<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-1200x675.jpg 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>This new search box aims to gives searchers easier access to AI search capabilities, with longer prompts and more AI options.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/05/google-intelligent-search-box-1920-1-1200x675.jpg 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google unveiled the biggest change to its search box in 25 years. It is calling the new search box the &#8220;Intelligent Search box.&#8221; The new search box aims to bring easier access to the AI search features in Google Search to Google&#8217;s users.</p>



<p>And yes, this is all powered by the latest Gemini release, Gemini 3.5 Flash.  </p>



<p><strong>What it looks like. </strong>Google redesigned this search box to give searchers more space to ask longer, deeper queries.  The search box will continue to expand as the user enters the query or prompt. There is an AI-powered suggestion that Google&#8217;s Head of Search, Liz Reid, said &#8220;goes beyond autocomplete.&#8221; </p>



<p>Plus, you can search with text, images, files, videos or your Chrome tabs. </p>



<p>Here is what the new intelligent search box looks like:</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Intelligent-Search-Box.mp4"></video></figure>



<p>This puts Google&#8217;s &#8220;most powerful AI tools right at your fingertips, making it easier to ask your questions,&#8221; Liz Reid of Google said.</p>



<p><strong>Seamless Google Search to AI Mode. </strong>Google also said it made the <a href="https://searchengineland.com/google-ai-overviews-follow-up-questions-jump-you-directly-to-ai-mode-468016">AI Overviews seamless link approach to AI Mode</a> live today globally both on desktop and mobile.  This is something that launched to many back in <a href="https://searchengineland.com/google-ai-overviews-follow-up-questions-jump-you-directly-to-ai-mode-468016">January</a> but is now fully live.</p>



<p>Here is how this works:</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Seamless-AI-Search.mp4"></video></figure>



<p><strong>Why we care. </strong>The Google Search box looks and feels different and that might be a big deal to how it leads to how users search on Google. It might impact the type of search traffic Google has been sending you and will send you in the future. It might lead to more people jumping to AI Mode sooner from Google Search and it might lead to more AI Overviews with deeper answers. It might lead to fewer clicks to your web site than before.</p>



<p>Change is not always easy, but it is inevitable, especially when it comes to Google Search.</p>



<p>Sundar Pichai, Google&#8217;s CEO told us that the extraordinary thing about Search is how people search and expect more from Google Search.&nbsp; Search is evolving, from individual queries to ongoing conversations and now to agentic workflows.&nbsp; Search is the most used product in the world, Sundar said and Google will evolve super hard to stay a step ahead of where our users want to be.</p>


Google unveiled the biggest change to its search box in 25 years. It is calling the new search box the “Intelligent Search box.” The new search box aims to bring easier access to the AI search features in Google Search to Google’s users.
And yes, this is all powered by the latest Gemini release, Gemini 3.5 Flash.  
What it looks like. Google redesigned this search box to give searchers more space to ask longer, deeper queries.  The search box will continue to expand as the user enters the query or prompt. There is an AI-powered suggestion that Google’s Head of Search, Liz Reid, said “goes beyond autocomplete.” 
Plus, you can search with text, images, files, videos or your Chrome tabs. 
Here is what the new intelligent search box looks like:




This puts Google’s “most powerful AI tools right at your fingertips, making it easier to ask your questions,” Liz Reid of Google said.
Seamless Google Search to AI Mode. Google also said it made the AI Overviews seamless link approach to AI Mode live today globally both on desktop and mobile.  This is something that launched to many back in January but is now fully live.
Here is how this works:




Why we care. The Google Search box looks and feels different and that might be a big deal to how it leads to how users search on Google. It might impact the type of search traffic Google has been sending you and will send you in the future. It might lead to more people jumping to AI Mode sooner from Google Search and it might lead to more AI Overviews with deeper answers. It might lead to fewer clicks to your web site than before.
Change is not always easy, but it is inevitable, especially when it comes to Google Search.
Sundar Pichai, Google’s CEO told us that the extraordinary thing about Search is how people search and expect more from Google Search.  Search is evolving, from individual queries to ongoing conversations and now to agentic workflows.  Search is the most used product in the world, Sundar said and Google will evolve super hard to stay a step ahead of where our users want to be.

This new search box aims to gives searchers easier access to AI search capabilities, with longer prompts and more AI options.

Google’s new intelligent Search box – its biggest change to the search box in 25 years

<div><img width="1920" height="1083" src="https://searchengineland.com/wp-content/seloads/2026/05/gemini.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/gemini.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/gemini-768x433.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/gemini-1536x866.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google announced Gemini 3.5 Flash today and immediately it is now powering Google Search as the new default for AI Mode.

<div><img width="1920" height="1083" src="https://searchengineland.com/wp-content/seloads/2026/05/gemini.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/gemini.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/gemini-768x433.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/gemini-1536x866.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google announced its latest and greatest AI model, Gemini 3.5 Flash today at Google I/O. Google&#8217;s head of Search, Liz Reid, <a href="https://blog.google/products-and-platforms/products/search/search-io-2026">said</a> Gemini 3.5 Flash is Google&#8217;s &#8220;newest Flash model delivering sustained frontier performance for agents and coding.&#8221; She added that is now being used to power AI Mode globally.</p>



<p><strong>Gemini 3.5 Flash. </strong>Not only is Gemini 3.5 Flash powering AI Mode in Google Search, but it is also powering the Gemini app, for all users, not just paid users.</p>



<p>For developers, 3.5 Flash is now live in Google Antigravity, Gemini API for Google AI Studio and Android Studio and for enterprise users for Enterprise Agent Platform and Gemini Enterprise.</p>



<p>Koray Kavukcuoglu, CTO of Google DeepMind and Chief AI Architect, said:</p>



<ul class="wp-block-list">
<li>&#8220;Gemini 3.5 Flash delivers intelligence that rivals large flagship models on multiple dimensions, at the speeds you have come to expect from the Flash series.&#8221;</li>



<li>&#8220;It&#8217;s our strongest agentic and coding model yet, outperforming Gemini 3.1 Pro on challenging coding and agentic benchmarks like Terminal-Bench 2.1 (76.2%), GDPval-AA (1656 Elo) and MCP Atlas (83.6%), and leading in multimodal understanding (84.2% on CharXiv Reasoning).&#8221;</li>



<li>&#8220;When looking at output tokens per second, it is 4 times faster than other frontier models. Landing in the top-right quadrant of the Artificial Analysis index, 3.5 Flash delivers frontier-level intelligence at exceptional speed — proving you no longer have to trade quality for latency.&#8221;</li>
</ul>



<p><strong>Why we care. </strong>Gemini 3.5 is already powering Google Search&#8217;s AI Mode and is likely soon to power AI Overviews.  It is a step up from the previous AI model and will continue to get smarter and more useful.</p>



<p>It is important for you to see how the AI Mode responses differ from the previous model for the queries and prompts that matter to your site.</p>



<p>Search is changing rapidly and you need to stay on top of these changes.</p>


Google announced its latest and greatest AI model, Gemini 3.5 Flash today at Google I/O. Google’s head of Search, Liz Reid, said Gemini 3.5 Flash is Google’s “newest Flash model delivering sustained frontier performance for agents and coding.” She added that is now being used to power AI Mode globally.
Gemini 3.5 Flash. Not only is Gemini 3.5 Flash powering AI Mode in Google Search, but it is also powering the Gemini app, for all users, not just paid users.
For developers, 3.5 Flash is now live in Google Antigravity, Gemini API for Google AI Studio and Android Studio and for enterprise users for Enterprise Agent Platform and Gemini Enterprise.
Koray Kavukcuoglu, CTO of Google DeepMind and Chief AI Architect, said:
“Gemini 3.5 Flash delivers intelligence that rivals large flagship models on multiple dimensions, at the speeds you have come to expect from the Flash series.”
“It’s our strongest agentic and coding model yet, outperforming Gemini 3.1 Pro on challenging coding and agentic benchmarks like Terminal-Bench 2.1 (76.2%), GDPval-AA (1656 Elo) and MCP Atlas (83.6%), and leading in multimodal understanding (84.2% on CharXiv Reasoning).”
“When looking at output tokens per second, it is 4 times faster than other frontier models. Landing in the top-right quadrant of the Artificial Analysis index, 3.5 Flash delivers frontier-level intelligence at exceptional speed — proving you no longer have to trade quality for latency.”
Why we care. Gemini 3.5 is already powering Google Search’s AI Mode and is likely soon to power AI Overviews.  It is a step up from the previous AI model and will continue to get smarter and more useful.
It is important for you to see how the AI Mode responses differ from the previous model for the queries and prompts that matter to your site.
Search is changing rapidly and you need to stay on top of these changes.

Google announced Gemini 3.5 Flash today and immediately it is now powering Google Search as the new default for AI Mode.

