<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit.png" class="attachment-large size-large wp-post-image" alt="How to run a local GEO baseline audit" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Find out whether AI recommends your business, gets your information right, or favors competitors before investing more in local SEO.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit.png" class="attachment-large size-large wp-post-image" alt="How to run a local GEO baseline audit" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Run-a-local-GEO-baseline-audit-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Ask 10 local business owners how they&#8217;re doing in AI search, and nine will point to their <a href="https://searchengineland.com/guide/google-business-profile">Google Business Profile</a>. That&#8217;s the wrong place to look.</p>



<p><a href="https://searchengineland.com/what-is-chatgpt-and-why-seos-should-care-392165">ChatGPT</a> recommended <a href="https://searchengineland.com/ai-local-visibility-report-2026-468085">only 1.2% of the nearly 350,000 business locations</a> analyzed in SOCi&#8217;s 2026 Local Visibility Index. Compare that to the 35.9% appearance rate those same brands get in Google&#8217;s local 3-pack, a gap of roughly 30-fold. Gemini recommended 11% of locations. Perplexity, 7.4%. </p>



<p>Business profile information across the web was only about 68% accurate on ChatGPT and Perplexity, compared with 100% on Gemini, which relies entirely on Google Maps data.</p>



<p>A business can dominate the map pack and still disappear the moment someone asks ChatGPT for a recommendation. Most local businesses have never actually looked at what AI says about them, so they&#8217;re investing in content and citations without knowing whether any of it shows up where it now counts.</p>



<p>A local <a href="https://searchengineland.com/what-is-generative-engine-optimization-geo-444418">GEO</a> baseline audit fixes that. It gives you a repeatable way to benchmark how AI describes, recommends, or ignores a business before you spend a dollar trying to improve it. Here&#8217;s how to run one.</p>



<h2 class="wp-block-heading" id="h-why-the-baseline-comes-first">Why the baseline comes first</h2>



<p>Think of it like stepping on a scale before starting a diet. If you don&#8217;t know your starting number, you&#8217;ll never know whether what you&#8217;re doing is working. A baseline gives you numbers you can track over time: share of voice, citation rate, and accuracy.</p>



<p>It also answers a bigger question: Can AI even crawl, understand, and trust this site? The answer changes everything you do next. That&#8217;s why you need to uncover eligibility problems before thinking about content strategy.</p>



<p>AI also weighs signals differently than traditional local search. Traditional local search leans heavily on proximity. Whoever&#8217;s closest tends to win. AI doesn&#8217;t play that game. It prioritizes data confidence, authority, and consistency across the web.&nbsp;</p>



<p>Third-party validation and accurate, consistent business information matter more than how far away the searcher is. AI often relies on the same business data as traditional local search, just weighted differently. That&#8217;s why map-pack rankings tell you almost nothing about AI visibility.</p>


<a href="https://www.semrush.com/gbp-optimization/start/?utm_campaign=ic_sel_0101local&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>
    
    <div>
      
      <div id="semrush-one-headline" class="headline-responsive">
        Turn Google searches into <span>more calls, visits, and sales</span>.
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        Everything you need to manage your GBP, dominate Google Maps, and attract more customers.
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      <span id="semrush-one-cta">Connect your business</span>
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<h2 class="wp-block-heading" id="h-step-1-assemble-your-audit-inputs">Step 1: Assemble your audit inputs</h2>



<p>Before running a single prompt, get organized. Open a spreadsheet and cover four query categories because each one exposes a different kind of weakness:</p>



<ul class="wp-block-list">
<li><strong>Discovery:</strong> &#8220;best [service] near me&#8221; or &#8220;top [service] in [city]&#8221;</li>



<li><strong>Comparison:</strong> &#8220;[Brand] vs. [Competitor] in [city]&#8221;</li>



<li><strong>Trust:</strong> &#8220;[Brand] reviews&#8221; or &#8220;is [Brand] reliable?&#8221;</li>



<li><strong>Logistics:</strong> hours, address, parking, and phone number</li>
</ul>



<p>Run each query across the AI platforms your customers actually use: ChatGPT, Perplexity, Gemini, and Google <a href="https://searchengineland.com/guide/google-ai-overviews">AI Overviews</a>. Each platform pulls from different sources and phrases answers differently, so appearing on one doesn&#8217;t guarantee you&#8217;ll appear on another.</p>



<p>A few variables can quietly wreck your data if you don&#8217;t control for them. AI answers change based on who&#8217;s asking, so test from a defined location and note the exact city or ZIP code.&nbsp;</p>



<p>Run a clean, logged-out session alongside a logged-in one to reduce personalization noise. Date-stamp every run. These models update constantly, and a screenshot from last month doesn&#8217;t tell you much without a date attached.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/localized-ai-search-optimization-playbook-478499">The new playbook for localized AI search optimization</a></em></strong>



<h2 class="wp-block-heading" id="h-step-2-run-the-prompts-and-record-the-results">Step 2: Run the prompts and record the results</h2>



<p>For every prompt on every platform, capture five things:</p>



<ul class="wp-block-list">
<li><strong>Mention:</strong> Did AI mention the business by name?</li>



<li><strong>Mention order:</strong> First, middle, last, or missing?</li>



<li><strong>Sentiment and framing:</strong> Positive, neutral, or negative?</li>



<li><strong>Factual accuracy:</strong> Are the hours, services, and prices correct?</li>



<li><strong>Cited sources:</strong> Which URLs and directories did the answer rely on?</li>
</ul>



<p>Those five data points will tell you more than most agencies ever measure for a client.</p>



<ul class="wp-block-list">
<li>Set up your spreadsheet with columns for:
<ul class="wp-block-list">
<li>Prompt.</li>



<li>Platform.</li>



<li>Mention.</li>



<li>Position.</li>



<li>Accuracy score.</li>



<li>Sentiment.</li>



<li>Citation count.</li>



<li>Top sources. </li>
</ul>
</li>



<li>Then calculate two summary metrics:
<ul class="wp-block-list">
<li>Visibility percentage (how often the business appears).</li>



<li>Accuracy percentage (how often the facts are correct).</li>
</ul>
</li>
</ul>



<p>If you&#8217;d rather not build this from scratch, <a href="https://docs.google.com/spreadsheets/d/1pz1oTKldsnNb2nlz57GvLEOmLmxTseFSUKnDE4lkYes/copy" target="_blank" rel="noopener">here&#8217;s a free template</a> that includes the response log, competitor tracker, scorecard, and gap tracker. The link opens your own editable copy.</p>



<p>While you&#8217;re at it, log competitors, too. Note who else appeared in each answer, where they ranked, and which sources supported them. That tells you who&#8217;s winning the category in AI&#8217;s eyes, and often why.</p>



<h2 class="wp-block-heading" id="h-step-3-diagnose-the-gaps">Step 3: Diagnose the gaps</h2>



<p>Every gap you find falls into one of three buckets:</p>



<ul class="wp-block-list">
<li><strong>Invisible:</strong> The business simply doesn&#8217;t appear for a relevant query. This is the most common failure mode for local businesses just starting to evaluate AI visibility. It usually traces back to blocked crawlers, a lack of citable content, or few third-party mentions.</li>



<li><strong>Inaccurate:</strong> The business appears, but the details are wrong. An old address. Hours that don&#8217;t match reality. A service discontinued two years ago. This isn&#8217;t just annoying. AI treats inconsistency as a trust signal, so businesses with unreliable information are more likely to be hedged or omitted from answers. This usually traces back to outdated on-site information or inconsistent NAP (name, address, phone) data across directories.</li>



<li><strong>Misframed:</strong> The business gets mentioned, but it&#8217;s buried beneath competitors or described as the weaker option. This usually stems from a thin review profile or weaker authority signals than the competitors winning that query.</li>
</ul>



<p>Once you know which bucket a gap falls into, you can prioritize the right fix.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-build-faqs-that-power-ai-driven-local-search-472773">How to build FAQs that power AI-driven local search</a></em></strong>



<div class="nl-inline-form border py-2 px-1 my-2">
	
	<div class="row align-items-center nl-inline-container">
		<div class="col-12 col-lg-3 col-xl-4 pe-md-0 pb-2 pb-lg-0">
			<p class="inline-form-text text-center mb-0">Get the newsletter search marketers rely on.</p>
		</div>
		<div class="col-12 col-lg-7 col-xl-6  pe-lg-0">
			<div class="form-nl-inline">
				<form id="mktoForm_16298"></form> 
				
				
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			<p class="text-center mb-0"><a class="nl-terms" href="https://searchengineland.com/termsofuse" target="_blank" aria-label="opens in a new tab">See terms.</a>
		</div>
	</div>
</div>




<hr class="wp-block-separator has-text-color has-cyan-bluish-gray-color has-css-opacity has-cyan-bluish-gray-background-color has-background"/>



<h2 class="wp-block-heading" id="h-step-4-fix-in-the-right-order">Step 4: Fix in the right order</h2>



<p>Sequence matters more than people expect. Skip ahead, and you&#8217;ll waste the work.</p>



<h3 class="wp-block-heading" id="h-eligibility-first">Eligibility first</h3>



<ul class="wp-block-list">
<li>Can AI crawlers even reach the site? Check robots.txt and any Cloudflare settings that might be blocking bots by default. Cloudflare <a href="https://blog.cloudflare.com/content-independence-day-no-ai-crawl-without-compensation/">announced</a> it would block AI crawlers by default for sites on its network, and plenty of site owners never noticed the setting had changed. </li>



<li>Clean up NAP consistency so the business name, address, and phone number match everywhere online. </li>



<li>Add and validate structured data, including LocalBusiness, Organization, FAQ, and Service schema markup. </li>
</ul>



<p><strong><em>Dig deeper: </em></strong><a href="https://searchengineland.com/a-90-day-seo-playbook-for-ai-driven-search-visibility-466751"><strong><em>A 90-day SEO playbook for AI-driven search visibility</em></strong>&nbsp;</a>



<h3 class="wp-block-heading" id="h-trust-signals-second">Trust signals second</h3>



<ul class="wp-block-list">
<li>Build a stronger review profile and healthier average ratings across Google Business Profile, Yelp, and industry-specific sites. </li>



<li>Respond to reviews and questions. AI notices engagement, not just star ratings. </li>



<li>Aim for cross-platform consistency, with the same story reflected across your website, directories, social profiles, and press coverage. Consistency signals credibility.</li>
</ul>



<h3 class="wp-block-heading" id="h-relevance-last">Relevance last</h3>



<p>Only now does content work make sense.&nbsp;</p>



<ul class="wp-block-list">
<li>Build genuine location-specific depth with city pages that include real local detail, service pages with actual examples, and clear logistics information. </li>



<li>Skip cookie-cutter pages that simply swap in a different city name.</li>
</ul>



<p>The logic behind the order is simple. If crawlers are blocked or your NAP data is inconsistent, AI may never see the new content. Optimizing relevance before eligibility is like repainting a house nobody can find.</p>



<h2 class="wp-block-heading" id="h-step-5-make-the-audit-repeatable">Step 5: Make the audit repeatable</h2>



<p>One audit is a snapshot. Real progress comes from repeating it on a schedule because AI models update constantly, and what&#8217;s true today might not hold next quarter.</p>



<p>Quarterly is a reasonable cadence for most local businesses. That&#8217;s often enough to catch model updates and measure whether your fixes worked without turning the process into a full-time job.&nbsp;</p>



<p>Don&#8217;t obsess over clicks as the primary success metric. That habit carries over from traditional SEO, but it doesn&#8217;t map cleanly to how AI answers work.&nbsp;</p>



<p>Watch for branded search lift, more phone calls, and more direction requests from local profiles instead. Those signals show whether AI recommendations are driving real business, even when there&#8217;s no click to attribute.&nbsp;</p>



<p>Within the audit itself, track mention rate, positioning, factual error rate, and citation count over time. If mention rate climbs but positioning remains buried beneath competitors, that&#8217;s a trust problem, not an eligibility problem, and it should shape your priorities for the next quarter.</p>



<p>Compare each audit with the last one. If AI suddenly prefers different sources or phrases answers differently, that&#8217;s model drift worth understanding, not a one-off glitch to ignore.&nbsp;</p>



<p>Keep tracking competitor share of voice, too. If a rival is climbing steadily across the same prompts, it&#8217;s worth investigating before they pull away. Sometimes it&#8217;s a genuine authority gap. Sometimes, they simply started responding to reviews while everyone else stood still.</p>



<p><strong><em>Dig deeper: </em></strong><a href="https://searchengineland.com/local-seo-sprints-a-90-day-plan-for-service-businesses-in-2026-469059"><strong><em>Local SEO sprints: A 90-day plan for service businesses in 2026</em></strong></a>


<a href="https://www.semrush.com/gbp-optimization/start/?utm_campaign=ic_sel_0102local&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
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      <div id="semrush-one-headline" class="headline-responsive">
        Get found by <span>more local customers</span>.
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      <p id="semrush-one-subhead">
        Boost your visibility, earn more reviews, climb higher on Maps, and stay ahead of local competitors.
      </p>
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    <div>
      <span id="semrush-one-cta">Start winning locally</span>
    </div>
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    </a>




<h2 class="wp-block-heading" id="h-start-here-not-with-content">Start here, not with content</h2>



<p>A local GEO baseline audit isn&#8217;t complicated. Benchmark where things stand, fix eligibility and trust issues before touching content, structure your information so AI has a reason to cite the business, and repeat the audit on a regular schedule.</p>



<p>The alternative is guessing. In local search, guesswork shows up as calls that never came in and customers who chose a competitor without anyone knowing why. If nobody&#8217;s actually looked at what AI says about a business lately, that&#8217;s the place to start.</p>

Ask 10 local business owners how they’re doing in AI search, and nine will point to their Google Business Profile. That’s the wrong place to look.
ChatGPT recommended only 1.2% of the nearly 350,000 business locations analyzed in SOCi’s 2026 Local Visibility Index. Compare that to the 35.9% appearance rate those same brands get in Google’s local 3-pack, a gap of roughly 30-fold. Gemini recommended 11% of locations. Perplexity, 7.4%. 
Business profile information across the web was only about 68% accurate on ChatGPT and Perplexity, compared with 100% on Gemini, which relies entirely on Google Maps data.
A business can dominate the map pack and still disappear the moment someone asks ChatGPT for a recommendation. Most local businesses have never actually looked at what AI says about them, so they’re investing in content and citations without knowing whether any of it shows up where it now counts.
A local GEO baseline audit fixes that. It gives you a repeatable way to benchmark how AI describes, recommends, or ignores a business before you spend a dollar trying to improve it. Here’s how to run one.
Why the baseline comes first
Think of it like stepping on a scale before starting a diet. If you don’t know your starting number, you’ll never know whether what you’re doing is working. A baseline gives you numbers you can track over time: share of voice, citation rate, and accuracy.
It also answers a bigger question: Can AI even crawl, understand, and trust this site? The answer changes everything you do next. That’s why you need to uncover eligibility problems before thinking about content strategy.
AI also weighs signals differently than traditional local search. Traditional local search leans heavily on proximity. Whoever’s closest tends to win. AI doesn’t play that game. It prioritizes data confidence, authority, and consistency across the web. 
Third-party validation and accurate, consistent business information matter more than how far away the searcher is. AI often relies on the same business data as traditional local search, just weighted differently. That’s why map-pack rankings tell you almost nothing about AI visibility.
more calls, visits, and sales.
      
