s actively shipping insights that acknowledge that it’s happening.</li>
</ul>


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<h2 id="h-what-you-can-do-this-week-to-take-advantage-of-platform-properties" class="wp-block-heading">What you can do this week to take advantage of Platform properties</h2>



<p class="wp-block-paragraph">You should connect every active social account now. Don&#8217;t wait for a question that needs answering. With no backfill, any account you haven&#8217;t connected to is a question you won&#8217;t be able to answer later. Take advantage.</p>



<p class="wp-block-paragraph">If you&#8217;re an SEO, rather than a social manager, get yourself into that reporting. Query groups and format comparisons are exactly the kind of data that should be shaping a content calendar. For most brands, that decision-making is happening without SEO as part of the conversation — the best brands will ensure that that changes.</p>



<p class="wp-block-paragraph">I’ll admit that this isn&#8217;t a dramatic feature, on the face of it, although I, for one, am extremely excited about the potential this affords &#8220;search everywhere&#8221; strategy considerations. The new platform properties are Google quietly conceding that &#8220;search performance&#8221; was never really about the website. It was always about wherever people go looking for answers.</p>

For the entirety of Google Search Console’s life, it has spoken one simple language: your website. Pages, queries, clicks, impressions, all tied to a domain you own and verify.
On July 7, that changed. Google shipped Platform properties, a new property type that lets you verify a social or video account and get the same first-party search performance data GSC has always given website owners. Think clicks, impressions, CTR, average position, and the actual queries behind them — just pointed at your social presence instead.
Worth noting up front: This covers Search, Discover, and News. So a TikTok clip or a YouTube Short can now be tracked across all three surfaces the same way you’d track a blog post.
The mechanics of the launch — which platforms are supported, how verification works, and how this differs from Google’s separate Search profiles feature — are already well covered.
However, one detail deserves repeating because it’s time-sensitive: there’s no historical backfill. Data collection starts the moment you verify. That means every week you spend deciding whether this is useful is a week of query data you can’t get back.
Let’s take a look at what this means for brands and SEOs, some examples of what it looks like in practice, and what it means for marketing going forward.
What GSC Platform properties actually changes for brands
The obvious win is a single first-party lens that gives brands access to both owned and earned content, instead of having to stitch together GA4 and native platform dashboards with a hefty dollop of guesswork.
But Google’s own guidance points at something more specific than better reporting. It points at a workflow. Three parts of it are worth knowing about:
Query groups: The Insights report clusters the search terms driving traffic into top, trending-up, and trending-down groups. That’s a real input for planning captions, hashtags and next topics. Ultimately, you’re working from demand that already exists rather than guessing at it.
The 24-hour filter: If a post starts picking up search traffic within a day of going live, you can catch it while it’s still live and act by cross-promoting to another platform or timing a follow-up.
Format comparisons: Using URL-based comparison filters, you can put Shorts against long-form, or Reels against static posts, and get an actual answer to “should we be putting more into short-form?”
These same three mechanics also change how you should work with creators. None of those three workflow parts are limited to owned content decisions, despite the signals coming from owned data. 
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How GSC Platform properties can reshape creator partnerships
Smart brands could already be considering running them through a creator program to answer the questions brands have historically had to take on faith.
Query groups show you which conversations you already have traction in, but that also means, by omission, they tell you which conversations you don’t have a presence in. These insights become the foundations of an honest brief for creator activity. 
Rather than simply picking creators based on reach and hoping the relevance follows, you can point to specific query territory you’re absent from and brief against it — developing your presence within new conversations. Alternatively, you could double down within a conversation by partnering with creators who can champion your brand, further developing your presence and preference.
This thinking reframes creator spend as buying coverage of conversations you don’t own yet or want to show up more within, rather than taking a risk on buying an audience you hope overlaps with yours.
Format comparisons can also feed straight into the brief itself. For example, if your own data shows Shorts consistently earning search visibility while long-form doesn’t for your category, that’s a concrete production instruction for a creator rather than a stylistic preference.
And the 24-hour filter gives campaign measurement a dimension it didn’t have before. During a live campaign, you can see whether creator content is earning genuine search visibility or just in-app impressions. This could provide a better read on whether the work is generating durable discovery or a spike that vanishes with feed changes.
There’s a neat symmetry here, too. This data lets creators show that their content genuinely ranks for specific searches, rather than simply racking up views. Platform properties give both sides of the negotiation the same evidence base and metrics.
Creator conversations that once centered on follower counts can now focus on which queries each party actually shows up for. That’s a far stronger basis for partnerships and can strengthen search marketing across the social-search landscape.
Dig deeper: Why creator-led content marketing is the new standard in search