Google Search now powered by Gemini 3.5 Flash

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google will continuously scan the web to give you updated information on your search - as an agent would do.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-agent-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google also <a href="https://blog.google/products-and-platforms/products/search/search-io-2026">announced</a> new search agents, including information agents and new agentic capabilities within Google Search.  The information agent will continue to scan the web to find and monitor changes to your tasks and help you along your tasks journey.</p>



<p>&#8220;We&#8217;re entering the era of Search agents, where you can easily create, customize and manage multiple Al agents for your many tasks, right in Search,&#8221; Liz Reid, the head of Google Search said.</p>



<p><strong>Information agents. </strong>The information agents will help you stay on top of your questions and tasks.  Google said the agent will &#8220;intelligently look across everything on the web, like blogs, news sites and social posts, plus our freshest data, such as real-time info on finance, shopping and sports, to monitor for changes related to your specific question.&#8221;</p>



<p>The information agent will then send you &#8220;an intelligent, synthesized update, with the ability to take action.&#8221; </p>



<p><strong>The example. </strong>Here is the example Google provided:</p>



<p>&#8220;So if you&#8217;re apartment hunting, you can brain dump all of the exact requirements you&#8217;re looking for, and your agent will continuously scan for you, notifying you when listings meet your needs. Or if you want to know the instant any of your favorite pro athletes announce a sneaker collab, your agent will let you know when a new drop lands so you don&#8217;t miss out.&#8221;</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Information-agents-in-Search.mp4"></video></figure>



<p><strong>Availability. </strong>This will first roll out in the summer to Google Al Pro &amp; Ultra subscribers.</p>



<p><strong>Agentic experiences. </strong>Google is also expanding its agentic booking capabilities in Google Search to handle new tasks including things like local experiences and services.  So if you want to find a place that has a private karaoke room for a specific time and night, that also serves specific food, you can use Google Search to book that place for you.  </p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Agentic-booking-in-Search.mp4"></video></figure>



<p>Google will pull together the latest pricing and availability with direct links for your to purchase it. </p>



<p>This works across home, repair, beauty or pet care and will roll out this summer in the U.S.</p>



<p><strong>Personal intelligence expanding. </strong>Google also announced it is expanding <a href="https://searchengineland.com/personal-intelligence-with-gemini-connect-your-searches-email-photos-and-youtube-history-467521">Personal Intelligence</a> in AI Mode to about 200 countries and territories and 98 languages.</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Peronal-Intelligence-in-Search.mp4"></video></figure>


Google also announced new search agents, including information agents and new agentic capabilities within Google Search.  The information agent will continue to scan the web to find and monitor changes to your tasks and help you along your tasks journey.
“We’re entering the era of Search agents, where you can easily create, customize and manage multiple Al agents for your many tasks, right in Search,” Liz Reid, the head of Google Search said.
Information agents. The information agents will help you stay on top of your questions and tasks.  Google said the agent will “intelligently look across everything on the web, like blogs, news sites and social posts, plus our freshest data, such as real-time info on finance, shopping and sports, to monitor for changes related to your specific question.”
The information agent will then send you “an intelligent, synthesized update, with the ability to take action.” 
The example. Here is the example Google provided:
“So if you’re apartment hunting, you can brain dump all of the exact requirements you’re looking for, and your agent will continuously scan for you, notifying you when listings meet your needs. Or if you want to know the instant any of your favorite pro athletes announce a sneaker collab, your agent will let you know when a new drop lands so you don’t miss out.”




Availability. This will first roll out in the summer to Google Al Pro & Ultra subscribers.
Agentic experiences. Google is also expanding its agentic booking capabilities in Google Search to handle new tasks including things like local experiences and services.  So if you want to find a place that has a private karaoke room for a specific time and night, that also serves specific food, you can use Google Search to book that place for you.  




Google will pull together the latest pricing and availability with direct links for your to purchase it. 
This works across home, repair, beauty or pet care and will roll out this summer in the U.S.
Personal intelligence expanding. Google also announced it is expanding Personal Intelligence in AI Mode to about 200 countries and territories and 98 languages.

Google will continuously scan the web to give you updated information on your search - as an agent would do.

Google Search gains information agents and improved agentic experiences

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>This is powered by Google Antigravity and uses Gemini 3.5 right in Google Search.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-coding-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is now letting searchers build their own apps directly into Google Search.  This enables searchers to set up a search feature that delivers the information they need, in the format they want, from the sources they want. </p>



<p>Liz Reid, the head of Google Search, <a href="https://blog.google/products-and-platforms/products/search/search-io-2026">announced</a> at Google I/O, &#8220;Search can build the ideal response, in the right format for your question &#8211; completely on the fly. So you can get custom generative Ul, including visual tools and simulations, tailored precisely to your needs.&#8221;</p>



<p><strong>Examples. </strong>Here are a few examples of what you can code yourself into Google Search:</p>



<p>(1) Whether you want to wrap your mind around astrophysics or visualize how your watch works, Search can design custom layouts, assembling components (like interactive visuals, tables, graphs or simulations) in real-time, Google wrote.</p>



<p>(2) Ongoing tasks widgets, like planning a wedding or managing a home move. Search can go a step further, building you custom dashboards or trackers that you can continue to come back to and make progress on. You can think of these like mini apps for your own specific tasks, Liz Reid explained.</p>



<p>(3) Fitness tracker in Search, where you can ask Google Search to build you a custom fitness tracker. Search will code it for you, tapping into fresh, real-time sources including reviews, live maps and local data like the weather, so you get a tracker that works for you, helping you stay on track week after week.</p>



<p><strong>What it looks like. </strong>Here are some examples of what this looks like in Google Seaerch.</p>



<p>Generative UI example:</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Agentic-coding-in-Search-gen-UI.mp4"></video></figure>



<p>Custom tracker example:</p>



<figure class="wp-block-video"><video height="1080" width="1920" controls src="https://searchengineland.com/wp-content/seloads/2026/05/Agentic-coding-in-Search-custom-tracker.mp4"></video></figure>



<p><br><strong>Availability. </strong>The generative Ul capabilities will be available for everyone in Search this summer, free of charge.</p>



<p>The custom experiences with Antigravity, like mini apps, right in Search in the coming months, starting first for Google Al Pro and Ultra subscribers in the U.S.</p>



<p><strong>Why we care. </strong>Google Search will not just answer your questions but you can code your own mini apps within Google Search to give you the answers you want, in the format and style you want.</p>



<p>This is really a unique way for search and likely can only be done with generative-AI features and tooling.</p>


Google is now letting searchers build their own apps directly into Google Search.  This enables searchers to set up a search feature that delivers the information they need, in the format they want, from the sources they want. 
Liz Reid, the head of Google Search, announced at Google I/O, “Search can build the ideal response, in the right format for your question – completely on the fly. So you can get custom generative Ul, including visual tools and simulations, tailored precisely to your needs.”
Examples. Here are a few examples of what you can code yourself into Google Search:
(1) Whether you want to wrap your mind around astrophysics or visualize how your watch works, Search can design custom layouts, assembling components (like interactive visuals, tables, graphs or simulations) in real-time, Google wrote.
(2) Ongoing tasks widgets, like planning a wedding or managing a home move. Search can go a step further, building you custom dashboards or trackers that you can continue to come back to and make progress on. You can think of these like mini apps for your own specific tasks, Liz Reid explained.
(3) Fitness tracker in Search, where you can ask Google Search to build you a custom fitness tracker. Search will code it for you, tapping into fresh, real-time sources including reviews, live maps and local data like the weather, so you get a tracker that works for you, helping you stay on track week after week.
What it looks like. Here are some examples of what this looks like in Google Seaerch.
Generative UI example:




Custom tracker example:





Availability. The generative Ul capabilities will be available for everyone in Search this summer, free of charge.
The custom experiences with Antigravity, like mini apps, right in Search in the coming months, starting first for Google Al Pro and Ultra subscribers in the U.S.
Why we care. Google Search will not just answer your questions but you can code your own mini apps within Google Search to give you the answers you want, in the format and style you want.
This is really a unique way for search and likely can only be done with generative-AI features and tooling.

This is powered by Google Antigravity and uses Gemini 3.5 right in Google Search.

Google lets you build your own app within Google Search with agentic coding

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google's Shopping Graph is now over 60 billion products.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-robot-shopping-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google also <a href="https://blog.google/products-and-platforms/products/shopping/google-shopping-cart">announced</a> some new agentic commerce features today in Google Search including Universal Cart, expanding Universal Commerce Protocol and Agent Payments Protocol (AP2).</p>



<p>Plus, Google&#8217;s Shopping Graph now contains 60 billion product listings, which is up from 50 billion from earlier this year, announced Vidhya Srinivasan, VP/GM Ads &amp; Commerce.</p>



<p><strong>Universal Cart. </strong>Google announced what it is calling the Universal Cart, where you can put products and items from multiple retailers into one single Google Universal Cart and check out on all those items with your Google Wallet with the click of a button.</p>



<p>As you are on Google Search, you can add items directly to your Google Universal Cart without having to go to a specific retailer&#8217;s website. This will work across Google Search, Gemini, YouTube and Gmail, so just keep throwing items in your cart &#8211; across Google interface and retailer and the cart will maintain your list.</p>



<p>Here is a screenshot of Universal Cart showing multiple retailers:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="1152" src="https://searchengineland.com/wp-content/seloads/2026/05/Multi-item-cart-Ulta-and-Nike-scaled.jpg" alt="" class="wp-image-478007" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Multi-item-cart-Ulta-and-Nike-scaled.jpg 2048w, https://searchengineland.com/wp-content/seloads/2026/05/Multi-item-cart-Ulta-and-Nike-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/Multi-item-cart-Ulta-and-Nike-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Multi-item-cart-Ulta-and-Nike-1200x675.jpg 1200w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p>Google will find the best prices and deals, including which retailer has it in stock and let you check out with your preferred retailer.</p>



<p>Plus, Google said Universal Cart will &#8220;anticipate your needs and help solve problems before they.&#8221; Google&#8217;s example:</p>



<p>&#8220;Say you&#8217;re building your first custom PC and add a few parts from several retailers to your cart. Your cart will proactively flag any product incompatibilities and suggest alternatives. Since the cart was built on Google Wallet, it understands your payment method perks, loyalty information and merchant offers to help you choose. This lets you quickly find opportunities for hidden savings or points without having to remember them yourself.&#8221;</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="1152" src="https://searchengineland.com/wp-content/seloads/2026/05/Universal-Cart-intelligent-insights-scaled.jpg" alt="" class="wp-image-478009" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Universal-Cart-intelligent-insights-scaled.jpg 2048w, https://searchengineland.com/wp-content/seloads/2026/05/Universal-Cart-intelligent-insights-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2026/05/Universal-Cart-intelligent-insights-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Universal-Cart-intelligent-insights-1200x675.jpg 1200w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p><strong>Merchants. </strong>Google listed a number of merchants that support this, including Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, and Shopify merchants such as Fenty and Steve Madden<strong>.</strong>