Connect your business
    
Step 1: Assemble your audit inputs
Before running a single prompt, get organized. Open a spreadsheet and cover four query categories because each one exposes a different kind of weakness:
Discovery: “best [service] near me” or “top [service] in [city]”
Comparison: “[Brand] vs. [Competitor] in [city]”
Trust: “[Brand] reviews” or “is [Brand] reliable?”
Logistics: hours, address, parking, and phone number
Run each query across the AI platforms your customers actually use: ChatGPT, Perplexity, Gemini, and Google AI Overviews. Each platform pulls from different sources and phrases answers differently, so appearing on one doesn’t guarantee you’ll appear on another.
A few variables can quietly wreck your data if you don’t control for them. AI answers change based on who’s asking, so test from a defined location and note the exact city or ZIP code. 
Run a clean, logged-out session alongside a logged-in one to reduce personalization noise. Date-stamp every run. These models update constantly, and a screenshot from last month doesn’t tell you much without a date attached.
Dig deeper: The new playbook for localized AI search optimization



Step 2: Run the prompts and record the results
For every prompt on every platform, capture five things:
Mention: Did AI mention the business by name?
Mention order: First, middle, last, or missing?
Sentiment and framing: Positive, neutral, or negative?
Factual accuracy: Are the hours, services, and prices correct?
Cited sources: Which URLs and directories did the answer rely on?
Those five data points will tell you more than most agencies ever measure for a client.
Set up your spreadsheet with columns for:

Prompt.
Platform.
Mention.
Position.
Accuracy score.
Sentiment.
Citation count.
Top sources. 
Then calculate two summary metrics:

Visibility percentage (how often the business appears).
Accuracy percentage (how often the facts are correct).
If you’d rather not build this from scratch, here’s a free template that includes the response log, competitor tracker, scorecard, and gap tracker. The link opens your own editable copy.
While you’re at it, log competitors, too. Note who else appeared in each answer, where they ranked, and which sources supported them. That tells you who’s winning the category in AI’s eyes, and often why.
Step 3: Diagnose the gaps
Every gap you find falls into one of three buckets:
Invisible: The business simply doesn’t appear for a relevant query. This is the most common failure mode for local businesses just starting to evaluate AI visibility. It usually traces back to blocked crawlers, a lack of citable content, or few third-party mentions.
Inaccurate: The business appears, but the details are wrong. An old address. Hours that don’t match reality. A service discontinued two years ago. This isn’t just annoying. AI treats inconsistency as a trust signal, so businesses with unreliable information are more likely to be hedged or omitted from answers. This usually traces back to outdated on-site information or inconsistent NAP (name, address, phone) data across directories.
Misframed: The business gets mentioned, but it’s buried beneath competitors or described as the weaker option. This usually stems from a thin review profile or weaker authority signals than the competitors winning that query.
Once you know which bucket a gap falls into, you can prioritize the right fix.
Dig deeper: How to build FAQs that power AI-driven local search




	
	
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
Step 4: Fix in the right order
Sequence matters more than people expect. Skip ahead, and you’ll waste the work.
Eligibility first
Can AI crawlers even reach the site? Check robots.txt and any Cloudflare settings that might be blocking bots by default. Cloudflare announced it would block AI crawlers by default for sites on its network, and plenty of site owners never noticed the setting had changed. 
Clean up NAP consistency so the business name, address, and phone number match everywhere online. 
Add and validate structured data, including LocalBusiness, Organization, FAQ, and Service schema markup. 
Dig deeper: A 90-day SEO playbook for AI-driven search visibility 



Trust signals second
Build a stronger review profile and healthier average ratings across Google Business Profile, Yelp, and industry-specific sites. 
Respond to reviews and questions. AI notices engagement, not just star ratings. 
Aim for cross-platform consistency, with the same story reflected across your website, directories, social profiles, and press coverage. Consistency signals credibility.
Relevance last
Only now does content work make sense. 
Build genuine location-specific depth with city pages that include real local detail, service pages with actual examples, and clear logistics information. 
Skip cookie-cutter pages that simply swap in a different city name.
The logic behind the order is simple. If crawlers are blocked or your NAP data is inconsistent, AI may never see the new content. Optimizing relevance before eligibility is like repainting a house nobody can find.
Step 5: Make the audit repeatable
One audit is a snapshot. Real progress comes from repeating it on a schedule because AI models update constantly, and what’s true today might not hold next quarter.
Quarterly is a reasonable cadence for most local businesses. That’s often enough to catch model updates and measure whether your fixes worked without turning the process into a full-time job. 
Don’t obsess over clicks as the primary success metric. That habit carries over from traditional SEO, but it doesn’t map cleanly to how AI answers work. 
Watch for branded search lift, more phone calls, and more direction requests from local profiles instead. Those signals show whether AI recommendations are driving real business, even when there’s no click to attribute. 
Within the audit itself, track mention rate, positioning, factual error rate, and citation count over time. If mention rate climbs but positioning remains buried beneath competitors, that’s a trust problem, not an eligibility problem, and it should shape your priorities for the next quarter.
Compare each audit with the last one. If AI suddenly prefers different sources or phrases answers differently, that’s model drift worth understanding, not a one-off glitch to ignore. 
Keep tracking competitor share of voice, too. If a rival is climbing steadily across the same prompts, it’s worth investigating before they pull away. Sometimes it’s a genuine authority gap. Sometimes, they simply started responding to reviews while everyone else stood still.
Dig deeper: Local SEO sprints: A 90-day plan for service businesses in 2026



  
more local customers.
      
Start winning locally
    
Start here, not with content
A local GEO baseline audit isn’t complicated. Benchmark where things stand, fix eligibility and trust issues before touching content, structure your information so AI has a reason to cite the business, and repeat the audit on a regular schedule.
The alternative is guessing. In local search, guesswork shows up as calls that never came in and customers who chose a competitor without anyone knowing why. If nobody’s actually looked at what AI says about a business lately, that’s the place to start.

Find out whether AI recommends your business, gets your information right, or favors competitors before investing more in local SEO.

How to run a local GEO baseline audit

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault.png" class="attachment-large size-large wp-post-image" alt="Google search vault" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Qualifying AI chatbots can also get the same search data Google uses to improve its services, subject to privacy safeguards.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault.png" class="attachment-large size-large wp-post-image" alt="Google search vault" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-search-vault-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The European Commission ordered Google to share anonymized search data with rival search engines under the Digital Markets Act, specifying how the company must give third parties access to data used to improve search services.</p>



<p>The legally binding measures clarify how Google must comply with the DMA’s search data-sharing rule. Google must begin sharing search data with eligible third-party search providers in January 2027.</p>



<p><strong>Google must share search data. </strong>The Commission said Google’s current data-sharing program has been ineffective and outlined how the company must provide search data to rival search engines.</p>



<ul class="wp-block-list">
<li>Google must share the same search data it uses to optimize its own search services, subject to anonymization. </li>



<li>The goal is to help rivals develop and improve search products, including privacy-focused alternatives.</li>
</ul>



<p><strong>AI search tools qualify. </strong>The Commission said AI chatbots that offer search functionality are eligible to receive shared data. Google’s data-sharing obligation applies to qualifying AI search services, not just traditional search engines.</p>



<p><strong>Why we care. </strong>Sharing Google&#8217;s search data could strengthen competing search and AI products, but the practical impact may be limited. Google alternatives already exist. The bigger challenge is changing users&#8217; search habits.</p>



<p><strong>Data safeguards.</strong> The Commission said the data must be anonymized through a multilayer process developed with privacy experts.</p>



<ul class="wp-block-list">
<li>Google may assess whether sharing data with a specific third party would create serious cybersecurity or data protection risks before providing access. </li>



<li>The measures also require a fair pricing formula and a transparent access process.</li>
</ul>



<p><strong>Android AI changes. </strong>The Commission also ordered Google to give rival AI assistants better access to Android features available to its own AI services, including Gemini.</p>



<ul class="wp-block-list">
<li>EU users will be able to activate their preferred AI assistants by voice and use them to perform actions in apps.</li>



<li>Those Android changes are expected to begin in July 2027.</li>
</ul>



<p><strong>The decision doesn&#8217;t impose fines. </strong>Under the DMA, specification proceedings clarify how a gatekeeper must comply with an obligation rather than determine whether it violated the law.</p>



<ul class="wp-block-list">
<li>The search data measures could be amended based on market developments, independent third-party evaluations, and future privacy assessments, the Commission said.</li>
</ul>



<p><strong>The ruling.</strong> <a href="https://ec.europa.eu/commission/presscorner/detail/en/ip_26_1634">Commission provides guidance to Google for AI interoperability on Android and sharing of Google Search data under the Digital Markets Act</a>






The European Commission ordered Google to share anonymized search data with rival search engines under the Digital Markets Act, specifying how the company must give third parties access to data used to improve search services.
The legally binding measures clarify how Google must comply with the DMA’s search data-sharing rule. Google must begin sharing search data with eligible third-party search providers in January 2027.
Google must share search data. The Commission said Google’s current data-sharing program has been ineffective and outlined how the company must provide search data to rival search engines.
Google must share the same search data it uses to optimize its own search services, subject to anonymization. 
The goal is to help rivals develop and improve search products, including privacy-focused alternatives.
AI search tools qualify. The Commission said AI chatbots that offer search functionality are eligible to receive shared data. Google’s data-sharing obligation applies to qualifying AI search services, not just traditional search engines.
Why we care. Sharing Google’s search data could strengthen competing search and AI products, but the practical impact may be limited. Google alternatives already exist. The bigger challenge is changing users’ search habits.
Data safeguards. The Commission said the data must be anonymized through a multilayer process developed with privacy experts.
Google may assess whether sharing data with a specific third party would create serious cybersecurity or data protection risks before providing access. 
The measures also require a fair pricing formula and a transparent access process.
Android AI changes. The Commission also ordered Google to give rival AI assistants better access to Android features available to its own AI services, including Gemini.
EU users will be able to activate their preferred AI assistants by voice and use them to perform actions in apps.
Those Android changes are expected to begin in July 2027.
The decision doesn’t impose fines. Under the DMA, specification proceedings clarify how a gatekeeper must comply with an obligation rather than determine whether it violated the law.
The search data measures could be amended based on market developments, independent third-party evaluations, and future privacy assessments, the Commission said.
The ruling. Commission provides guidance to Google for AI interoperability on Android and sharing of Google Search data under the Digital Markets Act

Qualifying AI chatbots can also get the same search data Google uses to improve its services, subject to privacy safeguards.

EU orders Google to share search data with rivals starting in 2027

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles.png" class="attachment-large size-large wp-post-image" alt="Lead volume is the wrong PPC goal in long B2B sales cycles" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>The longer the sales cycle, the less lead volume tells you. Build a feedback loop that helps Google Ads optimize for qualified opportunities.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles.png" class="attachment-large size-large wp-post-image" alt="Lead volume is the wrong PPC goal in long B2B sales cycles" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Lead-volume-is-the-wrong-PPC-goal-in-long-B2B-sales-cycles-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p>Many B2B advertisers still evaluate <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> performance with one simple question: &#8220;How many leads did we generate?&#8221;</p>



<p>But in long B2B sales cycles, that question can be misleading. Qualified pipeline and revenue tell a much more complete story.</p>



<p>Lead volume is easy to measure, but it doesn&#8217;t always reflect business value. This is especially true when the product is complex, expensive, regulated, or requires a consultative sales process.</p>



<p>In these cases, a form submission is only the beginning of the commercial process.</p>



<h2 class="wp-block-heading" id="h-the-lead-volume-trap">The lead volume trap</h2>



<p>Most PPC reports still focus on surface-level metrics: leads generated, cost per lead, conversion rate, form submissions, calls, and demo requests. These numbers are useful, but they shouldn&#8217;t define success on their own.</p>



<p>A campaign that generates 100 low-quality leads can look better in a dashboard than one that generates 15 highly qualified prospects. But if those 100 leads don&#8217;t become real sales opportunities, the campaign isn&#8217;t truly performing.</p>



<p>Take a premium pelvic floor therapy device. The target audience includes clinics, physiotherapists, doctors, medical practices, rehabilitation centers, fitness centers, and other potential business partners.</p>



<p>These aren&#8217;t mass-market buyers. Search volume is limited, the decision process is longer, and buyers often need to understand the product, business case, investment, implementation, and long-term value.</p>



<p>In this type of market, one qualified opportunity can be worth more than dozens of unqualified inquiries.</p>



<p>That&#8217;s why low lead volume doesn&#8217;t automatically mean weak PPC performance. Sometimes, it means the campaign is reaching a narrow but valuable audience. Lead volume alone doesn’t reflect B2B marketing performance.</p>



<figure class="wp-block-table"><table><tbody><tr><td><strong>Funnel stage</strong></td><td><strong>Example volume</strong></td><td><strong>What the platform sees</strong></td><td><strong>What the business should evaluate</strong></td></tr><tr><td>Clicks</td><td>1,000</td><td>Traffic from paid search</td><td>Are we attracting the right audience?</td></tr><tr><td>Form submissions</td><td>50</td><td>Conversions / leads</td><td>Are these leads relevant?</td></tr><tr><td>Qualified leads</td><td>10</td><td>Often not visible unless CRM is connected</td><td>Do they match our target customer profile?</td></tr><tr><td>Sales opportunities</td><td>5</td><td>Usually only visible in CRM</td><td>Is there real buying intent and business potential?</td></tr><tr><td>Closed deals</td><td>2</td><td>Usually not visible in ad platforms by default</td><td>Which campaigns actually generated customers?</td></tr><tr><td>Revenue</td><td>$80,000</td><td>Only visible if revenue data is imported</td><td>What was the real return on ad spend?</td></tr></tbody></table></figure>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/b2b-ppc-metrics-incremental-value-478925">Why your B2B PPC metrics may be lying to you</a></em></strong>


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<h2 class="wp-block-heading" id="h-a-form-submission-isn-t-a-business-outcome">A form submission isn&#8217;t a business outcome</h2>



<p>One of the biggest mistakes in B2B PPC is treating every conversion as equally valuable.</p>



<p>From the ad platform&#8217;s perspective, a lead form submission, a contact request, a route click, or a page visit can all appear as conversions. But from a business perspective, they aren&#8217;t worth the same.</p>



<p>A serious clinic owner who contacts the company directly is usually much more valuable than a generic lead form submission from a private consumer, student, competitor, or poor-fit lead.</p>



<p>If Google Ads only receives the signal &#8220;form submitted,&#8221; it&#8217;ll try to generate more form submissions. It doesn&#8217;t automatically understand which actions are commercially valuable unless you provide better feedback.</p>



<p>This is where many B2B advertisers get frustrated. The account shows more conversions, but sales still says lead quality is poor. Often, the problem is the conversion signal.</p>



<p>The screenshot below illustrates this problem. Google Ads is tracking several different conversion actions, including contacts, route clicks, page views, call leads, and lead form submissions. Technically, all of these can be counted as conversions. But strategically, they shouldn&#8217;t all be interpreted the same way.</p>



<p>A contact request usually shows stronger intent than a standard lead form submission. Someone classified as a contact in Google Ads is already considered a hot lead in the CRM because our feedback loop tracks every lifecycle stage change in HubSpot and sends that data back to Google Ads.</p>



<p>A lead form submission, on the other hand, can include many different types of users, from serious business prospects to private consumers, competitors, or people who aren&#8217;t commercially relevant.</p>



<p>That&#8217;s why the numbers are hidden in the screenshot. The number of lead form submissions is roughly twice the number of contact conversions. The goal is to show that the type of conversion matters. More conversions don&#8217;t automatically mean better performance if the platform is optimizing toward the wrong actions.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="853" src="https://searchengineland.com/wp-content/seloads/2026/07/Different-conversion-actions-in-a-Google-Ads-account-scaled.png" alt="Different conversion actions in a Google Ads account" class="wp-image-482453" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Different-conversion-actions-in-a-Google-Ads-account-scaled.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Different-conversion-actions-in-a-Google-Ads-account-768x320.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Different-conversion-actions-in-a-Google-Ads-account-1536x640.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /><figcaption class="wp-element-caption"><em><em>Different conversion actions in a Google Ads account</em></em></figcaption></figure>
</div>


<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-optimize-b2b-ppc-spend-when-budgets-and-confidence-are-low-454592">How to optimize B2B PPC spend when budgets and confidence are low</a></em></strong>



<h2 class="wp-block-heading" id="h-why-cost-per-lead-can-be-misleading">Why cost per lead can be misleading</h2>



<p>Cost per lead is one of the most common PPC metrics, but in B2B, it can create the wrong incentives. Imagine two campaigns:</p>



