<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations.png" class="attachment-large size-large wp-post-image" alt="How travel brands can earn AI recommendations" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>TripAdvisor, Google Business Profile, OTAs, and reviews help AI understand travel brands. Learn how to strengthen those signals.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations.png" class="attachment-large size-large wp-post-image" alt="How travel brands can earn AI recommendations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/How-travel-brands-can-earn-AI-recommendations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>AI Overviews and Google AI Mode now dominate conversations across the <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> community. One trend already stands out: Search is evolving from an information retrieval tool to a recommendation tool.</p>



<p>For travel brands, this changes the rules of online discovery. The challenge is no longer just helping search engines understand your website. It&#8217;s helping AI systems understand when your business should be recommended.</p>



<h2 class="wp-block-heading" id="h-how-ai-search-has-changed-travel-planning-nbsp">How AI search has changed travel planning&nbsp;</h2>



<p>Many users now spend substantial time every week interacting with large language models (LLMs). With LLMs, they can organize conversations by project and create folders for upcoming trips. They can also build on previous chats that already recognize their interests, travel preferences, and demographic profiles.</p>



<p>This marks a departure from the traditional search process. Historically, travel planning started with Google searches for topics like:</p>



<ul class="wp-block-list">
<li>&#8220;Hotels in Porto&#8221;</li>



<li>&#8220;Things to do in Rome&#8221;</li>



<li>&#8220;Best restaurants in Barcelona&#8221;</li>
</ul>



<p>Today, this process is far more conversational.</p>



<p>Rather than typing a series of disconnected searches, a traveler might create a new folder called &#8220;Summer 2026&#8221; in ChatGPT and start with a broad question that gradually evolves into a complete itinerary. For example:&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;Where should I stay in Porto for a quiet weekend within walking distance of the historic center?&#8221; </li>



<li>&#8220;Which area of Rome is best for families traveling with young children?&#8221;</li>
</ul>



<p>What follows is an ongoing conversation that might expand into restaurant recommendations, attractions, accommodation options, transportation advice, and day-by-day planning.</p>



<p>When travelers ask AI assistants these questions, they aren&#8217;t looking for a list of websites. Instead, they&#8217;re looking for a recommendation.</p>



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<h3 class="wp-block-heading" id="h-how-ai-overviews-impact-the-travel-search-experience">How AI Overviews impact the travel search experience</h3>



<p>AI Overviews synthesize information from multiple sources and present users with curated recommendations rather than a collection of links. As a result, trust, consistency, and contextual understanding become critical visibility factors.</p>



<p>A hotel may influence a traveler&#8217;s decision through an AI-generated response without leading to an immediate website visit. The traveler&#8217;s next action may be a branded search, a visit to a travel review site, or a booking through an online travel agency (OTA).</p>



<p>To earn recommendations from AI models, your brand first needs to be clearly defined. AI must have confidence in who you are, what you offer, who you serve, and when your brand is relevant.</p>



<p>To do this, choose one primary category and one clear position for your brand. Invest in digital PR and earn mentions beyond your own website. Aim to be included in travel articles that cover topics relevant to your category.</p>



<p>Most importantly, ensure your business information is accurate, consistent, and easy to interpret across your website, Google Business Profile, <a href="https://searchengineland.com/why-tripadvisor-still-matters-for-local-seo-in-2026-471311">TripAdvisor</a>, OTA listings, and social media platforms.</p>



<h3 class="wp-block-heading" id="h-zero-click-doesn-t-mean-zero-impact">Zero click doesn&#8217;t mean zero impact</h3>



<p>The way we measure search performance is changing. Traditional SEO metrics still matter. However, travel marketers should start expanding how they measure visibility.</p>



<p>One of the biggest mistakes is assuming that fewer clicks mean less visibility.</p>



<p>A traveler may discover your property through an AI-generated response, search for it later, visit a TripAdvisor profile, or book through another channel.</p>



<p>This is why branded search growth is becoming a valuable signal of AI visibility. Travel marketers should also monitor AI mentions, citations, and assisted conversions.</p>



<p>Assisted conversions reveal the channels and touchpoints that influence a booking, even if they aren&#8217;t the final source of the conversion. You can monitor these conversions in Google Analytics 4 by navigating to <em>Advertising &gt; Attribution &gt; Conversion Paths and Attribution Reports.</em>



<h2 class="wp-block-heading" id="h-why-tripadvisor-and-ota-listings-provide-semantic-context-for-ai-recommendations">Why TripAdvisor and OTA listings provide semantic context for AI recommendations</h2>



<p>TripAdvisor has become much more than a review platform. OTAs have become more than booking platforms.</p>



<p>When a user asks for recommendations, AI systems rarely rely on a single source. Instead, they build understanding by combining information from multiple platforms.</p>



<p>Your website is only one part of the ecosystem.</p>



<p>AI systems build confidence in recommendations by validating information across sources. What others say about your brand in reviews, travel guides, media mentions, OTA listings, or local citations increasingly matters. In many ways, this is simply online reputation at scale.</p>



<p>This additional context helps AI models determine when a property is relevant for specific traveler needs, such as:</p>



<ul class="wp-block-list">
<li>Family-friendly.</li>



<li>Popular with business travelers.</li>



<li>Located in a walkable area.</li>



<li>Known for exceptional dining.</li>



<li>Better suited to luxury or budget travelers.</li>
</ul>



<h3 class="wp-block-heading" id="h-how-to-differentiate-your-travel-brand">How to differentiate your travel brand</h3>



<p>A family-friendly hotel should consistently highlight family rooms, kids&#8217; activities, children&#8217;s pools, and family-focused reviews. A romantic hotel should reinforce signals like couples&#8217; stays, intimate atmospheres, spa experiences, and special-occasion packages.</p>



<p>Likewise, a business hotel should emphasize meeting rooms, workspaces, fast Wi-Fi, and proximity to business districts. A restaurant known for exceptional dining should earn reviews, media mentions, and third-party recommendations that consistently reference its food, chef, or culinary experience.</p>



<p>Many businesses naturally fit into more than one category. However, the clearer your primary positioning is, the easier it becomes for generative search engines to identify when your brand is relevant and should earn a recommendation.</p>



<p>The same principle applies to destinations. Generative search engines rely on signals across review platforms, travel guides, local listings, and publisher content when recommending where travelers should stay, visit, or explore.</p>



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<h2 class="wp-block-heading" id="h-3-practical-ways-to-strengthen-entity-signals-across-platforms">3 practical ways to strengthen entity signals across platforms</h2>



<p>As AI systems become more reliant on entities rather than individual webpages, travel businesses need to focus on creating a clear and consistent digital footprint.</p>



<h3 class="wp-block-heading" id="h-1-use-structured-data-to-clarify-business-attributes">1. Use structured data to clarify business attributes</h3>



<p>Structured data helps search engines and AI models interpret key business information. For travel brands, this type of data includes accommodation types, amenities, locations, and other business details.</p>



<p>Highlight the attributes that differentiate your property. That might include family-friendly facilities, wellness experiences, exceptional dining, pet-friendly accommodation, or proximity to major attractions.</p>



<p>The clearer and more structured your information is, the easier it becomes for AI-powered experiences to surface your business in relevant recommendations.</p>



<h3 class="wp-block-heading" id="h-2-eliminate-entity-ambiguity-across-platforms">2. Eliminate entity ambiguity across platforms</h3>



<p>Review what third-party sources say about your brand across the web. Look for conflicting information. AI search experiences pull information from multiple sources, and inconsistencies can reduce confidence in your brand.</p>



<p>Imagine a hotel with different phone numbers, outdated descriptions, inconsistent categories, or conflicting amenity information across various platforms. This is exactly the kind of ambiguity AI systems struggle with.</p>



<p>Maintain consistent information across your website, Google Business Profile, TripAdvisor listings, and OTA profiles to reduce ambiguity and strengthen confidence in your business data.</p>



<h3 class="wp-block-heading" id="h-3-prioritize-operational-business-information">3. Prioritize operational business information</h3>



<p>Start by auditing your existing customer reviews.</p>



<ul class="wp-block-list">
<li>What did they enjoy most about their stay?</li>



<li>What made their experience memorable?</li>



<li>What would they improve?</li>
</ul>



<p>Constructive feedback is a fast and easy way to identify what truly differentiates your brand from competitors. Details like amenities, accessibility features, opening hours, parking, and pet policies help AI systems answer specific travel queries.</p>



<p>Google Business Profile is another critical source of operational information. The categories, attributes, amenities, and opening hours listed on your profile help AI models answer travel queries with greater confidence.</p>



<p>If you need to provide additional context, Google Business Profile allows you to publish posts linking back to relevant content on your website. Regularly publishing Google Business Profile posts can help drive engagement, profile visits, and customer interactions while keeping your listing updated with fresh content about your products, services, events, and offers.</p>



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<h2 class="wp-block-heading" id="h-build-the-signals-ai-systems-trust">Build the signals AI systems trust</h2>



<p>Generative search is more democratic than traditional search. AI models recommend businesses, not websites. Visibility is no longer shaped exclusively by what happens on your website. It&#8217;s shaped by the broader digital footprint your brand has built across the web.</p>



<p>For travel brands, that means thinking beyond rankings and clicks. Reviews, OTA listings, travel guides, media mentions, and business profiles all contribute to how AI systems understand your brand and when they recommend it.</p>



<p>It&#8217;s time to be creative, experiment, and build partnerships with complementary businesses. Most importantly, it&#8217;s time to build the signals AI systems trust.</p>

AI Overviews and Google AI Mode now dominate conversations across the SEO community. One trend already stands out: Search is evolving from an information retrieval tool to a recommendation tool.
For travel brands, this changes the rules of online discovery. The challenge is no longer just helping search engines understand your website. It’s helping AI systems understand when your business should be recommended.
How AI search has changed travel planning 
Many users now spend substantial time every week interacting with large language models (LLMs). With LLMs, they can organize conversations by project and create folders for upcoming trips. They can also build on previous chats that already recognize their interests, travel preferences, and demographic profiles.
This marks a departure from the traditional search process. Historically, travel planning started with Google searches for topics like:
“Hotels in Porto”
“Things to do in Rome”
“Best restaurants in Barcelona”
Today, this process is far more conversational.
Rather than typing a series of disconnected searches, a traveler might create a new folder called “Summer 2026” in ChatGPT and start with a broad question that gradually evolves into a complete itinerary. For example: 
“Where should I stay in Porto for a quiet weekend within walking distance of the historic center?” 
“Which area of Rome is best for families traveling with young children?”
What follows is an ongoing conversation that might expand into restaurant recommendations, attractions, accommodation options, transportation advice, and day-by-day planning.
When travelers ask AI assistants these questions, they aren’t looking for a list of websites. Instead, they’re looking for a recommendation.
shows up.
      
Start Free Trial
    
Get started with
How AI Overviews impact the travel search experience
AI Overviews synthesize information from multiple sources and present users with curated recommendations rather than a collection of links. As a result, trust, consistency, and contextual understanding become critical visibility factors.
A hotel may influence a traveler’s decision through an AI-generated response without leading to an immediate website visit. The traveler’s next action may be a branded search, a visit to a travel review site, or a booking through an online travel agency (OTA).
To earn recommendations from AI models, your brand first needs to be clearly defined. AI must have confidence in who you are, what you offer, who you serve, and when your brand is relevant.
To do this, choose one primary category and one clear position for your brand. Invest in digital PR and earn mentions beyond your own website. Aim to be included in travel articles that cover topics relevant to your category.
Most importantly, ensure your business information is accurate, consistent, and easy to interpret across your website, Google Business Profile, TripAdvisor, OTA listings, and social media platforms.
Zero click doesn’t mean zero impact
The way we measure search performance is changing. Traditional SEO metrics still matter. However, travel marketers should start expanding how they measure visibility.
One of the biggest mistakes is assuming that fewer clicks mean less visibility.
A traveler may discover your property through an AI-generated response, search for it later, visit a TripAdvisor profile, or book through another channel.
This is why branded search growth is becoming a valuable signal of AI visibility. Travel marketers should also monitor AI mentions, citations, and assisted conversions.
Assisted conversions reveal the channels and touchpoints that influence a booking, even if they aren’t the final source of the conversion. You can monitor these conversions in Google Analytics 4 by navigating to Advertising > Attribution > Conversion Paths and Attribution Reports.