<p><strong>Availability. </strong>This is available in Google Search and the Gemini app in the U.S. starting this summer and with YouTube and Gmail later on.</p>



<p><strong>UCP and AP2</strong>. Google expanded the Universal Commerce Protocol on Google to Canada and Australia in the coming months and in the U.K. later on. UCP will also be coming to YouTube and more Google verticals including hotel booking and local food delivery.</p>



<p>Agent Payments Protocol (AP2) helps agents make payments for you, securely and with accountability, Google said. &#8220;Just tell your agent the specific brands and products you want and how much it can spend, and the agent only makes the purchase when your criteria are met,&#8221; Google explained.</p>



<p>Google will launch AP2 to Google products in the coming months, starting with Gemini Spark.</p>


Google also announced some new agentic commerce features today in Google Search including Universal Cart, expanding Universal Commerce Protocol and Agent Payments Protocol (AP2).
Plus, Google’s Shopping Graph now contains 60 billion product listings, which is up from 50 billion from earlier this year, announced Vidhya Srinivasan, VP/GM Ads & Commerce.
Universal Cart. Google announced what it is calling the Universal Cart, where you can put products and items from multiple retailers into one single Google Universal Cart and check out on all those items with your Google Wallet with the click of a button.
As you are on Google Search, you can add items directly to your Google Universal Cart without having to go to a specific retailer’s website. This will work across Google Search, Gemini, YouTube and Gmail, so just keep throwing items in your cart – across Google interface and retailer and the cart will maintain your list.
Here is a screenshot of Universal Cart showing multiple retailers:




Google will find the best prices and deals, including which retailer has it in stock and let you check out with your preferred retailer.
Plus, Google said Universal Cart will “anticipate your needs and help solve problems before they.” Google’s example:
“Say you’re building your first custom PC and add a few parts from several retailers to your cart. Your cart will proactively flag any product incompatibilities and suggest alternatives. Since the cart was built on Google Wallet, it understands your payment method perks, loyalty information and merchant offers to help you choose. This lets you quickly find opportunities for hidden savings or points without having to remember them yourself.”




Merchants. Google listed a number of merchants that support this, including Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, and Shopify merchants such as Fenty and Steve Madden.



Availability. This is available in Google Search and the Gemini app in the U.S. starting this summer and with YouTube and Gmail later on.
UCP and AP2. Google expanded the Universal Commerce Protocol on Google to Canada and Australia in the coming months and in the U.K. later on. UCP will also be coming to YouTube and more Google verticals including hotel booking and local food delivery.
Agent Payments Protocol (AP2) helps agents make payments for you, securely and with accountability, Google said. “Just tell your agent the specific brands and products you want and how much it can spend, and the agent only makes the purchase when your criteria are met,” Google explained.
Google will launch AP2 to Google products in the coming months, starting with Gemini Spark.

Google's Shopping Graph is now over 60 billion products.

Google Search Universal Cart, expands UCP and AP2

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/The-funnel-query-pathway-A-framework-for-measuring-AI-visibility.png" class="attachment-large size-large wp-post-image" alt="The funnel query pathway- A framework for measuring AI visibility" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/The-funnel-query-pathway-A-framework-for-measuring-AI-visibility.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/The-funnel-query-pathway-A-framework-for-measuring-AI-visibility-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/The-funnel-query-pathway-A-framework-for-measuring-AI-visibility-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/The-funnel-query-pathway-A-framework-for-measuring-AI-visibility-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Traditional SEO metrics break in AI environments. Here’s a new model for tracking visibility across search, assistants, and agents.

Traditional SEO metrics break in AI environments. Here’s a new model for tracking visibility across search, assistants, and agents.

The funnel query pathway: A framework for measuring AI visibility

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image.png" class="attachment-large size-large wp-post-image" alt="kevin-indig-reasoning-lift-featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image.png 1672w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>An analysis of 200 GPT-5.2 responses found high reasoning cites more sources, runs deeper research, and rewards early-funnel visibility.


<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image.png" class="attachment-large size-large wp-post-image" alt="kevin-indig-reasoning-lift-featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image.png 1672w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/kevin-indig-reasoning-lift-featured-image-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p>AI offers a conversational experience. We use LLMs through chatbots. But no one has yet looked at how citations and mentions evolve in a conversation.</p>



<p>I analyzed data from the <a href="https://www.semrush.com/ai-seo/" target="_blank" rel="noopener">Semrush AI Visibility Toolkit</a> to review 20 buyer journeys across four different verticals to compare high vs. low reasoning for ChatGPT5.2.</p>



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



<p><strong>In this analysis:</strong>



<ul class="wp-block-list">
<li>Why high reasoning cites a nearly different web (only 25.6% domain overlap with minimal) and which source types gain or lose ground.</li>



<li>Why TOFU content has a payoff again: Grands cited at the Problem stage are more likely to persist all the way to Selection under high reasoning, and never under minimal.</li>



<li>How to split your prompt tracking by reasoning mode so your AI visibility reporting reflects 2 different systems, not an averaged one.</li>
</ul>



<h2 class="wp-block-heading" id="h-methodology">Methodology</h2>



<p>Data comes from the <a href="https://www.semrush.com/ai-seo/" target="_blank" rel="noopener">Semrush AI Visibility Toolkit</a>, which captures the prompts, citations, and fan-out queries ChatGPT generates per response.</p>



<ul class="wp-block-list">
<li>We ran 100 prompts twice through GPT-5.2, once with minimal reasoning and once with high reasoning, for 200 total responses.</li>



<li>Prompts span 20 buyer journeys across 4 categories (B2B SaaS, Finance, Consumer Tech, Health/Lifestyle), with 5 stages per journey: Problem, Exploration, Comparison, Validation, Selection.</li>



<li>Citation rate is the share of prompts where the response cited at least one external source.</li>



<li>Average citation counts sources per cited response.</li>



<li>Fan-out queries are the sub-queries the model fires internally to research the prompt before answering, surfaced via the Semrush API.</li>
</ul>



<h2 class="wp-block-heading" id="h-gpt-5-2-s-high-reasoning-cites-and-searches-more">GPT 5.2’s high reasoning cites and searches more</h2>



<p>Turn high reasoning on, and the citation rate jumps from 50% to 68% (+18 percentage points), the average sources per response nearly doubles (2.6 to 4.5), and fan-out queries go up 4.6x. High reasoning also pulls from 173 unique domains across the test set vs. 127 for minimal; 99 of those domains never appear under minimal reasoning.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="1184" src="https://searchengineland.com/wp-content/seloads/2026/05/image3.png" alt="" class="wp-image-478011" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image3.png 1999w, https://searchengineland.com/wp-content/seloads/2026/05/image3-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image3-1536x910.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<p>*Citation Rate is defined as the share of prompts where the response cited at least one external source.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="1185" src="https://searchengineland.com/wp-content/seloads/2026/05/image6.png" alt="" class="wp-image-478012" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image6.png 1999w, https://searchengineland.com/wp-content/seloads/2026/05/image6-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image6-1536x911.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<p>This is grounding at its finest. When the model thinks harder, it relies more on web search. Reasoning plays a major role in brand visibility, though we don’t know how many users activate reasoning vs not.</p>



<p>Query intent is a cleaner proxy than user demographics. Free-tier users have reasoning access too, just rate-limited, and ChatGPT auto-routes hard prompts to Thinking mode without the user clicking anything. So the question isn&#8217;t who can afford reasoning. It&#8217;s which prompts trigger reasoning automatically.&nbsp;</p>



<p>Multi-criteria comparisons, evaluation frameworks, regulatory and compliance questions, and complex shopping builds are the prompts most likely to fire reasoning regardless of plan. Map your audience by query type, not by paywall status.</p>



<h2 class="wp-block-heading" id="h-high-reasoning-fires-more-fan-out-queries-deeper-in-the-funnel">High reasoning fires more fan-out queries deeper in the funnel</h2>



<p>Users move through problem-solving and purchase decisions in stages, often within the same conversation. The gap between minimal and high reasoning isn&#8217;t constant. It scales with where the user sits in the journey.</p>



<p>What the five stages look like in practice. Take a buyer evaluating CRM software:</p>



<ul class="wp-block-list">
<li><strong>Problem:</strong> &#8220;How do I know if my sales team needs a CRM?&#8221;</li>



<li><strong>Exploration:</strong> &#8220;What types of CRM software exist for B2B SaaS?&#8221;</li>



<li><strong>Comparison:</strong> &#8220;HubSpot vs. Salesforce vs. Pipedrive for a 50-person sales team.&#8221;</li>



<li><strong>Validation:</strong> &#8220;Is HubSpot worth the price for mid-market B2B?&#8221;</li>



<li><strong>Selection:</strong> &#8220;How do I get started with HubSpot Sales Hub?&#8221;</li>
</ul>



<p>The three patterns hold across all 20 journeys:</p>



<ul class="wp-block-list">
<li>Citation rate climbs through the funnel under both modes, but high reasoning closes the early-stage gap most aggressively: +35pp at Problem, only +5pp at Validation. The model treats early-funnel questions as research tasks when high reasoning is on, whereas it answers-from-memory when it&#8217;s off.</li>



<li>Fan-out queries peak at Comparison. High reasoning fires 24 sub-queries per response there vs. 5.5 for minimal. Selection runs 15.4 vs. 2.6.</li>



<li>Average citations per response peaks at Comparison (9.8 high, 5.8 minimal) and narrows at Selection (4.7 high, 2.6 minimal). The model resembles an hourglass across funnel stages.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="1265" src="https://searchengineland.com/wp-content/seloads/2026/05/image1.png" alt="" class="wp-image-478014" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image1.png 1999w, https://searchengineland.com/wp-content/seloads/2026/05/image1-768x486.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image1-1536x972.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<p>At the aggregate level, minimal reasoning fires 245 search queries across 100 prompts. High reasoning fires 1,130. When the model operates with high reasoning, it runs a mini investigation per prompt, and most of the investigation happens at the Comparison and Selection stages.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="1265" src="https://searchengineland.com/wp-content/seloads/2026/05/image4.png" alt="" class="wp-image-478015" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image4.png 1999w, https://searchengineland.com/wp-content/seloads/2026/05/image4-768x486.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image4-1536x972.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<p>What does a fan-out actually look like? </p>