<ul class="wp-block-list">
<li><strong>Campaign A</strong> generates 80 leads at $50 per lead.</li>



<li><strong>Campaign B</strong> generates 15 leads at $200 per lead.</li>
</ul>



<p>At first glance, Campaign A looks better. But if Campaign A creates only one qualified opportunity and Campaign B creates six, Campaign B delivers more business value.</p>



<p>Measure campaigns by the cost of generating qualified pipeline and revenue, not simply by cost per lead.</p>



<p>That means B2B advertisers should look beyond CPL and include metrics such as:</p>



<ul class="wp-block-list">
<li>Cost per qualified lead.</li>



<li>Cost per opportunity.</li>



<li>Pipeline value by campaign.</li>



<li>Close rate by source.</li>



<li>Revenue by campaign.</li>



<li>Customer acquisition cost.</li>



<li>ROAS.</li>
</ul>



<figure class="wp-block-table"><table><tbody><tr><td><strong>Metric</strong></td><td><strong>Campaign A</strong></td><td><strong>Campaign B</strong></td></tr><tr><td>Leads Generated</td><td>80</td><td>15</td></tr><tr><td>Cost per Lead (CPL)</td><td>$50</td><td>$200</td></tr><tr><td>Total Spend</td><td>$4,000</td><td>$3,000</td></tr><tr><td>Qualified Opportunities</td><td>2</td><td>8</td></tr><tr><td>Opportunity Value</td><td>$20,000</td><td>$120,000</td></tr><tr><td>Revenue Generated</td><td>$15,000</td><td>$95,000</td></tr><tr><td>ROAS</td><td>3.8x</td><td>31.7x</td></tr></tbody></table><figcaption class="wp-element-caption"><br><em>Campaign performance comparison</em><br></figcaption></figure>



<h2 class="wp-block-heading" id="h-the-crm-is-where-lead-quality-becomes-visible">The CRM is where lead quality becomes visible</h2>



<p>Marketing platforms show clicks, conversions, and costs. The CRM shows what happened next. That&#8217;s where PPC quality becomes visible.</p>



<p>In our CRM, we evaluate opportunities with two additional signals: Deal Probability and Deal Score. Deal Probability is manually updated by the sales team based on the actual conversation, budget, timing, and buying intent. Deal Score is AI-generated and helps identify which opportunities show stronger potential based on available deal and engagement data.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1200" height="516" src="https://searchengineland.com/wp-content/seloads/2026/07/CRM-Deal-View-1.png" alt="CRM Deal View" class="wp-image-482455" srcset="https://searchengineland.com/wp-content/seloads/2026/07/CRM-Deal-View-1.png 1200w, https://searchengineland.com/wp-content/seloads/2026/07/CRM-Deal-View-1-768x330.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /><figcaption class="wp-element-caption"><em>CRM deal view</em></figcaption></figure>
</div>


<p>This gives marketing a much clearer picture than a form submission alone.</p>



<p>A campaign may generate many leads in Google Ads, but if those leads enter the CRM with low deal probability or weak deal scores, the campaign isn&#8217;t creating a meaningful pipeline. Another campaign may generate fewer leads, but if those leads consistently become high-probability opportunities, it&#8217;s more valuable to the business.</p>



<p>That&#8217;s why Google Ads, GA4, and CRM data shouldn&#8217;t be evaluated separately. If these systems are disconnected, you optimize with incomplete information. Campaigns that appear efficient on the ad platform may yield weak sales outcomes, while campaigns with higher CPLs may create better opportunities.</p>



<p>A better PPC feedback loop should answer:</p>



<ul class="wp-block-list">
<li>Which campaigns generate high-probability opportunities?</li>



<li>Which keywords create strong sales conversations?</li>



<li>Which landing pages produce qualified pipeline?</li>



<li>Which sources generate low-quality or poor-fit leads?</li>



<li>Which campaigns influence revenue, not just form submissions?</li>
</ul>



<p>These questions can&#8217;t be answered with ad platform data alone. They require CRM data.</p>



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<h2 class="wp-block-heading" id="h-import-qualified-conversion-data-back-into-google-ads">Import qualified conversion data back into Google Ads</h2>



<p>For long B2B sales cycles, one of the most important steps is importing offline conversion data back into Google Ads.</p>



<p>When a lead becomes qualified, turns into an opportunity, or closes as a customer, that information should be sent back to the ad platform whenever possible.</p>



<p>This helps Google Ads understand which clicks created actual business value after the initial website conversion.</p>



<p>Instead of optimizing only for form submissions, campaigns can learn from deeper-funnel events such as:</p>



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



<li>Sales-qualified lead.</li>



<li>Opportunity created.</li>



<li>Deal won.</li>



<li>Revenue value.</li>
</ul>



<p>This is especially important when using automated bidding.</p>



<p>Smart Bidding is only as good as the signals it receives. If the algorithm is trained on poor-quality conversions, it&#8217;ll optimize toward more of them. If it receives stronger conversion data, it has a better chance of finding users who are more likely to become valuable customers.</p>



<p>The long-term goal is to move optimization closer to revenue.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/b2b-brands-shift-keywords-performance-max-464327">Why B2B brands are shifting from keywords to Performance Max</a></em></strong>



<h2 class="wp-block-heading" id="h-sales-feedback-is-performance-data">Sales feedback is performance data</h2>



<p>In long B2B sales cycles, sales feedback shouldn&#8217;t be treated as anecdotal. It&#8217;s performance data.</p>



<p>Sales teams know which leads are serious, which objections come up repeatedly, which prospects have budget, and which campaigns produce the best conversations.</p>



<p>That information should influence PPC strategy. If one campaign generates many poor-fit leads, review the search terms, targeting, landing page, and conversion action.</p>



<p>If one keyword produces fewer leads but better sales conversations, it may deserve more budget.</p>



<p>If prospects keep asking the same questions before booking a consultation, the landing page may need clearer information.</p>



<p>This is especially important in medical technology, where buyers are evaluating trust, expertise, support, implementation, and long-term business value.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1774" height="887" src="https://searchengineland.com/wp-content/seloads/2026/07/The-B2B-PPC-Feedback-loop.png" alt="The B2B PPC feedback loop" class="wp-image-482456" srcset="https://searchengineland.com/wp-content/seloads/2026/07/The-B2B-PPC-Feedback-loop.png 1774w, https://searchengineland.com/wp-content/seloads/2026/07/The-B2B-PPC-Feedback-loop-768x384.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/The-B2B-PPC-Feedback-loop-1536x768.png 1536w" sizes="(max-width: 1774px) 100vw, 1774px" /><figcaption class="wp-element-caption"><em><em>The B2B PPC feedback loop</em></em></figcaption></figure>
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<h2 class="wp-block-heading" id="h-the-goal-is-qualified-pipeline-and-revenue">The goal is qualified pipeline and revenue</h2>



<p>For high-ticket and complex B2B products, the companies that win with PPC will connect marketing data with sales reality.</p>



<p>They&#8217;ll move beyond surface-level conversions and build feedback loops that help campaigns optimize toward a qualified pipeline and revenue.</p>



<p>In long B2B sales cycles, the goal is to create qualified opportunities that become customers, not simply fill the CRM with contacts.</p>

Many B2B advertisers still evaluate PPC performance with one simple question: “How many leads did we generate?”
But in long B2B sales cycles, that question can be misleading. Qualified pipeline and revenue tell a much more complete story.
Lead volume is easy to measure, but it doesn’t always reflect business value. This is especially true when the product is complex, expensive, regulated, or requires a consultative sales process.
In these cases, a form submission is only the beginning of the commercial process.
The lead volume trap
Most PPC reports still focus on surface-level metrics: leads generated, cost per lead, conversion rate, form submissions, calls, and demo requests. These numbers are useful, but they shouldn’t define success on their own.
A campaign that generates 100 low-quality leads can look better in a dashboard than one that generates 15 highly qualified prospects. But if those 100 leads don’t become real sales opportunities, the campaign isn’t truly performing.
Take a premium pelvic floor therapy device. The target audience includes clinics, physiotherapists, doctors, medical practices, rehabilitation centers, fitness centers, and other potential business partners.
These aren’t mass-market buyers. Search volume is limited, the decision process is longer, and buyers often need to understand the product, business case, investment, implementation, and long-term value.
In this type of market, one qualified opportunity can be worth more than dozens of unqualified inquiries.
That’s why low lead volume doesn’t automatically mean weak PPC performance. Sometimes, it means the campaign is reaching a narrow but valuable audience. Lead volume alone doesn’t reflect B2B marketing performance.

Funnel stageExample volumeWhat the platform seesWhat the business should evaluate
Clicks1,000Traffic from paid searchAre we attracting the right audience?
Form submissions50Conversions / leadsAre these leads relevant?
Qualified leads10Often not visible unless CRM is connectedDo they match our target customer profile?
Sales opportunities5Usually only visible in CRMIs there real buying intent and business potential?
Closed deals2Usually not visible in ad platforms by defaultWhich campaigns actually generated customers?
Revenue$80,000Only visible if revenue data is importedWhat was the real return on ad spend?





Dig deeper: Why your B2B PPC metrics may be lying to you



  
your competitors win.
      
Analyze your competitors
    
A form submission isn’t a business outcome
One of the biggest mistakes in B2B PPC is treating every conversion as equally valuable.
From the ad platform’s perspective, a lead form submission, a contact request, a route click, or a page visit can all appear as conversions. But from a business perspective, they aren’t worth the same.
A serious clinic owner who contacts the company directly is usually much more valuable than a generic lead form submission from a private consumer, student, competitor, or poor-fit lead.
If Google Ads only receives the signal “form submitted,” it’ll try to generate more form submissions. It doesn’t automatically understand which actions are commercially valuable unless you provide better feedback.
This is where many B2B advertisers get frustrated. The account shows more conversions, but sales still says lead quality is poor. Often, the problem is the conversion signal.
The screenshot below illustrates this problem. Google Ads is tracking several different conversion actions, including contacts, route clicks, page views, call leads, and lead form submissions. Technically, all of these can be counted as conversions. But strategically, they shouldn’t all be interpreted the same way.
A contact request usually shows stronger intent than a standard lead form submission. Someone classified as a contact in Google Ads is already considered a hot lead in the CRM because our feedback loop tracks every lifecycle stage change in HubSpot and sends that data back to Google Ads.
A lead form submission, on the other hand, can include many different types of users, from serious business prospects to private consumers, competitors, or people who aren’t commercially relevant.
That’s why the numbers are hidden in the screenshot. The number of lead form submissions is roughly twice the number of contact conversions. The goal is to show that the type of conversion matters. More conversions don’t automatically mean better performance if the platform is optimizing toward the wrong actions.
Different conversion actions in a Google Ads account



Dig deeper: How to optimize B2B PPC spend when budgets and confidence are low



Why cost per lead can be misleading
Cost per lead is one of the most common PPC metrics, but in B2B, it can create the wrong incentives. Imagine two campaigns:
Campaign A generates 80 leads at $50 per lead.
Campaign B generates 15 leads at $200 per lead.
At first glance, Campaign A looks better. But if Campaign A creates only one qualified opportunity and Campaign B creates six, Campaign B delivers more business value.
Measure campaigns by the cost of generating qualified pipeline and revenue, not simply by cost per lead.
That means B2B advertisers should look beyond CPL and include metrics such as:
Cost per qualified lead.
Cost per opportunity.
Pipeline value by campaign.
Close rate by source.
Revenue by campaign.
Customer acquisition cost.
ROAS.

MetricCampaign ACampaign B
Leads Generated8015
Cost per Lead (CPL)$50$200
Total Spend$4,000$3,000
Qualified Opportunities28
Opportunity Value$20,000$120,000
Revenue Generated$15,000$95,000
ROAS3.8x31.7x


Campaign performance comparison




The CRM is where lead quality becomes visible
Marketing platforms show clicks, conversions, and costs. The CRM shows what happened next. That’s where PPC quality becomes visible.
In our CRM, we evaluate opportunities with two additional signals: Deal Probability and Deal Score. Deal Probability is manually updated by the sales team based on the actual conversation, budget, timing, and buying intent. Deal Score is AI-generated and helps identify which opportunities show stronger potential based on available deal and engagement data.
CRM deal view



This gives marketing a much clearer picture than a form submission alone.
A campaign may generate many leads in Google Ads, but if those leads enter the CRM with low deal probability or weak deal scores, the campaign isn’t creating a meaningful pipeline. Another campaign may generate fewer leads, but if those leads consistently become high-probability opportunities, it’s more valuable to the business.
That’s why Google Ads, GA4, and CRM data shouldn’t be evaluated separately. If these systems are disconnected, you optimize with incomplete information. Campaigns that appear efficient on the ad platform may yield weak sales outcomes, while campaigns with higher CPLs may create better opportunities.
A better PPC feedback loop should answer:
Which campaigns generate high-probability opportunities?
Which keywords create strong sales conversations?
Which landing pages produce qualified pipeline?
Which sources generate low-quality or poor-fit leads?
Which campaigns influence revenue, not just form submissions?
These questions can’t be answered with ad platform data alone. They require CRM data.
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Import qualified conversion data back into Google Ads
For long B2B sales cycles, one of the most important steps is importing offline conversion data back into Google Ads.
When a lead becomes qualified, turns into an opportunity, or closes as a customer, that information should be sent back to the ad platform whenever possible.
This helps Google Ads understand which clicks created actual business value after the initial website conversion.
Instead of optimizing only for form submissions, campaigns can learn from deeper-funnel events such as:
Qualified lead.
Sales-qualified lead.
Opportunity created.
Deal won.
Revenue value.
This is especially important when using automated bidding.
Smart Bidding is only as good as the signals it receives. If the algorithm is trained on poor-quality conversions, it’ll optimize toward more of them. If it receives stronger conversion data, it has a better chance of finding users who are more likely to become valuable customers.
The long-term goal is to move optimization closer to revenue.
Dig deeper: Why B2B brands are shifting from keywords to Performance Max



Sales feedback is performance data
In long B2B sales cycles, sales feedback shouldn’t be treated as anecdotal. It’s performance data.
Sales teams know which leads are serious, which objections come up repeatedly, which prospects have budget, and which campaigns produce the best conversations.
That information should influence PPC strategy. If one campaign generates many poor-fit leads, review the search terms, targeting, landing page, and conversion action.
If one keyword produces fewer leads but better sales conversations, it may deserve more budget.
If prospects keep asking the same questions before booking a consultation, the landing page may need clearer information.
This is especially important in medical technology, where buyers are evaluating trust, expertise, support, implementation, and long-term business value.
The B2B PPC feedback loop



  
a customer you lose.
      
See who’s stealing your traffic
    
The goal is qualified pipeline and revenue
For high-ticket and complex B2B products, the companies that win with PPC will connect marketing data with sales reality.
They’ll move beyond surface-level conversions and build feedback loops that help campaigns optimize toward a qualified pipeline and revenue.
In long B2B sales cycles, the goal is to create qualified opportunities that become customers, not simply fill the CRM with contacts.

The longer the sales cycle, the less lead volume tells you. Build a feedback loop that helps Google Ads optimize for qualified opportunities.

How to move beyond lead volume in B2B PPC

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/4-types-of-content-decay-and-how-to-fix-each-one.png" class="attachment-large size-large wp-post-image" alt="4 types of content decay and how to fix each one" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/4-types-of-content-decay-and-how-to-fix-each-one.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/4-types-of-content-decay-and-how-to-fix-each-one-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/4-types-of-content-decay-and-how-to-fix-each-one-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/4-types-of-content-decay-and-how-to-fix-each-one-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Some pages need a refresh. Others need a different strategy entirely. Here's how to tell the difference using data you already have.