Why TripAdvisor and OTA listings provide semantic context for AI recommendations
TripAdvisor has become much more than a review platform. OTAs have become more than booking platforms.
When a user asks for recommendations, AI systems rarely rely on a single source. Instead, they build understanding by combining information from multiple platforms.
Your website is only one part of the ecosystem.
AI systems build confidence in recommendations by validating information across sources. What others say about your brand in reviews, travel guides, media mentions, OTA listings, or local citations increasingly matters. In many ways, this is simply online reputation at scale.
This additional context helps AI models determine when a property is relevant for specific traveler needs, such as:
Family-friendly.
Popular with business travelers.
Located in a walkable area.
Known for exceptional dining.
Better suited to luxury or budget travelers.
How to differentiate your travel brand
A family-friendly hotel should consistently highlight family rooms, kids’ activities, children’s pools, and family-focused reviews. A romantic hotel should reinforce signals like couples’ stays, intimate atmospheres, spa experiences, and special-occasion packages.
Likewise, a business hotel should emphasize meeting rooms, workspaces, fast Wi-Fi, and proximity to business districts. A restaurant known for exceptional dining should earn reviews, media mentions, and third-party recommendations that consistently reference its food, chef, or culinary experience.
Many businesses naturally fit into more than one category. However, the clearer your primary positioning is, the easier it becomes for generative search engines to identify when your brand is relevant and should earn a recommendation.
The same principle applies to destinations. Generative search engines rely on signals across review platforms, travel guides, local listings, and publisher content when recommending where travelers should stay, visit, or explore.
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
3 practical ways to strengthen entity signals across platforms
As AI systems become more reliant on entities rather than individual webpages, travel businesses need to focus on creating a clear and consistent digital footprint.
1. Use structured data to clarify business attributes
Structured data helps search engines and AI models interpret key business information. For travel brands, this type of data includes accommodation types, amenities, locations, and other business details.
Highlight the attributes that differentiate your property. That might include family-friendly facilities, wellness experiences, exceptional dining, pet-friendly accommodation, or proximity to major attractions.
The clearer and more structured your information is, the easier it becomes for AI-powered experiences to surface your business in relevant recommendations.
2. Eliminate entity ambiguity across platforms
Review what third-party sources say about your brand across the web. Look for conflicting information. AI search experiences pull information from multiple sources, and inconsistencies can reduce confidence in your brand.
Imagine a hotel with different phone numbers, outdated descriptions, inconsistent categories, or conflicting amenity information across various platforms. This is exactly the kind of ambiguity AI systems struggle with.
Maintain consistent information across your website, Google Business Profile, TripAdvisor listings, and OTA profiles to reduce ambiguity and strengthen confidence in your business data.
3. Prioritize operational business information
Start by auditing your existing customer reviews.
What did they enjoy most about their stay?
What made their experience memorable?
What would they improve?
Constructive feedback is a fast and easy way to identify what truly differentiates your brand from competitors. Details like amenities, accessibility features, opening hours, parking, and pet policies help AI systems answer specific travel queries.
Google Business Profile is another critical source of operational information. The categories, attributes, amenities, and opening hours listed on your profile help AI models answer travel queries with greater confidence.
If you need to provide additional context, Google Business Profile allows you to publish posts linking back to relevant content on your website. Regularly publishing Google Business Profile posts can help drive engagement, profile visits, and customer interactions while keeping your listing updated with fresh content about your products, services, events, and offers.
complete picture of your search visibility.
      
Start Free Trial
    
Get started with
Build the signals AI systems trust
Generative search is more democratic than traditional search. AI models recommend businesses, not websites. Visibility is no longer shaped exclusively by what happens on your website. It’s shaped by the broader digital footprint your brand has built across the web.
For travel brands, that means thinking beyond rankings and clicks. Reviews, OTA listings, travel guides, media mentions, and business profiles all contribute to how AI systems understand your brand and when they recommend it.
It’s time to be creative, experiment, and build partnerships with complementary businesses. Most importantly, it’s time to build the signals AI systems trust.

TripAdvisor, Google Business Profile, OTAs, and reviews help AI understand travel brands. Learn how to strengthen those signals.

How travel brands can earn AI recommendations

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy.png" class="attachment-large size-large wp-post-image" alt="Retrieval vs. citation- How AI search changes content strategy" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>From product pages to third-party publications, learn how to create content that helps AI systems understand your brand and who it serves.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy.png" class="attachment-large size-large wp-post-image" alt="Retrieval vs. citation- How AI search changes content strategy" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Retrieval-vs.-citation-How-AI-search-changes-content-strategy-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>One topic that’s come up frequently in <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> circles is the difference between creating content for information retrieval and creating content that earns citations from large language models (LLMs) such as Claude, ChatGPT, and Google AI Overviews.</p>



<p>As AI search evolves, that distinction is reshaping content strategy. Content that delivers the best user experience and meets people where they are is more likely to earn citations and be recognized as a trusted source.</p>



<p>More importantly, we need to think beyond our own websites and consider third-party platforms as well. As algorithmic marketers, our goal is to keep our brand and messaging consistent so machines clearly understand what we do, who we serve, and when to surface our company and information.</p>



<h2 class="wp-block-heading" id="h-the-change-from-seo-to-experience-based-geo">The change from SEO to experience-based GEO</h2>



<p>For LLMs in particular, it’s important to stop thinking about interactive search as SEO. Instead, focus on the users you want to attract through citations, or those for whom you want information about your brand to surface.</p>



<p>Some SEO fundamentals apply, but LLMs and AI Overviews are looking to provide customized experiences based on users’ preferences. Your content marketing, both on your website and externally, should keep this in mind rather than focusing on creating content for citations and retrieval.</p>



<p>I’ll start with an example of this customization to show the difference between SEO and generative engine optimization (GEO) or AI Overview approaches, then jump into actionable items you can take.</p>



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<h3 class="wp-block-heading" id="h-llms-know-consumers-better-than-you-think">LLMs know consumers better than you think</h3>



<p>On a team call this week, I pointed out that the client’s CEO and I are very similar. We’re both around the same age, in the same geographic region, have executive job titles, are very similar demographically, and both like to drink red wine.</p>



<p>However, if we both asked an LLM to make recommendations for a new wine to try, and both said we were looking for a wine with dark fruit notes that was dry and had a big, bold mouth splash, it’s almost certain that we wouldn’t get the same recommendation, even if we were using the same LLM. Why? Because he likes Italian wines, and I prefer Napa Valley wineries.</p>



<p>Google, functioning as a search engine, may know what a big red wine is, but LLM systems know more about our buyer personas because of how we engage with them. They remember who we are, while Google does not. From LLMs, I’ll likely get a recommendation for a Cabernet from California, while he may get an Amarone from Italy.</p>



<p>The LLM and Google AI Overview may both source products to recommend from retailers like Total Wine &amp; More or Binny&#8217;s, and use publications like Food &amp; Wine, Wine Spectator, and Vivino for knowledge, but that’s where the similarities end.</p>



<p>LLMs know what we like in a result and what we engage with, so they show us different varietals that better match our preferences when we ask more in-depth questions. Google and traditional search engines, meanwhile, will show more general options for big, bold, red wines.</p>



<h3 class="wp-block-heading" id="h-google-search-seems-to-be-changing">Google search seems to be changing</h3>



<p>That said, Google appears to be moving toward more personalized results, so expect a more LLM-style approach in the future. Apply this approach to content on your own platforms and anywhere you can influence the narrative on third-party sites.</p>



<p>Shifting your content from retrieval-based to citation-based starts with understanding how LLM and AI Overview results are generated, how personalized those results are becoming, and how retrieval methods combine with trust signals from traditional SEO results.</p>



<h2 class="wp-block-heading" id="h-extending-your-content-strategy-beyond-your-website">Extending your content strategy beyond your website</h2>



<p>Retrieval-augmented generation (RAG) information sourcing requires trusted websites and resources to compile a reasonably factual result. When combined with a personal preference, it may favor one source over another while still using both.</p>



<h3 class="wp-block-heading" id="h-an-example-of-talking-points-in-action">An example of talking points in action</h3>



<p>If the wine suggestions above were to apply here and two retailers (say, one big-box store and one niche winery) were trying to get featured in the output, they’d need to approach the same publications differently.</p>



<p>Let’s look at an example of getting wines placed in listicle-style articles. The big-box retailer that carries both Italian and Napa wines will want to be featured under Italian reds with talking points that address the things that interest my colleague, my client’s CEO, while the Napa winery wouldn’t need to worry about making that list since it doesn’t produce Italian wines. However, both will want to be featured under Napa Cabernets since they both sell them, and both will want talking points that matter to my buyer persona.</p>



<p><strong>Tip:</strong> Listicle placements are easiest to get through a media buy or advertorial, an affiliate program, or good old PR work for an earned placement.</p>



<p>For articles about varietals, the big-box retailer would want to focus on multiple articles and use talking points that matter to the CEO. For example, mentioning that the wine is produced on old vines, as these are more common in Europe than in the U.S. For the Napa wines I prefer, the winery would want to talk about how its wines feature a strong mouthfeel, have legs, and feature softer tannins.</p>



<p>Big-brand stores will want mass coverage and to have their products featured under many or most wine descriptions and types to help build relevance and be seen as experts on the topic of wine across the website since they carry wines from all countries and varietals.</p>



<p>The Napa Valley winery, on the other hand, wouldn’t need to worry about being cited across the entire site. Instead, it would want to focus on being featured in the Napa and California wine sections, in articles about grapes that are more common in California wines like Cabernet Sauvignon, Merlot, and Petit Verdot, and anything else directly related to the products and services it offers, like California wine tours and tastings.</p>



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<h3 class="wp-block-heading" id="h-another-strategy-for-citation-ready-content">Another strategy for citation-ready content</h3>



<p>If you’re an individual brand or a small business that sells women’s clothing, for example, you could use a similar, yet modified, version of the strategy above.</p>



<p>You’d also want to focus on getting featured in listicles, and when they mention you as one of the best retailers for women’s T-shirts, ensure your brand is present with some of the reasons why, then look for other lists about women’s fashion and clothing to be added to. </p>



<p>Whenever possible, especially once you’ve developed a relationship with the editor or contributor, have your differentiators present, whether it’s moisture-wicking materials, a patent you own, plus-size or petite sizing, signature colors, or being on trend. This builds the topical relevance of your brand mention and feature.</p>



<p>Most importantly, don’t stress over being included in every article across each media company. Focus on having your brand featured as a place to shop within the specific content that addresses the common issues your brand solves. After all, this is why your customers shop with you and how LLMs may learn who to show your brand and products to.</p>



<p>Non-shopping content that’s on topic, like a guide to materials or seasonal fashion trends that feature your brand and someone from it as a thought leader, may help as these systems become more advanced.</p>



<h3 class="wp-block-heading" id="h-where-llms-are-sourcing-their-materials">Where LLMs are sourcing their materials</h3>



<p>Right now, LLMs are using shopping lists as sources, but they’re looking for expertise as well. Being cited as an expert in niche themes and selling points across the sources LLMs already trust, and as a place where someone can purchase X, Y, and Z products, can help LLMs make the connection and build their knowledge bases about you. You’re not just a name anymore, but a trusted brand that sells X, Y, and Z to A, B, and C demographics.</p>



<p>When you keep getting mentioned more often in new content and are cited by a trusted resource, it may add credibility to your company as a retailer, service provider, or publication. That’s what we’re focusing on now with many of our content optimizations.</p>



<p>The goal here is to let LLMs and SEO algorithms know what you do and sell, and who the specific buyer persona is that shops your brand. Once they have a clear understanding of this, and if they trust your brand and your website or app enough, you may be able to show up in citations and recommendations more frequently and for the long run. And that bleeds into your website experience.</p>



<h2 class="wp-block-heading" id="h-helping-users-and-ai-find-the-right-fit">Helping users and AI find the right fit</h2>



<p>You’ll find out pretty fast that practices that have been considered bad in SEO for years still don’t work for GEO and AI Overviews. By this, I mean things like creating satellite pages, pages just for AI to index and find, hidden copy, content in schema, and similar tactics. They don’t work, and in the long run, they’re likely to tank your SEO, too.</p>



<p>The silver bullets and “strategies” we’re seeing now, and consider my tongue firmly in my cheek here, are the same things sold as SEO marketing years ago. The LLMs will catch up, your domain and brand will get penalized, and you’ll need to recover the losses while spending money you may not have on consultants and new team members.</p>



<p>Instead, focus your website experience on the actual customers and buyers who shop with you. This will naturally communicate what your products and services are to search engines and LLMs, your website visitors will know they’re in the right place, and you should see conversions increase if you’re better at meeting your visitors’ needs. How do you do this?</p>



<ul class="wp-block-list">
<li>Survey your customers to find out what’s important to them about what you do and why they chose your products or brand.</li>



<li>Read through customer returns and chat histories in your customer support database to find out why consumers are returning products or what questions they have.</li>



<li>Add these talking points to product and category pages (where appropriate) so users know:
<ul class="wp-block-list">
<li>If this is the right product for their needs.</li>



<li>Which product is the best match for them from a collection.</li>



<li>If there’s a better option, via a keyword-rich internal link, for a product that’s a better fit.</li>
</ul>
</li>
</ul>



<p>Each of the items above helps users on your website know what to buy, how to engage, and what meets their needs. This also helps define for LLMs what’s the best fit for your customer and the solutions your products and services naturally provide. That’s information search engines and AI can use to know when to surface your products and who to show your brand to.</p>



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<h2 class="wp-block-heading" id="h-the-standard-seo-elements-to-keep-in-your-content">The standard SEO elements to keep in your content</h2>



<p>That’s not to say SEO is going away. Traditional SEO practices still help LLMs understand what your website, products, services, content, and company offer and who they’re for. For example:</p>



<ul class="wp-block-list">
<li>Properly applied schema can help define your products, the theme of your content, your services, and the areas where they’re provided, helping paint a clearer picture of who your brand is.</li>



<li>Content that doesn’t require JavaScript to view and is visible is one of the best ways to be featured in chatbots and AI-powered search engines. Try server-side rendering for your content.</li>



<li><a href="https://searchengineland.com/llms-txt-proposed-standard-453676">LLMs.txt</a> can be one option, but there’s no guarantee it’ll take off or be adopted.</li>



<li>Use proper structure on your pages with H1s, H2s, H3s, article, header, and related tags.</li>



<li>Create direct, easy-to-understand content that answers users’ questions, provides correct information, and solves users’ problems without fluff or over-the-top adjective usage.</li>



<li>Ensure the talking points that matter to your ideal customers are mixed throughout your site’s pages, both on your website and on external websites, as this signals who your products, services, or content are for.</li>
</ul>



<p>Creating content for citations and information retrieval isn&#8217;t just about technical optimization or the content on your page. It&#8217;s also about how third parties experience your brand and talk about it, which helps LLMs determine which users are the best fit for your company and content.</p>



<p>Focus on maintaining a consistent voice across every channel you control, make sure your pages are crawlable and easy to understand, and keep testing. LLMs are still new, and we all have an opportunity to learn and adapt as the technology evolves.</p>

One topic that’s come up frequently in SEO circles is the difference between creating content for information retrieval and creating content that earns citations from large language models (LLMs) such as Claude, ChatGPT, and Google AI Overviews.
As AI search evolves, that distinction is reshaping content strategy. Content that delivers the best user experience and meets people where they are is more likely to earn citations and be recognized as a trusted source.
More importantly, we need to think beyond our own websites and consider third-party platforms as well. As algorithmic marketers, our goal is to keep our brand and messaging consistent so machines clearly understand what we do, who we serve, and when to surface our company and information.
The change from SEO to experience-based GEO
For LLMs in particular, it’s important to stop thinking about interactive search as SEO. Instead, focus on the users you want to attract through citations, or those for whom you want information about your brand to surface.
Some SEO fundamentals apply, but LLMs and AI Overviews are looking to provide customized experiences based on users’ preferences. Your content marketing, both on your website and externally, should keep this in mind rather than focusing on creating content for citations and retrieval.
I’ll start with an example of this customization to show the difference between SEO and generative engine optimization (GEO) or AI Overview approaches, then jump into actionable items you can take.