An example of how GSC Platform properties could work in the wild
Picture a hypothetical running shoe brand called Tiger Feet. They connect their Instagram and YouTube properties to the GSC Platform properties, and a few weeks later, the Performance report shows something nobody expected: A Reel about lacing techniques for wide feet is pulling steady clicks from Google for variations of “how to lace running shoes wide feet,” while the website has no page targeting that query.
That’s three decisions in one data point:
There’s proven demand: You’re seeing real-world results for a topic nobody on the Tiger Feet content team had previously flagged, and you know it’s real because people are searching it and landing on your content.
You’re capturing it in the wrong format for conversion. A Reel earns the click but sells nothing. A product-linked guide on your site, with the video embedded, could.
You now know what to write and roughly how to angle it. Because Platform properties give you the exact query language, rather than a keyword tool’s approximation of it, you have a road map to where to focus your content next.
Run the same logic in reverse, and it’s just as useful: If a social post is already ranking well for a query, that’s a case for not commissioning a page that could end up competing with it. 
That’s the shift. Social content stops being measured purely on engagement and starts being measured on demand, which is a completely different question and a much more commercially useful one.
Platform properties give you first-party data, not competitive visibility
Platform properties only work on accounts you can verify, which means you get your own data and nothing else. No competitor view. No share of voice. No category benchmark.
Every other discipline in search has some form of competitive visibility. You can see who’s outranking you organically, estimate what competitors are bidding on, audit their backlinks, and track their positions. 
Here, you get a perfectly clear view of your own performance and no visibility elsewhere — so this data should be combined with SERP analysis and manual research rather than relying on it in isolation.
What are the practical consequences of this limitation? It means:
You can’t tell good from great. If an article pulls 400 clicks from Google in a month, is that strong for your category or embarrassing? There’s no external reference point, so you’re benchmarking against your own history and nothing more.
You’ll spot demand, not competition: Query groups will tell you people are searching a topic and finding you. They won’t tell you that three competitors are already better positioned for it, or that the space is wide open. That still needs conventional keyword and SERP research alongside it.
Absence of data isn’t absence of opportunity: A query showing nothing in your reports might mean no demand, or it might mean healthy demand that’s all going to someone else. The report can’t distinguish between the two, and it’s an easy mistake to make.
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What Platform properties change for SEOs
The useful framing here isn’t that it’s a new report for SEOs to get lost within. The way to approach this development is as if it’s a new content inventory that behaves like your existing one.
That’s because Platform properties speak the vocabulary SEOs already work in, which means social content can easily fold into existing workflows instead of sitting in a silo owned by another team — further affording brands the opportunity to break down silos at a time when discovery of brands relies on collaboration across organic media strategies.
What can you do as an SEO with Platform properties? Turns out, a lot:
Gap and overlap analysis: You can check whether a query is already being answered by the brand’s own social content (or ask creator partners to share insights on their answers on your behalf) before commissioning a page for it. You can also spot cases where a page and an article are quietly competing and determine whether or not this is a good or bad thing.
Test captions and titles like meta titles: You can annotate the date that you rewrote a TikTok caption or YouTube title and then compare performance on either side of it. Same discipline you’d apply to standard optimizations.
Apply structural thinking off-site: Comparing things like playlist performance or formats within a platform allows you to think about grouping and cannibalization for content that doesn’t even live on your domain at all.
There are two caveats worth bringing up with clients before this lands in a report. 
Reporting carries the usual Search Console delays, so this isn’t a real-time dashboard despite the 24-hour view. 
Coverage will vary by platform and content type while the rollout matures, so early numbers need to be treated as directional rather than definitive.
Social strategy has traditionally sat with the social team and been judged on engagement. Platform properties give SEOs a legitimate reason to be in that conversation. The content is now visible in the same tool, in the same terms they already report in and understand, and that they can develop effective strategies around.
Dig deeper: How to optimize influencer content for search everywhere



What GSC Platform properties change for search marketing, generally
If you step back and look at this new rollout, it confirms something Google has been building toward for years: The results page stopped being a list of blue links a long time ago.
Google’s own documentation shows exactly where this content appears — short-video carousels, “latest posts” carousels, and “what people are saying” SERP features — all within Search and Discover results.
Platform properties are Google handing marketers an instrument for a part of the SERP that was already there and simply going unmeasured. This points to three things worth thinking about:
The search universe is expanding, and the SEO/social divide keeps dissolving: When both are measured in the same tool with the same metrics, it gets harder to defend treating them as separate disciplines with separate owners and separate budgets.
Feed-based discovery is becoming as strategically important as query-based search: In terms of the role search plays in a brand’s discovery, that shift has been visible for a while, and this is the first proper measurement tool for it.
Google is now building on the assumption that search behavior is cross-platform: Google isn’t just tolerating the fact that people search for things they saw on TikTok anymore. Instead, it’s actively shipping insights that acknowledge that it’s happening.
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What you can do this week to take advantage of Platform properties
You should connect every active social account now. Don’t wait for a question that needs answering. With no backfill, any account you haven’t connected to is a question you won’t be able to answer later. Take advantage.
If you’re an SEO, rather than a social manager, get yourself into that reporting. Query groups and format comparisons are exactly the kind of data that should be shaping a content calendar. For most brands, that decision-making is happening without SEO as part of the conversation — the best brands will ensure that that changes.
I’ll admit that this isn’t a dramatic feature, on the face of it, although I, for one, am extremely excited about the potential this affords “search everywhere” strategy considerations. The new platform properties are Google quietly conceding that “search performance” was never really about the website. It was always about wherever people go looking for answers.

See how query data can reveal content gaps, guide creator partnerships, compare formats, and shape what you create next.

Google Search Console now connects social content to search demand

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Build-your-SEO-strategy-as-if-search-engines-didnt-exist.png" class="attachment-large size-large wp-post-image" alt="Build your SEO strategy as if search engines didn’t exist" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Build-your-SEO-strategy-as-if-search-engines-didnt-exist.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Build-your-SEO-strategy-as-if-search-engines-didnt-exist-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Build-your-SEO-strategy-as-if-search-engines-didnt-exist-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Build-your-SEO-strategy-as-if-search-engines-didnt-exist-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Search is only one part of discovery. Learn how distribution and brand visibility can create stronger signals across search and AI platforms.