Every page you publish is vulnerable to traffic decay. The question is whether you catch it when it’s down 15% or 80%, and whether you fix the right thing when you do.
Most teams catch it late, then reach for the same tool every time: refresh it. Update the date, add a few hundred words, republish. Sometimes that works. Often it does nothing. Occasionally, it makes the page worse.
That’s because falling clicks are only a symptom. A page can lose traffic for at least four reasons, and each requires a different fix.
The content decay playbook most of us inherited treats every decline as the same problem with the same cure. In 2026, that playbook is missing a cause, and it’s one many teams still overlook.
Here’s how to identify the type of decay you’re dealing with using data you already have, and what to do about it.
Content decay isn’t one problem
Content decay is a sustained loss of organic clicks and impressions over time. One-week fluctuations don’t qualify. It isn’t a new idea. For years, SEOs have explained it in terms of three root causes: a competitor improved, search intent shifted, or demand for the topic declined.
That model is still mostly right. It’s just incomplete because it predates AI Overviews.
In 2026, fewer than one in three Google searches sends a click to the open web. About 68% end without a click, up from roughly 60% two years ago. On queries where an AI Overview appears, the top organic result loses around 58% of its clicks. AI Overviews also appear far more often on informational queries than on commercial ones, which is exactly the kind of query most blogs are built to win.
AI Overviews introduced a new way for pages to lose traffic. Rankings can hold steady, demand can stay the same, and clicks can still disappear. 
That’s why content decay is no longer one problem. It’s four.
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The four types of content decay
Each type of content decay leaves a different fingerprint in your data. Here’s what to look for.
1. Ranking decay
Clicks down, impressions down, average position worse. A competitor overtook you, the content went stale, you lost links, or two of your own pages are cannibalizing each other. This is the classic case, and the only one a content refresh reliably fixes.
2. Zero-click capture (the new one)
Clicks down, but impressions are flat or up, and position is stable or better. You’re still ranking, often higher than before, and still losing clicks. 
That’s the fingerprint of an AI Overview, a featured snippet, or another SERP feature answering the query right on the results page. A routine refresh won’t bring the clicks back because you didn’t lose rankings. You lost the click to the answer box.
3. Intent drift
Clicks down, position roughly holding, but the SERP around you changed shape. Google reinterpreted the query and now rewards a different format, like video, a comparison table, or a product page, and yours no longer matches. This one needs a human eye on the SERP. The numbers alone won’t flag it.
4. Demand decay (the imposter)
Clicks down, impressions down, but your position held or even improved. You didn’t lose anything. The topic is simply searched less. This is the one that fools teams into refreshing a page that was never coming back.
Dig deeper: Why more content is no longer a reliable way to grow SEO



How to tell them apart
You don’t need an expensive tool. You need Google Search Console and a spreadsheet.
Pull two things for each page: monthly organic clicks for the last six months, which give you the trend, and a three-month year-over-year comparison of clicks, impressions, and average position, which gives you the diagnosis. 
Three months smooths out the noise, year-over-year comparisons cancel out seasonality, and the whole thing fits within GSC’s 16-month memory. A six-month year-over-year comparison would require 18 months of history Google doesn’t keep.
Then read the signature: the telltale way clicks, impressions, and average position move together. Each type of decay has its own signature. Match your page to the table below.

ClicksImpressionsAvg. positionDiagnosis
DownDownWorseRanking decay
DownFlat or upStable or betterZero-click capture
DownDownHeld or betterDemand decay
DownVariesHolding, but SERP reshapedIntent drift (confirm on the SERP)
Down site-wide, date-alignedDownDownAlgorithm update (different playbook)





Before you act on any of it, run one check first. Did the drop start right after you edited the page? If it did, you probably didn’t catch decay. You caused it. Restore the previous version and compare before you pile a refresh on top of a self-inflicted wound.
One caution specific to this moment: Search Console impression data from 2025 is shaky for year-over-year analysis. First, in September 2025, Google removed the &num=100 parameter, which stripped out bot-inflated impressions and pulled counts down. 
Months later, Google disclosed something bigger: a logging error had been inflating impressions since May 2025. It corrected the issue without repairing the historical numbers. Clicks were never affected.
So when a page looks like demand decay, with impressions down but position holding or improving, don’t trust the impression drop. Open the live SERP and look. If an AI Overview is sitting there, it’s zero-click capture wearing a demand-decay costume.
I built a Google Sheets version of this diagnostic. Paste in six months of clicks plus a year-over-year comparison, and it classifies the decay type and prioritizes pages by recoverable traffic. Use it as a starting point, then validate the results before acting.




Want to take it further? GSC and a spreadsheet are the floor on purpose. Anyone can run that today, for free. Two upgrades make it even sharper:
Add GA4: Conversions or revenue per page let you prioritize by what a page is actually worth, not just the clicks it lost. Engagement metrics help, too, because they often dip before clicks, giving you an earlier warning.
Add a rank tracker and SERP feature data: These let you confirm zero-click capture across hundreds of pages at once instead of checking one result at a time.
Neither changes the diagnosis. They just measure it with finer instruments.
Dig deeper: How to keep your content fresh in the age of AI




	
	
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The right fix for each diagnosis
Once you know the type, the fix gets specific. Here’s what each one looks like.
Ranking decay: The real refresh
In 2026, that means information gain, not a new date. Google’s guidance favors original, first-hand, people-first content, making cosmetic date swaps less useful than meaningful updates. 
Picture a buyer’s guide that ranked third and slid to the bottom of page one after a competitor published a deeper version and earned links you didn’t. Adding 300 words won’t move it. Focus on these moves:
Add what the current winners cover and you don’t: Original testing, a data point only you have, or the follow-up question every other result ignores.
Check who those winners are first: If a Reddit thread now holds your old spot, you’re up against a format Google chose to favor, so match that intent instead of trying to out-write an article.
Consolidate any cannibalizing URLs into one: Rebuild the internal links that signal authority.
Zero-click capture: Stop competing with the summary
The pattern that throws people most is a page that ranks better and still loses clicks. I audited a high-intent money page that climbed from an average position of 19 to 11, with impressions up 10% and clicks down by half. The reflex is a quick refresh. 
That won’t work because you didn’t lose rankings or quality. An AI Overview is now answering the query on the results page. Recovering value takes a different play. Part of it is still real work on the page.
Upgrade the page into something the answer box can’t replace: Original data, a calculator, a tool, or a genuine point of view. This is work on the content itself, not a date-and-paragraph refresh.
Make the page a quotable source: That same unique value, plus clean structure, gives the page a better chance of being cited in an AI Overview or used by answer engines, where ranking on page one no longer means you’re the source being quoted.
Know when the click is gone, and reallocate your effort: Some of these queries may never send a click again. Move your effort to a nearby page closer to conversion, like a service or comparison page, that people still click.
Follow the audience off Google: If demand has moved to Reddit or YouTube, meet it there by creating content for those platforms. That’s a separate effort, not an update to this page.




Google is answering the query through forums, AI Overviews, and video content.



Dig deeper: What replaces the ultimate guide in AI search



Intent drift: Re-match the format
When Google reinterprets a query, the winning format changes, and a technically strong page that no longer fits gets left behind. 
A “best [product]” search that used to surface buying guides might now return product pages. A how-to might now lead with video. 
If you published a narrative guide where the SERP wants a comparison table, content quality is irrelevant. The format is wrong.
Re-match the format the SERP now rewards, or split the page into the versions it’s asking for.
Keep the URL so you don’t lose its equity.
Recheck quarterly, not just once. The SERP is more volatile than it has been in years, with video carousels, forum blocks, and product modules surfacing and disappearing on the same query.
Demand decay: Usually, do nothing to the content
An old news article that spiked around an event and faded, or a guide for a product nobody buys anymore, isn’t coming back, and no rewrite resurrects a search people stopped running. 
First confirm the demand is really gone, not just relocated. A falling Google Trends line doesn’t always mean demand disappeared. It may mean some of that behavior moved to AI assistants, social search, forums, or video platforms.
If the topic still has an audience elsewhere, the play is to build a presence on that surface, not refresh the page.
If it’s genuinely gone, consolidate it into a broader page that still has demand, redirect it, or prune it.
Prune without guilt. If a page is outdated, unhelpful, and has no recoverable demand, keeping it may add noise instead of value. Google has long advised removing or improving unhelpful content when it no longer serves users.
Dig deeper: Refreshing content: How to update old content to drive new traffic



The mistakes that look like strategy
Most wasted refresh effort traces back to a handful of reflexes:
Treating every drop as a content problem. This is the core error the whole framework exists to prevent.
Changing the publish date with nothing behind it. Readers and Google both see through it.
Padding word count. Length was never the ranking factor. Thoroughness was.
Refreshing a demand problem. No amount of editing recovers a topic people stopped searching for.
Refreshing too often to measure anything. Give a change a quarter to prove itself before you touch it again.
Refreshing a page you broke. If traffic fell right after an edit, restore it. Don’t rewrite it.
before your competitors.
      
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Make it a habit, not a fire drill
The teams that stay ahead of decay don’t wait for a page to lose 80%. They run a quarterly sweep. Tag every slipping page by type, sort by recoverable traffic and business value, and act only where the diagnosis says action will work.
As zero-click results keep climbing, that discipline matters even more. The advantage no longer belongs to whoever refreshes the most pages. It belongs to whoever knows which pages are worth refreshing and which ones to leave alone.
Key takeaways:




Diagnose before you refresh. Falling clicks have at least four causes, and only one is fixed by rewriting. Identify the type first.
Watch impressions and position, not just clicks. Clicks tell you a page is decaying. Impressions and position tell you why. Rising impressions with falling clicks point to zero-click capture, not a content problem.
Know when not to act. Demand decay and “I broke it myself” pages don’t need a refresh. They need a different decision. Refreshing them wastes time and budget.
Confirm ambiguous cases on the live SERP. Especially after num=100, a demand-decay pattern with improving position is often an AI Overview in disguise.
Systematize it. A quarterly, signature-based decay sweep beats reactive, one-off rewrites every time.
Dig deeper: How to revise your old content for AI search optimization

Some pages need a refresh. Others need a different strategy entirely. Here's how to tell the difference using data you already have.

4 types of content decay and how to fix each one

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Learn the difference between notification, crawling, and indexing, and use a free tool to check whether your API is doing what you expect.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Googles-job-Indexing-API-isnt-the-shortcut-you-think-it-is-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>I wanted Google’s Indexing API to be the cheat code for job boards. The equation was simply:</p>



<ul class="wp-block-list">
<li>New job goes live? <strong>Push i</strong>t to Google.</li>



<li>Job gets updated? <strong>Notify</strong> Google.</li>



<li>Job expires? Tell Google to <strong>drop it</strong>.</li>
</ul>



<p>For any job board owner, that sounds incredible, especially considering job postings are not evergreen assets. They are short-lived, high-churn pages that need to be discovered and removed quickly. If Google is slow to crawl a job URL, the opportunity may already be gone by the time the page gets indexed.</p>



<p>So when Google offers an API that appears to let you notify them directly when job pages are created, updated, or deleted, it’s exactly the tool that hits “mandatory” status for job board owners.</p>



<p><strong>That was my assumption, too.</strong>



<p>Then I spent hours reviewing the documentation, testing server responses, checking quota limits, and comparing what <a href="https://developers.google.com/search/apis/indexing-api/v3/quickstart" target="_blank" rel="noopener">Google says the API does</a> with what most SEOs probably assume it does.</p>



<p>The conclusion?</p>



<p>The API is not useless. That would actually be easier to write about.</p>



<p>It is worse than that. It works just well enough to make you think you accomplished something. But 90% of you using this tool (legitimately or not) aren’t getting what you THINK you are.</p>



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



<p>This week’s newsletter gets a little long. <a href="https://www.seoforlunch.com/i/204923331/google-your-play-a-free-job-indexing-tool-to-determine-if-youre-actually-getting-service" target="_blank" rel="noopener"><strong>Go straight to the free tool</strong></a> to determine if your job indexing API is working the way you <strong>think</strong> it is.</p>



<h2 class="wp-block-heading" id="h-what-google-s-web-indexing-api-actually-does">What Google’s Web Indexing API actually does</h2>



<p>Google’s Indexing API lets site owners notify Google when certain pages are added, updated, or removed. But this is not a general-purpose indexing API for every URL on your website.</p>



<p>Google says the API can only be used for pages with JobPosting structured data or livestream pages using BroadcastEvent embedded inside a VideoObject. In other words, this is not for blog posts, category pages, location pages, service pages, product pages, or any other URL you wish Google would crawl faster.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="960" height="418" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-1.webp" alt="Google’s Indexing API " class="wp-image-482438" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-1.webp 960w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-1-768x334.webp 768w" sizes="(max-width: 960px) 100vw, 960px" /></figure>
</div>


<p><strong>For job boards, the API provides two primary actions.</strong>



<p>You can send <code>URL_UPDATED</code> when a job page is new or meaningfully changed. You can send <code>URL_DELETED</code> when a job page has been removed and should be dropped from Google’s index.</p>



<p>That sounds powerful, and to be fair, it can be insanely effective.</p>



<p>The problem is that <strong>a successful API response does not mean what many people want it to mean.</strong>



<p>It does not mean the URL was indexed. It does not mean the URL appears in Google’s index or in the Google Jobs experience. It does not mean the page will generate impressions, clicks, or conversions.</p>



<p>It means Google received your notification.</p>



<p><strong>That’s it.</strong>



<h2 class="wp-block-heading" id="h-job-indexing-api-default-quotas-and-limits">Job Indexing API default quotas and limits</h2>



<p>This is the part that really matters.</p>



<p>Google’s <a href="https://developers.google.com/search/apis/indexing-api/v3/using-api" target="_blank" rel="noopener">own documentation says</a> that when you send an update request and receive a HTTP 200 response, Google <strong>may</strong> try to recrawl the URL soon. When you send a delete request and receive a HTTP 200 response, Google <strong>may</strong> remove the URL from the index.</p>



<p>That word “<strong>may</strong>” is doing a lot of work.</p>



<p>Not will. Not did. Not confirmed.</p>



<p><strong>“May.”</strong>



<p>And that is where many SEOs get into trouble.</p>



<p>A successful API response feels like progress because technical actions are easy to measure. The request was sent. The server response was clean. The script ran without errors. The JSON response shows that Google received the notification.</p>



<p>Great.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1371" height="243" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-2.webp" alt="API filters" class="wp-image-482439" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-2.webp 1371w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-2-768x136.webp 768w" sizes="(max-width: 1371px) 100vw, 1371px" /></figure>
</div>


<p>But submitted is not indexed. Received is not crawled. Crawled is not ranked. Ranked is not clicked. Clicked is not an incremental conversion.</p>



<p>You get the point.</p>



<p>These are different events, and treating them like one connected guarantee is exactly how people overstate what this API actually does.</p>



<p>The API gives you notification confirmation.</p>



<p>It does not give you indexing confirmation.</p>



<p>And yes, this is also why the API has been abused to death by people trying to force Google to index non-job-related content.</p>



<p>Raise your hand if you’ve ever seen someone use the Job Indexing API for something that very clearly was not a job posting.</p>



<p>Actually, never mind.</p>



<p>We all know the answer.</p>



<p><strong>The asterisk that proves you’re wasting your time</strong>.</p>



<p>You can have the API configured correctly. You can send the right payload. You can get a successful response. You can store the notification metadata. You can even show logs that prove your system is working.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1456" height="648" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-3.webp" alt="Traffic by response code" class="wp-image-482440" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-3.webp 1456w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-3-768x342.webp 768w" sizes="(max-width: 1456px) 100vw, 1456px" /></figure>
</div>


<p>And you still do not know whether Google indexed the page. That is the gap.</p>



<h2 class="wp-block-heading" id="h-introducing-getmetadata-and-why-you-didn-t-trick-google-into-indexing-your-spam-after-all">Introducing <code>getMetadata</code> and why you didn’t trick Google into indexing your spam after all</h2>



<p>One of the more misleading parts of the API is the ability to check the status of a URL notification.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="947" height="207" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-4.webp" alt="Request quota and approval" class="wp-image-482441" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-4.webp 947w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-4-768x168.webp 768w" sizes="(max-width: 947px) 100vw, 947px" /></figure>
</div>