  
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LLMs know consumers better than you think
On a team call this week, I pointed out that the client’s CEO and I are very similar. We’re both around the same age, in the same geographic region, have executive job titles, are very similar demographically, and both like to drink red wine.
However, if we both asked an LLM to make recommendations for a new wine to try, and both said we were looking for a wine with dark fruit notes that was dry and had a big, bold mouth splash, it’s almost certain that we wouldn’t get the same recommendation, even if we were using the same LLM. Why? Because he likes Italian wines, and I prefer Napa Valley wineries.
Google, functioning as a search engine, may know what a big red wine is, but LLM systems know more about our buyer personas because of how we engage with them. They remember who we are, while Google does not. From LLMs, I’ll likely get a recommendation for a Cabernet from California, while he may get an Amarone from Italy.
The LLM and Google AI Overview may both source products to recommend from retailers like Total Wine & More or Binny’s, and use publications like Food & Wine, Wine Spectator, and Vivino for knowledge, but that’s where the similarities end.
LLMs know what we like in a result and what we engage with, so they show us different varietals that better match our preferences when we ask more in-depth questions. Google and traditional search engines, meanwhile, will show more general options for big, bold, red wines.
Google search seems to be changing
That said, Google appears to be moving toward more personalized results, so expect a more LLM-style approach in the future. Apply this approach to content on your own platforms and anywhere you can influence the narrative on third-party sites.
Shifting your content from retrieval-based to citation-based starts with understanding how LLM and AI Overview results are generated, how personalized those results are becoming, and how retrieval methods combine with trust signals from traditional SEO results.
Extending your content strategy beyond your website
Retrieval-augmented generation (RAG) information sourcing requires trusted websites and resources to compile a reasonably factual result. When combined with a personal preference, it may favor one source over another while still using both.
An example of talking points in action
If the wine suggestions above were to apply here and two retailers (say, one big-box store and one niche winery) were trying to get featured in the output, they’d need to approach the same publications differently.
Let’s look at an example of getting wines placed in listicle-style articles. The big-box retailer that carries both Italian and Napa wines will want to be featured under Italian reds with talking points that address the things that interest my colleague, my client’s CEO, while the Napa winery wouldn’t need to worry about making that list since it doesn’t produce Italian wines. However, both will want to be featured under Napa Cabernets since they both sell them, and both will want talking points that matter to my buyer persona.
Tip: Listicle placements are easiest to get through a media buy or advertorial, an affiliate program, or good old PR work for an earned placement.
For articles about varietals, the big-box retailer would want to focus on multiple articles and use talking points that matter to the CEO. For example, mentioning that the wine is produced on old vines, as these are more common in Europe than in the U.S. For the Napa wines I prefer, the winery would want to talk about how its wines feature a strong mouthfeel, have legs, and feature softer tannins.
Big-brand stores will want mass coverage and to have their products featured under many or most wine descriptions and types to help build relevance and be seen as experts on the topic of wine across the website since they carry wines from all countries and varietals.
The Napa Valley winery, on the other hand, wouldn’t need to worry about being cited across the entire site. Instead, it would want to focus on being featured in the Napa and California wine sections, in articles about grapes that are more common in California wines like Cabernet Sauvignon, Merlot, and Petit Verdot, and anything else directly related to the products and services it offers, like California wine tours and tastings.
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Another strategy for citation-ready content
If you’re an individual brand or a small business that sells women’s clothing, for example, you could use a similar, yet modified, version of the strategy above.
You’d also want to focus on getting featured in listicles, and when they mention you as one of the best retailers for women’s T-shirts, ensure your brand is present with some of the reasons why, then look for other lists about women’s fashion and clothing to be added to. 
Whenever possible, especially once you’ve developed a relationship with the editor or contributor, have your differentiators present, whether it’s moisture-wicking materials, a patent you own, plus-size or petite sizing, signature colors, or being on trend. This builds the topical relevance of your brand mention and feature.
Most importantly, don’t stress over being included in every article across each media company. Focus on having your brand featured as a place to shop within the specific content that addresses the common issues your brand solves. After all, this is why your customers shop with you and how LLMs may learn who to show your brand and products to.
Non-shopping content that’s on topic, like a guide to materials or seasonal fashion trends that feature your brand and someone from it as a thought leader, may help as these systems become more advanced.
Where LLMs are sourcing their materials
Right now, LLMs are using shopping lists as sources, but they’re looking for expertise as well. Being cited as an expert in niche themes and selling points across the sources LLMs already trust, and as a place where someone can purchase X, Y, and Z products, can help LLMs make the connection and build their knowledge bases about you. You’re not just a name anymore, but a trusted brand that sells X, Y, and Z to A, B, and C demographics.
When you keep getting mentioned more often in new content and are cited by a trusted resource, it may add credibility to your company as a retailer, service provider, or publication. That’s what we’re focusing on now with many of our content optimizations.
The goal here is to let LLMs and SEO algorithms know what you do and sell, and who the specific buyer persona is that shops your brand. Once they have a clear understanding of this, and if they trust your brand and your website or app enough, you may be able to show up in citations and recommendations more frequently and for the long run. And that bleeds into your website experience.
Helping users and AI find the right fit
You’ll find out pretty fast that practices that have been considered bad in SEO for years still don’t work for GEO and AI Overviews. By this, I mean things like creating satellite pages, pages just for AI to index and find, hidden copy, content in schema, and similar tactics. They don’t work, and in the long run, they’re likely to tank your SEO, too.
The silver bullets and “strategies” we’re seeing now, and consider my tongue firmly in my cheek here, are the same things sold as SEO marketing years ago. The LLMs will catch up, your domain and brand will get penalized, and you’ll need to recover the losses while spending money you may not have on consultants and new team members.
Instead, focus your website experience on the actual customers and buyers who shop with you. This will naturally communicate what your products and services are to search engines and LLMs, your website visitors will know they’re in the right place, and you should see conversions increase if you’re better at meeting your visitors’ needs. How do you do this?
Survey your customers to find out what’s important to them about what you do and why they chose your products or brand.
Read through customer returns and chat histories in your customer support database to find out why consumers are returning products or what questions they have.
Add these talking points to product and category pages (where appropriate) so users know:

If this is the right product for their needs.
Which product is the best match for them from a collection.
If there’s a better option, via a keyword-rich internal link, for a product that’s a better fit.
Each of the items above helps users on your website know what to buy, how to engage, and what meets their needs. This also helps define for LLMs what’s the best fit for your customer and the solutions your products and services naturally provide. That’s information search engines and AI can use to know when to surface your products and who to show your brand to.

  
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The standard SEO elements to keep in your content
That’s not to say SEO is going away. Traditional SEO practices still help LLMs understand what your website, products, services, content, and company offer and who they’re for. For example:
Properly applied schema can help define your products, the theme of your content, your services, and the areas where they’re provided, helping paint a clearer picture of who your brand is.
Content that doesn’t require JavaScript to view and is visible is one of the best ways to be featured in chatbots and AI-powered search engines. Try server-side rendering for your content.
LLMs.txt can be one option, but there’s no guarantee it’ll take off or be adopted.
Use proper structure on your pages with H1s, H2s, H3s, article, header, and related tags.
Create direct, easy-to-understand content that answers users’ questions, provides correct information, and solves users’ problems without fluff or over-the-top adjective usage.
Ensure the talking points that matter to your ideal customers are mixed throughout your site’s pages, both on your website and on external websites, as this signals who your products, services, or content are for.
Creating content for citations and information retrieval isn’t just about technical optimization or the content on your page. It’s also about how third parties experience your brand and talk about it, which helps LLMs determine which users are the best fit for your company and content.
Focus on maintaining a consistent voice across every channel you control, make sure your pages are crawlable and easy to understand, and keep testing. LLMs are still new, and we all have an opportunity to learn and adapt as the technology evolves.

From product pages to third-party publications, learn how to create content that helps AI systems understand your brand and who it serves.

Retrieval vs. citation: How AI search changes content strategy

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust.png" class="attachment-large size-large wp-post-image" alt="What new AI search data reveals about visibility and trust" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Consumers are validating information across more platforms before making decisions. New findings show where AI systems look for authority.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust.png" class="attachment-large size-large wp-post-image" alt="What new AI search data reveals about visibility and trust" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/What-new-AI-search-data-reveals-about-visibility-and-trust-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Trust in AI search is declining, consumers are validating information across more platforms, and AI visibility is increasingly tied to brand authority rather than traditional SEO metrics.</p>



<p>Those are among the key findings from new research by Fractl and Search Engine Land, presented by Fractl cofounder <a href="https://searchengineland.com/author/kelsey-libert">Kelsey Libert</a> at <a href="https://searchengineland.com/smx/advanced">SMX Advanced</a>. The study offers a detailed look at how consumers evaluate AI-generated answers, which signals influence AI recommendations, and where brands are falling short on governance and disclosure.</p>



<p>After the conference, I spoke with Libert to dig deeper into the data. Our conversation covered the growing trust gap in AI search, the role of earned media and entity authority in AI visibility, and why many organizations are still unprepared for the operational challenges AI introduces.</p>



<h2 class="wp-block-heading" id="h-the-honeymoon-is-over">The honeymoon is over</h2>



<p>The headline finding from Libert&#8217;s research is hard to ignore. In 2025, 82% of consumers found AI search more helpful than traditional search results. By 2026, that figure had dropped to 54%, a decline of 28 percentage points in a single year. The skeptic camp grew sixfold over the same period.</p>



<p>I asked Libert what she thinks is driving that erosion.</p>



<ul class="wp-block-list">
<li>&#8220;Hallucinations. Initially, AI was a frictionless instant-answer machine that felt superior to Google&#8217;s crowded SERPs. As people lost trust in AI answers and had to put in more effort to validate them, that instant gratification disappeared, and the helpfulness score dropped dramatically,&#8221; Libert said.</li>
</ul>



<p>She isn&#8217;t entirely pessimistic about where things are headed, though. </p>



<ul class="wp-block-list">
<li>&#8220;AI is on an exponential improvement scale, so I expect this number to restabilize over the next year as people learn how to refine their prompts and engineers improve the technology,&#8221; Libert said.</li>
</ul>



<p>That restabilization may come sooner than expected. Libert pointed to a June 5 CNN report covering Anthropic&#8217;s warnings that AI may soon be capable of improving itself without human intervention. Whether that accelerates the recovery of consumer trust or deepens concern about AI reliability remains to be seen.</p>



<p>In the meantime, consumers are hedging. The research found that buyers now check an average of 2.4 platforms before validating a purchase, a pattern consistent across Gen Z, millennials, and boomers. </p>



<p>Google still leads AI tools three to one for trusted product recommendations, commanding 39% of consumer trust versus 14% for AI tools. Reddit, at 15%, sits between them.</p>



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<h2 class="wp-block-heading" id="h-organic-visibility-is-diversifying">Organic visibility is diversifying</h2>



<p>For SEOs worried about the erosion of organic traffic, Libert&#8217;s framing offers a more nuanced picture than the typical doom narrative. About 50% of marketers report traffic declines since AI Overviews launched, and 61% directly blame AI tools.</p>



<p>At the same time, 57% see traffic growth from social platforms, including TikTok, Reddit, and YouTube, and 40% see growth from AI assistants such as ChatGPT and Perplexity.</p>



<p>The channel map Libert presented at SMX is worth understanding.&nbsp;</p>



<ul class="wp-block-list">
<li>Google remains dominant at 84.8 billion visits, serving primarily as an intent-capture engine.&nbsp;</li>



<li>YouTube and Instagram/TikTok together handle brand discovery.&nbsp;</li>



<li>ChatGPT and Gemini are used primarily for research and learning.&nbsp;</li>



<li>Facebook and Reddit serve human-validation functions.&nbsp;</li>
</ul>



<p>Search isn&#8217;t disappearing. It&#8217;s fragmenting, and brands that optimize for only one of these channels are leaving significant visibility on the table.</p>



<h2 class="wp-block-heading" id="h-the-geo-hierarchy-table-stakes-high-risk-and-the-moat">The GEO hierarchy: Table stakes, high risk, and the moat</h2>



<p>Libert&#8217;s research categorized generative engine optimization tactics into three tiers, and the distinctions matter for how marketers should allocate effort.</p>



<p>The most commonly used tactic is FAQ optimization, employed by 49% of marketers. Libert calls this high risk, and the reason is straightforward.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;The high-risk category is based on how easily AI can replicate that content, and general industry FAQs are typically pretty easy for AI and your competitors to produce.&#8221;</li>
</ul>