How would you get your brand discovered without a search engine? How would you make sure potential buyers learn about your brand, products, and the problems you solve?
You’d have to find your audience where they already spend time. You’d need to get your best ideas in front of them, create entry points into relevant conversations, and build relationships with people and platforms they already trust.
That might sound like a marketing strategy rather than an SEO strategy. But it’s what SEO requires. Search has changed dramatically in the past two to three years, and AI is accelerating that shift. 
The signals that help your brand perform in search increasingly come from what happens beyond your website — the people who mention you, the publications that reference you, the communities that discuss you, and the platforms where your expertise appears.
Take search engines out of the equation
Imagine the unimaginable. Tomorrow, Google disappears. Then what? 
You’d still have a product. 
You’d still need to reach your target audience. 
You’d still want people to know about your studies, your experiments, your product improvements, your customer stories, and the problems you can and do solve.
It would all be the same, in a way, except you wouldn’t be able to post your content in SEO-smart ways and then sit back and wait for rankings to bring people in.
Instead, you’d have to go back to pre-Internet marketing ways and find your audience where they already spend time. You’d need to create entry points into conversations. You’d need to put your best ideas directly in front of people.
Seriously, how would you go about doing this? 
The lazy answer? Social media. But if we dig a bit deeper, we can discover SEO gold. 
Instead of asking, “How do we rank this page?” you start asking:
Where does our audience already pay attention?
Who already has their trust?
Which communities shape their thinking?
Which platforms influence their decisions?
Which conversations should we be part of?
What topics are they interested in?
Which stories, studies, or examples are worth distributing?
What questions are they asking?
Where do we need to have a presence before someone ever searches?
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Distribution is no longer optional
For years, many content creators treated distribution as an afterthought.
The process used to be:
Make content that is better than competing content.
Publish the article.
Get it indexed.
Build a few links to it.
Wait for it to rank.
Turn the free Google traffic into leads and buyers.
But that isn’t enough anymore.
That’s because AI Overviews are eating away at your clicks. AI Mode and other AI-driven search experiences are reducing the need for users to open a website and browse for information by providing it all wrapped up in a paragraph or two of summary. 
Recently, the user experience and the quality of the answers they provide have begun pushing past the problem of hallucinations that had made those platforms unusable before.
More and more users rely on AI Overviews, AI Mode, ChatGPT, or Claude for quick, reliable answers.
As a result, search volume on the good old top keywords you were betting on might be dropping to close to zero.
What’s left for us as SEOs to do is to figure out distribution in general and to make certain that we leverage solid SEO work that actually covers things like:
Indexability and crawlability.
Internal linking.
Semantics.
Taxonomy.
Content design and layout.
Consistency.
The problem I see us having with these ideas is that we aren’t always aware of our discipline being just one, often small, part of the distribution process. 
If you look at the search everywhere optimization pyramid framework, owned content’s SEO might actually be the last thing you want to focus on these days.
Dig deeper: Content alone isn’t enough: Why SEO now requires distribution



What should platforms know about you?
If you want to teach platforms like Google, Perplexity, or ChatGPT something about your brand, you want to be consistent with the information they find about you.
Does your website cover who you are and what you do properly?
Is all of that information part of your About page on your site?
Do you stress those same points in your social media activities and on your profiles?
Are trade show descriptions about your brand reflecting the same information?
Is it a theme you stick to even when being interviewed on podcasts or in public?
How about on review sites? Is that information coming up as a match there as well?
A proper distribution process will provide you with multiple touchpoints to present important information with the consistency that’s required for AI to understand who you are.
Only consistent information will — consistently — stick with search platforms and LLMs.
Given the inaccuracies in AI visibility tracking, personalization through user context, location, and previous activities, it’s close to making an educated guess and getting directional insights, like share of voice over time.
What you can impact, though, is the input: 
What information is available about your brand, and on which platforms? 
Are those the ones being cited? 
Are you on the podcasts your audience listens to? 
Is your company featured in the magazines read by your buyers? 
Is your brand popping up in newsletters your potential customers subscribe to and actually open?
What ranking pages now have in common
Look at the pages that perform well today. Many of them have things that generic SEO content can’t fake:
Proprietary data.
Original studies.
Internal experiments.
Customer stories.
Product insights.
Industry-specific findings.
Founder or expert opinions.
Examples from real work.
Check out Google’s content quality guidelines for a complete list of what they’re specifically looking for in top-notch content.
These assets are valuable because they aren’t interchangeable.
Anyone can write another “ultimate guide.” Not everyone can publish original data from their own customers, platform, process, or market experience.
But the asset itself is only half the story. The other half is distribution.
If you publish proprietary data and nobody sees it, references it, quotes it, discusses it, or builds on it, the impact stays limited.
But if you distribute it properly instead, it starts generating signals across the web. People mention it. Publications reference it. Communities discuss it. Videos summarize it. Newsletters link to it. AI systems may pick up the association.
That external footprint supports search.
Dig deeper: How to turn news articles into assets for AI search




	
	
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This is where search everywhere optimization comes in
This is where search everywhere optimization becomes useful for organizing the work.
The idea is simple: Your audience doesn’t discover, compare, and decide only on Google. They move across platforms, listen to podcasts, read newsletters, scroll LinkedIn, watch YouTube, search Reddit, ask AI tools, see ads, follow creators, and ask peers.
Your strategy needs to account for all of these discovery paths. The search everywhere optimization pyramid provides a framework for doing that. You start by understanding where your audience spends time, then build the layers that help your message travel.
At a high level, those layers are:
Audience research: Where does your audience actually spend time?
Monitoring and alerts: Which conversations should you know about?
Industry publications and third-party presence: Where can you borrow trust for your own site?
Distribution: How do your ideas reach people beyond your own site?
Own content: What assets do you create once the other layers are clear?
To this day, most companies start at layer five, cranking out content that nobody actually clicks. They create more content for their own site, then hope search engines reward it.
The more useful move is to build the first four layers first. Know your audience. Track their conversations online. Get into trusted third-party environments. Build distribution. Then create content that has a real chance to travel.
Use ads to accelerate distribution
Organic distribution can be your preferred channel. But don’t rule out ads as part of the distribution layer. Especially at the beginning, ads can be a shortcut.
Take Reddit as an example of how this works. Many subreddits are highly targeted. They contain exactly the audience you want to reach. But if your profile is new, or you don’t yet have enough trust in that community, participating organically can be difficult. 
It’ll be much faster to build your mailing list off the back of a properly targeted Reddit Ads campaign than to start warming up a fresh user while navigating the algorithmic and moderation challenges. Reddit Ads can still get you in front of that audience.
The same applies elsewhere. Google Ads through YouTube and display campaigns can help you reach the right audience at the right time. Performance Max can play a role, depending on the setup. Meta Ads can help you target by interests, demographics, and connections to certain brands or individuals.
The point isn’t that ads replace organic distribution. They don’t. And often, it might be wise to wait for organic signals to stick out before pushing something through ads.
But if you remove search engines from the marketing mix for a moment, ads become one of the tools you can use to reach the audience directly. And that presence can still support the bigger goal: getting your brand, message, and expertise in front of the right people in the right context.
Dig deeper: Why paid search could be your AI search advantage



