<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Microsoft" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Microsoft now requires third-party publishers to use Clarity, ensuring transparent, brand-safe ad placements and filtering noncompliant traffic.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Microsoft" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/11/shutterstock_2199173649.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Microsoft is tightening its advertising standards. The company announced that all third-party publishers must now implement <em>Microsoft Clarity</em> — its free behavioral analytics tool — to remain eligible for paid impressions and clicks in Microsoft Advertising.</p>



<p><strong>The details:</strong></p>



<ul class="wp-block-list">
<li><strong>What’s required:</strong> Publishers must install Microsoft Clarity and enable <em>Consent Mode</em> to track and analyze user interactions while complying with privacy standards.</li>



<li><strong>What it does:</strong> Clarity helps publishers and advertisers visualize user behavior — including clicks, scrolls, and engagement patterns — to make data-driven CRO (conversion rate optimization) decisions.</li>



<li><strong>What changes:</strong> Only ad traffic from Clarity-enabled pages will count toward billing, ensuring every paid impression meets Microsoft’s editorial and safety standards.</li>
</ul>



<p><strong>Why we care.</strong> This move is aimed at improving transparency, user experience, and brand safety across the Microsoft Ads network. Any ad clicks or impressions from pages that don’t use Clarity will now be filtered out and marked as <em>nonbillable</em>, effectively cutting off monetization for noncompliant publishers.</p>



<p><strong>Between the lines.</strong> By tying Clarity to monetization, Microsoft is effectively using its ad network scale to enforce higher quality and transparency standards. It’s a move that could raise the bar for accountability in the ad ecosystem — and give advertisers more confidence that their placements appear on trusted, well-monitored inventory.</p>



<p>This update was announced by Microsoft Product Liaison Navah Hopkins on <a href="https://www.linkedin.com/posts/navahhopkins_breaking-news-microsoft-clarity-is-now-required-activity-7393723874984767488-d-Xf/">LinkedIn</a>. </p>



<p><strong>The bottom line</strong>. For publishers, implementing Clarity is no longer optional. For advertisers, it means greater brand safety and visibility into where their budgets go — a win for ad transparency in Microsoft’s growing network.</p>



<p></p>


Microsoft is tightening its advertising standards. The company announced that all third-party publishers must now implement Microsoft Clarity — its free behavioral analytics tool — to remain eligible for paid impressions and clicks in Microsoft Advertising.
The details:
What’s required: Publishers must install Microsoft Clarity and enable Consent Mode to track and analyze user interactions while complying with privacy standards.
What it does: Clarity helps publishers and advertisers visualize user behavior — including clicks, scrolls, and engagement patterns — to make data-driven CRO (conversion rate optimization) decisions.
What changes: Only ad traffic from Clarity-enabled pages will count toward billing, ensuring every paid impression meets Microsoft’s editorial and safety standards.
Why we care. This move is aimed at improving transparency, user experience, and brand safety across the Microsoft Ads network. Any ad clicks or impressions from pages that don’t use Clarity will now be filtered out and marked as nonbillable, effectively cutting off monetization for noncompliant publishers.
Between the lines. By tying Clarity to monetization, Microsoft is effectively using its ad network scale to enforce higher quality and transparency standards. It’s a move that could raise the bar for accountability in the ad ecosystem — and give advertisers more confidence that their placements appear on trusted, well-monitored inventory.
This update was announced by Microsoft Product Liaison Navah Hopkins on LinkedIn. 
The bottom line. For publishers, implementing Clarity is no longer optional. For advertisers, it means greater brand safety and visibility into where their budgets go — a win for ad transparency in Microsoft’s growing network.

Microsoft now requires third-party publishers to use Clarity, ensuring transparent, brand-safe ad placements and filtering noncompliant traffic.

Microsoft makes Clarity mandatory for publishers

<div><img width="800" height="502" src="https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-800x502.jpeg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-800x502.jpeg 800w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-539x338.jpeg 539w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-180x113.jpeg 180w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-768x482.jpeg 768w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-1536x963.jpeg 1536w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-scaled.jpeg 2048w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-150x94.jpeg 150w" sizes="(max-width: 800px) 100vw, 800px" /></div>The latest Editor update introduces campaign-level negatives, search term reporting for Performance Max, and smarter automation tools for large-scale ad management.

<div><img width="800" height="502" src="https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-800x502.jpeg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-800x502.jpeg 800w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-539x338.jpeg 539w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-180x113.jpeg 180w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-768x482.jpeg 768w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-1536x963.jpeg 1536w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-scaled.jpeg 2048w, https://searchengineland.com/wp-content/seloads/2022/08/AdobeStock_291513748_Editorial_Use_Only-150x94.jpeg 150w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google Ads Editor just got a major upgrade. The 2025 release of version 2.11 introduces smarter automation, better visibility, and tighter controls for advertisers managing large-scale accounts. The update focuses on control and transparency — giving advertisers more say in how Performance Max, Search, and account-wide settings behave.  </p>



<p><strong>Campaign-level negative keywords for Performance Max</strong>. Advertisers can now add negative keyword lists directly to Performance Max campaigns, giving finer control over where ads appear. It’s a long-awaited feature that prevents wasted spend on irrelevant searches — a crucial step toward performance parity with Search and Shopping campaigns.</p>



<p><strong>Search term reporting for Performance Max</strong>. A new search term report shows which queries trigger PMax ads, giving advertisers transparency into performance drivers and irrelevant queries.</p>



<p><strong>Scheduled link checks</strong>. Automated link scanning will now flag broken URLs on a set schedule, saving manual work and protecting conversion flows.</p>



<p><strong>Account-level placement and IP exclusions</strong>. Advertisers can now apply exclusions globally across an account instead of manually updating each campaign, ensuring faster setup and consistent brand safety.</p>



<p><strong>Smart Bidding Exploration (Search)</strong>. A new opt-in tool lets Google’s AI test high-performing queries using flexible ROAS targets, driving incremental conversions from new search categories without manual adjustments.</p>



<p><strong>Editable lead forms</strong>. Users can now edit existing lead form assets directly instead of rebuilding them from scratch, reducing setup friction.</p>



<p><strong>Video generation from assets</strong>. Google can now automatically generate on-brand video creatives using your existing assets and brand styles. This feature, enabled by default, lowers the barrier to YouTube advertising.</p>



<p><strong>Streamlined Search campaign creation</strong>. A new guided “construction flow” brings AI-assisted campaign setup to Search, helping advertisers build optimized campaigns through a step-by-step process.</p>



<p><strong>More granular tracking control</strong>. Asset groups now support their own tracking URL templates, suffixes, and custom parameters for improved measurement precision.</p>



<p><strong>CSV and download enhancements</strong>. The improved interface allows selective campaign syncing and more efficient management of large accounts.</p>



<p><strong>Other notables.</strong> Additional updates include expanded ad preview support for Demand Gen and responsive video ads, new Agency/Provider user lists for third-party audience targeting, high LTV targeting expansion for Search campaigns, updated “TrueView” metric names, and nudges to link Merchant Center feeds for Demand Gen setup.</p>



<p><strong>Why we care.</strong> This update gives advertisers more control over where their ads appear, greater transparency into Performance Max performance, and new automation tools that save time and improve campaign efficiency—all leading to smarter spending and stronger ROI.</p>



<p><strong>What&#8217;s gone.</strong> On the deprecation side, legacy App install and certain Display ad types are being phased out, though existing ads remain editable for status and labels. Manual CPV bidding is also retired in favor of Video View Campaigns with Target CPV, supported by a built-in upgrade tool.</p>



<p><strong>The bottom line:</strong> <a href="https://support.google.com/google-ads/editor/answer/16663512?hl=en">Google Ads Editor 2.11</a> strengthens advertisers’ control and efficiency with new automation, transparency, and management tools—particularly the long-requested ability to add campaign-level negative keywords in Performance Max campaigns.</p>


Google Ads Editor just got a major upgrade. The 2025 release of version 2.11 introduces smarter automation, better visibility, and tighter controls for advertisers managing large-scale accounts. The update focuses on control and transparency — giving advertisers more say in how Performance Max, Search, and account-wide settings behave.  
Campaign-level negative keywords for Performance Max. Advertisers can now add negative keyword lists directly to Performance Max campaigns, giving finer control over where ads appear. It’s a long-awaited feature that prevents wasted spend on irrelevant searches — a crucial step toward performance parity with Search and Shopping campaigns.
Search term reporting for Performance Max. A new search term report shows which queries trigger PMax ads, giving advertisers transparency into performance drivers and irrelevant queries.
Scheduled link checks. Automated link scanning will now flag broken URLs on a set schedule, saving manual work and protecting conversion flows.
Account-level placement and IP exclusions. Advertisers can now apply exclusions globally across an account instead of manually updating each campaign, ensuring faster setup and consistent brand safety.
Smart Bidding Exploration (Search). A new opt-in tool lets Google’s AI test high-performing queries using flexible ROAS targets, driving incremental conversions from new search categories without manual adjustments.
Editable lead forms. Users can now edit existing lead form assets directly instead of rebuilding them from scratch, reducing setup friction.
Video generation from assets. Google can now automatically generate on-brand video creatives using your existing assets and brand styles. This feature, enabled by default, lowers the barrier to YouTube advertising.
Streamlined Search campaign creation. A new guided “construction flow” brings AI-assisted campaign setup to Search, helping advertisers build optimized campaigns through a step-by-step process.
More granular tracking control. Asset groups now support their own tracking URL templates, suffixes, and custom parameters for improved measurement precision.
CSV and download enhancements. The improved interface allows selective campaign syncing and more efficient management of large accounts.
Other notables. Additional updates include expanded ad preview support for Demand Gen and responsive video ads, new Agency/Provider user lists for third-party audience targeting, high LTV targeting expansion for Search campaigns, updated “TrueView” metric names, and nudges to link Merchant Center feeds for Demand Gen setup.
Why we care. This update gives advertisers more control over where their ads appear, greater transparency into Performance Max performance, and new automation tools that save time and improve campaign efficiency—all leading to smarter spending and stronger ROI.
What’s gone. On the deprecation side, legacy App install and certain Display ad types are being phased out, though existing ads remain editable for status and labels. Manual CPV bidding is also retired in favor of Video View Campaigns with Target CPV, supported by a built-in upgrade tool.
The bottom line: Google Ads Editor 2.11 strengthens advertisers’ control and efficiency with new automation, transparency, and management tools—particularly the long-requested ability to add campaign-level negative keywords in Performance Max campaigns.