<p>At first glance, this seems to answer the big question.</p>



<p>Did Google index this URL? <strong>Nope.</strong>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1098" height="483" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-5.webp" alt="Indexing API" class="wp-image-482442" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-5.webp 1098w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-5-768x338.webp 768w" sizes="(max-width: 1098px) 100vw, 1098px" /></figure>
</div>


<p>This raw JSON response is everything you need to understand what’s happening. Unfortunately, it is just not the information most people actually want.</p>



<p><em>“API accepted”</em> and <em>“indexed”</em> are not the same.</p>



<h2 class="wp-block-heading" id="h-tell-me-more-about-getmetadata-and-google-s-sandbox">Tell me more about getMetadata and Google’s Sandbox</h2>



<p>The JSON above shows that Google received your update or delete notification, but you cannot use that API response as proof that the job page was crawled, indexed, removed, or shown in any meaningful way.</p>



<p>That does not mean <code>getMetadata</code> is useless.</p>



<p>It is actually one of the most important parts of validating whether your Indexing API setup is working.</p>



<h4 class="wp-block-heading" id="h-getting-a-404-error-in-your-getmetadata-request-like-me"><strong>Getting a 404 error in your getMetadata request, like me?</strong></h4>



<p>You are sending the letter by mail, but the recipient has removed the mailbox from their house. Unless your API has been approved for real use, you are operating entirely within Google’s sandbox, regardless of whether the quota screen makes it appear you have room to send more requests.</p>



<p>And honestly, can you imagine how many spam requests Google has seen through this API?</p>



<p>People spent all that time trying to jam non-job content through a job-indexing API, only to get a clean-looking response that did not actually do what they thought it would.</p>



<p><strong>Congrats. You got a receipt for wasted time.</strong>



<p>But don’t worry. Google says legitimate job posting URLs can be submitted once you <a href="https://docs.google.com/forms/d/e/1FAIpQLSc_mpLw3WnnCt3pVbUHYZZ6ZdOS-c0GIj-WZ_k54SG-jDqCXQ/viewform" target="_blank" rel="noopener">fill out a request form</a>, which will be reviewed on average in 2-3 weeks.</p>



<p><strong>HA!!!</strong>



<h2 class="wp-block-heading" id="h-the-approval-and-quota-increase-process">The approval and quota increase process</h2>



<p>Google’s quickstart documentation states that the API provides a default 200-request quota for onboarding and submission testing, but additional approval is required for usage and resource provisioning.</p>



<p>The process appears straightforward enough. Set up the API, prove your use case, submit the form, wait for review, and get approved.</p>



<p><strong>At least, that is how it used to work.</strong>



<p>A few years back, when I was working with a job board that had millions of jobs, I became best friends with that form. I submitted quota requests, showed that the existing quota was being burned through by legitimate job URLs, and within 2–3 weeks, Google would increase the quota.</p>



<p>That was my experience, and it worked.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1080" height="944" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-6.webp" alt="Request indexing API quota" class="wp-image-482443" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-6.webp 1080w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-6-768x671.webp 768w" sizes="(max-width: 1080px) 100vw, 1080px" /></figure>
</div>


<p>I also set up the API for SEOJobs.com a few years ago, and I was fortunate enough to get proper functioning access there, too.</p>



<p>Then one thing led to another, and I made a bonehead move that deleted my API. (<em>Booooo! Shame on me!)</em>



<p>So I set it all up again. This time, I submitted requests for both <a href="https://www.seojobs.com/" target="_blank" rel="noopener">SEOJobs.com</a> and <a href="https://www.ppcjobs.com/" target="_blank" rel="noopener">PPCJobs.com</a>.</p>



<p>That was six months ago. Yep. No response in 2026 at all.</p>



<p>Not an approval. Not a rejection. Not a request for more information.</p>



<p><strong>Simply NOTHING.</strong>



<p>Since my own data is limited, I’ve been talking with <a href="https://www.linkedin.com/in/chukovski/" target="_blank" rel="noopener">Alexander Chukovski</a>, who has worked with hundreds of job boards and puts my job board knowledge to shame.</p>



<p>He told me that none of the job boards he worked with over a roughly 10-12 month span received a response after submitting the same form.</p>



<p><strong>That is not one random site getting ignored.</strong>



<h2 class="wp-block-heading" id="h-google-it-s-now-your-turn">Google, it’s now your turn</h2>



<p>Everything above shows a pattern across legitimate job boards that are trying to use an API that Google specifically says is for job-posting content.</p>



<p>Alexander also wrote about <a href="https://www.alexanderchukovski.com/major-updates-to-the-indexing-api-impact-on-job-boards-and-aggregators/" target="_blank" rel="noopener">changes to the API documentation back in 2024</a>, which aligns with the timeline during which successful quota requests appear to have slowed or stopped being reviewed and approved altogether.</p>



<p>Can I confirm the number is zero? No.</p>



<p>But based on my experience, Alexander’s experience, and the lack of responses from legitimate job boards, it sure looks like approval has become significantly less likely than it used to be.</p>



<p>And that is the frustrating part. If the answer is no, fine <em>(I’ll just pout a bit in the corner.)</em>



<p>If the API is effectively locked down for new quota increases, that’s also fine.</p>



<p>If Google no longer wants to expand access because the API was abused to the point of exhaustion, I get that, too.</p>



<p><strong>But then say that.</strong>



<p>Do not leave the form sitting there like there is still a functioning review process.</p>



<p>Do not tell legitimate job boards to request more access if nobody is reviewing the requests.</p>



<p>Do not let people spend months waiting for a response that may never come.</p>



<p>Google does not owe us an indexing shortcut.</p>



<p>But if the front door is closed, please stop leaving the welcome mat out.</p>



<h2 class="wp-block-heading" id="h-a-free-job-indexing-tool-to-determine-if-you-re-actually-getting-service">A free job indexing tool to determine if you’re actually getting service</h2>



<p>OK, I’ve dangled the carrot long enough. I built a free tool for anyone with access to the API.</p>



<p>You can now find out in minutes whether it’s working the way you expected.</p>



<p><a href="https://www.seojobs.com/tools/job-indexing-checker/" target="_blank" rel="noopener"><strong>The Job Indexing Health Check</strong></a> is now available over on SEOJobs.com</p>



<p><strong>It offers two levels of service (both free).</strong>



<ul class="wp-block-list">
<li>Validate that your URL is marked up correctly with the job schema AND that it’s appears to be a supported job posting page.</li>



<li>The “full check” analyzes your job schema, your API responses, and Google Search Console responses.</li>
</ul>



<p><strong>All the results that matter, none of the technical hoops to jump through.</strong>



<p>The full results after running this report will look exactly like this (but hopefully you’ll get a 200 metadata response!) Example via SEOjobs API credentials, GSC, and job listing URL.</p>



<p>The full raw JSON response is also available at the bottom.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1456" height="909" src="https://searchengineland.com/wp-content/seloads/2026/07/spammer-7.webp" alt="The Job Indexing Health Check" class="wp-image-482444" srcset="https://searchengineland.com/wp-content/seloads/2026/07/spammer-7.webp 1456w, https://searchengineland.com/wp-content/seloads/2026/07/spammer-7-768x479.webp 768w" sizes="(max-width: 1456px) 100vw, 1456px" /></figure>
</div>


<p>Yes, the tool is 100% free. For folks submitting all content through this API, apologies, <s>not really</s> in advance if your non-SEO content never made it to Google.</p>



<p><em>This post first appeared on the author’s website and is republished here with permission.</em>


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

I wanted Google’s Indexing API to be the cheat code for job boards. The equation was simply:
New job goes live? Push it to Google.
Job gets updated? Notify Google.
Job expires? Tell Google to drop it.
For any job board owner, that sounds incredible, especially considering job postings are not evergreen assets. They are short-lived, high-churn pages that need to be discovered and removed quickly. If Google is slow to crawl a job URL, the opportunity may already be gone by the time the page gets indexed.
So when Google offers an API that appears to let you notify them directly when job pages are created, updated, or deleted, it’s exactly the tool that hits “mandatory” status for job board owners.
That was my assumption, too.



Then I spent hours reviewing the documentation, testing server responses, checking quota limits, and comparing what Google says the API does with what most SEOs probably assume it does.
The conclusion?
The API is not useless. That would actually be easier to write about.
It is worse than that. It works just well enough to make you think you accomplished something. But 90% of you using this tool (legitimately or not) aren’t getting what you THINK you are.
View embedded content



This week’s newsletter gets a little long. Go straight to the free tool to determine if your job indexing API is working the way you think it is.
What Google’s Web Indexing API actually does
Google’s Indexing API lets site owners notify Google when certain pages are added, updated, or removed. But this is not a general-purpose indexing API for every URL on your website.
Google says the API can only be used for pages with JobPosting structured data or livestream pages using BroadcastEvent embedded inside a VideoObject. In other words, this is not for blog posts, category pages, location pages, service pages, product pages, or any other URL you wish Google would crawl faster.




For job boards, the API provides two primary actions.



You can send URL_UPDATED when a job page is new or meaningfully changed. You can send URL_DELETED when a job page has been removed and should be dropped from Google’s index.
That sounds powerful, and to be fair, it can be insanely effective.
The problem is that a successful API response does not mean what many people want it to mean.



It does not mean the URL was indexed. It does not mean the URL appears in Google’s index or in the Google Jobs experience. It does not mean the page will generate impressions, clicks, or conversions.
It means Google received your notification.
That’s it.



Job Indexing API default quotas and limits
This is the part that really matters.
Google’s own documentation says that when you send an update request and receive a HTTP 200 response, Google may try to recrawl the URL soon. When you send a delete request and receive a HTTP 200 response, Google may remove the URL from the index.
That word “may” is doing a lot of work.
Not will. Not did. Not confirmed.
“May.”



And that is where many SEOs get into trouble.
A successful API response feels like progress because technical actions are easy to measure. The request was sent. The server response was clean. The script ran without errors. The JSON response shows that Google received the notification.
Great.




But submitted is not indexed. Received is not crawled. Crawled is not ranked. Ranked is not clicked. Clicked is not an incremental conversion.
You get the point.
These are different events, and treating them like one connected guarantee is exactly how people overstate what this API actually does.
The API gives you notification confirmation.
It does not give you indexing confirmation.
And yes, this is also why the API has been abused to death by people trying to force Google to index non-job-related content.
Raise your hand if you’ve ever seen someone use the Job Indexing API for something that very clearly was not a job posting.
Actually, never mind.
We all know the answer.
The asterisk that proves you’re wasting your time.
You can have the API configured correctly. You can send the right payload. You can get a successful response. You can store the notification metadata. You can even show logs that prove your system is working.




And you still do not know whether Google indexed the page. That is the gap.
Introducing getMetadata and why you didn’t trick Google into indexing your spam after all
One of the more misleading parts of the API is the ability to check the status of a URL notification.




At first glance, this seems to answer the big question.
Did Google index this URL? Nope.







This raw JSON response is everything you need to understand what’s happening. Unfortunately, it is just not the information most people actually want.
“API accepted” and “indexed” are not the same.
Tell me more about getMetadata and Google’s Sandbox
The JSON above shows that Google received your update or delete notification, but you cannot use that API response as proof that the job page was crawled, indexed, removed, or shown in any meaningful way.
That does not mean getMetadata is useless.
It is actually one of the most important parts of validating whether your Indexing API setup is working.
Getting a 404 error in your getMetadata request, like me?
You are sending the letter by mail, but the recipient has removed the mailbox from their house. Unless your API has been approved for real use, you are operating entirely within Google’s sandbox, regardless of whether the quota screen makes it appear you have room to send more requests.
And honestly, can you imagine how many spam requests Google has seen through this API?
People spent all that time trying to jam non-job content through a job-indexing API, only to get a clean-looking response that did not actually do what they thought it would.
Congrats. You got a receipt for wasted time.



But don’t worry. Google says legitimate job posting URLs can be submitted once you fill out a request form, which will be reviewed on average in 2-3 weeks.
HA!!!



The approval and quota increase process
Google’s quickstart documentation states that the API provides a default 200-request quota for onboarding and submission testing, but additional approval is required for usage and resource provisioning.
The process appears straightforward enough. Set up the API, prove your use case, submit the form, wait for review, and get approved.
At least, that is how it used to work.



A few years back, when I was working with a job board that had millions of jobs, I became best friends with that form. I submitted quota requests, showed that the existing quota was being burned through by legitimate job URLs, and within 2–3 weeks, Google would increase the quota.
That was my experience, and it worked.




I also set up the API for SEOJobs.com a few years ago, and I was fortunate enough to get proper functioning access there, too.
Then one thing led to another, and I made a bonehead move that deleted my API. (Booooo! Shame on me!)



So I set it all up again. This time, I submitted requests for both SEOJobs.com and PPCJobs.com.
That was six months ago. Yep. No response in 2026 at all.
Not an approval. Not a rejection. Not a request for more information.
Simply NOTHING.



Since my own data is limited, I’ve been talking with Alexander Chukovski, who has worked with hundreds of job boards and puts my job board knowledge to shame.
He told me that none of the job boards he worked with over a roughly 10-12 month span received a response after submitting the same form.
That is not one random site getting ignored.



Google, it’s now your turn
Everything above shows a pattern across legitimate job boards that are trying to use an API that Google specifically says is for job-posting content.
Alexander also wrote about changes to the API documentation back in 2024, which aligns with the timeline during which successful quota requests appear to have slowed or stopped being reviewed and approved altogether.
Can I confirm the number is zero? No.
But based on my experience, Alexander’s experience, and the lack of responses from legitimate job boards, it sure looks like approval has become significantly less likely than it used to be.
And that is the frustrating part. If the answer is no, fine (I’ll just pout a bit in the corner.)



If the API is effectively locked down for new quota increases, that’s also fine.
If Google no longer wants to expand access because the API was abused to the point of exhaustion, I get that, too.
But then say that.



Do not leave the form sitting there like there is still a functioning review process.
Do not tell legitimate job boards to request more access if nobody is reviewing the requests.
Do not let people spend months waiting for a response that may never come.
Google does not owe us an indexing shortcut.
But if the front door is closed, please stop leaving the welcome mat out.
A free job indexing tool to determine if you’re actually getting service
OK, I’ve dangled the carrot long enough. I built a free tool for anyone with access to the API.
You can now find out in minutes whether it’s working the way you expected.
The Job Indexing Health Check is now available over on SEOJobs.com
It offers two levels of service (both free).




Validate that your URL is marked up correctly with the job schema AND that it’s appears to be a supported job posting page.
The “full check” analyzes your job schema, your API responses, and Google Search Console responses.
All the results that matter, none of the technical hoops to jump through.



The full results after running this report will look exactly like this (but hopefully you’ll get a 200 metadata response!) Example via SEOjobs API credentials, GSC, and job listing URL.
The full raw JSON response is also available at the bottom.




Yes, the tool is 100% free. For folks submitting all content through this API, apologies, not really in advance if your non-SEO content never made it to Google.
This post first appeared on the author’s website and is republished here with permission.

Learn the difference between notification, crawling, and indexing, and use a free tool to check whether your API is doing what you expect.

Google’s job Indexing API isn’t the shortcut you think it is

<div><img width="1140" height="580" src="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png 1140w, https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature-768x391.png 768w" sizes="(max-width: 1140px) 100vw, 1140px" /></div>A look at how Web Push advertising is adapting in 2026 through better compliance, stronger traffic quality, and more mature market growth.