<p>FAQ strategies can be strengthened by layering in proprietary data, subject matter expertise, and unique insights, but on their own, they offer little defensibility.</p>



<p>Table-stakes tactics include building brand mentions (43%), establishing topical authority (36%), and implementing structured data (30%). These are necessary but not sufficient.</p>



<p>The moat, as Libert describes it, consists of original data and proprietary studies (35%) and digital PR (24%). These are harder for AI to replicate, which is precisely what makes them valuable.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;LLMs and Google need fresh content to pull into timely and common RAG queries. Beyond that, data journalism and digital PR efforts help increase your brand&#8217;s entity authority by helping you earn brand mentions across influential sources across the web,&#8221; Libert explained.</li>
</ul>



<p>The signal strength behind this approach is backed by Ahrefs research analyzing roughly 75,000 brands across ChatGPT, AI Mode, and AI Overviews.&nbsp;</p>



<p>Branded web mentions and YouTube impressions showed the strongest correlations with AI visibility, ranging from 0.50 to 0.74 on the Spearman scale. </p>



<p>Backlink count and ad spend fell in the weakest tier, below 0.30. The practical implication, as Libert put it, is that &#8220;AI systems reward brand presence and mentions more than traditional SEO scale metrics.&#8221;</p>



<p>I asked Libert what she would do first if building brand mentions from scratch. Her answer was tactical and specific:</p>



<ul class="wp-block-list">
<li>Use Semrush or Ahrefs to identify high-authority, niche-relevant publishers that have covered competitors, build relationships with those journalists, and pitch concepts that fill gaps in their coverage using proprietary data or subject matter expertise.</li>



<li>Use SparkToro to identify the publishers, YouTube channels, and podcasts a target audience actually consumes, then prioritize earned placements in those venues.</li>



<li>Use Reddit to study what performs well in relevant subreddits and contribute substantive commentary or content, not promotional noise.</li>
</ul>



<ul class="wp-block-list">
<li>&#8220;Earned media always comes back to one principle. Focus on creating fresh, educational, actionable, valuable, and newsworthy industry insights, and repurpose that content across the channels of influence for your target market,&#8221; LIbert said.</li>
</ul>



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<h2 class="wp-block-heading" id="h-the-trust-gap-brands-are-ignoring">The trust gap brands are ignoring</h2>



<p>One of the most striking data points in Libert&#8217;s presentation involves the gap between what consumers expect and what brands actually do.&nbsp;</p>



<p>Between 84% and 91% of consumers say they want AI labeling across all content formats, including text, video, audio, and images. Only 20% of organizations say they always disclose their AI use. One-third never disclose at all.</p>



<p>Libert doesn&#8217;t think consumers are simply opposed to AI in marketing. The concern is more specific.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;Consumers aren&#8217;t wary about AI use in marketing. They&#8217;re concerned when brands use it for their entire marketing workflow with zero checks and balances.&#8221;&nbsp;</li>
</ul>



<p>She cited the research finding that nearly half of marketers admit to not fact-checking their AI-produced content and that 48% say AI makes their work faster but more average.</p>



<p>Dove came up as one of the few brands actively positioning against what Libert calls &#8220;AI-dominant marketing slop,&#8221; though she acknowledges the field is still mostly treating disclosure as a compliance checkbox rather than a brand signal.</p>



<p>There is also a deeper question about where AI assistance ends and human creativity begins, one the industry hasn&#8217;t settled.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;There&#8217;s some debate on when it needs to be disclosed, since plenty of people use it more as an assistant in the creative process vs. having it do everything end-to-end,&#8221; Libert said. &#8220;In that case, who truly owns the creativity, and what level of disclosure is required? That&#8217;s still up for debate.&#8221;</li>
</ul>



<h2 class="wp-block-heading" id="h-the-inverted-pyramid-problem">The inverted pyramid problem</h2>



<p>The slide that drew the most reaction in the SMX room showed how marketers are allocating their human review time for AI-generated content. Editorial review claimed 72% of attention. Voice and tone review claimed 62%. Fact-checking fell to 54%, plagiarism and legal review to 42% each, and bias evaluation to just 27%.</p>



<p>Libert called this an &#8220;all of the above&#8221; problem, spanning training gaps, workflow fragmentation, and leadership priorities.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;When employees can&#8217;t keep up with the basic learning process to execute their workflow effectively with AI, how can you expect them to also focus on the checks and balances of AI&#8217;s output without the proper support from leadership to take time to develop and refine entirely new workflows?&#8221; she said.&nbsp;</li>



<li>&#8220;We&#8217;re focusing on the surface-level review of AI&#8217;s output because that&#8217;s all people have the capacity and proper support for. That data point is a huge leadership SOS.&#8221;</li>
</ul>



<p>Her core argument here aligns with the most pointed line in her presentation: fix the infrastructure before you scale the output. AI won&#8217;t kill credibility. Untrained oversight will.</p>



<h2 class="wp-block-heading" id="h-what-smaller-brands-can-actually-do">What smaller brands can actually do</h2>



<p>The closing argument of Libert&#8217;s SMX talk, that AI rewards brand equity rather than creating it, raises a fair concern for newer entrants who lack years of accumulated authority. I pushed her on this.</p>



<p>Her answer was more optimistic than the headline suggests. AI Overviews aren&#8217;t simply surfacing the top search results. They are surfacing brands that have built genuine authority around niche topics.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;Younger brands can still compete by focusing on building out their entity authority around the long tail, where most conversions actually live,&#8221; she said.</li>
</ul>



<p>She also sees an opening created by the same corporate inertia that slows large-brand adaptation.&nbsp;</p>



<ul class="wp-block-list">
<li>&#8220;Plenty of larger brands are stuck in more corporate bureaucracy and are slower to adapt to the changes and opportunities of using AI to scale insightful data analysis and thought leadership content. There&#8217;s actually plenty of room for smaller brands to compete, now more than ever.&#8221;&nbsp;</li>
</ul>



<p>The caveat?</p>



<ul class="wp-block-list">
<li>&#8220;It&#8217;s a matter of slowing down and learning how to use AI effectively, not scaling AI slop.&#8221;</li>
</ul>



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<h2 class="wp-block-heading" id="h-the-playbook-for-ai-visibility">The playbook for AI visibility</h2>



<p>The 2026 AI search playbook that Libert presented at SMX distills to four imperatives:&nbsp;</p>



<ul class="wp-block-list">
<li>Monitor brand representation across all influential platforms.</li>



<li>Build entity authority through original research and subject matter expertise.</li>



<li>Triangulate visibility across search, video, social proof, and trusted media.</li>



<li>Govern AI use with formal disclosure and review processes rather than ad hoc workarounds.</li>
</ul>



<p>None of this is particularly complicated in concept. The difficulty is organizational.&nbsp;</p>



<p>The brands that treat credibility as infrastructure rather than aesthetics are most likely to be cited, recommended, and trusted as AI search continues to mature.</p>

Trust in AI search is declining, consumers are validating information across more platforms, and AI visibility is increasingly tied to brand authority rather than traditional SEO metrics.
Those are among the key findings from new research by Fractl and Search Engine Land, presented by Fractl cofounder Kelsey Libert at SMX Advanced. The study offers a detailed look at how consumers evaluate AI-generated answers, which signals influence AI recommendations, and where brands are falling short on governance and disclosure.
After the conference, I spoke with Libert to dig deeper into the data. Our conversation covered the growing trust gap in AI search, the role of earned media and entity authority in AI visibility, and why many organizations are still unprepared for the operational challenges AI introduces.
The honeymoon is over
The headline finding from Libert’s research is hard to ignore. In 2025, 82% of consumers found AI search more helpful than traditional search results. By 2026, that figure had dropped to 54%, a decline of 28 percentage points in a single year. The skeptic camp grew sixfold over the same period.
I asked Libert what she thinks is driving that erosion.
“Hallucinations. Initially, AI was a frictionless instant-answer machine that felt superior to Google’s crowded SERPs. As people lost trust in AI answers and had to put in more effort to validate them, that instant gratification disappeared, and the helpfulness score dropped dramatically,” Libert said.
She isn’t entirely pessimistic about where things are headed, though. 
“AI is on an exponential improvement scale, so I expect this number to restabilize over the next year as people learn how to refine their prompts and engineers improve the technology,” Libert said.
That restabilization may come sooner than expected. Libert pointed to a June 5 CNN report covering Anthropic’s warnings that AI may soon be capable of improving itself without human intervention. Whether that accelerates the recovery of consumer trust or deepens concern about AI reliability remains to be seen.
In the meantime, consumers are hedging. The research found that buyers now check an average of 2.4 platforms before validating a purchase, a pattern consistent across Gen Z, millennials, and boomers. 
Google still leads AI tools three to one for trusted product recommendations, commanding 39% of consumer trust versus 14% for AI tools. Reddit, at 15%, sits between them.

  
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Organic visibility is diversifying
For SEOs worried about the erosion of organic traffic, Libert’s framing offers a more nuanced picture than the typical doom narrative. About 50% of marketers report traffic declines since AI Overviews launched, and 61% directly blame AI tools.
At the same time, 57% see traffic growth from social platforms, including TikTok, Reddit, and YouTube, and 40% see growth from AI assistants such as ChatGPT and Perplexity.
The channel map Libert presented at SMX is worth understanding. 
Google remains dominant at 84.8 billion visits, serving primarily as an intent-capture engine. 
YouTube and Instagram/TikTok together handle brand discovery. 
ChatGPT and Gemini are used primarily for research and learning. 
Facebook and Reddit serve human-validation functions. 
Search isn’t disappearing. It’s fragmenting, and brands that optimize for only one of these channels are leaving significant visibility on the table.
The GEO hierarchy: Table stakes, high risk, and the moat
Libert’s research categorized generative engine optimization tactics into three tiers, and the distinctions matter for how marketers should allocate effort.
The most commonly used tactic is FAQ optimization, employed by 49% of marketers. Libert calls this high risk, and the reason is straightforward. 
“The high-risk category is based on how easily AI can replicate that content, and general industry FAQs are typically pretty easy for AI and your competitors to produce.”
FAQ strategies can be strengthened by layering in proprietary data, subject matter expertise, and unique insights, but on their own, they offer little defensibility.
Table-stakes tactics include building brand mentions (43%), establishing topical authority (36%), and implementing structured data (30%). These are necessary but not sufficient.
The moat, as Libert describes it, consists of original data and proprietary studies (35%) and digital PR (24%). These are harder for AI to replicate, which is precisely what makes them valuable. 
“LLMs and Google need fresh content to pull into timely and common RAG queries. Beyond that, data journalism and digital PR efforts help increase your brand’s entity authority by helping you earn brand mentions across influential sources across the web,” Libert explained.
The signal strength behind this approach is backed by Ahrefs research analyzing roughly 75,000 brands across ChatGPT, AI Mode, and AI Overviews. 
Branded web mentions and YouTube impressions showed the strongest correlations with AI visibility, ranging from 0.50 to 0.74 on the Spearman scale. 
Backlink count and ad spend fell in the weakest tier, below 0.30. The practical implication, as Libert put it, is that “AI systems reward brand presence and mentions more than traditional SEO scale metrics.”
I asked Libert what she would do first if building brand mentions from scratch. Her answer was tactical and specific:
Use Semrush or Ahrefs to identify high-authority, niche-relevant publishers that have covered competitors, build relationships with those journalists, and pitch concepts that fill gaps in their coverage using proprietary data or subject matter expertise.
Use SparkToro to identify the publishers, YouTube channels, and podcasts a target audience actually consumes, then prioritize earned placements in those venues.
Use Reddit to study what performs well in relevant subreddits and contribute substantive commentary or content, not promotional noise.
“Earned media always comes back to one principle. Focus on creating fresh, educational, actionable, valuable, and newsworthy industry insights, and repurpose that content across the channels of influence for your target market,” LIbert said.
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The trust gap brands are ignoring
One of the most striking data points in Libert’s presentation involves the gap between what consumers expect and what brands actually do. 
Between 84% and 91% of consumers say they want AI labeling across all content formats, including text, video, audio, and images. Only 20% of organizations say they always disclose their AI use. One-third never disclose at all.
Libert doesn’t think consumers are simply opposed to AI in marketing. The concern is more specific. 
“Consumers aren’t wary about AI use in marketing. They’re concerned when brands use it for their entire marketing workflow with zero checks and balances.” 
She cited the research finding that nearly half of marketers admit to not fact-checking their AI-produced content and that 48% say AI makes their work faster but more average.
Dove came up as one of the few brands actively positioning against what Libert calls “AI-dominant marketing slop,” though she acknowledges the field is still mostly treating disclosure as a compliance checkbox rather than a brand signal.
There is also a deeper question about where AI assistance ends and human creativity begins, one the industry hasn’t settled. 
“There’s some debate on when it needs to be disclosed, since plenty of people use it more as an assistant in the creative process vs. having it do everything end-to-end,” Libert said. “In that case, who truly owns the creativity, and what level of disclosure is required? That’s still up for debate.”
The inverted pyramid problem
The slide that drew the most reaction in the SMX room showed how marketers are allocating their human review time for AI-generated content. Editorial review claimed 72% of attention. Voice and tone review claimed 62%. Fact-checking fell to 54%, plagiarism and legal review to 42% each, and bias evaluation to just 27%.
Libert called this an “all of the above” problem, spanning training gaps, workflow fragmentation, and leadership priorities. 
“When employees can’t keep up with the basic learning process to execute their workflow effectively with AI, how can you expect them to also focus on the checks and balances of AI’s output without the proper support from leadership to take time to develop and refine entirely new workflows?” she said. 
“We’re focusing on the surface-level review of AI’s output because that’s all people have the capacity and proper support for. That data point is a huge leadership SOS.”
Her core argument here aligns with the most pointed line in her presentation: fix the infrastructure before you scale the output. AI won’t kill credibility. Untrained oversight will.
What smaller brands can actually do
The closing argument of Libert’s SMX talk, that AI rewards brand equity rather than creating it, raises a fair concern for newer entrants who lack years of accumulated authority. I pushed her on this.
Her answer was more optimistic than the headline suggests. AI Overviews aren’t simply surfacing the top search results. They are surfacing brands that have built genuine authority around niche topics. 
“Younger brands can still compete by focusing on building out their entity authority around the long tail, where most conversions actually live,” she said.
She also sees an opening created by the same corporate inertia that slows large-brand adaptation. 
“Plenty of larger brands are stuck in more corporate bureaucracy and are slower to adapt to the changes and opportunities of using AI to scale insightful data analysis and thought leadership content. There’s actually plenty of room for smaller brands to compete, now more than ever.” 
The caveat?
“It’s a matter of slowing down and learning how to use AI effectively, not scaling AI slop.”