The latest Editor update introduces campaign-level negatives, search term reporting for Performance Max, and smarter automation tools for large-scale ad management.

Google Ads Editor 2.11 gets campaign-level negatives and smarter automation

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo.png" class="attachment-large size-large wp-post-image" alt="SEO AI optimization GEO AEO LLMO" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo.png 1920w, https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Here's why treating ChatGPT like Google will guarantee your failure in the age of RAG, reranking, and probabilistic systems.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo.png" class="attachment-large size-large wp-post-image" alt="SEO AI optimization GEO AEO LLMO" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo.png 1920w, https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/10/seo-ai-optimization-geo-aeo-llmo-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Look, I get it. Every time a new search technology appears, we try to map it to what we already know. </p>



<ul class="wp-block-list">
<li>When mobile search exploded, we called it “mobile SEO.” </li>



<li>When voice assistants arrived, we coined “voice search optimization” and told everyone this would be the new hype.</li>
</ul>



<p>I’ve been doing SEO for years. </p>



<p>I know how Google works – or at least I thought I did. </p>



<p>Then I started digging into how ChatGPT picks citations, how Perplexity ranks sources, and how Google’s AI Overviews select content.</p>



<p><strong>I’m not here to declare that SEO is dead or to state that everything has changed.</strong> I’m here to share the questions that keep me up at night – questions that suggest we might be dealing with fundamentally different systems that require fundamentally different thinking.</p>



<h2 class="wp-block-heading" id="the-questions-i-cant-stop-asking">The questions I can’t stop asking </h2>



<p>After months of analyzing AI search systems, documenting ChatGPT’s behavior, and reverse-engineering <a href="https://searchengineland.com/how-perplexity-ranks-content-research-460031">Perplexity’s ranking factors</a>, these are the questions that challenge most of the things I thought I knew about search optimization.</p>



<h3 class="wp-block-heading" id="when-math-stops-making-sense">When math stops making sense</h3>



<p>I understand PageRank. I understand link equity. But when I discovered Reciprocal Rank Fusion in ChatGPT’s code, I realized I don’t understand this:</p>



<ul class="wp-block-list">
<li><strong>Why does RRF mathematically reward mediocre consistency over single-query excellence?</strong> Is ranking #4 across 10 queries really better than ranking #1 for one?</li>



<li><strong>How do vector embeddings determine semantic distance differently from keyword matching?</strong> Are we optimizing for meaning or words?</li>



<li><strong>Why does temperature=0.7 create non-reproducible rankings?</strong> Should we test everything 10 times over now?</li>



<li><strong>How do cross-encoder rerankers evaluate query-document pairs differently than PageRank?</strong> Is real-time relevance replacing pre-computed authority?</li>
</ul>



<p>These are also SEO concepts. However, they appear to be entirely different mathematical frameworks within LLMs. Or are they?</p>



<h3 class="wp-block-heading" id="when-scale-becomes-impossible">When scale becomes impossible</h3>



<p>Google indexes trillions of pages. ChatGPT retrieves 38-65. This isn’t a small difference – it’s a 99.999% reduction, resulting in questions that haunt me:</p>



<ul class="wp-block-list">
<li><strong>Why do LLMs retrieve 38-65 results while Google indexes billions?</strong> Is this temporary or fundamental?</li>



<li><strong>How do token limits establish rigid boundaries that don’t exist in traditional searches? </strong>When did search results become limited in size?</li>



<li><strong>How does the k=60 constant in RRF create a mathematical ceiling for visibility?</strong> Is position 61 the new page 2?</li>
</ul>



<p>Maybe they’re just current limitations. Or maybe, they represent a different information retrieval paradigm.</p>



<h2 class="wp-block-heading" id="the-101-questions-that-haunt-me">The 101 questions that haunt me:</h2>



<ol class="wp-block-list">
<li>Is OpenAI also using CTR for citation rankings?</li>



<li>Does AI read our <strong>page layout</strong> the way Google does, or only the text?</li>



<li>Should we write <strong>short paragraphs</strong> to help AI chunk content better?</li>



<li>Can scroll depth or mouse movement affect AI ranking signals?</li>



<li>How do low bounce rates impact our chances of being cited?</li>



<li>Can AI models use session patterns (like reading order) to rerank pages?</li>



<li>How can a new brand be included in offline training data and become visible?</li>



<li>How do you optimize a web/product page for a probabilistic system?</li>



<li>Why are citations continuously changing?</li>



<li>Should we run multiple tests to see the <strong>variance</strong>?</li>



<li>Can we use long-form questions with the “blue links” on Google to find the exact answer?</li>



<li>Are LLMs using the same reranking process?</li>



<li>Is web_search a switch or a chance to trigger?</li>



<li>Are we chasing ranks or citations?</li>



<li>Is reranking fixed or stochastic?</li>



<li>Are Google &amp; LLMs using the same embedding model? If so, what’s the corpus difference?</li>



<li>Which pages are most requested by LLMs and most visited by humans?</li>



<li>Do we track drift after model updates?</li>



<li>Why is EEAT easily manipulated in LLMs but not in Google’s traditional search?</li>



<li>How many of us drove at least 10x traffic increases after Google’s algorithm leak?</li>



<li>Why does the answer structure always change even when asking the same question within a day’s difference? (If there is no cache)</li>



<li>Does post-click dwell on our site improve future inclusion?</li>



<li>Does session memory bias citations toward earlier sources?</li>



<li>Why are LLMs more biased than Google?</li>



<li>Does offering a downloadable dataset make a claim more citeable?</li>



<li>Why do we still have very outdated information in Turkish, even though we ask very up-to-date questions? (For example, when asking what’s the best e-commerce website in Turkiye, we still see brands from the late 2010s)</li>



<li>How do vector embeddings determine semantic distance differently from keyword matching?</li>



<li>Do we now find ourselves in need to understand the “temperature” value in LLMs?</li>



<li>How can a small website <strong>appear inside ChatGPT or Perplexity answers</strong>?</li>



<li>What happens if we optimize our entire website solely for LLMs?</li>



<li>Can AI systems <strong>read/evaluate images in webpages instantly</strong>, or only the text around them?</li>



<li>How can we track whether AI tools use our content?</li>



<li>Can a single sentence from a blog post be quoted by an AI model?</li>



<li>How can we ensure that AI understands what our company does?</li>



<li>Why do some pages show up in Perplexity or ChatGPT, but not in Google?</li>



<li>Does AI favor fresh pages over stable, older sources?</li>



<li>How does AI re-rank pages once it has already fetched them?</li>



<li>Can we train LLMs to remember our brand voice in their answers?</li>



<li>Is there any way to make AI summaries link directly to our pages?</li>



<li>Can we track when our content is quoted but not linked?</li>



<li>How can we know which prompts or topics bring us more citations? What’s the volume?</li>



<li>What would happen if we were to change our monthly client SEO reports by just renaming them to “AI Visibility AEO/GEO Report”?</li>



<li>Is there a way to track how many times our brand is named in AI answers? (Like brand search volumes)</li>



<li>Can we use Cloudflare logs to see if AI bots are visiting our site?</li>



<li>Do <a href="https://metehan.ai/blog/structured-data-schema/">schema</a> changes result in measurable differences in AI mentions?</li>



<li>Will AI agents remember our brand after their first visit?</li>



<li>How can we make a local business with a map result more visible in LLMs?</li>



<li>Will Google AI Overviews and ChatGPT web answers use the same signals?</li>



<li>Can AI build a trust score for our domain over time?</li>



<li>Why do we need to be visible in query fanouts? For multiple queries at the same time? Why is there synthetic answer generation by AI models/LLMs even when users are only asking a question?</li>



<li>How often do AI systems refresh their understanding of our site? Do they also have search <a href="https://metehan.ai/blog/algorithm-penalties-recovery/">algorithm</a> updates?</li>



<li>Is the freshness signal sitewide or page-level for LLMs?</li>



<li>Can form submissions or downloads act as quality signals?</li>



<li>Are internal links making it easier for bots to move through our sites?</li>



<li>How does the semantic relevance between our content and a prompt affect ranking?</li>



<li>Can two very similar pages compete inside the same embedding cluster?</li>



<li>Do internal links help strengthen a page’s ranking signals for AI?</li>



<li>What makes a passage “high-confidence” during reranking?</li>



<li>Does freshness outrank trust when signals conflict?</li>



<li>How many rerank layers occur before the model picks its citations?</li>



<li>Can a heavily cited paragraph lift the rest of the site’s trust score?</li>



<li>Do model updates reset past re-ranking preferences, or do they retain some memory?</li>