<div><img width="1140" height="580" src="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png 1140w, https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature-768x391.png 768w" sizes="(max-width: 1140px) 100vw, 1140px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1140" height="580" src="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png" alt="" class="wp-image-481772" srcset="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature.png 1140w, https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-Feature-768x391.png 768w" sizes="(max-width: 1140px) 100vw, 1140px" /></figure>
</div>


<p>Predictability is not the exact adjective we can apply to Push notifications. One day, they are at their all-time high; another, Google rolls out an update, and everything goes south very quickly.</p>



<p>Changes in platform policies have taken many businesses aback. In this article, we answer one of the most pressing questions: Has Web Push lost its momentum, or is it simply evolving — and if so, into what?</p>



<p>Let’s take a closer look at the state of the Web Push advertising market and explore its key challenges, major trends, and the opportunities available to those adapting to this changing environment.</p>



<h2 class="wp-block-heading" id="h-how-web-push-changed-in-2024-2025">How Web Push changed in 2024–2025</h2>



<p>In the fourth quarter of 2024, Google introduced updates that made the unsubscribe option more accessible on Android and strengthened its Google Safe Browsing (GSB) policies.</p>



<p>This update brings <a href="https://blog.rollerads.com/2025/04/14/push-notification-market-dead-or-alive/" target="_blank" rel="noopener sponsored nofollow">important changes</a> to the Web Push ad ecosystem.</p>



<h3 class="wp-block-heading" id="h-what-drove-the-shift-in-web-push">What drove the shift in Web Push</h3>



<p>As Google said, these changes were made to improve the user experience and maintain a healthier online ecosystem. By implementing stricter regulations, Google tried to make Push notifications seem less intrusive, misleading, or associated with clickbait. As part of these efforts, certain phrases and promotional tactics were restricted or banned altogether. At the end of the day, Google’s goals were to:</p>



<ul class="wp-block-list">
<li>Increase user control and transparency.</li>



<li>Reduce abusive or deceptive notification practices.</li>



<li>Improve overall engagement quality.</li>
</ul>



<h3 class="wp-block-heading" id="h-how-the-changes-impacted-the-industry">How the changes impacted the industry</h3>



<p>From the first day of this update, everyone noticed changes. An easier opt-out process provoked a spike in the number of unsubs. Some publishers experienced losses in subscriber bases and revenue pressure.</p>



<p>Right after the update, many domains were banned, flagged, or restricted due to compliance issues and negative quality signals. Everyone felt this strike; in fact, even on our platform, unsubscribe rates rose by 30–40% in some cases. Although we did everything we could to save users’ performance, the damage was done, and many clients faced immediate challenges that had to be resolved.</p>



<p>As a typical saturation cycle suggests, after such big changes, weaker players naturally exit, but this time, tight restrictions triggered a broader structural adjustment in the ecosystem. As the restrictions continue into 2026, one thing is clear: adapting to the new reality is no longer a competitive advantage; it’s a necessity.</p>



<p>To understand the future of Web Push, we need to look beyond recent platform updates and focus on the bigger picture. <a href="https://www.statista.com/" target="_blank" rel="noopener sponsored nofollow">Statista’s global forecast</a> provides exactly that perspective.</p>



<h2 class="wp-block-heading" id="h-a-data-driven-look-at-the-future-of-web-push">A data-driven look at the future of Web Push</h2>



<p>Despite these fluctuations and instability, experts expect <a href="https://www.statista.com/outlook/amo/advertising/direct-messaging-advertising/web-push-advertising/worldwide?currency=USD#ad-spending" target="_blank" rel="noopener sponsored nofollow">the Web Push advertising industry to continue to grow</a>. Most likely, compliance, traffic quality, and long-term sustainability will be valued more than rapid expansion.</p>



<p><strong>Global market dynamics:</strong>



<ul class="wp-block-list">
<li>Global web push ad spending in 2026: ~US$3.22 billion</li>



<li>Projected global market volume by 2030: ~US$3.61 billion</li>



<li>CAGR (2026–2030): ~2.88% </li>
</ul>



<p>Based on this compound growth rate, the market is expected to expand at a steady but moderate pace over the forecast period:</p>



<ul class="wp-block-list">
<li>2026: ~US$3.22 billion </li>



<li>2027: ~US$3.31 billion </li>



<li>2028: ~US$3.41 billion </li>



<li>2029: ~US$3.51 billion</li>



<li>2030: ~US$3.61 billion</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1200" height="1165" src="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-1.png" alt="" class="wp-image-481775" srcset="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-1.png 1200w, https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-1-768x746.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /><figcaption class="wp-element-caption"><em>Source: </em><a href="https://bit.ly/4b84TBk"><em>RollerAds</em></a><em><a href="https://bit.ly/4b84TBk" target="_blank" rel="noopener sponsored nofollow"> </a></em><a href="https://bit.ly/4b84TBk"><em>blog</em></a></figcaption></figure>
</div>


<p>While the Web Push market continues to expand, growth has become noticeably more moderate than in previous years. A CAGR of approximately 2.88% suggests that the channel is entering a more mature stage of development, moving away from its earlier position as a rapidly growing performance marketing format.</p>



<p>The industry&#8217;s current trajectory points to slow growth rather than large-scale expansion. But this trend shows that the market is stabilizing and becoming more sustainable. This is a natural shift in the channel&#8217;s evolutionary process. These changes are not restricting the growth of the market but creating conditions to cultivate it.&nbsp;</p>



<h3 class="wp-block-heading" id="h-regional-forecast-snippets">Regional forecast snippets</h3>



<p>Statista regional breakdowns also indicate continued growth through 2029–2030, although at different rates depending on market maturity:</p>



<ul class="wp-block-list">
<li><a href="https://www.statista.com/outlook/amo/advertising/direct-messaging-advertising/web-push-advertising/americas#ad-spending" target="_blank" rel="noopener sponsored nofollow">Americas</a>:<br>~US$1.53 billion (2026) → ~US$1.69 billion (2030), CAGR ~2.52% </li>



<li><a href="https://www.statista.com/outlook/amo/advertising/direct-messaging-advertising/web-push-advertising/g7#ad-spending" target="_blank" rel="noopener sponsored nofollow">G7 countries</a>:<br>~US$1.85 billion (2026) → ~US$2.03 billion (2030), CAGR ~2.32% </li>



<li><a href="https://www.statista.com/outlook/amo/advertising/direct-messaging-advertising/web-push-advertising/mena#ad-spending" target="_blank" rel="noopener sponsored nofollow">MENA region</a>:<br>~US$59.08 million (2026) → ~US$64.45 million (2030), CAGR ~2.20% </li>



<li><a href="https://www.statista.com/outlook/amo/advertising/direct-messaging-advertising/web-push-advertising/eaeu#ad-spending" target="_blank" rel="noopener sponsored nofollow">EAEU markets</a>:<br>~US$29.71 million (2026) → ~US$32.81 million (2030), CAGR ~2.51%</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1201" height="1165" src="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-2.png" alt="" class="wp-image-481776" srcset="https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-2.png 1201w, https://searchengineland.com/wp-content/seloads/2026/07/RollerAds-20260716-2-768x745.png 768w" sizes="(max-width: 1201px) 100vw, 1201px" /><figcaption class="wp-element-caption"><em>Source: </em><a href="https://bit.ly/4b84TBk" target="_blank" rel="noopener sponsored nofollow"><em>RollerAds blog</em></a></figcaption></figure>
</div>


<p>As you can see, there is a similarly steady growth across all regions. With that being said, the G7 and MENA regions are growing more slowly, suggesting these markets are already quite mature and expanding at a steadier pace. The Americas and EAEU markets show slightly higher growth but remain within a mature-market range.</p>



<p>Overall, regional differences don&#8217;t show fundamentally different growth directions. They mostly reflect varying levels of market maturity and digital advertising penetration.</p>



<h2 class="wp-block-heading" id="h-what-the-forecast-means-for-the-future-of-web-push">What the forecast means for the future of Web Push</h2>



<p>Based on Statista’s market outlook, we can say that growth in the Web Push advertising industry will be steady and consistent. Real-time and targeted messaging are the main features that will get the attention. Likewise, platform policies and enforcement mechanisms will continue to evolve. All these are demonstrations of an ongoing evolutionary process.</p>



<p>As restriction mechanisms become more sophisticated and detection systems continue to improve, low-quality traffic sources and questionable practices are being filtered out more effectively. This way, overall standards across the ecosystem are becoming higher, creating a healthier environment for advertisers, publishers, and users alike.</p>



<p>This shift should not be seen as a sign of decline. On the contrary, it shows a transition toward higher standards and, ultimately, higher CTR.</p>



<p>As the overall volume of messages decreases, the pressure on users is reduced. After some time (typically a year), this leads to increased user engagement and improved CTR.</p>



<h2 class="wp-block-heading" id="h-quality-over-quantity-a-new-market-reality">Quality over quantity: A new market reality</h2>



<p>Due to increasing pressure on low-quality and disruptive content, both the supply and demand sides of the ecosystem started to adjust, making the effects of these structural changes visible across the industry. The supply is lower, making short-term increases in traffic costs inevitable, but reduced competition also benefited higher-quality advertisers.</p>



<p>We expect that, over time, the perception of the format can and will improve, increasing demand from Tier 1 and Tier 2 advertisers.</p>



<p>But in the short term, the transition brings fluctuations in volume and performance. However, these spikes and drops do not harm the market, as it remains stable.</p>



<p>A volume-driven phase is slowly becoming history. Performance- and ROI-oriented environments replace it. With such changes, all participants are going through adaptation:</p>



<ul class="wp-block-list">
<li>Old strategies are no longer effective.</li>



<li>New optimization frameworks are still forming.</li>



<li>Traffic providers develop new technical solutions to meet stricter standards.</li>



<li>Advertisers are reworking their funnels, improving targeting strategies, and placing greater emphasis on long-term customer value rather than short-term ROI.</li>
</ul>



<h2 class="wp-block-heading" id="h-where-web-push-is-heading-next">Where Web Push is heading next</h2>



<p>Right now, in some segments, there is still volatility remaining, but overall strategy shifts to a slow but steady expansion:</p>



<ul class="wp-block-list">
<li>Inventory becomes more selective but higher quality.</li>



<li>Low-quality traffic continues to decline.</li>



<li>Each subscriber becomes more valuable over time.</li>
</ul>



<p>For everyone in the business, be that advertisers, publishers, or even networks, the volume is nothing if it is not relevant and of poor quality. This trend brings more informative and meaningful ads, rather than those designed solely to maximize CTR.</p>



<p>Our response? Well, as an ad network, we adapt to the changes. We know everything about Web Push notifications, including optimization tips and policy shifts. And yes, we&#8217;re always committed to helping our partners grow in the evolving Web Push landscape. <a href="https://bit.ly/4g0E4m7" target="_blank" rel="noopener sponsored nofollow">Register now</a> and see for yourself.</p>


Predictability is not the exact adjective we can apply to Push notifications. One day, they are at their all-time high; another, Google rolls out an update, and everything goes south very quickly.
Changes in platform policies have taken many businesses aback. In this article, we answer one of the most pressing questions: Has Web Push lost its momentum, or is it simply evolving — and if so, into what?
Let’s take a closer look at the state of the Web Push advertising market and explore its key challenges, major trends, and the opportunities available to those adapting to this changing environment.
How Web Push changed in 2024–2025
In the fourth quarter of 2024, Google introduced updates that made the unsubscribe option more accessible on Android and strengthened its Google Safe Browsing (GSB) policies.
This update brings important changes to the Web Push ad ecosystem.
What drove the shift in Web Push
As Google said, these changes were made to improve the user experience and maintain a healthier online ecosystem. By implementing stricter regulations, Google tried to make Push notifications seem less intrusive, misleading, or associated with clickbait. As part of these efforts, certain phrases and promotional tactics were restricted or banned altogether. At the end of the day, Google’s goals were to:
Increase user control and transparency.
Reduce abusive or deceptive notification practices.
Improve overall engagement quality.
How the changes impacted the industry
From the first day of this update, everyone noticed changes. An easier opt-out process provoked a spike in the number of unsubs. Some publishers experienced losses in subscriber bases and revenue pressure.
Right after the update, many domains were banned, flagged, or restricted due to compliance issues and negative quality signals. Everyone felt this strike; in fact, even on our platform, unsubscribe rates rose by 30–40% in some cases. Although we did everything we could to save users’ performance, the damage was done, and many clients faced immediate challenges that had to be resolved.
As a typical saturation cycle suggests, after such big changes, weaker players naturally exit, but this time, tight restrictions triggered a broader structural adjustment in the ecosystem. As the restrictions continue into 2026, one thing is clear: adapting to the new reality is no longer a competitive advantage; it’s a necessity.
To understand the future of Web Push, we need to look beyond recent platform updates and focus on the bigger picture. Statista’s global forecast provides exactly that perspective.
A data-driven look at the future of Web Push
Despite these fluctuations and instability, experts expect the Web Push advertising industry to continue to grow. Most likely, compliance, traffic quality, and long-term sustainability will be valued more than rapid expansion.
Global market dynamics:




Global web push ad spending in 2026: ~US$3.22 billion
Projected global market volume by 2030: ~US$3.61 billion
CAGR (2026–2030): ~2.88% 
Based on this compound growth rate, the market is expected to expand at a steady but moderate pace over the forecast period:
2026: ~US$3.22 billion 
2027: ~US$3.31 billion 
2028: ~US$3.41 billion 
2029: ~US$3.51 billion
2030: ~US$3.61 billion
Source: RollerAds blog



While the Web Push market continues to expand, growth has become noticeably more moderate than in previous years. A CAGR of approximately 2.88% suggests that the channel is entering a more mature stage of development, moving away from its earlier position as a rapidly growing performance marketing format.
The industry’s current trajectory points to slow growth rather than large-scale expansion. But this trend shows that the market is stabilizing and becoming more sustainable. This is a natural shift in the channel’s evolutionary process. These changes are not restricting the growth of the market but creating conditions to cultivate it. 
Regional forecast snippets
Statista regional breakdowns also indicate continued growth through 2029–2030, although at different rates depending on market maturity:
Americas:
~US$1.53 billion (2026) → ~US$1.69 billion (2030), CAGR ~2.52% 
G7 countries:
~US$1.85 billion (2026) → ~US$2.03 billion (2030), CAGR ~2.32% 
MENA region:
~US$59.08 million (2026) → ~US$64.45 million (2030), CAGR ~2.20% 
EAEU markets:
~US$29.71 million (2026) → ~US$32.81 million (2030), CAGR ~2.51%
Source: RollerAds blog



As you can see, there is a similarly steady growth across all regions. With that being said, the G7 and MENA regions are growing more slowly, suggesting these markets are already quite mature and expanding at a steadier pace. The Americas and EAEU markets show slightly higher growth but remain within a mature-market range.
Overall, regional differences don’t show fundamentally different growth directions. They mostly reflect varying levels of market maturity and digital advertising penetration.
What the forecast means for the future of Web Push
Based on Statista’s market outlook, we can say that growth in the Web Push advertising industry will be steady and consistent. Real-time and targeted messaging are the main features that will get the attention. Likewise, platform policies and enforcement mechanisms will continue to evolve. All these are demonstrations of an ongoing evolutionary process.
As restriction mechanisms become more sophisticated and detection systems continue to improve, low-quality traffic sources and questionable practices are being filtered out more effectively. This way, overall standards across the ecosystem are becoming higher, creating a healthier environment for advertisers, publishers, and users alike.
This shift should not be seen as a sign of decline. On the contrary, it shows a transition toward higher standards and, ultimately, higher CTR.
As the overall volume of messages decreases, the pressure on users is reduced. After some time (typically a year), this leads to increased user engagement and improved CTR.
Quality over quantity: A new market reality
Due to increasing pressure on low-quality and disruptive content, both the supply and demand sides of the ecosystem started to adjust, making the effects of these structural changes visible across the industry. The supply is lower, making short-term increases in traffic costs inevitable, but reduced competition also benefited higher-quality advertisers.
We expect that, over time, the perception of the format can and will improve, increasing demand from Tier 1 and Tier 2 advertisers.
But in the short term, the transition brings fluctuations in volume and performance. However, these spikes and drops do not harm the market, as it remains stable.
A volume-driven phase is slowly becoming history. Performance- and ROI-oriented environments replace it. With such changes, all participants are going through adaptation:
Old strategies are no longer effective.
New optimization frameworks are still forming.
Traffic providers develop new technical solutions to meet stricter standards.
Advertisers are reworking their funnels, improving targeting strategies, and placing greater emphasis on long-term customer value rather than short-term ROI.
Where Web Push is heading next
Right now, in some segments, there is still volatility remaining, but overall strategy shifts to a slow but steady expansion:
Inventory becomes more selective but higher quality.
Low-quality traffic continues to decline.
Each subscriber becomes more valuable over time.
For everyone in the business, be that advertisers, publishers, or even networks, the volume is nothing if it is not relevant and of poor quality. This trend brings more informative and meaningful ads, rather than those designed solely to maximize CTR.
Our response? Well, as an ad network, we adapt to the changes. We know everything about Web Push notifications, including optimization tips and policy shifts. And yes, we’re always committed to helping our partners grow in the evolving Web Push landscape. Register now and see for yourself.