Other people’s audiences matter
For newer brands, one of the quickest and most efficient entry points into a new market is leveraging other people’s audiences (OPA).
Take email, as an example. Many marketers think about email only in terms of their own list:
How do I grow my list?
How do I increase open rates?
How do I get more clicks from my next promotion?
Those questions do matter. But there’s another angle: other people’s audiences. Someone else almost certainly already has the audience you want to reach.
They may sell a related product. They may solve a different problem for the same customer profile. They may run a newsletter, private community, membership site, podcast, or content platform your audience already trusts.
That creates opportunities for collaboration. It can be as simple as reaching out and saying:
“Hey, I have this offer or resource. It could be useful for your audience. I can offer a kickback, create free training, or give you exposure to my network. Would you be open to including this in your next newsletter or exploring another way for us to get it in front of your audience?”
When I started my agency, one of the things that helped put my agency on the map was contributing SEO tutorial videos to private membership sites. They got free training content. 
And me? I got exposure to a warm audience. And because the introduction came through a trusted platform, some of that trust transferred to my personal brand. That’s distribution.
It also builds your brand. Today, it can support SEO by creating relevant mentions, associations, and authority beyond your own website.
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Your most sustainable SEO strategy
It’s easy to get trapped in a narrow view of SEO: keywords, rankings, pages, links, and technical fixes. Those things still matter, but they’re only part of how your brand gets discovered and understood.
If your entire SEO strategy depends on getting clicks from search results, it’s fragile. A stronger strategy helps your audience discover you across the places they already trust, while creating the signals search engines and AI systems use to understand your brand.
Your most sustainable strategy will always be to:
Find your audience.
Build the distribution layer.
Create assets worth talking about.
Get your ideas into the right conversations.
Then, let search engines and AI systems pick up the signals you’re creating everywhere else. That’s how search engine optimization becomes the more sustainable search everywhere optimization of the future.

Search is only one part of discovery. Learn how distribution and brand visibility can create stronger signals across search and AI platforms.

Build your SEO strategy as if search engines don’t exist

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Local-5.0-The-next-stage-of-AI-powered-local-search.png" class="attachment-large size-large wp-post-image" alt="Local 5.0- The next stage of AI-powered local search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Local-5.0-The-next-stage-of-AI-powered-local-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Local-5.0-The-next-stage-of-AI-powered-local-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Local-5.0-The-next-stage-of-AI-powered-local-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Local-5.0-The-next-stage-of-AI-powered-local-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The verification burden is moving from customers to AI. See what that means for location data, local context, and recommendations.

Local SEO has evolved through distinct stages, with each one building on what came before. The next stage, Local 5.0, is defined by AI’s ability to interpret intent, evaluate evidence, and connect context to determine which businesses it can understand, trust, and recommend.
For multi-location brands, that means connecting location data, local context, customer intent, and other signals to give AI the evidence it needs to evaluate each location. 
Success depends on making every location consistent, relevant, and trustworthy enough to earn recommendations — then measuring whether that visibility drives meaningful business outcomes.
The evolution of local search
Local marketing has evolved in distinct stages, with each evolution adding a requirement on top of the last rather than fully replacing it. Naming those stages makes it easier to see what’s actually new and what’s carried over from the last iteration. 
We call the current local marketing stage Local 5.0, and it’s the first stage where the deciding factor isn’t what a brand publishes about itself, but whether AI has enough connected context to understand, trust, and recommend each location.




Local search has compounded rather than cycled. Each stage still matters, and AI evaluates all of them at once. The old stalwarts of listings, reviews, and location pages remain the foundation. What’s changed in Local 5.0 is that the foundation alone no longer decides the outcome.
Where local marketing started
Let’s look at a quick roundup of the five stages we’ve seen so far for local marketing. At their most basic, these are the components that defined each evolution:
Local 1.0 – Listings and basic NAP consistency: The goal in the beginning stages of local marketing was presence — being indexed and included.
Local 2.0 – Map pack optimization and reviews: Visibility in local marketing during this stage was driven by proximity, profile completeness, and reputation.
Local 3.0 – Location pages, content, and ROI: Local marketing became a traffic and conversion driver tied to websites.
Local 4.0 – AI-mediated discovery and recommendation: Local marketing focused on decision infrastructure rather than a specific channel.
Local 5.0 – Context Intelligence: In this stage, which we’re presently in, AI interprets intent, evaluates evidence, and recommends. Visibility depends on connected, validated context across everything above, not on any single layer.
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So what makes Local 5.0 different?
Each earlier local stage rewarded completeness: be listed, be reviewed, be optimized. Local 5.0 rewards something different. AI doesn’t assume a location is a good fit. It looks for proof, and that proof has to exist somewhere it can read. Let’s look at the four ways we’re seeing this show up in Local 5.0.
AI works on evidence
Google’s AI-first direction, combined with the rapid adoption of ChatGPT, Gemini, Perplexity, and other AI assistants, marks the beginning of Local 5.0 — a stage where AI doesn’t simply index business information. 
AI determines which brands are discovered, understood, trusted, and ultimately recommended. AI relies on evidence, not assumptions, making strong entity authority and the elimination of any ambiguity essential for visibility.
Dig deeper: Why entity authority is the foundation of ai search visibility



Brand consistency with local relevance
For multi-location enterprises, this presents both a tremendous opportunity and a significant challenge. Traditional local SEO focused on websites, listings, and reviews to rank well in the SERPs. 
AI evaluates something much broader: whether a brand delivers complete, consistent, and locally relevant information across every digital touchpoint. Every location must be both brand-consistent and contextually relevant to its local audience.