<li>Why can we find better results by 10 blue links without any hallucination? (mostly)</li>



<li>Which part of the system actually <strong>chooses the final citations</strong>?</li>



<li>Do human feedback loops change how LLMs rank sources over time?</li>



<li>When does an AI decide to search again mid-answer? Why do we see more/multiple automatic LLM searches during a single chat window?</li>



<li>Does being cited once make it more likely for our brand to be cited again? If we rank in the top 10 on Google, we can remain visible while staying in the top 10. Is it the same with LLMs?</li>



<li>Can frequent citations raise a domain’s retrieval priority automatically?</li>



<li>Are user clicks on cited links stored as part of feedback signals?</li>



<li>Are Google and LLMs using the same deduplication process?</li>



<li>Can citation velocity (growth speed) be measured like link velocity in SEO?</li>



<li>Will LLMs eventually build a permanent “citation graph” like Google’s link graph?</li>



<li>Do LLMs connect brands that appear in similar topics or question clusters?</li>



<li>How long does it take for repeated exposure to become persistent brand memory in LLMs?</li>



<li>Why doesn’t Google show 404 links in results but LLMs in answers?</li>



<li>Why do LLMs fabricate citations while Google only links to existing URLs?</li>



<li>Do LLMs retraining cycles give us a reset chance after losing visibility?</li>



<li>How do we build a recovery plan when AI models misinterpret information about us?</li>



<li>Why do some LLMs cite us while others completely ignore us?</li>



<li>Are <strong>ChatGPT and Perplexity</strong> using the same web data sources?</li>



<li>Do OpenAI and Anthropic rank trust and freshness the same way?</li>



<li>Are per-source limits (max citations per answer) different for LLMs?</li>



<li>How can we determine if AI tools cite us following a change in our content?</li>



<li>What’s the easiest way to track prompt-level visibility over time?</li>



<li>How can we make sure LLMs assert our facts as facts?</li>



<li>Does linking a video to the same topic page strengthen multi-format grounding?</li>



<li>Can the same question suggest different brands to different users?</li>



<li>Will LLMs remember previous interactions with our brand?</li>



<li>Does past click behavior influence future LLM recommendations?</li>



<li>How do retrieval and reasoning jointly decide which citation deserves attribution?</li>



<li>Why do LLMs retrieve 38-65 results per search while Google indexes billions?</li>



<li>How do cross-encoder rerankers evaluate query-document pairs differently than PageRank?</li>



<li>Why can a site with zero backlinks outrank authority sites in LLM responses?</li>



<li>How do token limits create hard boundaries that don’t exist in traditional search?</li>



<li>Why does temperature setting in LLMs create non-deterministic rankings?</li>



<li>Does OpenAI allocate a crawl budget for websites?</li>



<li>How does Knowledge Graph entity recognition differ from LLM token embeddings?</li>



<li>How does crawl-index-serve differ from retrieve-rerank-generate?</li>



<li>How does temperature=0.7 create non-reproducible rankings?</li>



<li>Why is a tokenizer important?</li>



<li>How does knowledge cutoff create blind spots that real-time crawling doesn’t have?</li>
</ol>



<h3 class="wp-block-heading" id="when-trust-becomes-probabilistic">When trust becomes probabilistic</h3>



<p>This one really gets me. Google links to URLs that exist, whereas AI systems can completely make things up:</p>



<ul class="wp-block-list">
<li><strong>Why can LLMs fabricate citations while Google only links to existing URLs?</strong></li>



<li><strong>How does a 3-27% hallucination rate compare to Google’s 404 error rate?</strong></li>



<li><strong>Why do identical queries produce contradictory “facts” in AI but not in search indices?</strong></li>



<li><strong>Why do we still have outdated information in Turkish even though we ask up-to-date questions?</strong></li>
</ul>



<p>Are we optimizing for systems that might lie to users? How do we handle that?</p>



<h2 class="wp-block-heading" id="where-this-leaves-us">Where this leaves us</h2>



<p>I’m not saying AI search optimization/AEO/GEO is completely different from SEO. I’m just saying that I have 100+ questions that my SEO knowledge can’t answer <strong>well, yet</strong>. </p>



<p>Maybe you have the answers. Maybe nobody does (yet). <em>But as of now, I don’t have the answers to these questions.</em></p>



<p>What I do know, however, is this: These questions aren’t going anywhere. And, there will be new ones. </p>



<p>The systems that generate these questions aren’t going anywhere either. We need to engage with them, test against them, and maybe – just maybe – develop new frameworks to understand them.</p>



<p>The winners in this new field won’t be those who have all the answers. There’ll be those asking the right questions and testing relentlessly to find out what works.</p>



<p><em>This article was originally published on metehan.ai (as <a href="https://metehan.ai/blog/100-questions-that-show-aeo-geo-is-different-than-seo/">100+ Questions That Show AEO/GEO Is Different Than SEO</a>) and is republished with permission.</em><br><strong><br></strong></p>