A look at how Web Push advertising is adapting in 2026 through better compliance, stronger traffic quality, and more mature market growth.

Web Push advertising in 2026: Market trends and challenges by RollerAds

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads.png" class="attachment-large size-large wp-post-image" alt="Google AI Mode ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>High CPC searches were far likelier to show AI text ads, while paid placements rarely boosted citations or organic rankings.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads.png" class="attachment-large size-large wp-post-image" alt="Google AI Mode ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google’s AI Mode showed text ads on 29.45% of commercial queries in a new SE Ranking study, less than a year after ads began appearing in AI-generated search answers.</p>



<p>Ads appeared on 14,733 queries in the study, which analyzed U.S. commercial searches where text ads could appear, excluding product carousels.</p>



<p><strong>AI Mode ad adoption accelerated</strong>.<strong> </strong>SE Ranking said ads began appearing in AI Mode responses in late 2025. By mid-2026, nearly one in three commercial queries in its data set showed a text ad. SE Ranking said the real ad rate may be higher because AI Mode results are inconsistent across sessions.</p>



<p><strong>Two advertisers often appeared together</strong>. Most AI Mode ad blocks included more than one advertiser. SE Ranking found that 71.1% of ad-triggering queries showed two ads in the same AI Mode response, while 28.9% showed only one.</p>



<p><strong>CPC best predicted ad visibility.</strong> Higher-cost keywords were much more likely to trigger AI Mode ads.</p>



<ul class="wp-block-list">
<li>Ad presence was 24.33% for keywords with CPCs below $2. </li>



<li>It rose to 32.45% for keywords between $2 and $10, then jumped to 53.56% for keywords at $10 or more.</li>



<li>SE Ranking said search volume and keyword difficulty did not show the same relationship with ad frequency.</li>
</ul>



<p><strong>Ad presence varied across categories</strong>. Pets had the highest rate, with ads appearing on 72.38% of analyzed keywords. Healthcare had the lowest, at 2.64%.</p>



<ul class="wp-block-list">
<li>Higher-ad categories were typically lead-generation markets with clear paths to paid conversions. </li>



<li>Lower-ad categories were more likely to involve informational or YMYL intent, where commercial demand may be lower or Google may be more cautious.</li>
</ul>



<p><strong>Advertisers were rarely cited</strong>. Buying an AI Mode ad didn&#8217;t make advertisers more likely to be cited as a source in the same response. Only 11.53% of advertiser domains appeared among the cited sources for the keywords they advertised on. At the URL level, overlap fell to 1.95%.</p>



<ul class="wp-block-list">
<li>This held true even after comparing advertisers with similar non-advertising domains based on domain strength, backlinks, referring domains, and organic visibility, SE Ranking said.</li>
</ul>



<p><strong>Organic overlap was limited.</strong> Advertisers also rarely ranked organically for the same keywords. Only 2.32% of advertised URLs ranked organically for the queries where their ads appeared. At the domain level, overlap increased to 15.35%.</p>



<ul class="wp-block-list">
<li>About 85% of advertisers didn&#8217;t appear in organic results for the same keywords where they showed AI Mode ads, according to the study.</li>
</ul>



<p><strong>Why we care.</strong> Buying visibility in AI Mode doesn&#8217;t increase your chances of being cited or ranking organically. Treat AI Mode ads, cited sources, and organic rankings as separate visibility channels.</p>



<p><strong>About the data. </strong>SE Ranking analyzed 50,032 commercial keywords across 20 niches, averaging about 2,500 keywords per niche. The data reflects U.S. AI Mode results collected on June 30. SE Ranking noted that ad behavior may change as Google expands AI-specific formats.</p>



<p><strong>The study. </strong><a href="https://seranking.com/blog/google-ai-mode-ads/" target="_blank" rel="noopener">AI Mode now shows ads on nearly 1 in 3 commercial queries</a>


Google’s AI Mode showed text ads on 29.45% of commercial queries in a new SE Ranking study, less than a year after ads began appearing in AI-generated search answers.
Ads appeared on 14,733 queries in the study, which analyzed U.S. commercial searches where text ads could appear, excluding product carousels.
AI Mode ad adoption accelerated. SE Ranking said ads began appearing in AI Mode responses in late 2025. By mid-2026, nearly one in three commercial queries in its data set showed a text ad. SE Ranking said the real ad rate may be higher because AI Mode results are inconsistent across sessions.
Two advertisers often appeared together. Most AI Mode ad blocks included more than one advertiser. SE Ranking found that 71.1% of ad-triggering queries showed two ads in the same AI Mode response, while 28.9% showed only one.
CPC best predicted ad visibility. Higher-cost keywords were much more likely to trigger AI Mode ads.
Ad presence was 24.33% for keywords with CPCs below $2. 
It rose to 32.45% for keywords between $2 and $10, then jumped to 53.56% for keywords at $10 or more.
SE Ranking said search volume and keyword difficulty did not show the same relationship with ad frequency.
Ad presence varied across categories. Pets had the highest rate, with ads appearing on 72.38% of analyzed keywords. Healthcare had the lowest, at 2.64%.
Higher-ad categories were typically lead-generation markets with clear paths to paid conversions. 
Lower-ad categories were more likely to involve informational or YMYL intent, where commercial demand may be lower or Google may be more cautious.
Advertisers were rarely cited. Buying an AI Mode ad didn’t make advertisers more likely to be cited as a source in the same response. Only 11.53% of advertiser domains appeared among the cited sources for the keywords they advertised on. At the URL level, overlap fell to 1.95%.
This held true even after comparing advertisers with similar non-advertising domains based on domain strength, backlinks, referring domains, and organic visibility, SE Ranking said.
Organic overlap was limited. Advertisers also rarely ranked organically for the same keywords. Only 2.32% of advertised URLs ranked organically for the queries where their ads appeared. At the domain level, overlap increased to 15.35%.
About 85% of advertisers didn’t appear in organic results for the same keywords where they showed AI Mode ads, according to the study.
Why we care. Buying visibility in AI Mode doesn’t increase your chances of being cited or ranking organically. Treat AI Mode ads, cited sources, and organic rankings as separate visibility channels.
About the data. SE Ranking analyzed 50,032 commercial keywords across 20 niches, averaging about 2,500 keywords per niche. The data reflects U.S. AI Mode results collected on June 30. SE Ranking noted that ad behavior may change as Google expands AI-specific formats.
The study. AI Mode now shows ads on nearly 1 in 3 commercial queries

High CPC searches were far likelier to show AI text ads, while paid placements rarely boosted citations or organic rankings.

Google AI Mode ads reach nearly 30% of queries: Study

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="6 mistakes that hurt ecommerce campaigns on Google Ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google is testing new PMax controls that let advertisers control ads showing on Search Partners and the Google Display Network.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="6 mistakes that hurt ecommerce campaigns on Google Ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is testing a new Partners (Alpha) setting in Performance Max that gives advertisers the ability to opt in or out of Search Partners and the Google Display Network—a level of control that hasn&#8217;t previously existed in the automated campaign type.</p>



<p><strong>What&#8217;s happening</strong>. Some advertisers are seeing a new Partners (Alpha) setting within Performance Max campaigns that lets them choose whether to include:</p>



<ul class="wp-block-list">
<li><strong>Search Partners</strong></li>



<li><strong>Google Display Network (GDN)</strong></li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="800" height="479" src="https://searchengineland.com/wp-content/seloads/2026/07/Pmax-Partner-Setting.jpeg" alt="" class="wp-image-482470" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Pmax-Partner-Setting.jpeg 800w, https://searchengineland.com/wp-content/seloads/2026/07/Pmax-Partner-Setting-768x460.jpeg 768w" sizes="(max-width: 800px) 100vw, 800px" /></figure>



<p>Until now, both networks were automatically included in Performance Max with no option to exclude them.</p>



<p><strong>Why we care</strong>. The update gives advertisers greater control over where Performance Max ads appear, making it easier to align inventory with campaign objectives. Those focused on efficiency metrics such as ROAS or CPA can now test whether excluding certain networks improves performance.</p>



<p><strong>What we&#8217;re watching</strong>. The feature is currently labelled Alpha, indicating it is only available to a limited number of advertisers. Google has not announced when—or if—it plans to roll the setting out more broadly.</p>



<p><strong>The bottom line</strong>. Google&#8217;s new Partners (Alpha) setting could give Performance Max advertisers one of their most requested controls: the ability to decide whether campaigns run across Search Partners and the Display Network, rather than relying entirely on Google&#8217;s automation.</p>



<p><strong>Spotted</strong>. This update was spotted by PPC Growth Strategist Saquib Syed, who shared spotting it on LinkedIn. </p>


Google is testing a new Partners (Alpha) setting in Performance Max that gives advertisers the ability to opt in or out of Search Partners and the Google Display Network—a level of control that hasn’t previously existed in the automated campaign type.
What’s happening. Some advertisers are seeing a new Partners (Alpha) setting within Performance Max campaigns that lets them choose whether to include:
Search Partners
Google Display Network (GDN)




Until now, both networks were automatically included in Performance Max with no option to exclude them.
Why we care. The update gives advertisers greater control over where Performance Max ads appear, making it easier to align inventory with campaign objectives. Those focused on efficiency metrics such as ROAS or CPA can now test whether excluding certain networks improves performance.
What we’re watching. The feature is currently labelled Alpha, indicating it is only available to a limited number of advertisers. Google has not announced when—or if—it plans to roll the setting out more broadly.
The bottom line. Google’s new Partners (Alpha) setting could give Performance Max advertisers one of their most requested controls: the ability to decide whether campaigns run across Search Partners and the Display Network, rather than relying entirely on Google’s automation.
Spotted. This update was spotted by PPC Growth Strategist Saquib Syed, who shared spotting it on LinkedIn.

Google is testing new PMax controls that let advertisers control ads showing on Search Partners and the Google Display Network.

Google tests Performance Max network controls with new Partners (Alpha) setting

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself.png" class="attachment-large size-large wp-post-image" alt="Google AI Mode cites Google" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google-owned business and product cards are taking a bigger role in AI Mode, especially for local and shopping searches.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself.png" class="attachment-large size-large wp-post-image" alt="Google AI Mode cites Google" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/google-ai-mode-cites-itself-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google’s AI Mode increased citations to google.com by 8.4x in about two months, making it the No. 2 cited domain in Profound’s tracking.</p>



<p>The increase came almost entirely from Google Business Profiles and Product Knowledge Panels, according to Profound. Those Google-hosted cards now appear within AI Mode answers for many local and product searches.</p>



<p><strong>Google cards moved up. </strong>AI Mode now surfaces Google Business Profiles as inline panels for local-intent queries.</p>



<p>These panels can display a business’s hours, photos, location, and reviews before users reach the company’s website. Profound said the shift makes the Google-hosted profile the first page many users see.</p>



<p><strong>Local categories led. </strong>The change was strongest in industries where local intent drives revenue, including:</p>



<ul class="wp-block-list">
<li>Hospitality and travel</li>



<li>Home services</li>



<li>Restaurants and dining</li>



<li>Real estate</li>



<li>Healthcare</li>
</ul>



<p id="h-product-panels-gained-ground"><strong>Product panels gained ground</strong>. Product searches also shifted toward Google-hosted results. Queries about comparisons, compatibility, or specifications increasingly surfaced Product Knowledge Panels instead of direct links to ecommerce or brand websites, Profound said.</p>



<p id="h-product-panels-gained-ground"><strong>Why we care. </strong>Your Google-hosted profile may shape a user’s first impression before they ever reach your website. Missing hours, outdated photos, incomplete information, or poor reviews can cost you the click before users visit your site.</p>



<p id="h-product-panels-gained-ground"><strong>About the data. </strong>Profound tracked AI Mode citation share from April 15 through June 30, analyzing more than 32 million google.com/searchviewer instances.</p>



<p><strong>The report. </strong><a href="https://www.tryprofound.com/blog/google-com-is-now-ai-mode-s-2-cited-domain">Google AI Mode&#8217;s shift to citing itself</a>


Google’s AI Mode increased citations to google.com by 8.4x in about two months, making it the No. 2 cited domain in Profound’s tracking.
The increase came almost entirely from Google Business Profiles and Product Knowledge Panels, according to Profound. Those Google-hosted cards now appear within AI Mode answers for many local and product searches.
Google cards moved up. AI Mode now surfaces Google Business Profiles as inline panels for local-intent queries.
These panels can display a business’s hours, photos, location, and reviews before users reach the company’s website. Profound said the shift makes the Google-hosted profile the first page many users see.
Local categories led. The change was strongest in industries where local intent drives revenue, including:
Hospitality and travel
Home services
Restaurants and dining
Real estate
Healthcare
Product panels gained ground. Product searches also shifted toward Google-hosted results. Queries about comparisons, compatibility, or specifications increasingly surfaced Product Knowledge Panels instead of direct links to ecommerce or brand websites, Profound said.
Why we care. Your Google-hosted profile may shape a user’s first impression before they ever reach your website. Missing hours, outdated photos, incomplete information, or poor reviews can cost you the click before users visit your site.
About the data. Profound tracked AI Mode citation share from April 15 through June 30, analyzing more than 32 million google.com/searchviewer instances.
The report. Google AI Mode’s shift to citing itself

Google-owned business and product cards are taking a bigger role in AI Mode, especially for local and shopping searches.