<p>A B2B SaaS prompt under high reasoning comparing Salesforce, HubSpot, and Pipedrive for a 50-person sales team breaks into separate queries about API rate limits per vendor, SOC 2 / ISO 27001 compliance, SAML/SSO/SCIM support, webhook architecture, OAuth flow, developer documentation, enterprise pricing tiers, and change-data-capture support. Each becomes its own retrieval. The brand that wins the answer is the one whose documentation surfaces clean for each sub-query, not the one that ranks for the parent prompt.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1440" height="1640" src="https://searchengineland.com/wp-content/seloads/2026/05/One-prompt-becomes-eight-retrievals.png" alt="One prompt becomes eight retrievals" class="wp-image-477891" srcset="https://searchengineland.com/wp-content/seloads/2026/05/One-prompt-becomes-eight-retrievals.png 1440w, https://searchengineland.com/wp-content/seloads/2026/05/One-prompt-becomes-eight-retrievals-768x875.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/One-prompt-becomes-eight-retrievals-1349x1536.png 1349w" sizes="(max-width: 1440px) 100vw, 1440px" /></figure>
</div>


<p>The Selection stage has the widest per-response query variance: 0 to 40 fan-out queries on the same five-stage cohort. The driver is prompt specificity. Bounded prompts (like &#8220;should I finance through the dealer at 0% APR or use a bank?&#8221; or &#8220;draft an RFP to 3 SEO agencies&#8221;) run zero queries because the answer&#8217;s structure is given. Open-ended product builds (&#8220;shopping list for a $3,000 home gym&#8221; or &#8220;which travel card ecosystem fits our grocery spending?&#8221;) run 28 to 40 queries. The Selection stage isn&#8217;t bounded by one type of question, and the model&#8217;s research effort tracks how many degrees of freedom the prompt leaves on the table.</p>



<figure class="wp-block-table"><table><tbody><tr><td><strong>Stage</strong></td><td><strong>Minimal: Avg queries</strong></td><td><strong>High: Avg queries</strong></td></tr><tr><td>Problem</td><td>0.0</td><td>5.2</td></tr><tr><td>Exploration</td><td>0.8</td><td>2.6</td></tr><tr><td>Comparison</td><td>5.5</td><td>24.1</td></tr><tr><td>Validation</td><td>3.4</td><td>9.1</td></tr><tr><td>Selection</td><td>2.6</td><td>15.4</td></tr></tbody></table></figure>



<p>For marketers: Early-funnel visibility is a reasoning-mode story. If your buyers use ChatGPT with reasoning on, problem-stage, and exploration-stage content is in play. If they don&#8217;t, you&#8217;re effectively invisible until Comparison.</p>



<h2 class="wp-block-heading" id="h-reasoning-affects-how-brands-appear-in-a-conversation">Reasoning affects how brands appear in a conversation</h2>



<p>An LLM session is a conversation, not a single query. The question that it opens up: Does a brand cited at the start of the journey carry through to the end? If yes, early-funnel visibility compounds. If not, every stage is a fresh fight.</p>



<p>When a brand gets cited in the Problem stage (step 1), does it survive to the Selection stage (step 5)? When using minimal reasoning: No. Zero journeys show this kind of persistence. In high reasoning: Yes. Brand continuity is maintained in 4 journeys across all 5 stages.</p>



<p>Within a single response, high reasoning also anchors harder on individual sources. 51 of 100 high-reasoning responses cite the same domain more than once in the same answer, vs. 26 of 100 for minimal. High reasoning quotes a source repeatedly when it commits to it.</p>



<p>Brand mentions tell a softer version of the same story. If you loosen the test from cited domain to brand named in the answer text, persistence shows up in 3 high-reasoning journeys (HubSpot across CRM Selection, American Express across Business Credit Cards, Sony and Canon across Mirrorless Camera) and 2 minimal-reasoning journeys (HubSpot, Mercury). Consumer Tech shows up here even though it doesn&#8217;t show up in the citation persistence table. Brands like Sony and Canon are mentioned through the conversation without the model linking out to them, which is its own form of category dominance and worth tracking separately.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="1184" src="https://searchengineland.com/wp-content/seloads/2026/05/image2.png" alt="" class="wp-image-478016" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image2.png 1999w, https://searchengineland.com/wp-content/seloads/2026/05/image2-768x455.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/image2-1536x910.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<p>High reasoning builds a consistent mental model of the solution space throughout a session. The headline finding: <strong>TOFU prompts have value</strong>. If a brand shows up at the Problem stage, it tends to carry through to Selection. Top-of-funnel content isn&#8217;t just brand awareness for AI visibility. It&#8217;s a leading indicator of where the model lands at decision time.</p>



<p>Two more implications:</p>



<ul class="wp-block-list">
<li>All four persistent journeys are in Finance, which suggests persistence rides on the same authoritative-source content (regulatory pages, official brand sites) that drives the +28pp Finance lift overall.</li>



<li>For marketers running an account-based or category-creation play, reasoning-mode visibility is the prize. It&#8217;s the only mode where early-funnel content compounds into selection-stage citations.</li>
</ul>



<h2 class="wp-block-heading" id="h-reasoning-mode-is-a-separate-search-engine">Reasoning mode is a separate search engine</h2>



<p>The brand that wins under minimal reasoning is not the brand that wins under high reasoning: 3 in 4 cited domains are different. The mix of source types is different. The stages where citations appear are different.</p>



<p>I’m excited about two findings in particular from this analysis:&nbsp;</p>



<p>The first is measurement. We need to track low vs. high reasoning in our prompt trackers. It’s best to avoid an aggregate view because the mechanisms are truly different.&nbsp;</p>



<p>Bad news: This adds more effort and cost to prompt tracking. Good news: We can make prompt tracking a lot more accurate.</p>



<p>The second is funnel stages. In the <a href="https://www.growth-memo.com/p/how-consumers-navigate-high-stakes" target="_blank" rel="noopener">latest AI Mode user behavior study</a>, I found that users react strongly to shortlists, demonstrating a similar behavior seen with Google’s classic search results where the top result matters most. That result made it seem to me that focusing on BOFU prompts that return shortlists is the game.&nbsp;</p>



<p>However, <strong>now</strong> we know there is value in TOFU prompts because of persistence: Brands that appear early in the buyer journey can persist all the way through. The best way to find that out for yourself is to map buyer journeys and track your persistence.</p>



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


AI offers a conversational experience. We use LLMs through chatbots. But no one has yet looked at how citations and mentions evolve in a conversation.
I analyzed data from the Semrush AI Visibility Toolkit to review 20 buyer journeys across four different verticals to compare high vs. low reasoning for ChatGPT5.2.
View embedded content



In this analysis:




Why high reasoning cites a nearly different web (only 25.6% domain overlap with minimal) and which source types gain or lose ground.
Why TOFU content has a payoff again: Grands cited at the Problem stage are more likely to persist all the way to Selection under high reasoning, and never under minimal.
How to split your prompt tracking by reasoning mode so your AI visibility reporting reflects 2 different systems, not an averaged one.
Methodology
Data comes from the Semrush AI Visibility Toolkit, which captures the prompts, citations, and fan-out queries ChatGPT generates per response.
We ran 100 prompts twice through GPT-5.2, once with minimal reasoning and once with high reasoning, for 200 total responses.
Prompts span 20 buyer journeys across 4 categories (B2B SaaS, Finance, Consumer Tech, Health/Lifestyle), with 5 stages per journey: Problem, Exploration, Comparison, Validation, Selection.
Citation rate is the share of prompts where the response cited at least one external source.
Average citation counts sources per cited response.
Fan-out queries are the sub-queries the model fires internally to research the prompt before answering, surfaced via the Semrush API.
GPT 5.2’s high reasoning cites and searches more
Turn high reasoning on, and the citation rate jumps from 50% to 68% (+18 percentage points), the average sources per response nearly doubles (2.6 to 4.5), and fan-out queries go up 4.6x. High reasoning also pulls from 173 unique domains across the test set vs. 127 for minimal; 99 of those domains never appear under minimal reasoning.




*Citation Rate is defined as the share of prompts where the response cited at least one external source.




This is grounding at its finest. When the model thinks harder, it relies more on web search. Reasoning plays a major role in brand visibility, though we don’t know how many users activate reasoning vs not.
Query intent is a cleaner proxy than user demographics. Free-tier users have reasoning access too, just rate-limited, and ChatGPT auto-routes hard prompts to Thinking mode without the user clicking anything. So the question isn’t who can afford reasoning. It’s which prompts trigger reasoning automatically. 
Multi-criteria comparisons, evaluation frameworks, regulatory and compliance questions, and complex shopping builds are the prompts most likely to fire reasoning regardless of plan. Map your audience by query type, not by paywall status.
High reasoning fires more fan-out queries deeper in the funnel
Users move through problem-solving and purchase decisions in stages, often within the same conversation. The gap between minimal and high reasoning isn’t constant. It scales with where the user sits in the journey.
What the five stages look like in practice. Take a buyer evaluating CRM software:
Problem: “How do I know if my sales team needs a CRM?”
Exploration: “What types of CRM software exist for B2B SaaS?”
Comparison: “HubSpot vs. Salesforce vs. Pipedrive for a 50-person sales team.”
Validation: “Is HubSpot worth the price for mid-market B2B?”
Selection: “How do I get started with HubSpot Sales Hub?”
The three patterns hold across all 20 journeys:
Citation rate climbs through the funnel under both modes, but high reasoning closes the early-stage gap most aggressively: +35pp at Problem, only +5pp at Validation. The model treats early-funnel questions as research tasks when high reasoning is on, whereas it answers-from-memory when it’s off.
Fan-out queries peak at Comparison. High reasoning fires 24 sub-queries per response there vs. 5.5 for minimal. Selection runs 15.4 vs. 2.6.
Average citations per response peaks at Comparison (9.8 high, 5.8 minimal) and narrows at Selection (4.7 high, 2.6 minimal). The model resembles an hourglass across funnel stages.