Dig deeper: Winning the AI decision layer: From AI discovery to agentic commerce



Trusted: AI-ready foundation of location data
Most enterprises suffer from disconnected data. Customer information, listings, booking systems, CRM, reviews, operational systems, and local content often exist in silos, creating conflicting signals that reduce AI’s confidence in its ability to understand and recommend a business. 
A trusted, AI-ready foundation of location data is now a competitive advantage.
Rich context wins
Generic location pages are no longer sufficient. 
AI is expected to answer highly specific customer questions, such as whether a hotel is family-friendly, a clinic accepts a particular insurance plan, or whether a bank branch offers same-day appointments. 
Delivering these answers requires rich, location-specific context that’s continuously updated, accurate, and trusted.
That means evidence and verification are key to success in Local 5.0. A customer who once typed “banks near me” will often now instead say to an AI agent, “I just moved to Denver and I’m self-employed. Which bank near me has free small-business checking and is open on Saturdays?”
The old query might have returned a local pack and a page of links, ranked mostly on proximity and prominence, with nothing in the result tied to small-business checking or weekend hours. The customer had to click into each listing, go to the website, and confirm the details themselves.
However, the new query is likely to return three specific branches that meet those conditions, with distance and Saturday hours stated. Answering that kind of query requires all kinds of information, like account eligibility and fees, weekend hours, and proximity, to be pulled together and verified across sources. The verification step didn’t disappear. It instead moved from the customer to the machine, and the machine only verifies what it can find.
The new Local 5.0 also requires trusted sources for building a foundational AI layer. That’s because the sources AI trusts also vary by the question. 
First-party websites are the primary source for factual information, such as hours, services, policies, and availability, while reviews, directories, publishers, and third-party platforms carry greater weight for subjective questions like “best,” “most convenient,” or “recommended.” 
To maximize visibility, brands must build authority across both first- and third-party sources.
AI-driven local visibility follows a clear progression. Information must first be discoverable, then credible enough to serve as evidence, and, finally, authoritative enough to earn a recommendation. Simply being indexed or cited is no longer enough. AI will favor the business that provides the most complete, current, and relevant answer.
Dig deeper: How AI is reshaping local search and what enterprises must do now




	
	
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The Local 5.0 roadmap




Now that you know where you need to go, how do you do it? 
Let’s look at the five steps that will move you toward being successful at local marketing in Local 5.0.
Step 1: Build a trusted digital foundation
AI can only recommend businesses it understands and trusts. Start with a governed source of truth for every location by connecting your knowledge graph, structured data, website, Google Business Profile[s], maps, and directories. Consistent, machine-readable data that matches across every AI touchpoint eliminates entity ambiguity and establishes trust with AI systems.
Dig deeper: 7 focus areas as AI transforms search and the customer journey in 2026



Step 2: Add context that answers customer intent
Facts alone don’t earn recommendations. AI needs context to answer customer questions and compare businesses. You can help it do that by connecting location data with reviews, customer intent, local demand, operational updates, and competitive insights through a Context Memory Graph, enabling AI to deliver relevant, personalized recommendations.




Let’s look at two examples of how that’s done.
For location pages, the graph knows what each location actually offers, what customers in that market ask about, and which of those questions the page doesn’t yet answer. It drafts the missing section, say a parking and transit block for a downtown branch, an accepted-insurance list for a clinic, or a family-suitability detail for a hotel, then keeps it aligned with the listing data so the two never drift apart.
For social and Google Business Profile posts, the graph reads review themes, seasonal demand, and operational updates for that specific location, then drafts posts that answer what that market is asking right now rather than recycling a national message. In both cases, the human role shifts to approving and governing rather than writing from scratch.
Step 3: Deliver consistent, localized experiences
Every customer touchpoint should tell the same story while remaining locally relevant. To do this, you need to publish consistent information across websites, listings, maps, and social channels, while allowing each location to highlight unique services, promotions, and neighborhood insights — all within centralized brand governance.




Step 4: Continuously measure and optimize
AI visibility is a continuous process, not a one-time SEO project. To get this right, you need to track four signals:
Visibility: How often you appear in AI answers.
Share of voice: How often AI picks you over a competitor.
Accuracy: Whether what AI says about each location is correct.
Opportunity: What you would gain by fixing the biggest gaps first.
All four trace back to one root: the depth and accuracy of your entity data. Measuring tells you where you stand. Enriching entity data is how you move.




Dig deeper: From search to answer engines: How to optimize for the next era of discovery



Step 5: Scale with AI agents
The biggest challenge enterprise businesses have when trying to scale up to meet Local 5.0’s needs is broken, manual workflow. Managing thousands of locations manually isn’t sustainable. 
Utilizing AI agents to monitor listings, detect inconsistencies, recommend updates, optimize content, and identify reputation risks in real time can help with this scaling difficulty. The direction goes further: agents can act directly on the entity information AI reads from, enriching, correcting, and updating location records in place.
Human touch is still a vital part of this process. That’s because human teams focus on strategy and governance while AI strengthens the foundation at scale.
The connected local visibility flywheel
Winning local visibility is a continuous cycle of improvement. It helps to imagine it as a flywheel with five ever-cycling requirements you need to meet:





Measure: Track how AI engines discover, cite, and recommend each location, and identify visibility gaps and unanswered customer questions.
Create: Produce location-specific content using trusted business data, customer intent, reviews, and local insights to fill those gaps.
Publish: Utilize the same verified information consistently across your website, Google Business Profile, local listings, maps, and third-party platforms from a single source of truth across every bit of content you publish. And keep it fresh.
Discover: Make new and updated information easy for AI to find and verify. Schema and structured data establish meaning, IndexNow signals change immediately rather than waiting for a crawl, and ongoing technical health monitoring confirms pages stay accessible. The test for every update is whether it adds value AI can’t get elsewhere.
Optimize: Stay Local 5.0 compliant by measuring citations, recommendations, share of voice, and business outcomes, then feeding those insights back into the next round of improvements.
Across a portfolio of locations, this flywheel creates a powerful learning system. High-performing locations reveal patterns that can be adapted — not simply copied — to similar markets, allowing brands to continuously improve local visibility while accounting for differences in competition, customer behavior, and market dynamics.
more local customers.
      