Google is AI Mode’s No. 2 most-cited domain: Report

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image.png" class="attachment-large size-large wp-post-image" alt="Where AI agents get stuck on your site" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI agents retrieve most B2B website content, but pricing often sends them to third-party sources. Learn why and how to fix it.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image.png" class="attachment-large size-large wp-post-image" alt="Where AI agents get stuck on your site" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Where-AI-agents-get-stuck-on-your-site-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The next mass frontier of AI is agentic:</p>



<ul class="wp-block-list">
<li>Google introduced agentic tasks in Search.</li>



<li>The <a href="https://radar.cloudflare.com/traffic#bot-vs-human" target="_blank" rel="noopener">web gets more visits from bots than humans</a> now.</li>



<li>Salesforce found 20% of sales coming from agents marks a signpost.</li>



<li>60% of companies use agents live in production, and <a href="https://learn.g2.com/g2-2025-ai-agent-insight-report" target="_blank" rel="noopener">3 out of 4 companies</a> invest in AI agents.</li>
</ul>



<p>To figure out how ready B2B sites are for agentic visitors, I teamed up with David Kaufman, founder of <a href="https://siteline.ai/" target="_blank" rel="noopener">Siteline</a>, and I analyzed how agents scan websites and where they get stuck. The answer: most sites are agent-ready, but there is one critical breaking point.</p>



<p>Agents don’t read websites like humans. They receive a task, search the web, fetch pages, extract facts, and cite the sources they used. A page can persuade a human and still fail an agent if the facts are hard to find (opacity), hard to fetch (machine-readability), or hard to cite (access friction).&nbsp;</p>



<p>AI agents turn websites from showrooms into barcodes.</p>



<p>How we looked at agent behavior:</p>



<ul class="wp-block-list">
<li>The agent had to find the official site itself. We did not provide starting links, eg to homepages.</li>



<li>We gave agents three buyer-related tasks for 100 B2B products: find pricing/features, integrations, and security/compliance. We ran each task five times to measure the impact of the probabilistic nature of LLMs.</li>



<li>We weren’t comparing whether or not the information existed somewhere on the web; instead, we measured whether the agent could reliably answer from the vendor’s own site.&nbsp;</li>
</ul>



<p><a href="https://www.growth-memo.com/embed?transparent=1" rel="noopener noreferrer">View embedded content</a>



<h2 class="wp-block-heading" id="h-1-pricing-breaks-first-party-sites">1. Pricing breaks first-party sites</h2>



<p>The moment a prospect looks at pricing, they stop browsing and start comparing. High buyer intent, bottom of the funnel. That makes pricing the hardest and most important test of whether a vendor site can serve agents directly.</p>



<p>Pricing also sits in a triangle of 3 “wants” that good pricing pages need to satisfy:</p>



<ul class="wp-block-list">
<li>Companies want to control pricing disclosure.</li>



<li>Buyers want fast comparison.</li>



<li>Agents need clear, fetchable, citable facts.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1159" src="https://searchengineland.com/wp-content/seloads/2026/07/Pricing-breaks-first-party-sites.png" alt="Pricing breaks first-party sites" class="wp-image-482352" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Pricing-breaks-first-party-sites.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Pricing-breaks-first-party-sites-768x435.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Pricing-breaks-first-party-sites-1536x869.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>When AI agents try to retrieve pricing, they get stuck much more than for security or integrations.</p>



<ul class="wp-block-list">
<li>Pricing/features: 79% first-party answer rate, 84% first-party citation share.</li>



<li>Integrations: 93% and 99%.</li>



<li>Security: 92% and 99%.</li>



<li>Pricing/features produced 77% of all third-party citations.</li>
</ul>



<p>If you wonder whether that’s because some B2B companies don’t publicly show pricing, you’re only half right.</p>



<h2 class="wp-block-heading" id="h-2-hidden-pricing-is-only-part-of-it">2. Hidden pricing is only part of it</h2>



<p>Hiding prices forces agents to look elsewhere, but published prices do not fully solve the problem. Among pricing prompt runs where the vendor did not disclose a real price, 45% cited at least one third-party source. The other 55% stayed on first-party citations, usually by saying the vendor required contact sales or did not publish a concrete price.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1159" src="https://searchengineland.com/wp-content/seloads/2026/07/Hidden-pricing-is-only-part-of-it.png" alt="Hidden pricing is only part of it" class="wp-image-482353" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Hidden-pricing-is-only-part-of-it.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Hidden-pricing-is-only-part-of-it-768x435.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Hidden-pricing-is-only-part-of-it-1536x869.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>Even when the vendor showed a numeric public price, agents still cited at least one third-party source in 18% of runs, suggesting price can be on the page but still be hard for the agent to extract, trust, or cite cleanly.</p>



<p>You can try to hide your pricing, but you better make sure no one else knows and writes about it. Once it’s “out there”, it’s too late. If you have complex pricing methodology, the best way is to explain it clearly and make it accessible to agents.</p>



<p>Some pricing pages are visible to humans but not reliable enough for agents to parse and cite. You can’t always trust your eyes.</p>



<h2 class="wp-block-heading" id="h-3-agents-fail-for-three-reasons">3. Agents fail for three reasons</h2>



<p>Agents fail to retrieve pricing from a brand for 3 reasons: opacity, machine-readability, and access friction.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="965" height="546" src="https://searchengineland.com/wp-content/seloads/2026/07/image-141.png" alt="" class="wp-image-482346" srcset="https://searchengineland.com/wp-content/seloads/2026/07/image-141.png 965w, https://searchengineland.com/wp-content/seloads/2026/07/image-141-768x435.png 768w" sizes="(max-width: 965px) 100vw, 965px" /></figure>
</div>


<p>Example of an agent struggling to retrieve Zendesk’s pricing and pivoting to third-party sources.</p>



<ul class="wp-block-list">
<li><strong>Pricing opacity </strong>simply means the brand doesn’t publicly disclose the price, or it’s vaguely packaged. Opacity explains elevated fallback, meaning agents have to rely on third parties for information.</li>



<li><strong>Machine-readability</strong> describes the situation when prices exist, but agents still do not confidently extract them. Machine-readability explains fallback despite disclosed pricing. Machine-readability fails when the price is hard to extract because of page structure, JavaScript, calculators, toggles, screenshots, PDFs, or ambiguous tables.</li>



<li><strong>Access friction</strong> is what most people expect to be the problem with agents.&nbsp;The agent hits fetch failures, rate limits, blocking, or unreachable pages, making agent runs more costly.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1159" src="https://searchengineland.com/wp-content/seloads/2026/07/Agents-miss-pricing-at-three-gates.png" alt="Agents miss pricing at three gates" class="wp-image-482355" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Agents-miss-pricing-at-three-gates.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Agents-miss-pricing-at-three-gates-768x435.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Agents-miss-pricing-at-three-gates-1536x869.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>Access errors were not the main reason agents left first-party sources, but when they happened, they were severe. They appeared in only 7% of all runs. In pricing runs, access errors pushed third-party fallback to 77%, compared to 17% without access errors.</p>



<p>The impact of errors on agent run cost (tokens, web searches, fetches, retrieves, time) is significant when comparing the 90th with the 10th percentile in our study:</p>



<ul class="wp-block-list">
<li><strong>Cost:</strong> 4.4x</li>



<li><strong>Token:</strong> 4.7x</li>



<li><strong>Time:</strong> 2.0x</li>
</ul>



<p>Brands don’t pay that bill directly, but it is a useful proxy for friction. The harder your site is to retrieve, the more work an agent has to do before it can answer from your page. If your pricing page is blocked, slow, hard to fetch, or hard to parse, the agent has two choices: spend more work on your site… or get the answer somewhere else.</p>



<h2 class="wp-block-heading" id="h-4-the-fallback-web-is-messy">4. The fallback web is messy</h2>



<p>Fallback occurs when agents have to rely on third-party sources rather than first-party sources as a result of the three failure modes. This is the biggest risk because third-party information is spotty and beyond your control.</p>



<p>Agents do not fall back to one clean source category. They reconstruct pricing from a mixed web of explainers, directories, app stores, partner pages, and low-trust aggregators.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1159" src="https://searchengineland.com/wp-content/seloads/2026/07/Pricing-fallback-is-not-one-source.png" alt="Pricing fallback is not one source" class="wp-image-482356" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Pricing-fallback-is-not-one-source.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Pricing-fallback-is-not-one-source-768x435.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Pricing-fallback-is-not-one-source-1536x869.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>Key stats from the 580 pricing third-party citations:</p>



<ul class="wp-block-list">
<li><strong>52% were editorial</strong> (blogs, media articles, comparison guides, explainers, and other article-style pages).</li>



<li><strong>46% fell into the directory category</strong> (review, procurement, and software-listing sites such as G2, Capterra, Vendr, Tekpon, and similar domains).</li>



<li><strong>2% from broader ecosystem pages</strong> (app stores, marketplaces, partner pages, and integration directories tied to another platform).</li>
</ul>



<p>The examples show the risk of missing pricing transparency and agent stumbling blocks on your site.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1213" src="https://searchengineland.com/wp-content/seloads/2026/07/image-143.png" alt="" class="wp-image-482348" srcset="https://searchengineland.com/wp-content/seloads/2026/07/image-143.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/image-143-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/image-143-1536x910.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>Example journey:</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="2048" height="1213" src="https://searchengineland.com/wp-content/seloads/2026/07/Example-journey.png" alt="Example journey" class="wp-image-482359" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Example-journey.png 2048w, https://searchengineland.com/wp-content/seloads/2026/07/Example-journey-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Example-journey-1536x910.png 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>
</div>


<p>Here, failure mode indicates the reason the agent failed to obtain on-site / first-party pricing information.</p>



<h2 class="wp-block-heading" id="h-5-how-to-make-your-site-agent-proof">5. How to make your site agent-proof</h2>



<p>An agent-proof pricing page is how you keep the agent quoting you instead of a directory like Vendr. The fixes map to the three failure modes.</p>



<p><strong>Disclose the fact (opacity)</strong>



<ul class="wp-block-list">
<li>Publish real prices in text for every self-serve tier. If a tier is genuinely custom, say what drives the number instead of &#8220;contact sales.&#8221;</li>



<li>Keep plan names, prices, limits, and features on one canonical pricing URL, and point every other mention back to it.</li>



<li>Mark legacy plans clearly so third-party content can&#8217;t keep stale tiers alive.</li>
</ul>



<p><strong>Make the fact extractable (machine-readability)</strong>



<ul class="wp-block-list">
<li>Put prices in crawlable HTML. Many agent fetches never run JavaScript, so a price rendered client-side is invisible. In testing, prices in server HTML got read in under a second; a JavaScript-only price got missed.</li>



<li>Add schema.org Product and Offer markup with price and priceCurrency. This single lever moved a page from 73 to 93 in the readiness test.</li>



<li>Explain usage-based pricing in text, not a calculator-only widget.</li>
</ul>



<p><strong>Let the agent in (access friction)</strong>



<ul class="wp-block-list">
<li>Allow AI crawlers in robots.txt (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). Check you aren&#8217;t allowing Googlebot while blocking them.</li>



<li>Don&#8217;t block server-side AI fetches on pricing pages. Access errors hit only 7% of runs, but they push fallback from 17% to 77% when they do.</li>



<li>Keep the price early in the DOM and the page light. A 1 MB pricing page taxes every agent and pushes cheap runs to route around you.</li>
</ul>



<p>Fix opacity and machine-readability first; they drive most of the fallback. Then run the query yourself, &#8220;Find all pricing and features for [product],” and measure it with the skill below.</p>



<p><em>This post first appeared on the author’s website and is republished here with permission.</em>


The next mass frontier of AI is agentic:
Google introduced agentic tasks in Search.
The web gets more visits from bots than humans now.
Salesforce found 20% of sales coming from agents marks a signpost.
60% of companies use agents live in production, and 3 out of 4 companies invest in AI agents.
To figure out how ready B2B sites are for agentic visitors, I teamed up with David Kaufman, founder of Siteline, and I analyzed how agents scan websites and where they get stuck. The answer: most sites are agent-ready, but there is one critical breaking point.
Agents don’t read websites like humans. They receive a task, search the web, fetch pages, extract facts, and cite the sources they used. A page can persuade a human and still fail an agent if the facts are hard to find (opacity), hard to fetch (machine-readability), or hard to cite (access friction). 
AI agents turn websites from showrooms into barcodes.
How we looked at agent behavior:
The agent had to find the official site itself. We did not provide starting links, eg to homepages.
We gave agents three buyer-related tasks for 100 B2B products: find pricing/features, integrations, and security/compliance. We ran each task five times to measure the impact of the probabilistic nature of LLMs.
We weren’t comparing whether or not the information existed somewhere on the web; instead, we measured whether the agent could reliably answer from the vendor’s own site. 
View embedded content



1. Pricing breaks first-party sites
The moment a prospect looks at pricing, they stop browsing and start comparing. High buyer intent, bottom of the funnel. That makes pricing the hardest and most important test of whether a vendor site can serve agents directly.
Pricing also sits in a triangle of 3 “wants” that good pricing pages need to satisfy:
Companies want to control pricing disclosure.
Buyers want fast comparison.
Agents need clear, fetchable, citable facts.




When AI agents try to retrieve pricing, they get stuck much more than for security or integrations.
Pricing/features: 79% first-party answer rate, 84% first-party citation share.
Integrations: 93% and 99%.
Security: 92% and 99%.
Pricing/features produced 77% of all third-party citations.
If you wonder whether that’s because some B2B companies don’t publicly show pricing, you’re only half right.
2. Hidden pricing is only part of it
Hiding prices forces agents to look elsewhere, but published prices do not fully solve the problem. Among pricing prompt runs where the vendor did not disclose a real price, 45% cited at least one third-party source. The other 55% stayed on first-party citations, usually by saying the vendor required contact sales or did not publish a concrete price.




Even when the vendor showed a numeric public price, agents still cited at least one third-party source in 18% of runs, suggesting price can be on the page but still be hard for the agent to extract, trust, or cite cleanly.
You can try to hide your pricing, but you better make sure no one else knows and writes about it. Once it’s “out there”, it’s too late. If you have complex pricing methodology, the best way is to explain it clearly and make it accessible to agents.
Some pricing pages are visible to humans but not reliable enough for agents to parse and cite. You can’t always trust your eyes.
3. Agents fail for three reasons
Agents fail to retrieve pricing from a brand for 3 reasons: opacity, machine-readability, and access friction.




Example of an agent struggling to retrieve Zendesk’s pricing and pivoting to third-party sources.
Pricing opacity simply means the brand doesn’t publicly disclose the price, or it’s vaguely packaged. Opacity explains elevated fallback, meaning agents have to rely on third parties for information.
Machine-readability describes the situation when prices exist, but agents still do not confidently extract them. Machine-readability explains fallback despite disclosed pricing. Machine-readability fails when the price is hard to extract because of page structure, JavaScript, calculators, toggles, screenshots, PDFs, or ambiguous tables.
Access friction is what most people expect to be the problem with agents. The agent hits fetch failures, rate limits, blocking, or unreachable pages, making agent runs more costly.




Access errors were not the main reason agents left first-party sources, but when they happened, they were severe. They appeared in only 7% of all runs. In pricing runs, access errors pushed third-party fallback to 77%, compared to 17% without access errors.
The impact of errors on agent run cost (tokens, web searches, fetches, retrieves, time) is significant when comparing the 90th with the 10th percentile in our study:
Cost: 4.4x
Token: 4.7x
Time: 2.0x
Brands don’t pay that bill directly, but it is a useful proxy for friction. The harder your site is to retrieve, the more work an agent has to do before it can answer from your page. If your pricing page is blocked, slow, hard to fetch, or hard to parse, the agent has two choices: spend more work on your site… or get the answer somewhere else.
4. The fallback web is messy
Fallback occurs when agents have to rely on third-party sources rather than first-party sources as a result of the three failure modes. This is the biggest risk because third-party information is spotty and beyond your control.
Agents do not fall back to one clean source category. They reconstruct pricing from a mixed web of explainers, directories, app stores, partner pages, and low-trust aggregators.




Key stats from the 580 pricing third-party citations:
52% were editorial (blogs, media articles, comparison guides, explainers, and other article-style pages).
46% fell into the directory category (review, procurement, and software-listing sites such as G2, Capterra, Vendr, Tekpon, and similar domains).
2% from broader ecosystem pages (app stores, marketplaces, partner pages, and integration directories tied to another platform).
The examples show the risk of missing pricing transparency and agent stumbling blocks on your site.




Example journey:




Here, failure mode indicates the reason the agent failed to obtain on-site / first-party pricing information.
5. How to make your site agent-proof
An agent-proof pricing page is how you keep the agent quoting you instead of a directory like Vendr. The fixes map to the three failure modes.
Disclose the fact (opacity)




Publish real prices in text for every self-serve tier. If a tier is genuinely custom, say what drives the number instead of “contact sales.”
Keep plan names, prices, limits, and features on one canonical pricing URL, and point every other mention back to it.
Mark legacy plans clearly so third-party content can’t keep stale tiers alive.
Make the fact extractable (machine-readability)




Put prices in crawlable HTML. Many agent fetches never run JavaScript, so a price rendered client-side is invisible. In testing, prices in server HTML got read in under a second; a JavaScript-only price got missed.
Add schema.org Product and Offer markup with price and priceCurrency. This single lever moved a page from 73 to 93 in the readiness test.
Explain usage-based pricing in text, not a calculator-only widget.
Let the agent in (access friction)




Allow AI crawlers in robots.txt (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). Check you aren’t allowing Googlebot while blocking them.
Don’t block server-side AI fetches on pricing pages. Access errors hit only 7% of runs, but they push fallback from 17% to 77% when they do.
Keep the price early in the DOM and the page light. A 1 MB pricing page taxes every agent and pushes cheap runs to route around you.
Fix opacity and machine-readability first; they drive most of the fallback. Then run the query yourself, “Find all pricing and features for [product],” and measure it with the skill below.
This post first appeared on the author’s website and is republished here with permission.

AI agents retrieve most B2B website content, but pricing often sends them to third-party sources. Learn why and how to fix it.

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