At the aggregate level, minimal reasoning fires 245 search queries across 100 prompts. High reasoning fires 1,130. When the model operates with high reasoning, it runs a mini investigation per prompt, and most of the investigation happens at the Comparison and Selection stages.




What does a fan-out actually look like? 
A B2B SaaS prompt under high reasoning comparing Salesforce, HubSpot, and Pipedrive for a 50-person sales team breaks into separate queries about API rate limits per vendor, SOC 2 / ISO 27001 compliance, SAML/SSO/SCIM support, webhook architecture, OAuth flow, developer documentation, enterprise pricing tiers, and change-data-capture support. Each becomes its own retrieval. The brand that wins the answer is the one whose documentation surfaces clean for each sub-query, not the one that ranks for the parent prompt.




The Selection stage has the widest per-response query variance: 0 to 40 fan-out queries on the same five-stage cohort. The driver is prompt specificity. Bounded prompts (like “should I finance through the dealer at 0% APR or use a bank?” or “draft an RFP to 3 SEO agencies”) run zero queries because the answer’s structure is given. Open-ended product builds (“shopping list for a $3,000 home gym” or “which travel card ecosystem fits our grocery spending?”) run 28 to 40 queries. The Selection stage isn’t bounded by one type of question, and the model’s research effort tracks how many degrees of freedom the prompt leaves on the table.

StageMinimal: Avg queriesHigh: Avg queries
Problem0.05.2
Exploration0.82.6
Comparison5.524.1
Validation3.49.1
Selection2.615.4





For marketers: Early-funnel visibility is a reasoning-mode story. If your buyers use ChatGPT with reasoning on, problem-stage, and exploration-stage content is in play. If they don’t, you’re effectively invisible until Comparison.
Reasoning affects how brands appear in a conversation
An LLM session is a conversation, not a single query. The question that it opens up: Does a brand cited at the start of the journey carry through to the end? If yes, early-funnel visibility compounds. If not, every stage is a fresh fight.
When a brand gets cited in the Problem stage (step 1), does it survive to the Selection stage (step 5)? When using minimal reasoning: No. Zero journeys show this kind of persistence. In high reasoning: Yes. Brand continuity is maintained in 4 journeys across all 5 stages.
Within a single response, high reasoning also anchors harder on individual sources. 51 of 100 high-reasoning responses cite the same domain more than once in the same answer, vs. 26 of 100 for minimal. High reasoning quotes a source repeatedly when it commits to it.
Brand mentions tell a softer version of the same story. If you loosen the test from cited domain to brand named in the answer text, persistence shows up in 3 high-reasoning journeys (HubSpot across CRM Selection, American Express across Business Credit Cards, Sony and Canon across Mirrorless Camera) and 2 minimal-reasoning journeys (HubSpot, Mercury). Consumer Tech shows up here even though it doesn’t show up in the citation persistence table. Brands like Sony and Canon are mentioned through the conversation without the model linking out to them, which is its own form of category dominance and worth tracking separately.




High reasoning builds a consistent mental model of the solution space throughout a session. The headline finding: TOFU prompts have value. If a brand shows up at the Problem stage, it tends to carry through to Selection. Top-of-funnel content isn’t just brand awareness for AI visibility. It’s a leading indicator of where the model lands at decision time.
Two more implications:
All four persistent journeys are in Finance, which suggests persistence rides on the same authoritative-source content (regulatory pages, official brand sites) that drives the +28pp Finance lift overall.
For marketers running an account-based or category-creation play, reasoning-mode visibility is the prize. It’s the only mode where early-funnel content compounds into selection-stage citations.
Reasoning mode is a separate search engine
The brand that wins under minimal reasoning is not the brand that wins under high reasoning: 3 in 4 cited domains are different. The mix of source types is different. The stages where citations appear are different.
I’m excited about two findings in particular from this analysis: 
The first is measurement. We need to track low vs. high reasoning in our prompt trackers. It’s best to avoid an aggregate view because the mechanisms are truly different. 
Bad news: This adds more effort and cost to prompt tracking. Good news: We can make prompt tracking a lot more accurate.
The second is funnel stages. In the latest AI Mode user behavior study, I found that users react strongly to shortlists, demonstrating a similar behavior seen with Google’s classic search results where the top result matters most. That result made it seem to me that focusing on BOFU prompts that return shortlists is the game. 
However, now we know there is value in TOFU prompts because of persistence: Brands that appear early in the buyer journey can persist all the way through. The best way to find that out for yourself is to map buyer journeys and track your persistence.
This post first appeared on the author’s website and is republished here with permission.

An analysis of 200 GPT-5.2 responses found high reasoning cites more sources, runs deeper research, and rewards early-funnel visibility.

Reasoning lift: What happens to brand visibility when AI thinks harder

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console.png" class="attachment-large size-large wp-post-image" alt="How to build custom SEO reports with Claude Code and Google Search Console" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Connect GSC data to Claude Code, generate custom visualizations, and create flexible reporting workflows for stakeholder meetings.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console.png" class="attachment-large size-large wp-post-image" alt="How to build custom SEO reports with Claude Code and Google Search Console" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/How-to-build-custom-SEO-reports-with-Claude-Code-and-Google-Search-Console-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>For a long time, <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> <a href="https://searchengineland.com/guide/seo-reporting">reporting</a> revolved around dashboards. When a meeting was on your schedule, you’d spend your day preparing by exporting data from <a href="https://searchengineland.com/google-search-console-seo-guide-443942">Google Search Console</a>, cleaning it in spreadsheets, and layering charts into Data Studio. </p>



<p>Now, AI coding agents are changing that workflow. Instead of the manual work that would previously take hours, you can use tools like Claude Code to surface customized data with polished visuals in just minutes.&nbsp;&nbsp;</p>



<p>Here’s how to turn Google Search Console data into custom reports and speed up your reporting workflow.</p>



<h2 class="wp-block-heading" id="h-what-claude-code-can-do-with-gsc-data">What Claude Code can do with GSC data</h2>



<p>Claude Code isn’t the same as using Claude in a browser tab. The standard Claude.ai interface works like a regular chatbot. Claude Code, on the other hand, is Anthropic’s terminal-based AI coding assistant.&nbsp;</p>



<p>It still feels conversational, but instead of living in a browser tab, it can interact directly with files, folders, spreadsheets, and scripts on your machine. It can read exported GSC CSV files, process large datasets locally, generate charts and summaries, analyze trends across pages and queries, and ultimately create structured deliverables from raw data.</p>



<p>Claude Code isn’t simply generating text responses like a chatbot. Instead, it’s creating a local reporting environment that behaves like a lightweight software project.&nbsp;</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/claude-code-seo-work-470668">How to turn Claude Code into your SEO command center</a></em></strong>



<a href="https://www.semrush.com/lp/semrush-one/en/?utm_campaign=ic_semrush_one&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>

    <div>

      <div id="semrush-one-headline" class="headline-responsive">
        Your customers search everywhere. Make sure your brand <span>shows up</span>.
      </div>
      <p id="semrush-one-subhead">
        The SEO toolkit you know, plus the AI visibility data you need.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta">Start Free Trial</span>
    </div>

    <div>
      <div>Get started with</div>
      <img decoding="async" src="https://searchengineland.com/wp-content/seloads/2025/11/semrush-one.webp" alt="Semrush One Logo">
    </div>
  </div>
</a>




<h2 class="wp-block-heading" id="h-there-s-a-learning-curve-nbsp">There’s a learning curve&nbsp;</h2>



<p>Before you can start building beautiful, custom reports, you’ll need to set up Claude Code. If you’re not an engineer or developer, this process can feel overwhelming at first. There is a learning curve, but don’t give up. </p>



<p>Setup is actually the most time-intensive piece of the process, but it’s a one-time process. Depending on your technical experience, the initial setup may take a couple of hours.</p>



<p>The “reports in minutes” concept really applies after the environment is configured. Once you’re past the initial setup and Claude is connected to GSC, you can run any custom SEO report you want in a matter of minutes.</p>



<p>If you’re in an enterprise environment, this setup process can go faster with a little help from the tech team. If you’re an agency or an SEO consultant, you can always lean on the expertise of in-house developers or engineers or an outside contractor.</p>



<h2 class="wp-block-heading" id="h-getting-started">Getting started</h2>



<p>If you don’t already have one, create an account at<a href="https://claude.ai/?utm_source=chatgpt.com"> </a>Claude.ai. You can sign up with Google, email/password, or enterprise SSO.</p>



<p>Most SEOs using Claude Code for reporting have a paid plan or use Anthropic API access. But you can use a free plan at the time of writing.</p>



<h3 class="wp-block-heading" id="h-install-node-js">Install Node.js</h3>



<p>Claude Code runs locally on your machine, so you’ll first need Node.js installed. You can also use it on a Chromebook by activating the Linux subsystem.&nbsp;</p>



<p>For the purposes of this tutorial, I used a Mac.</p>



<p>Next, download the current LTS (Long-Term Support) version. Once installed, you’ll have access to npm, which is used to install Claude Code.</p>



<p>To verify the installation, open Terminal (Mac/Linux) or PowerShell (Windows) and run:</p>