Look, I get it. Every time a new search technology appears, we try to map it to what we already know. 
When mobile search exploded, we called it “mobile SEO.” 
When voice assistants arrived, we coined “voice search optimization” and told everyone this would be the new hype.
I’ve been doing SEO for years. 
I know how Google works – or at least I thought I did. 
Then I started digging into how ChatGPT picks citations, how Perplexity ranks sources, and how Google’s AI Overviews select content.
I’m not here to declare that SEO is dead or to state that everything has changed. I’m here to share the questions that keep me up at night – questions that suggest we might be dealing with fundamentally different systems that require fundamentally different thinking.
The questions I can’t stop asking 
After months of analyzing AI search systems, documenting ChatGPT’s behavior, and reverse-engineering Perplexity’s ranking factors, these are the questions that challenge most of the things I thought I knew about search optimization.
When math stops making sense
I understand PageRank. I understand link equity. But when I discovered Reciprocal Rank Fusion in ChatGPT’s code, I realized I don’t understand this:
Why does RRF mathematically reward mediocre consistency over single-query excellence? Is ranking #4 across 10 queries really better than ranking #1 for one?
How do vector embeddings determine semantic distance differently from keyword matching? Are we optimizing for meaning or words?
Why does temperature=0.7 create non-reproducible rankings? Should we test everything 10 times over now?
How do cross-encoder rerankers evaluate query-document pairs differently than PageRank? Is real-time relevance replacing pre-computed authority?
These are also SEO concepts. However, they appear to be entirely different mathematical frameworks within LLMs. Or are they?
When scale becomes impossible
Google indexes trillions of pages. ChatGPT retrieves 38-65. This isn’t a small difference – it’s a 99.999% reduction, resulting in questions that haunt me:
Why do LLMs retrieve 38-65 results while Google indexes billions? Is this temporary or fundamental?
How do token limits establish rigid boundaries that don’t exist in traditional searches? When did search results become limited in size?
How does the k=60 constant in RRF create a mathematical ceiling for visibility? Is position 61 the new page 2?
Maybe they’re just current limitations. Or maybe, they represent a different information retrieval paradigm.
The 101 questions that haunt me:
Is OpenAI also using CTR for citation rankings?
Does AI read our page layout the way Google does, or only the text?
Should we write short paragraphs to help AI chunk content better?
Can scroll depth or mouse movement affect AI ranking signals?
How do low bounce rates impact our chances of being cited?
Can AI models use session patterns (like reading order) to rerank pages?
How can a new brand be included in offline training data and become visible?
How do you optimize a web/product page for a probabilistic system?
Why are citations continuously changing?
Should we run multiple tests to see the variance?
Can we use long-form questions with the “blue links” on Google to find the exact answer?
Are LLMs using the same reranking process?
Is web_search a switch or a chance to trigger?
Are we chasing ranks or citations?
Is reranking fixed or stochastic?
Are Google & LLMs using the same embedding model? If so, what’s the corpus difference?
Which pages are most requested by LLMs and most visited by humans?
Do we track drift after model updates?
Why is EEAT easily manipulated in LLMs but not in Google’s traditional search?
How many of us drove at least 10x traffic increases after Google’s algorithm leak?
Why does the answer structure always change even when asking the same question within a day’s difference? (If there is no cache)
Does post-click dwell on our site improve future inclusion?
Does session memory bias citations toward earlier sources?
Why are LLMs more biased than Google?
Does offering a downloadable dataset make a claim more citeable?
Why do we still have very outdated information in Turkish, even though we ask very up-to-date questions? (For example, when asking what’s the best e-commerce website in Turkiye, we still see brands from the late 2010s)
How do vector embeddings determine semantic distance differently from keyword matching?
Do we now find ourselves in need to understand the “temperature” value in LLMs?
How can a small website appear inside ChatGPT or Perplexity answers?
What happens if we optimize our entire website solely for LLMs?
Can AI systems read/evaluate images in webpages instantly, or only the text around them?
How can we track whether AI tools use our content?
Can a single sentence from a blog post be quoted by an AI model?
How can we ensure that AI understands what our company does?
Why do some pages show up in Perplexity or ChatGPT, but not in Google?
Does AI favor fresh pages over stable, older sources?
How does AI re-rank pages once it has already fetched them?
Can we train LLMs to remember our brand voice in their answers?
Is there any way to make AI summaries link directly to our pages?
Can we track when our content is quoted but not linked?
How can we know which prompts or topics bring us more citations? What’s the volume?
What would happen if we were to change our monthly client SEO reports by just renaming them to “AI Visibility AEO/GEO Report”?
Is there a way to track how many times our brand is named in AI answers? (Like brand search volumes)
Can we use Cloudflare logs to see if AI bots are visiting our site?
Do schema changes result in measurable differences in AI mentions?
Will AI agents remember our brand after their first visit?
How can we make a local business with a map result more visible in LLMs?
Will Google AI Overviews and ChatGPT web answers use the same signals?
Can AI build a trust score for our domain over time?
Why do we need to be visible in query fanouts? For multiple queries at the same time? Why is there synthetic answer generation by AI models/LLMs even when users are only asking a question?
How often do AI systems refresh their understanding of our site? Do they also have search algorithm updates?
Is the freshness signal sitewide or page-level for LLMs?
Can form submissions or downloads act as quality signals?
Are internal links making it easier for bots to move through our sites?
How does the semantic relevance between our content and a prompt affect ranking?
Can two very similar pages compete inside the same embedding cluster?
Do internal links help strengthen a page’s ranking signals for AI?
What makes a passage “high-confidence” during reranking?
Does freshness outrank trust when signals conflict?
How many rerank layers occur before the model picks its citations?
Can a heavily cited paragraph lift the rest of the site’s trust score?
Do model updates reset past re-ranking preferences, or do they retain some memory?
Why can we find better results by 10 blue links without any hallucination? (mostly)
Which part of the system actually chooses the final citations?
Do human feedback loops change how LLMs rank sources over time?
When does an AI decide to search again mid-answer? Why do we see more/multiple automatic LLM searches during a single chat window?
Does being cited once make it more likely for our brand to be cited again? If we rank in the top 10 on Google, we can remain visible while staying in the top 10. Is it the same with LLMs?
Can frequent citations raise a domain’s retrieval priority automatically?
Are user clicks on cited links stored as part of feedback signals?
Are Google and LLMs using the same deduplication process?
Can citation velocity (growth speed) be measured like link velocity in SEO?
Will LLMs eventually build a permanent “citation graph” like Google’s link graph?
Do LLMs connect brands that appear in similar topics or question clusters?
How long does it take for repeated exposure to become persistent brand memory in LLMs?
Why doesn’t Google show 404 links in results but LLMs in answers?
Why do LLMs fabricate citations while Google only links to existing URLs?
Do LLMs retraining cycles give us a reset chance after losing visibility?
How do we build a recovery plan when AI models misinterpret information about us?
Why do some LLMs cite us while others completely ignore us?
Are ChatGPT and Perplexity using the same web data sources?
Do OpenAI and Anthropic rank trust and freshness the same way?
Are per-source limits (max citations per answer) different for LLMs?
How can we determine if AI tools cite us following a change in our content?
What’s the easiest way to track prompt-level visibility over time?
How can we make sure LLMs assert our facts as facts?
Does linking a video to the same topic page strengthen multi-format grounding?
Can the same question suggest different brands to different users?
Will LLMs remember previous interactions with our brand?
Does past click behavior influence future LLM recommendations?
How do retrieval and reasoning jointly decide which citation deserves attribution?
Why do LLMs retrieve 38-65 results per search while Google indexes billions?
How do cross-encoder rerankers evaluate query-document pairs differently than PageRank?
Why can a site with zero backlinks outrank authority sites in LLM responses?
How do token limits create hard boundaries that don’t exist in traditional search?
Why does temperature setting in LLMs create non-deterministic rankings?
Does OpenAI allocate a crawl budget for websites?
How does Knowledge Graph entity recognition differ from LLM token embeddings?
How does crawl-index-serve differ from retrieve-rerank-generate?
How does temperature=0.7 create non-reproducible rankings?
Why is a tokenizer important?
How does knowledge cutoff create blind spots that real-time crawling doesn’t have?
When trust becomes probabilistic
This one really gets me. Google links to URLs that exist, whereas AI systems can completely make things up:
Why can LLMs fabricate citations while Google only links to existing URLs?
How does a 3-27% hallucination rate compare to Google’s 404 error rate?
Why do identical queries produce contradictory “facts” in AI but not in search indices?
Why do we still have outdated information in Turkish even though we ask up-to-date questions?
Are we optimizing for systems that might lie to users? How do we handle that?
Where this leaves us
I’m not saying AI search optimization/AEO/GEO is completely different from SEO. I’m just saying that I have 100+ questions that my SEO knowledge can’t answer well, yet. 
Maybe you have the answers. Maybe nobody does (yet). But as of now, I don’t have the answers to these questions.
What I do know, however, is this: These questions aren’t going anywhere. And, there will be new ones. 
The systems that generate these questions aren’t going anywhere either. We need to engage with them, test against them, and maybe – just maybe – develop new frameworks to understand them.
The winners in this new field won’t be those who have all the answers. There’ll be those asking the right questions and testing relentlessly to find out what works.
This article was originally published on metehan.ai (as 100+ Questions That Show AEO/GEO Is Different Than SEO) and is republished with permission.

Here's why treating ChatGPT like Google will guarantee your failure in the age of RAG, reranking, and probabilistic systems.

SEO vs. AI search: 101 questions that keep me up at night

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Sir Tim Berners-Lee helped build the modern web. Now he’s worried AI could help destroy its business model.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/ai-ad-supported-web-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Sir Tim Berners-Lee, who invented the World Wide Web, is worried that the ad-supported web will collapse due to AI. In a new interview with Nilay Patel on Decoder, Berners-Lee said:</p>



<ul class="wp-block-list">
<li>“I do worry about the infrastructure of the web when it comes to the stack of all the flow of data, which is produced by people who make their money from advertising. If nobody is actually following through the links, if people are not using search engines, they’re not actually using their websites, then we lose that flow of ad revenue. That whole model crumbles. I do worry about that.&#8221;</li>
</ul>



<p><strong>Why we care.</strong> There is a split in our industry, where one side thinks &#8220;it&#8217;s just SEO&#8221; and the other sees a near future where visibility in AI platforms has replaced rankings, clicks, and traffic. We know SEO still isn&#8217;t dead and people are still using search engines, but the writing is still on the wall (<a href="https://searchengineland.com/google-search-traffic-decline-inevitable-455345">Google execs have said as much in private</a>). Berners-Lee seems to envision the same future, warning that if people stop following links and visiting websites, the entire web model &#8220;crumbles,” leaving AI platforms with value while the ad-supported web and SEO fade.</p>



<p><strong>On monopolies.</strong> In the same interview, Berners-Lee said a centralized provider or monopoly isn&#8217;t good for the web:</p>



<ul class="wp-block-list">
<li>“When you have a market and a network, then you end up with monopolies. That’s the way markets work.</li>



<li>“There was a time before Google Chrome was totally dominant, when there was a reasonable market for different browsers. Now Chrome is dominant. </li>



<li>&#8220;There was a time before Google Search came along, there were a number of search engines and so on, but now we have basically one search engine. </li>



<li>&#8220;We have basically one social network. We have basically one marketplace, which is a real problem for people.”</li>
</ul>



<p><strong>On the semantic web. </strong>Berners-Lee worked on the Semantic Web for decades (a web that machines can read as easily as humans). As for where it&#8217;s heading next: data by AI, for AI (and also people, but especially AI):</p>



<ul class="wp-block-list">
<li>&#8220;The Semantic Web has succeeded to the extent that there’s the linked open data world of public databases of all kinds of things, about proteins, about geography, the OpenStreetMap, and so on. To a certain extent, the Semantic Web has succeeded in two ways: all of that, and because of Schema.org.</li>



<li>&#8220;Schema.org is this project of Google. If you have a website and you want it to be recognized by the search engine, then you put metadata in Semantic Web data, you put machine-readable data on your website. And then the Google search engine will build a mental model of your band or your music, whatever it is you’re selling.</li>



<li>&#8220;In those ways, with the link to the data group and product database, the Semantic Web has been a success. But then we never built the things that would extract semantic data from non-semantic data. Now AI will do that. </li>



<li>&#8220;Now we’ve got another wave of the Semantic Web with AI. You have a possibility where AIs use the Semantic Web to communicate between one and two possibilities and they communicate with each other. There is a web of data that is generated by AIs and used by AIs and used by people, but also mainly used by AIs.&#8221;</li>
</ul>



<p><strong>On blocking AI crawlers.</strong> Discussion turned to Cloudflare and their attempt to <a href="https://searchengineland.com/cloudflare-to-block-ai-crawlers-by-default-with-new-pay-per-crawl-initiative-457708">block crawlers and its pay per crawl initiative</a>. Berners-Lee was asked whether the web’s architecture could be redesigned so websites and database owners could bake a “not unless you pay me” rule into open standards, forcing AI crawlers and other clients across the ecosystem to honor payment requirements by default. His response:</p>



<ul class="wp-block-list">
<li>&#8220;You could write the protocols. One, in fact, is micropayments. We’ve had micropayments projects in W3C every now and again over the decades. There have been projects at MIT, for example, for micropayments and so on. So, suddenly there’s a “payment required” error code in HTTP. The idea that people would pay for information on the web; that’s always been there. But of course whether you’re an AI crawler or whether you are an individual person, it’s the way you want to pay for things that’s going to be very different.&#8221;</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><strong>The interview.</strong> <a href="https://www.theverge.com/podcast/814552/tim-berners-lee-world-wide-web-ai-future-interview">Sir Tim Berners-Lee doesn’t think AI will destroy the web</a></p>
</blockquote>