  
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The playbook for AI visibility
The 2026 AI search playbook that Libert presented at SMX distills to four imperatives: 
Monitor brand representation across all influential platforms.
Build entity authority through original research and subject matter expertise.
Triangulate visibility across search, video, social proof, and trusted media.
Govern AI use with formal disclosure and review processes rather than ad hoc workarounds.
None of this is particularly complicated in concept. The difficulty is organizational. 
The brands that treat credibility as infrastructure rather than aesthetics are most likely to be cited, recommended, and trusted as AI search continues to mature.

Consumers are validating information across more platforms before making decisions. New findings show where AI systems look for authority.

What new AI search data reveals about visibility and trust

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads.png" class="attachment-large size-large wp-post-image" alt="Law firm PPC- How to optimize for signed cases instead of leads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Learn how to identify leaks between the ad click and signed retainer, and make smarter budget decisions based on case outcomes.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads.png" class="attachment-large size-large wp-post-image" alt="Law firm PPC- How to optimize for signed cases instead of leads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Law-firm-PPC-How-to-optimize-for-signed-cases-instead-of-leads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>A lower cost per lead and higher lead volume don&#8217;t necessarily translate into more signed cases. That&#8217;s because leads and signed cases are not the same thing. </p>



<p>Between the ad click and the signed retainer sit intake qualification, follow-up speed, and conversion. If you&#8217;re measuring <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> success based only on cost per lead, you&#8217;re making budget decisions with incomplete data.</p>



<p>I&#8217;ve managed more than 1,000 ad accounts across plaintiff-side law firms, and I see the same pattern repeatedly. The ads generate activity, but the system that turns leads into clients leaks at multiple points.</p>



<p>The firms that consistently grow signed cases connect their advertising data to intake performance, lead qualification, and retained clients. That requires a different approach to keywords, budget allocation, landing pages, and attribution.</p>



<h2 class="wp-block-heading" id="h-start-with-the-right-keywords-hint-they-re-not-google-s-suggestions">Start with the right keywords (hint: they&#8217;re not Google&#8217;s suggestions!)</h2>



<p>Most law firms build a campaign backward. They start with broad-match keywords like injury attorney, best lawyer, and legal advice. Those terms bring in volume, but also noise. You end up getting tons of unqualified, early-stage prospects, and this equates to low-intent traffic that burns through your budget.</p>



<p>We protect our budget and improve conversions by reverse-engineering a keyword strategy from actual signed-case data. Instead of relying on Google&#8217;s keyword suggestions as a starting point, we mine call transcripts, intake notes, and CRM records to identify the real language that precedes retained clients.</p>



<p>With practice, you can pinpoint the exact phrase-match terms that people may be using to find attorneys like you. Phrases like &#8220;truck accident lawyer near me,&#8221; &#8220;motorcycle injury attorney Houston,&#8221; or &#8220;wrongful death law firm Tampa.&#8221;</p>



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<h2 class="wp-block-heading" id="h-search-intent-matters">Search intent matters</h2>



<p>The core principle is to segment every keyword by funnel stage and intent. High-intent exact- and phrase-match terms get the budget. Low-intent terms get tested and throttled, or excluded.</p>



<p>The single most important ritual for effective law firm PPC management is integrating <a href="https://searchengineland.com/google-ads-search-terms-report-tips-465174">the search terms report</a> into your workflow. This report shows you exactly what someone typed before clicking your ad and whether that click generated a quality lead or was a waste of money. Most law firms, or the advertising agencies they work with, either skip this entirely or check it once a quarter.</p>



<p>Keep your spend efficient by reviewing the report every week to identify and add negative keywords to your campaign. This weekly hygiene compounds over the long term.</p>



<h2 class="wp-block-heading" id="h-allocate-budget-by-funnel-stage-not-by-channel">Allocate budget by funnel stage, not by channel</h2>



<p>Most law firms treat Google Ads like a monolith. You&#8217;ll get a better ROI if you separate campaigns by funnel stage, intent, budget allocation, and conversion goals.</p>



<p>My <a href="https://searchengineland.com/full-funnel-ppc-strategy-437426">PPC strategy</a> is based completely on the Pareto Principle (aka the 80/20 rule): About 80% of your spend goes to bottom-of-funnel direct response, and 20% goes to mid-funnel and retargeting. Here&#8217;s what that looks like in practice:</p>



<h3 class="wp-block-heading" id="h-bottom-of-funnel">Bottom of funnel</h3>



<p>This is where most of your signed cases will come from. These are high-intent search campaigns and Local Services Ads. </p>



<p>LSAs are the best-converting channel for personal injury firms, Pareto Legal’s “<a href="https://pareto.legal/law-firm-ppc-statistics-2026/">The State of Law Firm PPC</a>” report found. They are pay-per-lead, review-driven, and require no landing page infrastructure from you. <em>(</em><strong><em>Disclosure: </em></strong><em>I’m the CEO and co-founder of Pareto Legal.)</em>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1444" height="822" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-vs-LSA-performance.png" alt="Google Ads vs LSA performance" class="wp-image-480016" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-vs-LSA-performance.png 1444w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-vs-LSA-performance-768x437.png 768w" sizes="(max-width: 1444px) 100vw, 1444px" /></figure>
</div>


<p>One of the fastest lead-quality wins we consistently see with new clients is correcting their LSA category selections from broad practice areas to specific case types, such as personal injury or motor vehicle accidents. </p>



<h3 class="wp-block-heading" id="h-mid-funnel">Mid-funnel</h3>



<p>This includes non-brand search, Dynamic Search Ads, and segmented <a href="https://searchengineland.com/guide/ppc/performance-max">Performance Max</a>. Evaluate these on qualified lead rate, not raw volume. If a campaign generates 200 leads but only 10 are qualified, it&#8217;s a budget drain, even with a good-looking CPL.</p>



<h3 class="wp-block-heading" id="h-top-of-funnel">Top of funnel</h3>



<p>Meta and YouTube retargeting can target people who have already visited your website. Expand these campaigns to cold prospecting only after attribution proves incremental lift.</p>



<p>This framework is simple, but it can dramatically improve your PPC results. For one injury firm, we generated 273 signed cases from $765,000 in ad spend (3.57x ROI) without increasing the budget. All it required was a restructuring of the firm&#8217;s Google Ads.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/why-law-firm-best-leads-dont-convert-472012">Why your law firm’s best leads don’t convert after research</a></em></strong>



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<h2 class="wp-block-heading" id="h-build-landing-pages-that-match-intent-not-just-keywords">Build landing pages that match intent, not just keywords</h2>



<p>Sending paid traffic to your homepage or a generic practice area page that doesn&#8217;t match the ad you ran is a conversion-rate killer. This is common knowledge, yet <a href="https://searchengineland.com/guide/types-of-landing-pages">effective landing pages</a> are probably the most overlooked part of PPC management.&nbsp;</p>



<p>Many great PPC marketers know bidding strategy, campaign structure, and audience targeting inside and out. But when it comes to building a high-quality, compelling user experience, many marketers fall short.</p>



<h3 class="wp-block-heading" id="h-what-kind-of-landing-pages-work-nbsp">What kind of landing pages work?&nbsp;</h3>



<p>Your goal should be to match the intent of what your prospect was searching for. Here are the important components:</p>



<ul class="wp-block-list">
<li>An intent-matched H1 headline.</li>



<li>Settlement amounts.</li>



<li>Client reviews as social proof.</li>



<li>Click-to-call and live chat options.</li>
</ul>



<p>Your landing pages should also load quickly and be mobile-first.</p>



<p>You need one page per practice area, per intent. For example, a &#8220;car accident lawyer&#8221; landing page and a &#8220;truck accident attorney&#8221; landing page should be different. Each practice area and intent level deserves its own experience and unique design.</p>



<h3 class="wp-block-heading" id="h-what-kind-of-results-will-you-see">What kind of results will you see?</h3>



<p>I split one client&#8217;s generic personal injury page into intent-segmented pages, added a stack of recent reviews and results, and reduced form fields from nine to four. Our team also optimized load time from 5.1 seconds to 2.1 seconds.</p>



<p>The page conversion rate went from 3.8% to 17.4%. The cost per signed case dropped by 42% with the same ad spend.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/authority-law-firm-seo-477512">The future of law firm SEO depends on authority, not volume</a></em></strong>



<h2 class="wp-block-heading" id="h-fix-the-intake-bottleneck-before-you-scale-ads">Fix the intake bottleneck before you scale ads</h2>



<p>Most agencies won&#8217;t tell you the primary reason law firm advertising fails. It&#8217;s not the marketing process itself. </p>



<p>Surface-level numbers like cost per click (CPC) are often fine. What fails is the intake process. You need to focus on what happens after the form fill or phone call.</p>



<p>Here are the key intake KPIs to track alongside your ad metrics:</p>



<ul class="wp-block-list">
<li><strong>Answer rate:</strong> Target 90% or higher.</li>



<li><strong>Speed to lead:</strong> Target under 60 seconds.</li>



<li><strong>Signed rate (the percentage of qualified leads that become retained clients):</strong> A healthy benchmark is 25% to 40% of qualified leads.</li>
</ul>



<p>The math is simple: If you&#8217;re spending $20,000 on Google Ads every month and your average cost per lead is $250, that&#8217;s 80 leads. If your intake team only contacts 70% of them and signs 30% of those contacts, you get about 17 cases.</p>



<p>If your team responds to 95% and converts 40%, that&#8217;s 30 cases from the same $20,000. You&#8217;ve essentially doubled your return on Google Ads, and it had nothing to do with your ad spend.</p>



<p>The key is for your marketing and intake teams to share KPIs. You can&#8217;t have the media buyer optimizing for lead volume while the intake team cherry-picks easy calls.</p>



<h2 class="wp-block-heading" id="h-connect-the-full-attribution-chain-ad-click-to-signed-retainer">Connect the full attribution chain: Ad click to signed retainer</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1404" height="500" src="https://searchengineland.com/wp-content/seloads/2026/06/What-of-signed-cases-can-law-firms-attribute-to-marketing-channels.png" alt="What % of signed cases can law firms attribute to marketing channels" class="wp-image-480017" srcset="https://searchengineland.com/wp-content/seloads/2026/06/What-of-signed-cases-can-law-firms-attribute-to-marketing-channels.png 1404w, https://searchengineland.com/wp-content/seloads/2026/06/What-of-signed-cases-can-law-firms-attribute-to-marketing-channels-768x274.png 768w" sizes="(max-width: 1404px) 100vw, 1404px" /></figure>
</div>


<p>Most law firm reporting isn&#8217;t detailed enough to serve as a decision-making tool. It stops at platform metrics such as impressions, clicks, and cost per lead. These reports rarely reach the CRM, where signed cases actually live and where the most valuable intelligence resides.</p>



<p>Your attribution infrastructure needs these components:</p>



<ul class="wp-block-list">
<li>UTMs and click IDs from ad platforms to capture the traffic source.</li>



<li>Call tracking through a tool like CallRail to handle phone leads.</li>



<li><a href="https://searchengineland.com/guide/how-to-use-google-analytics-4">Google Analytics 4</a> for tracking post-click behavior on the site.</li>



<li>A CRM, such as Lawmatics or Clio, that tracks post-conversion activity all the way through to the signed case.</li>
</ul>



<p>The metric that ties everything together is marketing efficiency ratio (MER): total revenue divided by total marketing spend.</p>



<p>MER forces you to evaluate marketing as an ecosystem instead of looking at each channel through last-click attribution. For example, knowing you have a healthy MER can help you spot the hidden work a single channel is doing, even if it looks expensive on a last-click basis. MER can help you maintain confidence in your budget allocation.</p>



<h3 class="wp-block-heading" id="h-your-ideal-dashboard-setup">Your ideal dashboard setup</h3>



<p>Every law firm should build a one-page dashboard with these metrics: spend, leads, qualified leads, signed cases, cost per lead (CPL), and cost per acquisition (CPA), all broken down by channel and practice area.</p>



<p>If your reports can&#8217;t drill down to this level of granularity, they&#8217;re probably just a slideshow. Building this tracking infrastructure makes it easy to identify winning campaigns and reallocate budget intelligently. This is how you increase ROI without additional funding.</p>



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<h2 class="wp-block-heading" id="h-treating-ppc-like-a-system-leads-to-success">Treating PPC like a system leads to success</h2>



<p>The firms that succeed with PPC treat it like a system. They:</p>



<ul class="wp-block-list">
<li>Use precise keyword targeting tied to their prospects&#8217; real behavior. </li>



<li>Allocate budget by funnel stage and intent. </li>



<li>Review search terms weekly.</li>



<li>Know their numbers: cost per case, not just cost per click. </li>



<li>Connect the ad click to the signed retainer, so every budget decision is based on what actually matters.</li>
</ul>



<p>Don&#8217;t trust Google to figure this out for you.</p>

A lower cost per lead and higher lead volume don’t necessarily translate into more signed cases. That’s because leads and signed cases are not the same thing. 
Between the ad click and the signed retainer sit intake qualification, follow-up speed, and conversion. If you’re measuring PPC success based only on cost per lead, you’re making budget decisions with incomplete data.
I’ve managed more than 1,000 ad accounts across plaintiff-side law firms, and I see the same pattern repeatedly. The ads generate activity, but the system that turns leads into clients leaks at multiple points.
The firms that consistently grow signed cases connect their advertising data to intake performance, lead qualification, and retained clients. That requires a different approach to keywords, budget allocation, landing pages, and attribution.
Start with the right keywords (hint: they’re not Google’s suggestions!)
Most law firms build a campaign backward. They start with broad-match keywords like injury attorney, best lawyer, and legal advice. Those terms bring in volume, but also noise. You end up getting tons of unqualified, early-stage prospects, and this equates to low-intent traffic that burns through your budget.
We protect our budget and improve conversions by reverse-engineering a keyword strategy from actual signed-case data. Instead of relying on Google’s keyword suggestions as a starting point, we mine call transcripts, intake notes, and CRM records to identify the real language that precedes retained clients.
With practice, you can pinpoint the exact phrase-match terms that people may be using to find attorneys like you. Phrases like “truck accident lawyer near me,” “motorcycle injury attorney Houston,” or “wrongful death law firm Tampa.”