<p><code>node -v<br>npm -v</code>



<p>If both commands return version numbers, you’re ready to continue.</p>



<h3 class="wp-block-heading" id="h-install-claude-code">Install Claude Code</h3>



<p>Next, install Claude Code globally:</p>



<p><code>npm install -g @anthropic-ai/claude-code</code>



<p>Once the installation finishes, start Claude Code by running:</p>



<p><code>claude</code>



<p>The CLI will walk you through authentication and connect to your Anthropic account. After that, Claude Code can work directly with local project folders containing exported SEO data, scripts, spreadsheets, and reporting templates.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/seo-reporting-data-studio-what-comes-next-474813">SEO reporting outgrew Data Studio — here’s what comes next</a></em></strong>



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




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



<h2 class="wp-block-heading" id="h-establishing-the-reporting-framework">Establishing the reporting framework</h2>



<p>At this point, you’ll be able to interact with Claude Code in the terminal using commands much like you would with an AI chatbot.</p>



<p>To kick off the workflow, I gave Claude a prompt: </p>



<ul class="wp-block-list">
<li>“I have a marketing meeting coming up, and I want to show our performance from Google Search Console.”</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1395" height="1008" src="https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-report-using-Claude-Code.png" alt="Example SEO report using Claude Code" class="wp-image-477900" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-report-using-Claude-Code.png 1395w, https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-report-using-Claude-Code-768x555.png 768w" sizes="(max-width: 1395px) 100vw, 1395px" /></figure>
</div>


<p>One benefit is that Claude now becomes an onboarding assistant. Claude will ask a handful of clarifying questions to get started. For example, during the setup process, Claude asked:</p>



<ul class="wp-block-list">
<li>Whether to use a service account or OAuth credentials to access the Google Search Console API.</li>



<li>Which reporting views or marketing priorities mattered most.</li>



<li>Where the reporting project should live locally on the machine.</li>



<li>Which Google Search Console property to connect to.</li>
</ul>



<p>Claude also asked where the reporting project should live locally.&nbsp;</p>



<p>(As an aside, we prefer to store it inside a dedicated code directory rather than a standard Documents folder because development projects can sometimes run into file permission or syncing issues when stored inside cloud-synced folders like Documents or Desktop.)</p>



<p>Next, I established how the visuals will be built before connecting to GSC.&nbsp;</p>



<p>We like using Observable Framework, an open-source framework for building data apps, dashboards, and reports.&nbsp;</p>



<p>You don’t necessarily need to follow this exact structure; Claude Code is highly customizable, and you’ll settle into what works for you. </p>



<p>And remember: if you’re unsure about any next steps, you can just ask Claude, and it will help guide the setup. </p>



<h2 class="wp-block-heading" id="h-connecting-to-gsc">Connecting to GSC</h2>



<p>Before Claude Code can start generating reports from live GSC data, you’ll need to connect it to the Search Console API.</p>



<p>This is another technical part of the process, but the good news is that Claude can walk you through much of the setup interactively.</p>



<p>To establish the connection, you’ll need to create a <a href="https://console.cloud.google.com/projectcreate?pli=1" target="_blank" rel="noopener">Google Cloud Project </a>(GCP) and configure API credentials.</p>



<p>That setup process typically includes:</p>



<ul class="wp-block-list">
<li>Creating a Google Cloud project.</li>



<li>Enabling the Search Console API.</li>



<li>Generating OAuth credentials or API secrets.</li>



<li>Adding those credentials to a local environment file.</li>
</ul>



<p>In larger organizations, your IT or development team may already manage this infrastructure.&nbsp;</p>



<p>If not, you can still configure it yourself using a standard Google account or Google Workspace account.</p>



<h2 class="wp-block-heading" id="h-generating-reports">Generating reports</h2>



<p>Once you’ve finished connecting to GSC, congratulations! You made it through the hardest part. Once setup is complete, your reporting process changes entirely.</p>



<p>You can now focus on the reporting views you want to create, such as:&nbsp;</p>



<ul class="wp-block-list">
<li>“Show me the top 10 landing pages that gained traffic this month.”</li>



<li>“Create a chart of declining nonbrand queries over the last 90 days.”</li>



<li>“Compare CTR trends by device type.”</li>



<li>“Show me the top-performing pages from New York last month.”</li>
</ul>



<p>Claude is now like an on-demand reporting assistant. You simply open the project folder, launch Claude Code, and ask for the charts you need.</p>



<p>In addition, you can be more dynamic in your meetings.&nbsp;</p>



<p>Instead of building a rigid dashboard ahead of time and hoping stakeholders ask predictable questions, you can generate new views dynamically as questions come up.&nbsp;</p>



<p>That means you can walk into a meeting, ask Claude for a completely new chart or segmentation, and generate it in minutes rather than rebuilding an entire dashboard manually.</p>



<p>Now let’s look at some reports you might quickly run before your next meeting.</p>



<p>Here’s an example of a custom SEO performance dashboard generated from Google Search Console data.&nbsp;</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1395" height="1008" src="https://searchengineland.com/wp-content/seloads/2026/05/image-214.png" alt="" class="wp-image-477895" srcset="https://searchengineland.com/wp-content/seloads/2026/05/image-214.png 1395w, https://searchengineland.com/wp-content/seloads/2026/05/image-214-768x555.png 768w" sizes="(max-width: 1395px) 100vw, 1395px" /></figure>



<p>While some of these metrics are available inside GSC, building your own report gives you much more flexibility in how trends, comparisons, and supporting metrics are visualized together.&nbsp;</p>



<p>You could also generate a bar chart with YoY rankings, or a heat map of rankings for keywords by month. Both examples are below.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1113" height="1284" src="https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-ranking-report-using-Claude-Code.png" alt="Example SEO ranking report using Claude Code" class="wp-image-477901" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-ranking-report-using-Claude-Code.png 1113w, https://searchengineland.com/wp-content/seloads/2026/05/Example-SEO-ranking-report-using-Claude-Code-768x886.png 768w" sizes="(max-width: 1113px) 100vw, 1113px" /></figure>
</div>


<p>What we like to include in our reporting is a combination of scorecards, time-series charts, year-over-year bar chart comparisons, and heat maps that break down the key drivers behind a metric.&nbsp;</p>



<a href="https://www.semrush.com/lp/semrush-one/en/?utm_campaign=ic_semrush_one&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>

    <div>

      <div id="semrush-one-headline-bottom" class="headline-responsive">
        See the <span>complete picture</span> of your search visibility.
      </div>
      <p id="semrush-one-subhead-bottom">
        Track, optimize, and win in Google and AI search from one platform.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta-bottom">Start Free Trial</span>
    </div>

    <div>
      <div>Get started with</div>
      <img decoding="async" src="https://searchengineland.com/wp-content/seloads/2025/11/semrush-one.webp" alt="Semrush One Logo">
    </div>
  </div>
</a>




<h2 class="wp-block-heading" id="h-claude-code-completely-transforms-seo-reporting">Claude Code completely transforms SEO reporting</h2>



<p>SEO reporting has always been a push and pull between speed and flexibility.&nbsp;</p>



<p>Dashboards are fast once they are built, but they are often rigid. Custom analysis is powerful but historically has been time-intensive.&nbsp;</p>



<p>Claude Code changes everything.&nbsp;</p>



<p>Now you can interact with your GSC data more dynamically, explore new questions as they arise, and create reporting views that would have previously taken hours to build manually.&nbsp;</p>



<p>Once the initial setup is complete, reporting becomes far more adaptable to the needs of you and your stakeholders.&nbsp;</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/vibe-code-seo-tool-469657">How to vibe-code an SEO tool without losing control of your LLM</a></em></strong>

For a long time, SEO reporting revolved around dashboards. When a meeting was on your schedule, you’d spend your day preparing by exporting data from Google Search Console, cleaning it in spreadsheets, and layering charts into Data Studio. 
Now, AI coding agents are changing that workflow. Instead of the manual work that would previously take hours, you can use tools like Claude Code to surface customized data with polished visuals in just minutes.  
Here’s how to turn Google Search Console data into custom reports and speed up your reporting workflow.
What Claude Code can do with GSC data
Claude Code isn’t the same as using Claude in a browser tab. The standard Claude.ai interface works like a regular chatbot. Claude Code, on the other hand, is Anthropic’s terminal-based AI coding assistant. 
It still feels conversational, but instead of living in a browser tab, it can interact directly with files, folders, spreadsheets, and scripts on your machine. It can read exported GSC CSV files, process large datasets locally, generate charts and summaries, analyze trends across pages and queries, and ultimately create structured deliverables from raw data.
Claude Code isn’t simply generating text responses like a chatbot. Instead, it’s creating a local reporting environment that behaves like a lightweight software project. 
Dig deeper: How to turn Claude Code into your SEO command center




  
shows up.
      
Start Free Trial
    
Get started with
There’s a learning curve 
Before you can start building beautiful, custom reports, you’ll need to set up Claude Code. If you’re not an engineer or developer, this process can feel overwhelming at first. There is a learning curve, but don’t give up. 
Setup is actually the most time-intensive piece of the process, but it’s a one-time process. Depending on your technical experience, the initial setup may take a couple of hours.
The “reports in minutes” concept really applies after the environment is configured. Once you’re past the initial setup and Claude is connected to GSC, you can run any custom SEO report you want in a matter of minutes.
If you’re in an enterprise environment, this setup process can go faster with a little help from the tech team. If you’re an agency or an SEO consultant, you can always lean on the expertise of in-house developers or engineers or an outside contractor.
Getting started
If you don’t already have one, create an account at Claude.ai. You can sign up with Google, email/password, or enterprise SSO.
Most SEOs using Claude Code for reporting have a paid plan or use Anthropic API access. But you can use a free plan at the time of writing.
Install Node.js
Claude Code runs locally on your machine, so you’ll first need Node.js installed. You can also use it on a Chromebook by activating the Linux subsystem. 
For the purposes of this tutorial, I used a Mac.
Next, download the current LTS (Long-Term Support) version. Once installed, you’ll have access to npm, which is used to install Claude Code.
To verify the installation, open Terminal (Mac/Linux) or PowerShell (Windows) and run:
node -v
npm -v



If both commands return version numbers, you’re ready to continue.
Install Claude Code
Next, install Claude Code globally:
npm install -g @anthropic-ai/claude-code



Once the installation finishes, start Claude Code by running:
claude



The CLI will walk you through authentication and connect to your Anthropic account. After that, Claude Code can work directly with local project folders containing exported SEO data, scripts, spreadsheets, and reporting templates.
Dig deeper: SEO reporting outgrew Data Studio — here’s what comes next




	
	
Get the newsletter search marketers rely on.
 