Start winning locally
    
Shift from managing digital presence to managing context intelligence
Local 5.0 marks the shift from managing digital presence to managing context intelligence. 
Success is no longer measured by rankings or traffic alone. It’s measured by whether AI can discover, trust, and recommend your brand. That requires trusted data, rich local context, consistent brand experiences, strong reputation signals, and continuous optimization.
The brands that win at Local 5.0 are those that connect governed location data, AI-ready context, publishing, measurement, and intelligent automation into a continuous visibility flywheel. 
By combining brand consistency with local relevance and AI-powered workflows, enterprises can solve the biggest problem of consistency, relevancy, and trust at a hyperlocal level.

The verification burden is moving from customers to AI. See what that means for location data, local context, and recommendations.

Local 5.0: The next evolution of local SEO is here

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google is expanding PMax video optimization with generative AI that automatically creates missing aspect ratios from existing ads.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/PMax-video-ads-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google Ads is rolling out an asset optimization upgrade for existing Performance Max video ads.</p>



<p class="wp-block-paragraph">The update uses generative AI to extend videos into missing aspect ratios, allowing Google to create versions of an advertiser&#8217;s creative that can appear across more inventory.</p>



<p class="wp-block-paragraph"><strong>The details.</strong> The new capability builds on Google&#8217;s existing video enhancements, which can automatically convert horizontal videos into vertical and square formats.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="914" height="960" src="https://searchengineland.com/wp-content/seloads/2026/08/Asset-Optimization-Upgrade.jpeg" alt="" class="wp-image-485253" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Asset-Optimization-Upgrade.jpeg 914w, https://searchengineland.com/wp-content/seloads/2026/08/Asset-Optimization-Upgrade-768x807.jpeg 768w" sizes="(max-width: 914px) 100vw, 914px" /></figure>



<p class="wp-block-paragraph">The goal, according to Google, is to maximize video ad reach while improving the viewing experience.</p>



<p class="wp-block-paragraph">Advertisers who don&#8217;t want Google to apply the new generative AI optimization can contact their account management team or submit Google&#8217;s opt-out form by September 4th.</p>



<p class="wp-block-paragraph">Video settings can also be changed at any time from within a Google Ads account.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Performance Max advertisers are increasingly handing creative decisions to Google&#8217;s automation. Generating missing aspect ratios could help brands get more mileage from existing video assets without producing every format themselves, particularly for inventory that favors vertical or square creative.</p>



<p class="wp-block-paragraph"><strong>Yes, but</strong>. Automatically generated versions of brand creative won&#8217;t be appropriate for every advertiser. Extending or adapting a video with generative AI introduces another layer of automation that brands may want to review closely for visual consistency, product accuracy and brand guidelines.</p>



<p class="wp-block-paragraph">The opt-out deadline is therefore worth noting for advertisers that want tighter control over how their video assets are modified.</p>



<p class="wp-block-paragraph"><strong>The big picture</strong>. Google has steadily expanded Performance Max from automated media buying into automated creative production. This update pushes that further, with generative AI increasingly filling gaps in the assets advertisers provide rather than simply choosing how and where those assets run.</p>



<p class="wp-block-paragraph"><strong>First spotted. </strong>This update was shared by JXT Group founder Menachem Ani who shared the comms he received on <a href="https://x.com/MenachemAni/status/2089406204158099860">X</a>.</p>


Google Ads is rolling out an asset optimization upgrade for existing Performance Max video ads.
The update uses generative AI to extend videos into missing aspect ratios, allowing Google to create versions of an advertiser’s creative that can appear across more inventory.
The details. The new capability builds on Google’s existing video enhancements, which can automatically convert horizontal videos into vertical and square formats.




The goal, according to Google, is to maximize video ad reach while improving the viewing experience.
Advertisers who don’t want Google to apply the new generative AI optimization can contact their account management team or submit Google’s opt-out form by September 4th.
Video settings can also be changed at any time from within a Google Ads account.
Why we care. Performance Max advertisers are increasingly handing creative decisions to Google’s automation. Generating missing aspect ratios could help brands get more mileage from existing video assets without producing every format themselves, particularly for inventory that favors vertical or square creative.
Yes, but. Automatically generated versions of brand creative won’t be appropriate for every advertiser. Extending or adapting a video with generative AI introduces another layer of automation that brands may want to review closely for visual consistency, product accuracy and brand guidelines.
The opt-out deadline is therefore worth noting for advertisers that want tighter control over how their video assets are modified.
The big picture. Google has steadily expanded Performance Max from automated media buying into automated creative production. This update pushes that further, with generative AI increasingly filling gaps in the assets advertisers provide rather than simply choosing how and where those assets run.
First spotted. This update was shared by JXT Group founder Menachem Ani who shared the comms he received on X.

Google is expanding PMax video optimization with generative AI that automatically creates missing aspect ratios from existing ads.