  
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Search intent matters
The core principle is to segment every keyword by funnel stage and intent. High-intent exact- and phrase-match terms get the budget. Low-intent terms get tested and throttled, or excluded.
The single most important ritual for effective law firm PPC management is integrating the search terms report into your workflow. This report shows you exactly what someone typed before clicking your ad and whether that click generated a quality lead or was a waste of money. Most law firms, or the advertising agencies they work with, either skip this entirely or check it once a quarter.
Keep your spend efficient by reviewing the report every week to identify and add negative keywords to your campaign. This weekly hygiene compounds over the long term.
Allocate budget by funnel stage, not by channel
Most law firms treat Google Ads like a monolith. You’ll get a better ROI if you separate campaigns by funnel stage, intent, budget allocation, and conversion goals.
My PPC strategy is based completely on the Pareto Principle (aka the 80/20 rule): About 80% of your spend goes to bottom-of-funnel direct response, and 20% goes to mid-funnel and retargeting. Here’s what that looks like in practice:
Bottom of funnel
This is where most of your signed cases will come from. These are high-intent search campaigns and Local Services Ads. 
LSAs are the best-converting channel for personal injury firms, Pareto Legal’s “The State of Law Firm PPC” report found. They are pay-per-lead, review-driven, and require no landing page infrastructure from you. (Disclosure: I’m the CEO and co-founder of Pareto Legal.)







One of the fastest lead-quality wins we consistently see with new clients is correcting their LSA category selections from broad practice areas to specific case types, such as personal injury or motor vehicle accidents. 
Mid-funnel
This includes non-brand search, Dynamic Search Ads, and segmented Performance Max. Evaluate these on qualified lead rate, not raw volume. If a campaign generates 200 leads but only 10 are qualified, it’s a budget drain, even with a good-looking CPL.
Top of funnel
Meta and YouTube retargeting can target people who have already visited your website. Expand these campaigns to cold prospecting only after attribution proves incremental lift.
This framework is simple, but it can dramatically improve your PPC results. For one injury firm, we generated 273 signed cases from $765,000 in ad spend (3.57x ROI) without increasing the budget. All it required was a restructuring of the firm’s Google Ads.
Dig deeper: Why your law firm’s best leads don’t convert after research




	
	
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Build landing pages that match intent, not just keywords
Sending paid traffic to your homepage or a generic practice area page that doesn’t match the ad you ran is a conversion-rate killer. This is common knowledge, yet effective landing pages are probably the most overlooked part of PPC management. 
Many great PPC marketers know bidding strategy, campaign structure, and audience targeting inside and out. But when it comes to building a high-quality, compelling user experience, many marketers fall short.
What kind of landing pages work? 
Your goal should be to match the intent of what your prospect was searching for. Here are the important components:
An intent-matched H1 headline.
Settlement amounts.
Client reviews as social proof.
Click-to-call and live chat options.
Your landing pages should also load quickly and be mobile-first.
You need one page per practice area, per intent. For example, a “car accident lawyer” landing page and a “truck accident attorney” landing page should be different. Each practice area and intent level deserves its own experience and unique design.
What kind of results will you see?
I split one client’s generic personal injury page into intent-segmented pages, added a stack of recent reviews and results, and reduced form fields from nine to four. Our team also optimized load time from 5.1 seconds to 2.1 seconds.
The page conversion rate went from 3.8% to 17.4%. The cost per signed case dropped by 42% with the same ad spend.
Dig deeper: The future of law firm SEO depends on authority, not volume



Fix the intake bottleneck before you scale ads
Most agencies won’t tell you the primary reason law firm advertising fails. It’s not the marketing process itself. 
Surface-level numbers like cost per click (CPC) are often fine. What fails is the intake process. You need to focus on what happens after the form fill or phone call.
Here are the key intake KPIs to track alongside your ad metrics:
Answer rate: Target 90% or higher.
Speed to lead: Target under 60 seconds.
Signed rate (the percentage of qualified leads that become retained clients): A healthy benchmark is 25% to 40% of qualified leads.
The math is simple: If you’re spending $20,000 on Google Ads every month and your average cost per lead is $250, that’s 80 leads. If your intake team only contacts 70% of them and signs 30% of those contacts, you get about 17 cases.
If your team responds to 95% and converts 40%, that’s 30 cases from the same $20,000. You’ve essentially doubled your return on Google Ads, and it had nothing to do with your ad spend.
The key is for your marketing and intake teams to share KPIs. You can’t have the media buyer optimizing for lead volume while the intake team cherry-picks easy calls.
Connect the full attribution chain: Ad click to signed retainer




Most law firm reporting isn’t detailed enough to serve as a decision-making tool. It stops at platform metrics such as impressions, clicks, and cost per lead. These reports rarely reach the CRM, where signed cases actually live and where the most valuable intelligence resides.
Your attribution infrastructure needs these components:
UTMs and click IDs from ad platforms to capture the traffic source.
Call tracking through a tool like CallRail to handle phone leads.
Google Analytics 4 for tracking post-click behavior on the site.
A CRM, such as Lawmatics or Clio, that tracks post-conversion activity all the way through to the signed case.
The metric that ties everything together is marketing efficiency ratio (MER): total revenue divided by total marketing spend.
MER forces you to evaluate marketing as an ecosystem instead of looking at each channel through last-click attribution. For example, knowing you have a healthy MER can help you spot the hidden work a single channel is doing, even if it looks expensive on a last-click basis. MER can help you maintain confidence in your budget allocation.
Your ideal dashboard setup
Every law firm should build a one-page dashboard with these metrics: spend, leads, qualified leads, signed cases, cost per lead (CPL), and cost per acquisition (CPA), all broken down by channel and practice area.
If your reports can’t drill down to this level of granularity, they’re probably just a slideshow. Building this tracking infrastructure makes it easy to identify winning campaigns and reallocate budget intelligently. This is how you increase ROI without additional funding.

  
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Treating PPC like a system leads to success
The firms that succeed with PPC treat it like a system. They:
Use precise keyword targeting tied to their prospects’ real behavior. 
Allocate budget by funnel stage and intent. 
Review search terms weekly.
Know their numbers: cost per case, not just cost per click. 
Connect the ad click to the signed retainer, so every budget decision is based on what actually matters.
Don’t trust Google to figure this out for you.

Learn how to identify leaks between the ad click and signed retainer, and make smarter budget decisions based on case outcomes.

Law firm PPC: How to optimize for signed cases instead of leads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google is adding new ways for advertisers to scale campaigns while maintaining tighter control over efficiency targets.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/SMart-Bidding-Exploration-expands-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p id="h-google-is-rolling-out-a-series-of-smart-bidding-and-budgeting-updates-designed-to-help-advertisers-uncover-new-demand-capitalize-on-seasonal-opportunities-and-maintain-more-predictable-campaign-performance">Google is rolling out a series of Smart Bidding and budgeting updates designed to help advertisers uncover new demand, capitalize on seasonal opportunities and maintain more predictable campaign performance.</p>



<p><strong>What&#8217;s new</strong>. The updates include an expansion of <a href="https://searchengineland.com/google-smart-bidding-exploration-455756">Smart Bidding Exploration</a>, a new Promotion Mode beta and changes to bidding target optimization for budget-constrained campaigns.</p>



<p><strong>Driving discovery</strong>. Smart Bidding Exploration now allows advertisers to set a return on ad spend (ROAS) tolerance that enables campaigns to pursue additional conversion opportunities from search queries they may not currently be capturing.</p>



<p>Google says campaigns using the feature see, on average, an 18% increase in unique converting search query categories and a 19% increase in conversions.</p>



<p>The company is expanding the capability to Performance Max campaigns without product feeds and opening a beta for Shopping ads across both Performance Max and Standard Shopping campaigns.</p>



<p><strong>Peak period bidding</strong>. Promotion Mode allows advertisers to temporarily adjust ROAS targets and allocate additional daily budget during high-demand periods such as seasonal events, product launches and flash sales.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="625" height="436" src="https://searchengineland.com/wp-content/seloads/2026/06/Promotion-mode.png" alt="" class="wp-image-480166"/></figure>



<p><strong>What else is changing</strong>. Beginning Aug. 17, Google will update bidding target optimization for campaigns limited by budget, with the goal of delivering more consistent performance that better aligns with advertisers&#8217; CPA and ROAS targets.</p>



<p>Starting July 6, advertisers will begin receiving notifications in Google Ads if campaign adjustments may be needed.</p>



<p><strong>Why we care. </strong>These updates give Google&#8217;s AI bidding systems more freedom to find incremental conversions beyond existing keyword and audience patterns, potentially unlocking new demand that campaigns might otherwise miss. </p>



<p>The new Promotion Mode is particularly relevant for retailers and seasonal advertisers, as it allows temporary adjustments to ROAS targets and budgets during peak demand periods without requiring major campaign restructuring. Meanwhile, the bidding optimization changes aim to make performance more predictable for campaigns that are constrained by budget.</p>



<p><strong>The bottom line</strong>. <a href="https://business.google.com/us/accelerate/announcements/bidding-and-budgeting-updates-to-scale-your-growth/">Google&#8217;s latest bidding updates</a> are designed to help advertisers find new conversion opportunities, respond more aggressively during peak demand periods and maintain steadier performance as campaigns scale.</p>


Google is rolling out a series of Smart Bidding and budgeting updates designed to help advertisers uncover new demand, capitalize on seasonal opportunities and maintain more predictable campaign performance.
What’s new. The updates include an expansion of Smart Bidding Exploration, a new Promotion Mode beta and changes to bidding target optimization for budget-constrained campaigns.
Driving discovery. Smart Bidding Exploration now allows advertisers to set a return on ad spend (ROAS) tolerance that enables campaigns to pursue additional conversion opportunities from search queries they may not currently be capturing.
Google says campaigns using the feature see, on average, an 18% increase in unique converting search query categories and a 19% increase in conversions.
The company is expanding the capability to Performance Max campaigns without product feeds and opening a beta for Shopping ads across both Performance Max and Standard Shopping campaigns.
Peak period bidding. Promotion Mode allows advertisers to temporarily adjust ROAS targets and allocate additional daily budget during high-demand periods such as seasonal events, product launches and flash sales.




What else is changing. Beginning Aug. 17, Google will update bidding target optimization for campaigns limited by budget, with the goal of delivering more consistent performance that better aligns with advertisers’ CPA and ROAS targets.
Starting July 6, advertisers will begin receiving notifications in Google Ads if campaign adjustments may be needed.
Why we care. These updates give Google’s AI bidding systems more freedom to find incremental conversions beyond existing keyword and audience patterns, potentially unlocking new demand that campaigns might otherwise miss. 
The new Promotion Mode is particularly relevant for retailers and seasonal advertisers, as it allows temporary adjustments to ROAS targets and budgets during peak demand periods without requiring major campaign restructuring. Meanwhile, the bidding optimization changes aim to make performance more predictable for campaigns that are constrained by budget.
The bottom line. Google’s latest bidding updates are designed to help advertisers find new conversion opportunities, respond more aggressively during peak demand periods and maintain steadier performance as campaigns scale.

Google is adding new ways for advertisers to scale campaigns while maintaining tighter control over efficiency targets.