				
				
			
See terms.
		
Establishing the reporting framework
At this point, you’ll be able to interact with Claude Code in the terminal using commands much like you would with an AI chatbot.
To kick off the workflow, I gave Claude a prompt: 
“I have a marketing meeting coming up, and I want to show our performance from Google Search Console.”




One benefit is that Claude now becomes an onboarding assistant. Claude will ask a handful of clarifying questions to get started. For example, during the setup process, Claude asked:
Whether to use a service account or OAuth credentials to access the Google Search Console API.
Which reporting views or marketing priorities mattered most.
Where the reporting project should live locally on the machine.
Which Google Search Console property to connect to.
Claude also asked where the reporting project should live locally. 
(As an aside, we prefer to store it inside a dedicated code directory rather than a standard Documents folder because development projects can sometimes run into file permission or syncing issues when stored inside cloud-synced folders like Documents or Desktop.)
Next, I established how the visuals will be built before connecting to GSC. 
We like using Observable Framework, an open-source framework for building data apps, dashboards, and reports. 
You don’t necessarily need to follow this exact structure; Claude Code is highly customizable, and you’ll settle into what works for you. 
And remember: if you’re unsure about any next steps, you can just ask Claude, and it will help guide the setup. 
Connecting to GSC
Before Claude Code can start generating reports from live GSC data, you’ll need to connect it to the Search Console API.
This is another technical part of the process, but the good news is that Claude can walk you through much of the setup interactively.
To establish the connection, you’ll need to create a Google Cloud Project (GCP) and configure API credentials.
That setup process typically includes:
Creating a Google Cloud project.
Enabling the Search Console API.
Generating OAuth credentials or API secrets.
Adding those credentials to a local environment file.
In larger organizations, your IT or development team may already manage this infrastructure. 
If not, you can still configure it yourself using a standard Google account or Google Workspace account.
Generating reports
Once you’ve finished connecting to GSC, congratulations! You made it through the hardest part. Once setup is complete, your reporting process changes entirely.
You can now focus on the reporting views you want to create, such as: 
“Show me the top 10 landing pages that gained traffic this month.”
“Create a chart of declining nonbrand queries over the last 90 days.”
“Compare CTR trends by device type.”
“Show me the top-performing pages from New York last month.”
Claude is now like an on-demand reporting assistant. You simply open the project folder, launch Claude Code, and ask for the charts you need.
In addition, you can be more dynamic in your meetings. 
Instead of building a rigid dashboard ahead of time and hoping stakeholders ask predictable questions, you can generate new views dynamically as questions come up. 
That means you can walk into a meeting, ask Claude for a completely new chart or segmentation, and generate it in minutes rather than rebuilding an entire dashboard manually.
Now let’s look at some reports you might quickly run before your next meeting.
Here’s an example of a custom SEO performance dashboard generated from Google Search Console data. 




While some of these metrics are available inside GSC, building your own report gives you much more flexibility in how trends, comparisons, and supporting metrics are visualized together. 
You could also generate a bar chart with YoY rankings, or a heat map of rankings for keywords by month. Both examples are below.




What we like to include in our reporting is a combination of scorecards, time-series charts, year-over-year bar chart comparisons, and heat maps that break down the key drivers behind a metric. 
complete picture of your search visibility.
      
Start Free Trial
    
Get started with
Claude Code completely transforms SEO reporting
SEO reporting has always been a push and pull between speed and flexibility. 
Dashboards are fast once they are built, but they are often rigid. Custom analysis is powerful but historically has been time-intensive. 
Claude Code changes everything. 
Now you can interact with your GSC data more dynamically, explore new questions as they arise, and create reporting views that would have previously taken hours to build manually. 
Once the initial setup is complete, reporting becomes far more adaptable to the needs of you and your stakeholders. 
Dig deeper: How to vibe-code an SEO tool without losing control of your LLM

Connect GSC data to Claude Code, generate custom visualizations, and create flexible reporting workflows for stakeholder meetings.

How to build custom SEO reports with Claude Code and Google Search Console

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/How-AI-may-increase-the-value-of-SEO-expertise.png" class="attachment-large size-large wp-post-image" alt="How AI may increase the value of SEO expertise" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/How-AI-may-increase-the-value-of-SEO-expertise.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/How-AI-may-increase-the-value-of-SEO-expertise-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/How-AI-may-increase-the-value-of-SEO-expertise-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/How-AI-may-increase-the-value-of-SEO-expertise-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>As AI automates repetitive SEO tasks, the biggest advantage may go to practitioners who know how to guide it.

As AI automates repetitive SEO tasks, the biggest advantage may go to practitioners who know how to guide it.

How AI may increase the value of SEO expertise

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>A review of 25,000 URLs yielded insights about the type of content most cited by ChatGPT and other popular large language models.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png" alt="" class="wp-image-477696" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-header-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>
</div>


<p>Large language models (LLMs) excel at synthesizing enormous amounts of information into personalized responses to plain-language prompts. These responses draw on <a href="https://www.evertune.ai/resources/insights-on-ai/foundational-knowledge-vs-consumer-app-why-tracking-both-matters-for-ai-brand-visibility?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">massive training datasets</a> and are often <a href="https://www.evertune.ai/resources/insights-on-ai/what-are-sources-in-ai-search-understanding-rag-and-ai-model-citations?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">enhanced with internet searches</a>. The fastest way to influence what LLMs say about your brand is to influence the content they retrieve through those searches.</p>



<p>At Evertune Research, we use the <a href="https://www.evertune.ai/?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">Evertune</a> AI marketing platform to track hundreds of brands across 250 categories across every major LLM. This gives us clear insight into which content AI models cite most often, especially when users ask for brand or product recommendations across industries.</p>



<p>For this analysis, we reviewed the 6,000 most-cited URLs per model across ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overview, and Perplexity for March and April. We found that these models share a key behavior: they heavily cite listicles.</p>



<h2 class="wp-block-heading" id="h-half-of-llms-most-cited-urls-are-listicles">Half of LLMs’ most-cited URLs are listicles</h2>



<p>Of the roughly 25,000 unique URLs we reviewed, half were listicles. Across nearly 400 million citations from all models, 63% pointed to listicles.</p>



<p>Listicles have many qualities that make them <a href="https://www.evertune.ai/resources/insights-on-ai/9-ways-to-structure-your-content-to-be-cited-by-chatgpt?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">ideal for models’ consumption</a>.&nbsp;</p>



<ul class="wp-block-list">
<li>They’re tightly focused on a single topic, like “best laptops for gamers,” which makes them highly relevant to user prompts.&nbsp;</li>



<li>Their structured format also makes the content easy for models to parse and reproduce.&nbsp;</li>



<li>For brand-related queries, listicles do much of the work for LLMs by comparing products head-to-head on features, price, materials, and more—a format ChatGPT now <a href="https://www.evertune.ai/resources/insights-on-ai/the-new-face-of-chatgpt-shopping-ai-product-comparisons?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article">features prominently</a> in its shopping widget.</li>
</ul>



<p>Listicles were pervasive across every model we reviewed. They accounted for 40–65% of the most-cited URLs, with Copilot at the low end and Gemini at the high end.</p>



<p>The vast majority of listicles in our analysis featured ranked lists, such as “Top 5 CRM Tools.” Depending on the model, these made up 71% to 86% of listicles. Unranked lists, such as “7 Ways to Save on Groceries,” were a distant second. Institutional rankings (e.g., data-heavy lists like U.S. News &amp; World Report’s Best Colleges rankings) accounted for just 1.4% to 4.7% of listicles.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="900" height="520" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-1.png" alt="" class="wp-image-477691" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-1.png 900w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-1-768x444.png 768w" sizes="(max-width: 900px) 100vw, 900px" /></figure>
</div>


<p>Corporate, earned media, and affiliate domains were the top sources of listicles in our analysis. It’s worth noting, however, that individual pages may contain affiliate content even when the broader domain does not.&nbsp;</p>



<ul class="wp-block-list">
<li>For example, Forbes.com is an earned media domain, but it includes affiliate segments such as Forbes Advisor and Forbes Vetted. It ranked among the top three sources on every model for listicles in our URL dataset.</li>
</ul>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-2.png" alt="" class="wp-image-477692" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-2.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-2-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-2-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-2-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>
</div>


<p>A word of warning before making listicles the foundation of a <a href="https://www.evertune.ai/resources/a-beginners-guide-to-geo?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">GEO</a> strategy: Google has already signaled its intent to <a href="https://searchengineland.com/google-cracking-down-self-promotional-best-of-listicles-468227" target="_blank" rel="noopener sponsored nofollow">crack down on promotional listicles</a>. Simply ranking your own brand No. 1 alongside competitors could also run afoul of a <a href="https://www.ftc.gov/legal-library/browse/federal-register-notices/16-cfr-part-465-trade-regulation-rule-use-consumer-reviews-testimonials-final-rule" target="_blank" rel="noopener sponsored nofollow">Federal Trade Commission rule</a> that “prohibits a business from misrepresenting that a website or entity it controls provides independent reviews or opinions about a category of products or services that includes its own products or services,” among <a href="https://www.ftc.gov/news-events/news/press-releases/2024/08/federal-trade-commission-announces-final-rule-banning-fake-reviews-testimonials" target="_blank" rel="noopener sponsored nofollow">other prohibitions</a>.</p>



<h2 class="wp-block-heading" id="h-urls-that-thrive-on-multiple-models">URLs that thrive on multiple models</h2>