Sir Tim Berners-Lee, who invented the World Wide Web, is worried that the ad-supported web will collapse due to AI. In a new interview with Nilay Patel on Decoder, Berners-Lee said:
“I do worry about the infrastructure of the web when it comes to the stack of all the flow of data, which is produced by people who make their money from advertising. If nobody is actually following through the links, if people are not using search engines, they’re not actually using their websites, then we lose that flow of ad revenue. That whole model crumbles. I do worry about that.”
Why we care. There is a split in our industry, where one side thinks “it’s just SEO” and the other sees a near future where visibility in AI platforms has replaced rankings, clicks, and traffic. We know SEO still isn’t dead and people are still using search engines, but the writing is still on the wall (Google execs have said as much in private). Berners-Lee seems to envision the same future, warning that if people stop following links and visiting websites, the entire web model “crumbles,” leaving AI platforms with value while the ad-supported web and SEO fade.
On monopolies. In the same interview, Berners-Lee said a centralized provider or monopoly isn’t good for the web:
“When you have a market and a network, then you end up with monopolies. That’s the way markets work.
“There was a time before Google Chrome was totally dominant, when there was a reasonable market for different browsers. Now Chrome is dominant. 
“There was a time before Google Search came along, there were a number of search engines and so on, but now we have basically one search engine. 
“We have basically one social network. We have basically one marketplace, which is a real problem for people.”
On the semantic web. Berners-Lee worked on the Semantic Web for decades (a web that machines can read as easily as humans). As for where it’s heading next: data by AI, for AI (and also people, but especially AI):
“The Semantic Web has succeeded to the extent that there’s the linked open data world of public databases of all kinds of things, about proteins, about geography, the OpenStreetMap, and so on. To a certain extent, the Semantic Web has succeeded in two ways: all of that, and because of Schema.org.
“Schema.org is this project of Google. If you have a website and you want it to be recognized by the search engine, then you put metadata in Semantic Web data, you put machine-readable data on your website. And then the Google search engine will build a mental model of your band or your music, whatever it is you’re selling.
“In those ways, with the link to the data group and product database, the Semantic Web has been a success. But then we never built the things that would extract semantic data from non-semantic data. Now AI will do that. 
“Now we’ve got another wave of the Semantic Web with AI. You have a possibility where AIs use the Semantic Web to communicate between one and two possibilities and they communicate with each other. There is a web of data that is generated by AIs and used by AIs and used by people, but also mainly used by AIs.”
On blocking AI crawlers. Discussion turned to Cloudflare and their attempt to block crawlers and its pay per crawl initiative. Berners-Lee was asked whether the web’s architecture could be redesigned so websites and database owners could bake a “not unless you pay me” rule into open standards, forcing AI crawlers and other clients across the ecosystem to honor payment requirements by default. His response:
“You could write the protocols. One, in fact, is micropayments. We’ve had micropayments projects in W3C every now and again over the decades. There have been projects at MIT, for example, for micropayments and so on. So, suddenly there’s a “payment required” error code in HTTP. The idea that people would pay for information on the web; that’s always been there. But of course whether you’re an AI crawler or whether you are an individual person, it’s the way you want to pay for things that’s going to be very different.”
The interview. Sir Tim Berners-Lee doesn’t think AI will destroy the web

Sir Tim Berners-Lee helped build the modern web. Now he’s worried AI could help destroy its business model.

Tim Berners-Lee warns AI may collapse the ad-funded web

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome.png 1920w, https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google is expanding ad placements into mobile image search, giving brands a new, visually engaging way to capture user attention.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome.png 1920w, https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/09/google-ai-mode-chrome-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google rolled out AI-powered ad carousels in the Images tab on mobile, now appearing across all categories — not just shopping-related ones.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2025/11/image-search-expanded.png" alt="" class="wp-image-464544" srcset="https://searchengineland.com/wp-content/seloads/2025/11/image-search-expanded.png 1280w, https://searchengineland.com/wp-content/seloads/2025/11/image-search-expanded-768x432.png 768w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<p><strong>Why we care.</strong> Ads are now showing directly within image search results, giving brands a new, highly visual placement to grab attention where users are actively browsing and comparing visuals. With users often browsing images to explore ideas or compare options, these AI-powered carousels give brands a chance to influence discovery earlier in the journey.</p>



<p><strong>The details:</strong></p>



<ul class="wp-block-list">
<li>The new format features <strong>horizontally scrollable carousels</strong> with images, headlines, and links.</li>



<li>These carousels are powered by <strong>AI-driven ad matching</strong>, pulling in visuals relevant to the user’s query — even in non-commerce categories like <strong>law or insurance</strong>.</li>



<li>The feature was first spotted by ADSQUIRE founder <strong>Anthony Higman</strong>, who shared screenshots of the new layout on <a href="https://x.com/AnthonyHigman/status/1986242726245908679">X</a>. </li>
</ul>



<p><strong>The big picture</strong>. By integrating ads more seamlessly into visual search, Google is blurring the line between organic and paid discovery a continued shift toward immersive, image-based ad experiences that go beyond traditional text and product listings.</p>


Google rolled out AI-powered ad carousels in the Images tab on mobile, now appearing across all categories — not just shopping-related ones.




Why we care. Ads are now showing directly within image search results, giving brands a new, highly visual placement to grab attention where users are actively browsing and comparing visuals. With users often browsing images to explore ideas or compare options, these AI-powered carousels give brands a chance to influence discovery earlier in the journey.
The details:
The new format features horizontally scrollable carousels with images, headlines, and links.
These carousels are powered by AI-driven ad matching, pulling in visuals relevant to the user’s query — even in non-commerce categories like law or insurance.
The feature was first spotted by ADSQUIRE founder Anthony Higman, who shared screenshots of the new layout on X. 
The big picture. By integrating ads more seamlessly into visual search, Google is blurring the line between organic and paid discovery a continued shift toward immersive, image-based ad experiences that go beyond traditional text and product listings.

Google is expanding ad placements into mobile image search, giving brands a new, visually engaging way to capture user attention.

Google expands image search ads with mobile carousel format

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Last month, Google launched a form to report negative review extortion scams and it seems to work.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/broken-google-review-stars-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Business Profiles has a form where you can report negative review extortion scams, the form launched a <a href="https://www.seroundtable.com/google-business-profile-report-negative-review-extortion-scams-40250.html">month ago</a>.  You can find access to the form in <a href="https://support.google.com/business/answer/16404809">this help document</a> and I believe you need to be logged into your Google account with access to the Business Profile you want to report.</p>



<p><strong>Review extortion scams. </strong>This negative review extortion scams are on the rise and a huge concern for local SEOs and businesses. A scammer will message you, likely over WhatsApp or email, and tell you that they left a one-star negative review and the only way to remove it is to pay them.</p>



<p>Google wrote in its help document, &#8220;These scams may involve a sudden increase in 1-star and 2-star reviews on your Google Business Profile, followed by someone demanding money, goods, or services in exchange for removing the negative reviews.&#8221;</p>



<p><strong>The form. </strong>The form can be accessed while logged into your Google account by <a href="https://support.google.com/business/contact/merchant_extortion">clicking here</a>. The form asks for your information, the affected Google Business Profile details, more details on the extortion review, and additional evidence.</p>



<p><strong>Do not engage. </strong>Google posted four tips when you are confronted with these scams:</p>



<ul class="wp-block-list">
<li>Do not engage with or pay the malicious individuals. This can encourage further attempts and doesn’t guarantee the removal of reviews.</li>



<li>Do not try to resolve it yourself by offering money or services.</li>



<li>Gather all evidence immediately. The sooner you collect proof, the better.</li>



<li>Report all relevant communication you receive in the form.</li>
</ul>



<p><strong>Give it a try. </strong>There are some who are doubtful that this form actually does anything. But one local SEO <a href="https://www.seroundtable.com/google-negative-review-extortion-scams-works-40406.html">tried it out</a> over the weekend and within a few days, the review in question was removed. So it is worth giving it a shot.</p>



<p><strong>Why we care. </strong>Reviews on your local listing, especially on Google Maps and Google Search, can have a huge impact on your business. Negative reviews will encourage customers to look for other businesses, even if those reviews are fraudulent. So, being on top of your reviews and removing the fake and fraudulent reviews is an important task most businesses should do on an ongoing basis.</p>



<p>This form will help you manage some of those fake reviews.</p>


Google Business Profiles has a form where you can report negative review extortion scams, the form launched a month ago.  You can find access to the form in this help document and I believe you need to be logged into your Google account with access to the Business Profile you want to report.
Review extortion scams. This negative review extortion scams are on the rise and a huge concern for local SEOs and businesses. A scammer will message you, likely over WhatsApp or email, and tell you that they left a one-star negative review and the only way to remove it is to pay them.
Google wrote in its help document, “These scams may involve a sudden increase in 1-star and 2-star reviews on your Google Business Profile, followed by someone demanding money, goods, or services in exchange for removing the negative reviews.”
The form. The form can be accessed while logged into your Google account by clicking here. The form asks for your information, the affected Google Business Profile details, more details on the extortion review, and additional evidence.
Do not engage. Google posted four tips when you are confronted with these scams:
Do not engage with or pay the malicious individuals. This can encourage further attempts and doesn’t guarantee the removal of reviews.
Do not try to resolve it yourself by offering money or services.
Gather all evidence immediately. The sooner you collect proof, the better.
Report all relevant communication you receive in the form.
Give it a try. There are some who are doubtful that this form actually does anything. But one local SEO tried it out over the weekend and within a few days, the review in question was removed. So it is worth giving it a shot.
Why we care. Reviews on your local listing, especially on Google Maps and Google Search, can have a huge impact on your business. Negative reviews will encourage customers to look for other businesses, even if those reviews are fraudulent. So, being on top of your reviews and removing the fake and fraudulent reviews is an important task most businesses should do on an ongoing basis.
This form will help you manage some of those fake reviews.