Google expands Smart Bidding Exploration, adds Promotion Mode

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Clear branding and positive user experiences may play a larger role in maintaining Google Search ad reach going forward.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Ads-visibility-update-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p>Google is broadening its Limited ad serving policy on Search, giving itself more authority to restrict impressions from advertisers it considers unqualified or potentially confusing to users.</p>



<p>The update could affect how frequently ads appear on certain searches, particularly for newer advertisers, brands with poor user feedback or advertisers whose identity is not clearly communicated in their ads.</p>



<p><strong>What&#8217;s changing</strong>. Starting this month, Google expanded the policy to cover additional Search scenarios, with implementation rolling out gradually through 2028.</p>



<p>Under the updated rules, Google may limit ad impressions on searches that it believes have a higher risk of creating negative user experiences.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1078" height="1076" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-limited-ad-serving-policy.png" alt="" class="wp-image-480138" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-limited-ad-serving-policy.png 1078w, https://searchengineland.com/wp-content/seloads/2026/06/Google-limited-ad-serving-policy-768x767.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Google-limited-ad-serving-policy-95x95.png 95w, https://searchengineland.com/wp-content/seloads/2026/06/Google-limited-ad-serving-policy-675x675.png 675w" sizes="(max-width: 1078px) 100vw, 1078px" /></figure>



<p><strong>How Google decides</strong>. User feedback will play a larger role in determining whether an advertiser is qualified. Advertisers that receive persistent and disproportionate reports about misleading content, products or business practices may see their ads restricted on certain searches.</p>



<p>Google also says it may limit ads that make it difficult for users to identify who the advertiser actually is.</p>



<p><strong>Why we care. </strong>Google is applying more discretion to limiting ad visibility, making it based on advertiser trust signals and branding clarity, not just policy compliance. That means advertisers with generic ad copy, unclear brand identity or a history of negative user feedback could see reduced reach on certain searches.</p>



<p>The change also reinforces the growing importance of brand transparency in Search ads. Advertisers may need to revisit ad copy, landing pages and branding elements to ensure users can immediately identify who is behind an ad and why they&#8217;re seeing it.</p>



<p><strong>What advertisers should do</strong>. Google is encouraging advertisers to strengthen brand visibility across both ads and landing pages, avoid overly generic messaging and clearly communicate any affiliation with other brands.</p>



<p>The company also recommends pinning a domain headline in the first position of responsive search ads to make advertiser identity more obvious to users.</p>



<p><strong>The bottom line</strong>. <a href="https://support.google.com/adspolicy/answer/17122370?hl=en">Google&#8217;s updated policy</a> gives greater weight to advertiser trustworthiness and clear branding, potentially limiting visibility for advertisers whose identity or business practices create confusion for users.</p>



<p><strong>First spotted</strong>. This update was spotted by Founder of Adsquire, Anthony Higman, who shared his displeasure of this update on <a href="https://www.linkedin.com/posts/anthony-higman-a3656a46_this-is-actually-insane-we-have-share-7471249928388993024-ja0x/?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAJTV04Bw5M-1qqJtnImkpsEOFw9bHvfSSs">LinkedIn</a>. </p>


Google is broadening its Limited ad serving policy on Search, giving itself more authority to restrict impressions from advertisers it considers unqualified or potentially confusing to users.
The update could affect how frequently ads appear on certain searches, particularly for newer advertisers, brands with poor user feedback or advertisers whose identity is not clearly communicated in their ads.
What’s changing. Starting this month, Google expanded the policy to cover additional Search scenarios, with implementation rolling out gradually through 2028.
Under the updated rules, Google may limit ad impressions on searches that it believes have a higher risk of creating negative user experiences.




How Google decides. User feedback will play a larger role in determining whether an advertiser is qualified. Advertisers that receive persistent and disproportionate reports about misleading content, products or business practices may see their ads restricted on certain searches.
Google also says it may limit ads that make it difficult for users to identify who the advertiser actually is.
Why we care. Google is applying more discretion to limiting ad visibility, making it based on advertiser trust signals and branding clarity, not just policy compliance. That means advertisers with generic ad copy, unclear brand identity or a history of negative user feedback could see reduced reach on certain searches.
The change also reinforces the growing importance of brand transparency in Search ads. Advertisers may need to revisit ad copy, landing pages and branding elements to ensure users can immediately identify who is behind an ad and why they’re seeing it.
What advertisers should do. Google is encouraging advertisers to strengthen brand visibility across both ads and landing pages, avoid overly generic messaging and clearly communicate any affiliation with other brands.
The company also recommends pinning a domain headline in the first position of responsive search ads to make advertiser identity more obvious to users.
The bottom line. Google’s updated policy gives greater weight to advertiser trustworthiness and clear branding, potentially limiting visibility for advertisers whose identity or business practices create confusion for users.
First spotted. This update was spotted by Founder of Adsquire, Anthony Higman, who shared his displeasure of this update on LinkedIn.

Clear branding and positive user experiences may play a larger role in maintaining Google Search ad reach going forward.

Google expands limited ad serving policy on Search

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Search marketing jobs" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing-550x310.jpg 550w, https://searchengineland.com/wp-content/seloads/2021/10/hiring-in-search-marketing.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Land your next job in SEO or PPC. These brands and agencies are hiring to fill open search marketing positions right now.

Looking to take the next step in your search marketing career? 
Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.
Newest SEO Jobs 
(Provided to Search Engine Land by SEOjobs.com) 



VP / Head of Search & AI Visibility
June 15, 2026 
VP / Head of Search & AI Visibility Location: United States (Remote / Hybrid Preferred) Reports To – President/Founder Company: Milestone Inc. (direct hire) Term: Full-time About Milestone Milestone Inc. is a leading Digital Experience Software and Services company dedicated to providing comprehensive solutions across all touch points that enhance customer engagement and drive business growth. […]

SEO Specialist
June 11, 2026 
About Us At The Law Office of Yohana Saucedo, we are more than an immigration law firm—we are a mission-driven organization dedicated to helping immigrants build secure futures in the United States. Every case represents a family, a dream, and an opportunity to change a life. As our firm continues to grow, we are seeking […]

Content Marketing Manager
June 11, 2026 
Mission 4Minds is an enterprise AI fine-tuning platform that transforms how organizations build and operate private, domain-specific AI. Unlike static systems, 4Minds’s AI platform learns continuously from live data in real time and can be deployed on-prem or your cloud provider. Our patented technologies scale existing engineering teams and empower new AI teams, enabling rapid […]

Marketing Manager SEO, AWS Search Marketing
June 11, 2026 
This job is with Amazon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. DESCRIPTION: Amazon Web Services (AWS) is seeking an experienced, results-driven Search Engine Optimization Manager to own the development, implementation, and optimization of the search experience […]

Client Account Manager
June 9, 2026 
We’re a content and organic discovery agency that helps brands show up in the right places — Reddit, YouTube, editorial, AI search. Our team is small, the work is real, and everyone here actually cares about doing it well. We’re looking for a Client Account Manager to be the connective tissue between our clients and […]

SEO Link Builder
June 8, 2026 
ABOUT NOGIGIDDY NoGigiddy is a digital platform built for gig workers, side hustlers, and anyone building an income outside the traditional 9-to-5. We connect our community with real earning opportunities — remote jobs, surveys, gig platforms, and financial tools — all in one place, free to access, no gatekeeping. We built what we wish had […]

Senior Content Marketer, SEO
June 7, 2026 
Animalz is a content marketing agency that partners with B2B SaaS companies, venture capital firms, and other tech organizations to drive long-term, sustainable growth through high-quality content. Our fully remote team of strategists and content marketers delivers content strategies tailored to each customer’s goals and context. We pride ourselves on our deep interest and understanding […]

Director of SEO
June 6, 2026 
Job Description:   The Director of SEO will be responsible for leading the SEO department, including overseeing the daily operations of the team, and setting the direction for future SEO growth and product efforts. The Director of SEO will lead the SEO management team and be responsible for offering SEO expertise to the team, establishing […]

SEO & Web Analytics Manager
June 6, 2026 
Description Are you an SEO professional who enjoys solving technical challenges, uncovering insights in data, and helping organizations improve their visibility in search? Interactive Strategies, a leading digital agency in Washington, DC, is seeking an SEO & Web Analytics Manager to join our Data Insights team. This is a hands-on role focused on technical SEO, analytics reporting, […]

SEO Specialist
June 4, 2026 
SEO SPECIALIST Location: U.S. (Remote) Working Hours: 8:30 AM – 5:30 PM CST, Monday to Friday Salary: 45-50k/per year About the Role We are looking for a motivated and experienced SEO Specialist to join our MedTech-focused marketing team. This role is ideal for someone who enjoys both strategic thinking and hands-on execution. You will be […]

Newest PPC and paid media jobs
(Provided to Search Engine Land by PPCjobs.com) 







Paid Social Media Manager: Campaigns & Optimization
June 15, 2026 
Whalar Group in New York is seeking a Manager, Media to execute and optimize paid social media campaigns. You will drive tactical excellence and support strategy development through analysis and reporting. The ideal candidate has 3-4 years of experience in social media, familiarity with various tools, and strong communication skills. This role comes with a […]

Hybrid Paid Social Strategy Manager
June 15, 2026 
WPP Media Limited in New York seeks a Manager, Paid Social to oversee the operational management of clients' paid social marketing initiatives. This role involves managing team members while focusing on strategic development for dedicated accounts. The ideal candidate should have proven experience in campaign strategy development, as well as the ability to analyze campaign […]

Senior Paid Social Marketing Manager
June 15, 2026 
TEGNA is seeking a Paid Marketing Manager – Social for its New York City location. The ideal candidate will have extensive experience in scaling social media campaigns and strong analytical skills. This role focuses on developing strategies for driving traffic and engagement across various platforms. With a competitive pay range of $100,000—$130,000, TEGNA offers comprehensive […]

Growth Marketing Specialist – Paid Social & Search (Hybrid)
June 15, 2026 
Constellation-Software,-Inc. in New York, NY is seeking a Growth Specialist to drive success through paid social, search, and programmatic campaigns. This full-time hybrid role offers the chance to manage over 50 clients while optimizing campaign performance and maximizing ROI. Qualifications include a Bachelor’s degree, strong interpersonal skills, and up to 2 years of experience in […]

Hybrid Paid Search Manager — AI-Driven Campaigns & Leadership
June 15, 2026 
Digital Matter, located in New York, is seeking a Paid Search Manager to oversee day-to-day management of paid search campaigns. The ideal candidate will have at least 5 years of experience in campaign management, strong analytical skills, and experience mentoring junior staff. In this hybrid role, you will collaborate across teams, present performance updates to […]

Other roles you may be interested in
Search Engine Optimization Manager, Seer Interactive (Remote)
Salary: $70,000 – $100,000
Lead organic strategy for a portfolio of clients, building annual and quarterly roadmaps that account for both traditional SEO performance and Generative Engine Optimization (GEO) visibility across AI-driven search environments.
Serve as the primary point of contact for clients, guiding strategic conversations around organic growth, AI Overviews, LLM-powered discovery tools, and how evolving search behavior impacts brand visibility and competitive positioning.
SEO Manager, Prosum (Dallas-Fort Worth Metroplex)
Salary: $114,000 – $148,000
Develop and execute multi-brand SEO and search visibility strategies aligned to revenue, traffic, and share-of-voice goals.
Manage internal and external resources, including contractors and cross-functional partners, to deliver against SEO and search visibility initiatives.
Senior Manager SEO/Gen AI (FTC), Jellyfish (Hybrid, New York, US)
Salary: $90,000 – $115,000
Act as the lead interpreter of search performance and visibility quality across both traditional and AI-led discovery experiences
Maintain a broad expertise across the evolving landscape of LLMs and generative engines, including Google Gemini, OpenAI GPT, Anthropic Claude, and other leading frontier models
Lead Marketing Manager, SEO, Care.com (Hybrid, Dallas, TX)
Salary: $125,000 – $135,000
Organic Growth: Build and execute the SEO roadmap across technical, content, and off-page. Own the numbers: traffic, rankings, conversions. No handoffs, no excuses.
AI-Optimized Search (AIO): Define and drive CARE.com’s strategy for visibility in AI-generated results — Google AI Overviews, ChatGPT, Perplexity, and whatever comes next. Optimize entity coverage, content structure, and schema to ensure we’re the answer, not just a result.
SEO Marketing Manager (phone accessories), Velvet Caviar ($100,000 – $120,000)
Salary: $100,000 – $120,000
Own and execute the SEO strategy for a high-growth e-commerce business, driving organic traffic, revenue, and conversion improvements.
Conduct keyword research, competitive analysis, and SEO audits to identify and prioritize high-impact growth opportunities.
Sr. Content Marketing Manager, Dayforce (Remote)
Salary: $82,700 – $147,000
Write and publish high-quality, search-optimized content on a consistent cadence, including (but not limited to) blogs, thought leadership, comparison pages, FAQs, infographics, and other digital content assets.
Create structured, answer-first content designed to be surfaced in AI-generated responses and LLM-driven experiences.
Paid Media Manager, Clients Blackbox, Inc. (Remote)
Salary: $90,000 – $125,000
Build, launch, and optimize Meta advertising campaigns focused on lead generation and appointment booking
Manage campaign budgets, audience targeting, bid strategies, and creative testing
Senior Manager, Paid Search, Talkiatry (Hybrid, New York, NY)
Salary: $150,000 – $180,000
Own and scale Talkiatry’s paid search program end-to-end, including forecasting, budgeting, pacing, bidding strategies, account structure, and creative testing for Google, Bing, and ZocDoc.
Develop and execute a rigorous testing roadmap, including ad copy, keyword strategy, landing page variants, and automation/algorithmic controls; quantify impact using sound experimental design.
Paid Digital Marketing Manager, Pei Wei (Irving, Texas)
Salary: $75,000 – $110,000
Develop and manage paid digital marketing strategies across multiple channels, including: Paid Search, Performance Max (PMAX), Meta Ads (Facebook & Instagram)
Monitor, optimize, and scale campaigns based on performance KPIs including ROAS,CPA, conversions, traffic, impressions, engagement, and sales.
Marketing, Social Media & PR Manager, PARTNERS Staffing (Fort Myers, FL)
Salary: $75,000 – $85,000
Develop and execute integrated marketing campaigns for shows, content releases, events, and brand initiatives
Identify target audiences and create strategies to grow reach and engagement
Senior Paid Media Manager, Brightly Media Lab (Remote)
Salary: $70,000 – $100,000
Directly build, manage, and optimize campaigns within Google Ads, Microsoft Ads, and Facebook Ads (Meta).
Serve as the lead point of contact for your book of clients, taking full ownership of their success and growth.
Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)
Salary: $65,000 – $70,000
Plan, set up, and manage paid search, display, and shopping campaigns on Google Ads.
Manage and optimize advertising budgets to achieve revenue and efficiency targets.
Note: We update this post weekly. So make sure to bookmark this page and check back.