<p>We reviewed the 6,000 most-cited URLs across six LLMs, which in theory produced a pool of 36,000 URLs. In practice, the dataset contained about 25,000 unique URLs, since many appeared among the most-cited results across multiple models.</p>



<p>Among the models, the three Google <a href="https://www.evertune.ai/resources/insights-on-ai/google-ai-mode-vs-google-ai-overviews-whats-the-difference?utm_source=ppc&amp;utm_medium=cpc&amp;utm_campaign=branded_google_search&amp;utm_term=%7Bevertune%20ai%7D&amp;utm_content=brand_core?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">Gemini-powered models</a> — Gemini, AI Mode, and AI Overviews — showed the highest overlap. More than half of Google AI Mode’s most-cited URLs also appeared among Google AI Overviews&#8217; most-cited URLs. Gemini likewise shared a large portion of its top-cited URLs with both Google AI Mode and Google AI Overview.</p>



<p>The remaining models also shared the most URLs with Google AI Mode and Google AI Overviews, though the overlap was much smaller. Perplexity shared more than 20% of its URLs with both models, while ChatGPT shared more than 15% with each.&nbsp;</p>



<p>Given the <a href="https://www.linkedin.com/posts/williamarobinson3_geo-seo-activity-7436847664610033665-gmU7?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAyPkEcBJeGxTx4o4gbLjhDXUKvIqJ8KZOM" target="_blank" rel="noopener sponsored nofollow">thousands of URLs</a> models cite on any topic, that still represents meaningful overlap. Copilot, by contrast, shared just 4% to 6% of its URLs with any other model.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1000" height="530" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-3.png" alt="" class="wp-image-477693" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-3.png 1000w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-3-768x407.png 768w" sizes="(max-width: 1000px) 100vw, 1000px" /></figure>
</div>


<p>The URLs that models cite most deviate for many reasons, including model training, sites’ <a href="https://www.evertune.ai/products/ai-site-audit?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">crawl permissions</a> and other factors. Traditional SEO that moves content higher in search results, no matter if the search is by a bot or a person, also plays a role, especially for Google AI Mode and Google AI Overview.</p>



<h2 class="wp-block-heading" id="h-page-components-of-heavily-cited-urls">Page components of heavily cited URLs</h2>



<p>Our review of the roughly 25,000 URLs heavily cited by LLMs found that these pages typically ranged from 1,000 to 2,000 words, averaged 18 words per sentence, linked frequently, and used structured headings (H2s and H3s) throughout.</p>



<p>Copilot favored the most concise content, typically citing pages with 964 words and 24 paragraphs. Gemini skewed more verbose, typically citing pages with 1,977 words and 53 paragraphs.</p>



<p>Although there&#8217;s no cookie-cutter formula for <a href="https://www.evertune.ai/resources/insights-on-ai/how-a-luxury-handbag-brand-increased-its-ai-brand-score-by-221-in-six-weeks?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">success in AI visibility</a>, we found that the most-cited pages typically included the following components:</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="900" height="360" src="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-4.png" alt="" class="wp-image-477694" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-4.png 900w, https://searchengineland.com/wp-content/seloads/2026/05/Evertune-20260519-4-768x307.png 768w" sizes="(max-width: 900px) 100vw, 900px" /></figure>
</div>


<h2 class="wp-block-heading" id="h-geo-takeaways">GEO takeaways</h2>



<p>Each LLM has its own preferences and quirks, and a strong GEO strategy accounts for them. But our analysis of more than 25,000 URLs suggests that some GEO best practices can improve brand visibility and sentiment across models.</p>



<ul class="wp-block-list">
<li>All LLMs cite large volumes of highly structured, hyper-specific content, which listicles exemplify. Avoid spammy, self-promotional listicles that <a href="https://www.evertune.ai/resources/insights-on-ai/googles-march-2026-core-update-a-content-best-practices-guide-for-seo-and-ai-search?utm_source=searchengineland&amp;utm_medium=sponsor&amp;utm_campaign=may2026article" target="_blank" rel="noopener sponsored nofollow">Google penalizes</a>, but otherwise aim to create and appear in lists where relevant.</li>



<li>Traditional SEO supports GEO. Pages that perform well in human search results also tend to perform well in bot-driven searches. This is especially true for Gemini-based models.</li>



<li>Pay attention to the page structures most often cited by the model you want to target. Copilot tends to favor brevity, while Gemini responds better to more expansive content. In general, keep pages under 2,000 words, use frequent links, apply strong structure, and include images and lists when relevant.</li>
</ul>


Large language models (LLMs) excel at synthesizing enormous amounts of information into personalized responses to plain-language prompts. These responses draw on massive training datasets and are often enhanced with internet searches. The fastest way to influence what LLMs say about your brand is to influence the content they retrieve through those searches.
At Evertune Research, we use the Evertune AI marketing platform to track hundreds of brands across 250 categories across every major LLM. This gives us clear insight into which content AI models cite most often, especially when users ask for brand or product recommendations across industries.
For this analysis, we reviewed the 6,000 most-cited URLs per model across ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overview, and Perplexity for March and April. We found that these models share a key behavior: they heavily cite listicles.
Half of LLMs’ most-cited URLs are listicles
Of the roughly 25,000 unique URLs we reviewed, half were listicles. Across nearly 400 million citations from all models, 63% pointed to listicles.
Listicles have many qualities that make them ideal for models’ consumption. 
They’re tightly focused on a single topic, like “best laptops for gamers,” which makes them highly relevant to user prompts. 
Their structured format also makes the content easy for models to parse and reproduce. 
For brand-related queries, listicles do much of the work for LLMs by comparing products head-to-head on features, price, materials, and more—a format ChatGPT now features prominently in its shopping widget.
Listicles were pervasive across every model we reviewed. They accounted for 40–65% of the most-cited URLs, with Copilot at the low end and Gemini at the high end.
The vast majority of listicles in our analysis featured ranked lists, such as “Top 5 CRM Tools.” Depending on the model, these made up 71% to 86% of listicles. Unranked lists, such as “7 Ways to Save on Groceries,” were a distant second. Institutional rankings (e.g., data-heavy lists like U.S. News & World Report’s Best Colleges rankings) accounted for just 1.4% to 4.7% of listicles.




Corporate, earned media, and affiliate domains were the top sources of listicles in our analysis. It’s worth noting, however, that individual pages may contain affiliate content even when the broader domain does not. 
For example, Forbes.com is an earned media domain, but it includes affiliate segments such as Forbes Advisor and Forbes Vetted. It ranked among the top three sources on every model for listicles in our URL dataset.




A word of warning before making listicles the foundation of a GEO strategy: Google has already signaled its intent to crack down on promotional listicles. Simply ranking your own brand No. 1 alongside competitors could also run afoul of a Federal Trade Commission rule that “prohibits a business from misrepresenting that a website or entity it controls provides independent reviews or opinions about a category of products or services that includes its own products or services,” among other prohibitions.
URLs that thrive on multiple models
We reviewed the 6,000 most-cited URLs across six LLMs, which in theory produced a pool of 36,000 URLs. In practice, the dataset contained about 25,000 unique URLs, since many appeared among the most-cited results across multiple models.
Among the models, the three Google Gemini-powered models — Gemini, AI Mode, and AI Overviews — showed the highest overlap. More than half of Google AI Mode’s most-cited URLs also appeared among Google AI Overviews’ most-cited URLs. Gemini likewise shared a large portion of its top-cited URLs with both Google AI Mode and Google AI Overview.
The remaining models also shared the most URLs with Google AI Mode and Google AI Overviews, though the overlap was much smaller. Perplexity shared more than 20% of its URLs with both models, while ChatGPT shared more than 15% with each. 
Given the thousands of URLs models cite on any topic, that still represents meaningful overlap. Copilot, by contrast, shared just 4% to 6% of its URLs with any other model.




The URLs that models cite most deviate for many reasons, including model training, sites’ crawl permissions and other factors. Traditional SEO that moves content higher in search results, no matter if the search is by a bot or a person, also plays a role, especially for Google AI Mode and Google AI Overview.
Page components of heavily cited URLs
Our review of the roughly 25,000 URLs heavily cited by LLMs found that these pages typically ranged from 1,000 to 2,000 words, averaged 18 words per sentence, linked frequently, and used structured headings (H2s and H3s) throughout.
Copilot favored the most concise content, typically citing pages with 964 words and 24 paragraphs. Gemini skewed more verbose, typically citing pages with 1,977 words and 53 paragraphs.
Although there’s no cookie-cutter formula for success in AI visibility, we found that the most-cited pages typically included the following components:




GEO takeaways
Each LLM has its own preferences and quirks, and a strong GEO strategy accounts for them. But our analysis of more than 25,000 URLs suggests that some GEO best practices can improve brand visibility and sentiment across models.
All LLMs cite large volumes of highly structured, hyper-specific content, which listicles exemplify. Avoid spammy, self-promotional listicles that Google penalizes, but otherwise aim to create and appear in lists where relevant.
Traditional SEO supports GEO. Pages that perform well in human search results also tend to perform well in bot-driven searches. This is especially true for Gemini-based models.
Pay attention to the page structures most often cited by the model you want to target. Copilot tends to favor brevity, while Gemini responds better to more expansive content. In general, keep pages under 2,000 words, use frequent links, apply strong structure, and include images and lists when relevant.

A review of 25,000 URLs yielded insights about the type of content most cited by ChatGPT and other popular large language models.

All About
Digital Marketing

Read the Latest Trends and Headlines in Digital Marketing.

Here are some of the latest headlines on digital marketing insights, search, and ecommerce:

Free Consultation

Reach out with any questions you might have regarding how RSO can help you with digital marketing.

All About Digital Marketing

Read the Latest Trends and Headlines in Digital Marketing.

Here are some of the latest headlines on digital marketing insights, search, and ecommerce:

Free Consultation

Reach out with any questions you might have regarding how RSO can help you with digital marketing.

All About
Digital Marketing