Last month, Google launched a form to report negative review extortion scams and it seems to work.

With negative review extortion scams on the rise, use Google’s report form

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop.png" class="attachment-large size-large wp-post-image" alt="Google Ads tactics to drop" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Advertisers should review and verify all phone numbers in their ads, as Google will soon disallow any linked to fraud or past policy violations.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop.png" class="attachment-large size-large wp-post-image" alt="Google Ads tactics to drop" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/Google-Ads-tactics-to-drop-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Ads is updating its Destination requirements policy to block phone numbers tied to fraud or prior policy violations, part of the company’s ongoing effort to curb deceptive advertising practices.</p>



<p><strong>The timeline:</strong></p>



<ul class="wp-block-list">
<li><strong>Policy update effective:</strong> December 10, 2025</li>



<li><strong>Enforcement ramp-up:</strong> Over roughly 8 weeks after rollout</li>
</ul>



<p><strong>What’s changing</strong>. Phone numbers flagged as fraudulent or with a history of violations will now be deemed unacceptable under the Destination requirements policy, leading to ad disapprovals.</p>



<p><strong>Why we care</strong>. The change targets bad actors who use legitimate-looking phone numbers to mislead users or bypass enforcement, a recurring issue in sectors like tech support scams and lead generation. It’s a reminder to audit contact information across campaigns and ensure all numbers are verified and legitimate. Failing to do so could disrupt ad delivery, delay approvals, and hurt campaign performance during the enforcement rollout.</p>



<p><strong>For advertisers</strong>. Those impacted will receive disapproval notices and can refer to Google’s help center for guidance on fixing disapproved ads or assets.</p>



<p><strong>First seen.</strong> This update was shared by ADSQUIRE founder, Anthony Higman on <a href="https://x.com/AnthonyHigman/status/1987947716589068695?s=20">X</a>. </p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="609" height="572" src="https://searchengineland.com/wp-content/seloads/2025/11/G5abkWWXQAAIuOp.png" alt="" class="wp-image-464510"/></figure></div>


<p><strong>Between the lines</strong>. Google continues tightening ad verification and destination standards amid growing scrutiny over scams and consumer trust — showing that accountability for ad content now extends beyond just the landing page.</p>


Google Ads is updating its Destination requirements policy to block phone numbers tied to fraud or prior policy violations, part of the company’s ongoing effort to curb deceptive advertising practices.
The timeline:
Policy update effective: December 10, 2025
Enforcement ramp-up: Over roughly 8 weeks after rollout
What’s changing. Phone numbers flagged as fraudulent or with a history of violations will now be deemed unacceptable under the Destination requirements policy, leading to ad disapprovals.
Why we care. The change targets bad actors who use legitimate-looking phone numbers to mislead users or bypass enforcement, a recurring issue in sectors like tech support scams and lead generation. It’s a reminder to audit contact information across campaigns and ensure all numbers are verified and legitimate. Failing to do so could disrupt ad delivery, delay approvals, and hurt campaign performance during the enforcement rollout.
For advertisers. Those impacted will receive disapproval notices and can refer to Google’s help center for guidance on fixing disapproved ads or assets.
First seen. This update was shared by ADSQUIRE founder, Anthony Higman on X. 

Between the lines. Google continues tightening ad verification and destination standards amid growing scrutiny over scams and consumer trust — showing that accountability for ad content now extends beyond just the landing page.

Advertisers should review and verify all phone numbers in their ads, as Google will soon disallow any linked to fraud or past policy violations.

Google tightens rules on fraud-linked phone numbers in ads

<div><img width="1920" height="1081" src="https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept.png" class="attachment-large size-large wp-post-image" alt="AI availability concept" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept-1536x865.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>GEO redefines visibility through AI availability – how likely your brand is to be recognized and recommended by AI systems.

<div><img width="1920" height="1081" src="https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept.png" class="attachment-large size-large wp-post-image" alt="AI availability concept" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept.png 1920w, https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/AI-availability-concept-1536x865.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p><a href="https://searchengineland.com/what-is-generative-engine-optimization-geo-444418">GEO</a>, AI SEO, AEO – <a href="https://searchengineland.com/seo-ai-future-whatever-you-call-it-optimization-463462">call it what you like</a>.</p>



<p>The label doesn’t matter nearly as much as understanding the shift behind it.</p>



<p>At the center of that shift lies one idea that explains everything: AI availability – and here’s why it matters.</p>



<h2 class="wp-block-heading" id="h-what-is-ai-availability">What is AI availability?</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="696" height="780" src="https://searchengineland.com/wp-content/seloads/2025/11/The-three-pillars-of-brand-availability.png" alt="The three pillars of brand availability" class="wp-image-464489"/></figure></div>


<p>The idea of AI availability comes from <a href="https://au.linkedin.com/in/professorbyronsharp" target="_blank" rel="noopener">Byron Sharp</a>, research professor at the Ehrenberg-Bass Institute, who introduced it in a comment on one of my LinkedIn posts.</p>



<p>Sharp’s work underpins modern brand science and shows that growth depends on availability.</p>



<p>Brands grow through sales, and sales grow through two kinds of availability: mental and physical.</p>



<ul class="wp-block-list">
<li>Mental availability refers to the likelihood of being considered in a purchasing situation.</li>



<li>Physical availability refers to the ease and convenience with which an item can be bought.</li>
</ul>



<p>For years, these two principles have guided brand strategy. </p>



<p>They explain why Coca-Cola invests in constant visibility and why Amazon makes every click lead to a checkout.</p>



<p>But in the era of generative search, there’s now a third kind of availability marketers need to understand – the likelihood that your brand or product will be recommended by an AI system when a user is ready to buy.</p>



<p>That is AI availability – and it changes everything.</p>



<h2 class="wp-block-heading" id="h-ai-as-the-new-influencer">AI as the new influencer</h2>



<p>If you are still thinking of AI as a technology, you are already behind.</p>



<p>Think of it instead as the world’s most powerful influencer.</p>



<p><a href="https://searchengineland.com/what-is-chatgpt-and-why-seos-should-care-392165">ChatGPT</a> alone is used by <a href="https://cdn.openai.com/pdf/a253471f-8260-40c6-a2cc-aa93fe9f142e/economic-research-chatgpt-usage-paper.pdf?utm_source=chatgpt.com" target="_blank" rel="noopener">about 10%</a> of the global adult population, according to recent research from OpenAI, Harvard, and Duke.&nbsp;</p>



<p>That makes it far more pervasive than any social media platform at a similar stage in its life cycle.</p>



<p>Most people do not use it to code or write poetry – they use it to make decisions.&nbsp;</p>



<p>Nearly 80% of ChatGPT conversations, the same study found, fall into three categories:&nbsp;</p>



<ul class="wp-block-list">
<li>Practical guidance.</li>



<li>Seeking information.</li>



<li>Writing.</li>
</ul>



<p>In other words, people are asking AI to help them decide what to do, buy, and believe. </p>



<p>The study also shows that these conversations are increasingly focused on everyday decisions rather than work.&nbsp;</p>



<p>The distinction between search, research, and conversation is collapsing.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1318" height="850" src="https://searchengineland.com/wp-content/seloads/2025/11/Source-How-People-Use-ChatGPT-OpenAI-Harvard-University-and-Duke-University.png" alt="Source- “How People Use ChatGPT,” OpenAI, Harvard University, and Duke University" class="wp-image-464487" srcset="https://searchengineland.com/wp-content/seloads/2025/11/Source-How-People-Use-ChatGPT-OpenAI-Harvard-University-and-Duke-University.png 1318w, https://searchengineland.com/wp-content/seloads/2025/11/Source-How-People-Use-ChatGPT-OpenAI-Harvard-University-and-Duke-University-768x495.png 768w" sizes="(max-width: 1318px) 100vw, 1318px" /><figcaption class="wp-element-caption"><em><em>Source: “</em><a href="https://cdn.openai.com/pdf/a253471f-8260-40c6-a2cc-aa93fe9f142e/economic-research-chatgpt-usage-paper.pdf" target="_blank" rel="noopener"><em>How People Use ChatGPT</em></a><em>,” OpenAI, Harvard University, and Duke University</em></em></figcaption></figure></div>


<p>The result is simple.</p>



<p>AI systems are now the gatekeepers of modern discovery. They decide what information to surface and which businesses appear in front of consumers.</p>



<p>Forget the Kardashians. Forget influencer marketing.</p>



<p>If you&#8217;re invisible to AI, you&#8217;re invisible to the market.</p>



<p>AI is the new influencer.</p>



<h2 class="wp-block-heading" id="h-from-keywords-to-fitness-signals">From keywords to fitness signals</h2>



<p>The <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> industry has spent two decades optimizing for how humans search with keywords – but that is changing.</p>