Land your next job in SEO or PPC. These brands and agencies are hiring to fill open search marketing positions right now.

The latest jobs in search marketing

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Microsoft Ads' Product Explorer helps advertisers quickly identify catalog issues that may be limiting ad performance.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer1-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p>Microsoft Ads is introducing Product Explorer, a new reporting tool designed to give advertisers a centralized view of product catalog health and performance, according to Microsoft Product Liaison Navah Hopkins.</p>



<p>Managing large product feeds can make it difficult to identify which items are eligible to serve, generating impressions or missing critical data. Product Explorer aims to simplify that process.</p>



<p><strong>What&#8217;s new</strong>. Product Explorer provides a searchable view of an advertiser&#8217;s entire product catalog, allowing users to filter products by attributes such as SKU, title, GTIN and product ID.</p>



<p>Advertisers can quickly see which products are active, serving ads and driving performance.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="713" height="541" src="https://searchengineland.com/wp-content/seloads/2026/06/Microsoft-Product-Explorer.png" alt="" class="wp-image-480122"/></figure>



<p><strong>What it does</strong>. The tool highlights eligibility issues, metadata gaps and other factors preventing products from serving. It also surfaces recommended actions and allows advertisers to export filtered product lists for further analysis.</p>



<p><strong>Why we care.</strong> By combining feed diagnostics and performance reporting in a single interface, Microsoft is making it easier for advertisers to move more products into a servable state and identify underperforming inventory.</p>



<p>Advertisers will now get searchable catalog reporting, product-level performance data covering the previous 30 days, issue detection and actionable recommendations to improve feed quality.</p>



<p><strong>The big picture</strong>. Retail advertisers are increasingly focused on feed quality as product-based advertising becomes more automated. Visibility into catalog issues can have a direct impact on campaign reach and performance.</p>



<p><strong>Availability. </strong>Hopkins said it should be live in accounts already.</p>


Microsoft Ads is introducing Product Explorer, a new reporting tool designed to give advertisers a centralized view of product catalog health and performance, according to Microsoft Product Liaison Navah Hopkins.
Managing large product feeds can make it difficult to identify which items are eligible to serve, generating impressions or missing critical data. Product Explorer aims to simplify that process.
What’s new. Product Explorer provides a searchable view of an advertiser’s entire product catalog, allowing users to filter products by attributes such as SKU, title, GTIN and product ID.
Advertisers can quickly see which products are active, serving ads and driving performance.




What it does. The tool highlights eligibility issues, metadata gaps and other factors preventing products from serving. It also surfaces recommended actions and allows advertisers to export filtered product lists for further analysis.
Why we care. By combining feed diagnostics and performance reporting in a single interface, Microsoft is making it easier for advertisers to move more products into a servable state and identify underperforming inventory.
Advertisers will now get searchable catalog reporting, product-level performance data covering the previous 30 days, issue detection and actionable recommendations to improve feed quality.
The big picture. Retail advertisers are increasingly focused on feed quality as product-based advertising becomes more automated. Visibility into catalog issues can have a direct impact on campaign reach and performance.
Availability. Hopkins said it should be live in accounts already.

Microsoft Ads' Product Explorer helps advertisers quickly identify catalog issues that may be limiting ad performance.

Microsoft Ads launches Product Explorer for catalog insights

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google Analytics is introducing cleaner source attribution and new filtering controls, for easier cross-channel performance analysis

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping.png 1672w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/Google-Analytics-source-grouping-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p>Google Analytics is introducing a new Source Group reporting dimension and hostname filtering controls aimed at improving attribution analysis and data quality.</p>



<p>The updates are designed to help advertisers clean up fragmented traffic source reporting, better analyze cross-channel performance and reduce noise in their analytics data.</p>



<p><strong>What&#8217;s new</strong>. Source Group is a new reporting dimension that consolidates multiple variations of the same traffic source into a standardized category.</p>



<p>For example, traffic from Facebook can now be grouped under a single reporting value instead of appearing across multiple naming conventions such as &#8220;facebook,&#8221; &#8220;fb&#8221; or other variations.</p>



<p>At the same time, Google is updating its existing Source Platform field to align with the new grouping structure and provide more consistent classifications across advertising channels.</p>



<p><strong>Why we care. </strong>Cleaner source classification means more accurate attribution and cross-channel reporting. Instead of traffic being fragmented across inconsistent labels, marketers can more easily understand which platforms are actually driving conversions and where budgets are performing best.</p>



<p>The inclusion of AI traffic sources like ChatGPT and Perplexity is particularly noteworthy, as it gives advertisers a standardized way to measure and compare emerging AI-driven referral traffic alongside traditional channels. The new hostname filters also help improve data quality by ensuring only traffic from approved domains is included in reporting.</p>



<p><strong>The big picture</strong>. As advertisers manage campaigns across a growing number of platforms, inconsistent source naming can make attribution and budget analysis more difficult. The new reporting structure is intended to simplify performance comparisons across channels.</p>



<p><strong>Between the lines</strong>. The update expands source standardization beyond Google&#8217;s own properties, creating consistent classifications for platforms including TikTok, Pinterest and Amazon while also introducing support for emerging AI-driven traffic sources such as ChatGPT and Perplexity.</p>



<p><strong>Also new</strong>. Google is launching hostname filters within the Admin section, allowing advertisers to exclude events from unapproved domains before they enter reporting.</p>



<p>The feature is designed to help improve data accuracy by preventing unwanted traffic from influencing analysis.</p>



<p><strong>What advertisers get</strong>. Standardized source reporting, retroactive access to historical source group data, cleaner attribution analysis and greater control over which domains contribute data to reporting.</p>



<p><strong>The bottom line</strong>. <a href="https://support.google.com/analytics/answer/9164320?hl=en#06112026">Google is adding new tools to help advertisers improve reporting consistency</a>, strengthen attribution analysis and maintain cleaner datasets as traffic sources become more fragmented.</p>


Google Analytics is introducing a new Source Group reporting dimension and hostname filtering controls aimed at improving attribution analysis and data quality.
The updates are designed to help advertisers clean up fragmented traffic source reporting, better analyze cross-channel performance and reduce noise in their analytics data.
What’s new. Source Group is a new reporting dimension that consolidates multiple variations of the same traffic source into a standardized category.
For example, traffic from Facebook can now be grouped under a single reporting value instead of appearing across multiple naming conventions such as “facebook,” “fb” or other variations.
At the same time, Google is updating its existing Source Platform field to align with the new grouping structure and provide more consistent classifications across advertising channels.
Why we care. Cleaner source classification means more accurate attribution and cross-channel reporting. Instead of traffic being fragmented across inconsistent labels, marketers can more easily understand which platforms are actually driving conversions and where budgets are performing best.
The inclusion of AI traffic sources like ChatGPT and Perplexity is particularly noteworthy, as it gives advertisers a standardized way to measure and compare emerging AI-driven referral traffic alongside traditional channels. The new hostname filters also help improve data quality by ensuring only traffic from approved domains is included in reporting.
The big picture. As advertisers manage campaigns across a growing number of platforms, inconsistent source naming can make attribution and budget analysis more difficult. The new reporting structure is intended to simplify performance comparisons across channels.
Between the lines. The update expands source standardization beyond Google’s own properties, creating consistent classifications for platforms including TikTok, Pinterest and Amazon while also introducing support for emerging AI-driven traffic sources such as ChatGPT and Perplexity.
Also new. Google is launching hostname filters within the Admin section, allowing advertisers to exclude events from unapproved domains before they enter reporting.
The feature is designed to help improve data accuracy by preventing unwanted traffic from influencing analysis.
What advertisers get. Standardized source reporting, retroactive access to historical source group data, cleaner attribution analysis and greater control over which domains contribute data to reporting.
The bottom line. Google is adding new tools to help advertisers improve reporting consistency, strengthen attribution analysis and maintain cleaner datasets as traffic sources become more fragmented.

Google Analytics is introducing cleaner source attribution and new filtering controls, for easier cross-channel performance analysis

Google Analytics adds source grouping and hostname filtering

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers.png" class="attachment-large size-large wp-post-image" alt="Top 10 search ranking AI answers" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Claude frequently pulls from Brave Search results, with ranking, recency, and comparison prompts triggering searches most often.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers.png" class="attachment-large size-large wp-post-image" alt="Top 10 search ranking AI answers" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers.png 1920w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/06/top-10-search-ranking-ai-answers-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Claude may be more directly tied to Brave Search rankings than other AI answer engines, according to information <a href="https://searchengineland.com/author/jon-clark">Jonathan Clark</a> shared <a href="https://www.linkedin.com/posts/ppcmarketing_claude-doesnt-re-rank-search-results-it-activity-7470936887109664769-TOBd/">on LinkedIn</a> from a Zero Click by Profound session.</p>



<p>Clark, managing partner at Moving Traffic Media, said the session’s key takeaway was that Claude “doesn’t re-rank search results” and instead appears to use Brave’s top 10 results directly in its answers.</p>



<p><strong>Claude searched less often. </strong>Claude used web search in 36.6% of prompts, compared with about 90% for ChatGPT, according to Clark.</p>



<ul class="wp-block-list">
<li>Claude was most likely to search when prompts signaled freshness, rankings, location, or comparison intent. Recency-focused prompts such as “best XYZ” triggered search 81% of the time, while ranking-focused prompts triggered search 67% of the time.</li>



<li>Location-focused prompts triggered search 55% of the time, while comparison prompts such as “X vs. Y” triggered search 51% of the time.</li>
</ul>



<p><strong>Brave rankings carried weight. </strong>Claude’s citations overlapped with ChatGPT’s in only 8% of cases when responding to the same prompts, according to Clark.</p>



<ul class="wp-block-list">
<li>Claude’s results had much higher overlap with Google rankings, at 64%. This suggests that Google SEO efforts may carry over more readily to Claude than strategies focused specifically on improving visibility in ChatGPT, according to Clark.</li>



<li>The finding also increased the importance of Brave rank tracking. Clark said Claude uses Brave, and that ranking well in Brave gives us “something we can monitor and correlate to data.”</li>
</ul>



<p><strong>Some prompts stayed in memory. </strong>Prompts such as “how does,” “what is,” and “steps to” were less likely to trigger Claude to search the web. When Claude doesn&#8217;t search, it can&#8217;t cite web pages. Claude searched most often for prompts containing terms such as “best,” “top,” “near me,” and comparison-style queries, according to Clark.</p>



<p><strong>Years showed up often. </strong>Clark also noted two patterns that could make Claude easier to test:</p>



<ul class="wp-block-list">
<li>Claude’s query fan-outs were nearly deterministic, producing the same fan-out 65% of the time across users. </li>



<li>The fan-outs often included years.
<ul class="wp-block-list">
<li>That means page titles with current-year signals may have an advantage in Claude-triggered searches, especially for ranking and freshness-driven prompts.</li>
</ul>
</li>
</ul>



<p><strong>Why we care.</strong> Claude visibility appears to depend more heavily on ranking in the search results Claude uses. Clark’s takeaway was that Claude may be one of the most optimizable AI answer engines today because its search behavior appears more consistent and more closely tied to observable search rankings.</p>


Claude may be more directly tied to Brave Search rankings than other AI answer engines, according to information Jonathan Clark shared on LinkedIn from a Zero Click by Profound session.
Clark, managing partner at Moving Traffic Media, said the session’s key takeaway was that Claude “doesn’t re-rank search results” and instead appears to use Brave’s top 10 results directly in its answers.
Claude searched less often. Claude used web search in 36.6% of prompts, compared with about 90% for ChatGPT, according to Clark.
Claude was most likely to search when prompts signaled freshness, rankings, location, or comparison intent. Recency-focused prompts such as “best XYZ” triggered search 81% of the time, while ranking-focused prompts triggered search 67% of the time.
Location-focused prompts triggered search 55% of the time, while comparison prompts such as “X vs. Y” triggered search 51% of the time.
Brave rankings carried weight. Claude’s citations overlapped with ChatGPT’s in only 8% of cases when responding to the same prompts, according to Clark.
Claude’s results had much higher overlap with Google rankings, at 64%. This suggests that Google SEO efforts may carry over more readily to Claude than strategies focused specifically on improving visibility in ChatGPT, according to Clark.
The finding also increased the importance of Brave rank tracking. Clark said Claude uses Brave, and that ranking well in Brave gives us “something we can monitor and correlate to data.”
Some prompts stayed in memory. Prompts such as “how does,” “what is,” and “steps to” were less likely to trigger Claude to search the web. When Claude doesn’t search, it can’t cite web pages. Claude searched most often for prompts containing terms such as “best,” “top,” “near me,” and comparison-style queries, according to Clark.
Years showed up often. Clark also noted two patterns that could make Claude easier to test:
Claude’s query fan-outs were nearly deterministic, producing the same fan-out 65% of the time across users. 
The fan-outs often included years.

That means page titles with current-year signals may have an advantage in Claude-triggered searches, especially for ranking and freshness-driven prompts.
Why we care. Claude visibility appears to depend more heavily on ranking in the search results Claude uses. Clark’s takeaway was that Claude may be one of the most optimizable AI answer engines today because its search behavior appears more consistent and more closely tied to observable search rankings.

Claude frequently pulls from Brave Search results, with ranking, recency, and comparison prompts triggering searches most often.

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