Google Ads will use generative AI to resize Performance Max video ads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>ChatGPT draws a higher share of Google clicks than any other top destination, highlighting overlap between search and AI discovery.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/give-me-a-16-9-featured-image-that-doesnt-include-a-face-the-title-of-the-article-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">iPullRank analyzed 13.1 billion search events from 9.1 million opted-in users, covering October 2024 through December 2025, to understand how Google users behave when they search and where their clicks ultimately go.</p>



<p class="wp-block-paragraph">One of the standout findings for paid search marketers was ChatGPT&#8217;s unusually high share of paid traffic.</p>



<p class="wp-block-paragraph"><strong>By the numbers.</strong> ChatGPT was the sixth-most-clicked destination from Google Search in the dataset, trailing only YouTube, Google&#8217;s own properties, Reddit, Facebook and Wikipedia. Millions of searches for ChatGPT occurred each week within the panel.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="795" height="477" src="https://searchengineland.com/wp-content/seloads/2026/08/Sites-ppl-click-from-google.png" alt="" class="wp-image-485250" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Sites-ppl-click-from-google.png 795w, https://searchengineland.com/wp-content/seloads/2026/08/Sites-ppl-click-from-google-768x461.png 768w" sizes="(max-width: 795px) 100vw, 795px" /></figure>



<p class="wp-block-paragraph">More significantly for advertisers, iPullRank found ChatGPT drew a greater proportion of paid clicks than any of the other leading Google destinations it analyzed.</p>



<p class="wp-block-paragraph">That suggests OpenAI isn&#8217;t relying solely on organic visibility or direct traffic to attract users. Paid search is also playing a role in moving people from Google to ChatGPT.</p>



<p class="wp-block-paragraph"><strong>Why we care.</strong> This research suggests paid search is holding up even as Google sends fewer organic clicks, while ChatGPT itself is becoming a significant paid-search destination. It also shows that AI and Google Search aren’t necessarily separate customer journeys — users are moving between them, creating new opportunities for advertisers to think about how paid search fits into an increasingly AI-driven discovery landscape.</p>



<p class="wp-block-paragraph"><strong>The bigger picture.</strong> ChatGPT also appears relatively difficult for Google to replace with its own search features.</p>



<p class="wp-block-paragraph">Only 11.1% of searches that would otherwise lead toward OpenAI were intercepted by a zero-click Google experience, one of the lowest rates among the major destinations iPullRank studied.</p>



<p class="wp-block-paragraph">That is partly because many ChatGPT searches are navigational. Google can answer a factual question directly in Search, but it can&#8217;t fully satisfy someone whose intention is simply to open ChatGPT.</p>



<p class="wp-block-paragraph"><strong>Paid clicks are holding up.</strong> The research also contained another potentially important signal for Google Ads advertisers.</p>



<p class="wp-block-paragraph">Google&#8217;s overall zero-click rate rose about 2.6 percentage points during the 15-month study period, while the share of searches producing an organic click fell roughly 2.8 points.</p>



<p class="wp-block-paragraph">Paid clicks, however, showed no meaningful change during that period, according to iPullRank.</p>



<p class="wp-block-paragraph">That doesn&#8217;t mean paid search is immune to changing search behavior. But within this dataset, the growth of zero-click searches appears to have come primarily at the expense of organic clicks rather than ads.</p>



<p class="wp-block-paragraph"><strong>Brand bidding still matters.</strong> The study also found paid clicks were more common on branded searches.</p>



<p class="wp-block-paragraph">When branded searches resulted in a click, 4.4% were paid, compared with 3.3% for non-branded searches. iPullRank describes this as evidence of brands paying to defend their own names in search results.</p>



<p class="wp-block-paragraph">That context is particularly relevant to ChatGPT. People searching Google specifically for &#8220;ChatGPT&#8221; represent highly valuable navigational traffic, making prominent paid placement potentially useful even when the brand already has strong organic visibility.</p>



<p class="wp-block-paragraph">The research does not, however, reveal which queries OpenAI bids on or how much it spends, so it can&#8217;t establish how much of ChatGPT&#8217;s paid traffic comes specifically from defensive brand bidding.</p>



<p class="wp-block-paragraph"><strong>Search is still a discovery engine.</strong> Another notable finding is that only about 14% of Google clicks went to a website explicitly named in the user&#8217;s query. The remaining 86% were classified as discovery clicks, where Google sent users to destinations they hadn&#8217;t specifically requested.</p>



<p class="wp-block-paragraph">For advertisers, that&#8217;s important because it suggests Google&#8217;s value isn&#8217;t limited to capturing existing brand demand.</p>



<p class="wp-block-paragraph">A large majority of clicks remain potentially contestable territory where ads, rankings and other search experiences can introduce users to a destination.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> ChatGPT’s position as both a Google competitor and a significant recipient of paid Google traffic shows how intertwined traditional search and AI discovery are becoming. For paid search marketers, that suggests the emerging AI journey isn&#8217;t simply Google versus ChatGPT. Increasingly, it could be Google to ChatGPT — with an ad helping users get there.</p>



<p class="wp-block-paragraph"><strong>Dig deeper. </strong><a href="https://ipullrank.com/zero-click-behavior-analysis-q3-2026">What 13 Billion Google Searches Reveal About Zero-Click Behavior</a>


iPullRank analyzed 13.1 billion search events from 9.1 million opted-in users, covering October 2024 through December 2025, to understand how Google users behave when they search and where their clicks ultimately go.
One of the standout findings for paid search marketers was ChatGPT’s unusually high share of paid traffic.
By the numbers. ChatGPT was the sixth-most-clicked destination from Google Search in the dataset, trailing only YouTube, Google’s own properties, Reddit, Facebook and Wikipedia. Millions of searches for ChatGPT occurred each week within the panel.