<p><a href="https://searchengineland.com/seo-guide-large-language-models-413227">Large language models</a> (LLMs) infer meaning from context, probability, and performance.</p>



<p>They are scanning for what we can call fitness signals – a term from network science.</p>



<p>Fitness describes a product or service’s inherent ability to outcompete rivals, allowing one business to dominate a market even if others started earlier or invested more.</p>



<p>Think of how Google overtook Yahoo.&nbsp;</p>



<p>It wasn’t just about better search algorithms – it was a better business model built on a stronger performance attribute: relevance.</p>



<p>These performance attributes are what make a business fit for survival. They are the qualities that define how well you solve a problem for a customer.</p>



<p>AI deploys search strategies to identify which businesses solve which problems most effectively.&nbsp;</p>



<p>Because it exists to serve human needs, those same signals determine your AI availability.</p>



<p>Yes, AI uses search strings, fan-out queries, and reciprocal rank fusion, among many other strategies and tactics.&nbsp;</p>



<p>It doesn’t search like humans because it isn’t bound by the same cognitive and speed limitations.</p>



<p>Humans search by “satisficing.” Keywords + Page 1 rankings = good enough.</p>



<p>Machines operate on an industrial scale – searching, gathering, assessing, and recommending.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/fame-engineering-key-generative-engine-optimization-461969">Fame engineering: The key to generative engine optimization</a></em></strong></p>



<h2 class="wp-block-heading" id="h-the-psychology-of-performance">The psychology of performance</h2>



<p>To understand why this works, we turn to evolutionary psychology.</p>



<p><a href="https://www.linkedin.com/in/geoffrey-miller-002a3710">Geoffrey Miller</a>, author of “Spent,” explained that humans have always been driven by two fundamental needs.&nbsp;</p>



<ul class="wp-block-list">
<li>We seek to display fitness indicators that enhance our status.</li>



<li>We chase fitness cues that increase our chances of survival or pleasure.</li>
</ul>



<p>Consumer products have evolved to meet those needs. Luxury goods signal success.&nbsp;</p>



<p>Convenience products signal control. Both deliver psychological reassurance.</p>



<p>AI works in a similar way. Its goal is to satisfy human intent.&nbsp;</p>



<p>When someone types a complex prompt into an LLM, the AI interprets it not as a string of keywords but as a statement of need.&nbsp;</p>



<p>It then searches its training data and live information to find the most relevant and trustworthy performance attributes that match that need.</p>



<p>That is why context matters so much more than content.&nbsp;</p>



<p>You are no longer competing for blue links – you are competing for cognitive inclusion in an AI’s mental model of your category.&nbsp;</p>



<p>Your job is to make your brand’s fitness and performance attributes unmissable to that model.</p>



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<h2 class="wp-block-heading" id="h-category-entry-points-and-the-new-seo">Category entry points and the new SEO</h2>



<p>Category entry points are the situations, needs, and triggers that put someone in the market to buy.</p>



<p>In the world of GEO, these are your new keywords.</p>



<p>They are what users express in prompts rather than in search terms.&nbsp;</p>



<p>“Where can I find sustainable running shoes for flat feet?” is not a keyword query – it is a buying situation.</p>



<p>Your strategy is to:</p>



<ul class="wp-block-list">
<li>Understand those buying situations.</li>



<li>Map them to your own performance attributes.</li>



<li>Create enough context that AI can confidently associate your brand with the solution.</li>
</ul>



<p>That means describing not only what you do, but how you do it, who you do it for, and why you are distinctive.</p>



<p>This isn’t new. It’s the same foundational brand positioning marketers have always needed.</p>



<p>What’s changed is that it now feeds the world’s most sophisticated recommender system.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-search-booming-seo-still-not-dead-458935">AI search is booming, but SEO is still not dead</a></em></strong></p>



<h2 class="wp-block-heading" id="h-a-local-example-the-sandwich-shop-in-stoke">A local example: The sandwich shop in Stoke</h2>



<p>Imagine a small sandwich shop in Stoke. It’s not glamorous, serving sausage sandwiches, bacon rolls, and coffee.&nbsp;</p>



<p>The owners don’t want to be influencers. They just want customers.</p>



<p>How does a business like this make itself visible to AI?</p>



<h3 class="wp-block-heading" id="h-turn-everyday-details-into-data-signals">Turn everyday details into data signals</h3>



<p>The first step is to make its performance attributes explicit.</p>



<ul class="wp-block-list">
<li>What ingredients are used?</li>



<li>Where do they come from?</li>



<li>What makes the sandwiches good value?</li>



<li>How long has the business served the local community?</li>



<li>Where is it located?</li>



<li>What is the hygiene rating?</li>
</ul>



<p>All these details are small signals of trust and quality.&nbsp;</p>



<p>A strong website should describe them in clear, human language.&nbsp;</p>



<p>Every piece of information tells AI that:</p>



<ul class="wp-block-list">
<li>This business exists.</li>



<li>It serves specific needs.</li>



<li>It performs well in doing so.</li>
</ul>



<h3 class="wp-block-heading" id="h-build-reputation-where-ai-listens">Build reputation where AI listens</h3>



<p>Next, build local reputation.&nbsp;</p>



<ul class="wp-block-list">
<li>Encourage reviews on Google, TripAdvisor, and social media.&nbsp;</li>



<li>Invite local bloggers to taste and review the food.&nbsp;</li>



<li>Issue a press release about an anniversary or charity event.&nbsp;</li>
</ul>



<p>Every third-party mention adds more mutual information between your brand and the market – and that’s what AI learns from.</p>



<p>GEO is where good brand marketing meets intelligent technology.</p>



<h3 class="wp-block-heading" id="h-embrace-both-seo-and-geo">Embrace both SEO and GEO</h3>



<p>And for the “GEO is just SEO” crowd, yes, ranking on Google and in the local pack might be the best bet for increasing AI availability for this shop.&nbsp;</p>



<p>However, it might also be hosting a relaunch event and inviting 30 local bloggers and press members to secure coverage.</p>



<p>Both are valid tactics with multiple benefits – and you can do both.</p>



<p>Until Google decides what it’s doing with the 10 blue links and AI Mode, bothism is the best plan – SEO and GEO, not just one.</p>



<h2 class="wp-block-heading" id="h-from-pr-to-performance">From PR to performance</h2>



<p>Larger businesses apply the same logic at scale. The recent wave of acquisitions in the SEO and analytics sector is a testament to this.&nbsp;</p>



<ul class="wp-block-list">
<li><a href="https://searchengineland.com/semrush-acquires-search-engine-land-447555">Semrush acquiring Search Engine Land</a>.&nbsp;</li>



<li>Ahrefs buying Detailed.com.</li>



<li>Countless agencies launching their own media arms are not random expansions.</li>
</ul>



<p>These are deliberate attempts to control information ecosystems.</p>



<p>Owning media outlets, communities, and data platforms increases a company’s visibility in the information that AIs learn from.&nbsp;</p>



<p>It creates an abundance of references that confirm expertise, authoritativeness, and relevance.</p>



<p>In traditional SEO, this is referred to as off-page optimization.&nbsp;</p>



<p>In GEO, it is strategic distribution – where performance attributes and PR meet.</p>



<p>Your goal is to describe what you do, while making sure others also describe it.</p>



<p>Fame, distinctive assets, and consistency still matter. But the audience is no longer just human.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-search-citations-brand-controlled-sources-463166">AI search relies on brand-controlled sources, not Reddit: Report</a></em></strong></p>



<h2 class="wp-block-heading" id="h-building-ai-availability">Building AI availability</h2>



<p>To make your brand visible to machines that now mediate discovery, you need to understand how and where that visibility is built.</p>



<h3 class="wp-block-heading" id="h-start-with-a-visibility-audit">Start with a visibility audit</h3>



<p>Diagnose your current presence.&nbsp;</p>



<p>Identify the category entry points most relevant to your products, and ask what prompts a user might type when they are ready to buy.&nbsp;</p>



<p>Tools such as Semrush’s AI Enterprise platform can simulate these scenarios and show where your brand appears.</p>



<h3 class="wp-block-heading" id="h-get-listed-where-ai-looks">Get listed where AI looks</h3>



<p>Identify the sources that AI models reference.&nbsp;</p>



<p>Many LLMs use a mix of training data and live search, with listicles, directories, and “best of” articles among the most common data sources.</p>



<p>Being included in those lists is a sensible marketing strategy.&nbsp;</p>



<p>Just as supermarkets stock their own shelves with their best products, you should position your brand among the best available options.</p>



<h3 class="wp-block-heading" id="h-expand-your-owned-ecosystem">Expand your owned ecosystem</h3>



<p>Over time, you’ll find saturation points where every competitor appears in the same lists.&nbsp;</p>



<p>At that stage, innovation and owned media become essential.&nbsp;</p>



<p>Start your own publication, commission original research, and contribute to conversations in your category.</p>



<h3 class="wp-block-heading" id="h-create-context-that-earns-recommendations">Create context that earns recommendations</h3>



<p>Digital shelf space isn’t the problem. Credible context amplifies your fitness signals.</p>



<p>Efficient, data-led, and creative, this is GEO’s manufactured style. But its success depends entirely on having a brand worth recommending.&nbsp;</p>



<p>That’s why GEO is the outcome of proper marketing.&nbsp;</p>



<p>Still, it’s proper marketing with a specific focus: increasing the likelihood of being recommended by AI.</p>