More significantly for advertisers, iPullRank found ChatGPT drew a greater proportion of paid clicks than any of the other leading Google destinations it analyzed.
That suggests OpenAI isn’t relying solely on organic visibility or direct traffic to attract users. Paid search is also playing a role in moving people from Google to ChatGPT.
Why we care. This research suggests paid search is holding up even as Google sends fewer organic clicks, while ChatGPT itself is becoming a significant paid-search destination. It also shows that AI and Google Search aren’t necessarily separate customer journeys — users are moving between them, creating new opportunities for advertisers to think about how paid search fits into an increasingly AI-driven discovery landscape.
The bigger picture. ChatGPT also appears relatively difficult for Google to replace with its own search features.
Only 11.1% of searches that would otherwise lead toward OpenAI were intercepted by a zero-click Google experience, one of the lowest rates among the major destinations iPullRank studied.
That is partly because many ChatGPT searches are navigational. Google can answer a factual question directly in Search, but it can’t fully satisfy someone whose intention is simply to open ChatGPT.
Paid clicks are holding up. The research also contained another potentially important signal for Google Ads advertisers.
Google’s overall zero-click rate rose about 2.6 percentage points during the 15-month study period, while the share of searches producing an organic click fell roughly 2.8 points.
Paid clicks, however, showed no meaningful change during that period, according to iPullRank.
That doesn’t mean paid search is immune to changing search behavior. But within this dataset, the growth of zero-click searches appears to have come primarily at the expense of organic clicks rather than ads.
Brand bidding still matters. The study also found paid clicks were more common on branded searches.
When branded searches resulted in a click, 4.4% were paid, compared with 3.3% for non-branded searches. iPullRank describes this as evidence of brands paying to defend their own names in search results.
That context is particularly relevant to ChatGPT. People searching Google specifically for “ChatGPT” represent highly valuable navigational traffic, making prominent paid placement potentially useful even when the brand already has strong organic visibility.
The research does not, however, reveal which queries OpenAI bids on or how much it spends, so it can’t establish how much of ChatGPT’s paid traffic comes specifically from defensive brand bidding.
Search is still a discovery engine. Another notable finding is that only about 14% of Google clicks went to a website explicitly named in the user’s query. The remaining 86% were classified as discovery clicks, where Google sent users to destinations they hadn’t specifically requested.
For advertisers, that’s important because it suggests Google’s value isn’t limited to capturing existing brand demand.
A large majority of clicks remain potentially contestable territory where ads, rankings and other search experiences can introduce users to a destination.
Bottom line. ChatGPT’s position as both a Google competitor and a significant recipient of paid Google traffic shows how intertwined traditional search and AI discovery are becoming. For paid search marketers, that suggests the emerging AI journey isn’t simply Google versus ChatGPT. Increasingly, it could be Google to ChatGPT — with an ad helping users get there.
Dig deeper. What 13 Billion Google Searches Reveal About Zero-Click Behavior

ChatGPT draws a higher share of Google clicks than any other top destination, highlighting overlap between search and AI discovery.

ChatGPT draws more paid clicks from Google than any other top destination

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google has confirmed the issue starting on August 13, and the result is a decrease in impressions.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Google has confirmed the <a href="https://www.seroundtable.com/google-search-console-performance-reports-drop-41884.html">reports of a bug</a> in the Search Console performance reports, specifically with the Generative AI in Search performance report.  There is a data logging issue that has caused a decrease in impressions shown in the report.  This is just a reporting issue, not a true issue in Google Search.</p>



<p class="wp-block-paragraph"><strong>What was the issue. </strong>If you look at your Generative AI report for Search in Google Search Console&#8217;s performance report, you may see a deep dive in impressions reported starting on August 13th.</p>



<p class="wp-block-paragraph">Here is a screenshot of one example:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="956" src="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-performance-reports-drop-Aqmaq2gf-scaled.png" alt="" class="wp-image-485217" srcset="https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-performance-reports-drop-Aqmaq2gf-scaled.png 2048w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-performance-reports-drop-Aqmaq2gf-768x358.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/google-search-console-performance-reports-drop-Aqmaq2gf-1536x717.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p class="wp-block-paragraph"><strong>What Google said. </strong>Google wrote on its <a href="https://support.google.com/webmasters/answer/6211453?hl=en#zippy=%2Cperformance-reports-search-results-discover-google-news">data anomalies</a> page:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">August 13 (Generative AI in Search)</p>



<p class="wp-block-paragraph">A logging error caused a decrease in impressions on the Generative AI performance report in Search for data starting on August 13, 2026. This issue affects data logging only and is ongoing.</p>
</blockquote>



<p class="wp-block-paragraph">John Mueller from Google added on Bluesky <a href="https://bsky.app/profile/johnmu.com/post/3mtchhfyizs25">saying</a>:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">We&#8217;re aware of this issue and working on resolving it. This is just a logging issue and not representative of visibility changes in Search. We&#8217;re adding an annotation in Search Console to let folks know about this in the near future.</p>
</blockquote>



<p class="wp-block-paragraph"><strong>Why we care. </strong>If you noticed the dip in impressions on this report, you are not alone. This is widespread; Google confirmed the issue and is working on fixing it going forward.</p>


Google has confirmed the reports of a bug in the Search Console performance reports, specifically with the Generative AI in Search performance report.  There is a data logging issue that has caused a decrease in impressions shown in the report.  This is just a reporting issue, not a true issue in Google Search.
What was the issue. If you look at your Generative AI report for Search in Google Search Console’s performance report, you may see a deep dive in impressions reported starting on August 13th.
Here is a screenshot of one example:




What Google said. Google wrote on its data anomalies page:
August 13 (Generative AI in Search)
A logging error caused a decrease in impressions on the Generative AI performance report in Search for data starting on August 13, 2026. This issue affects data logging only and is ongoing.
John Mueller from Google added on Bluesky saying:
We’re aware of this issue and working on resolving it. This is just a logging issue and not representative of visibility changes in Search. We’re adding an annotation in Search Console to let folks know about this in the near future.
Why we care. If you noticed the dip in impressions on this report, you are not alone. This is widespread; Google confirmed the issue and is working on fixing it going forward.

Google has confirmed the issue starting on August 13, and the result is a decrease in impressions.

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