<h2 class="wp-block-heading" id="h-the-future-of-visibility">The future of visibility</h2>



<p>SEO has always been about optimization.&nbsp;</p>



<p>GEO is about promotion – building and distributing enough credible, distinctive information about your business that an AI can recognize it as a trusted source.</p>



<p>The techniques look familiar: PR, branding, copywriting, partnerships, directories, and reviews.&nbsp;</p>



<p>The difference lies in intent. You’re not feeding a search engine – you’re training an intelligence.</p>



<p>This requires a new mindset.&nbsp;</p>



<ul class="wp-block-list">
<li>You’re no longer optimizing for human users who type short queries into Google. You’re optimizing for a probabilistic model that interprets human intent across millions of contexts.&nbsp;</li>



<li>It doesn’t care about your title tags. It cares about whether you look like the right answer to a real problem.</li>
</ul>



<p>GEO is both exciting and humbling.&nbsp;</p>



<p>It reconnects brand marketing and search after years of false division, and reminds us that while the tools evolve, the fundamentals endure.</p>



<p>You still need to be known, available, and distinctive.&nbsp;</p>



<p>And now your audience includes machines that think like humans but learn on their own terms.</p>



<h2 class="wp-block-heading" id="h-back-to-fundamentals-forward-with-ai">Back to fundamentals, forward with AI</h2>



<p>GEO is a return to marketing fundamentals seen through a new lens.&nbsp;</p>



<p>Businesses still grow by increasing availability.&nbsp;</p>



<p>Consumers still buy from the brands they notice and can easily access.&nbsp;</p>



<p>What has changed is the mediator: AI has become the primary distributor of attention.</p>



<p>Your task as a marketer is to make your brand’s performance attributes, category entry points, and distinctive assets visible in the data that AI consumes.&nbsp;</p>



<p>The goal hasn’t changed – to be chosen. Only the mechanics are new.</p>



<p>Because in the age of AI, the only brands that matter are the ones the machines remember.</p>

GEO, AI SEO, AEO – call it what you like.
The label doesn’t matter nearly as much as understanding the shift behind it.
At the center of that shift lies one idea that explains everything: AI availability – and here’s why it matters.
What is AI availability?

The idea of AI availability comes from Byron Sharp, research professor at the Ehrenberg-Bass Institute, who introduced it in a comment on one of my LinkedIn posts.
Sharp’s work underpins modern brand science and shows that growth depends on availability.
Brands grow through sales, and sales grow through two kinds of availability: mental and physical.
Mental availability refers to the likelihood of being considered in a purchasing situation.
Physical availability refers to the ease and convenience with which an item can be bought.
For years, these two principles have guided brand strategy. 
They explain why Coca-Cola invests in constant visibility and why Amazon makes every click lead to a checkout.
But in the era of generative search, there’s now a third kind of availability marketers need to understand – the likelihood that your brand or product will be recommended by an AI system when a user is ready to buy.
That is AI availability – and it changes everything.
AI as the new influencer
If you are still thinking of AI as a technology, you are already behind.
Think of it instead as the world’s most powerful influencer.
ChatGPT alone is used by about 10% of the global adult population, according to recent research from OpenAI, Harvard, and Duke. 
That makes it far more pervasive than any social media platform at a similar stage in its life cycle.
Most people do not use it to code or write poetry – they use it to make decisions. 
Nearly 80% of ChatGPT conversations, the same study found, fall into three categories: 
Practical guidance.
Seeking information.
Writing.
In other words, people are asking AI to help them decide what to do, buy, and believe. 
The study also shows that these conversations are increasingly focused on everyday decisions rather than work. 
The distinction between search, research, and conversation is collapsing.
Source: “How People Use ChatGPT,” OpenAI, Harvard University, and Duke University
The result is simple.
AI systems are now the gatekeepers of modern discovery. They decide what information to surface and which businesses appear in front of consumers.
Forget the Kardashians. Forget influencer marketing.
If you’re invisible to AI, you’re invisible to the market.
AI is the new influencer.
From keywords to fitness signals
The SEO industry has spent two decades optimizing for how humans search with keywords – but that is changing.
Large language models (LLMs) infer meaning from context, probability, and performance.
They are scanning for what we can call fitness signals – a term from network science.
Fitness describes a product or service’s inherent ability to outcompete rivals, allowing one business to dominate a market even if others started earlier or invested more.
Think of how Google overtook Yahoo. 
It wasn’t just about better search algorithms – it was a better business model built on a stronger performance attribute: relevance.
These performance attributes are what make a business fit for survival. They are the qualities that define how well you solve a problem for a customer.
AI deploys search strategies to identify which businesses solve which problems most effectively. 
Because it exists to serve human needs, those same signals determine your AI availability.
Yes, AI uses search strings, fan-out queries, and reciprocal rank fusion, among many other strategies and tactics. 
It doesn’t search like humans because it isn’t bound by the same cognitive and speed limitations.
Humans search by “satisficing.” Keywords + Page 1 rankings = good enough.
Machines operate on an industrial scale – searching, gathering, assessing, and recommending.
Dig deeper: Fame engineering: The key to generative engine optimization
The psychology of performance
To understand why this works, we turn to evolutionary psychology.
Geoffrey Miller, author of “Spent,” explained that humans have always been driven by two fundamental needs. 
We seek to display fitness indicators that enhance our status.
We chase fitness cues that increase our chances of survival or pleasure.
Consumer products have evolved to meet those needs. Luxury goods signal success. 
Convenience products signal control. Both deliver psychological reassurance.
AI works in a similar way. Its goal is to satisfy human intent. 
When someone types a complex prompt into an LLM, the AI interprets it not as a string of keywords but as a statement of need. 
It then searches its training data and live information to find the most relevant and trustworthy performance attributes that match that need.
That is why context matters so much more than content. 
You are no longer competing for blue links – you are competing for cognitive inclusion in an AI’s mental model of your category. 
Your job is to make your brand’s fitness and performance attributes unmissable to that model.
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See terms.
Category entry points and the new SEO
Category entry points are the situations, needs, and triggers that put someone in the market to buy.
In the world of GEO, these are your new keywords.
They are what users express in prompts rather than in search terms. 
“Where can I find sustainable running shoes for flat feet?” is not a keyword query – it is a buying situation.
Your strategy is to:
Understand those buying situations.
Map them to your own performance attributes.
Create enough context that AI can confidently associate your brand with the solution.
That means describing not only what you do, but how you do it, who you do it for, and why you are distinctive.
This isn’t new. It’s the same foundational brand positioning marketers have always needed.
What’s changed is that it now feeds the world’s most sophisticated recommender system.
Dig deeper: AI search is booming, but SEO is still not dead
A local example: The sandwich shop in Stoke
Imagine a small sandwich shop in Stoke. It’s not glamorous, serving sausage sandwiches, bacon rolls, and coffee. 
The owners don’t want to be influencers. They just want customers.
How does a business like this make itself visible to AI?
Turn everyday details into data signals
The first step is to make its performance attributes explicit.
What ingredients are used?
Where do they come from?
What makes the sandwiches good value?
How long has the business served the local community?
Where is it located?
What is the hygiene rating?
All these details are small signals of trust and quality. 
A strong website should describe them in clear, human language. 
Every piece of information tells AI that:
This business exists.
It serves specific needs.
It performs well in doing so.
Build reputation where AI listens
Next, build local reputation. 
Encourage reviews on Google, TripAdvisor, and social media. 
Invite local bloggers to taste and review the food. 
Issue a press release about an anniversary or charity event. 
Every third-party mention adds more mutual information between your brand and the market – and that’s what AI learns from.
GEO is where good brand marketing meets intelligent technology.
Embrace both SEO and GEO
And for the “GEO is just SEO” crowd, yes, ranking on Google and in the local pack might be the best bet for increasing AI availability for this shop. 
However, it might also be hosting a relaunch event and inviting 30 local bloggers and press members to secure coverage.
Both are valid tactics with multiple benefits – and you can do both.
Until Google decides what it’s doing with the 10 blue links and AI Mode, bothism is the best plan – SEO and GEO, not just one.
From PR to performance
Larger businesses apply the same logic at scale. The recent wave of acquisitions in the SEO and analytics sector is a testament to this. 
Semrush acquiring Search Engine Land. 
Ahrefs buying Detailed.com.
Countless agencies launching their own media arms are not random expansions.
These are deliberate attempts to control information ecosystems.
Owning media outlets, communities, and data platforms increases a company’s visibility in the information that AIs learn from. 
It creates an abundance of references that confirm expertise, authoritativeness, and relevance.
In traditional SEO, this is referred to as off-page optimization. 
In GEO, it is strategic distribution – where performance attributes and PR meet.
Your goal is to describe what you do, while making sure others also describe it.
Fame, distinctive assets, and consistency still matter. But the audience is no longer just human.
Dig deeper: AI search relies on brand-controlled sources, not Reddit: Report
Building AI availability
To make your brand visible to machines that now mediate discovery, you need to understand how and where that visibility is built.
Start with a visibility audit
Diagnose your current presence. 
Identify the category entry points most relevant to your products, and ask what prompts a user might type when they are ready to buy. 
Tools such as Semrush’s AI Enterprise platform can simulate these scenarios and show where your brand appears.
Get listed where AI looks
Identify the sources that AI models reference. 
Many LLMs use a mix of training data and live search, with listicles, directories, and “best of” articles among the most common data sources.
Being included in those lists is a sensible marketing strategy. 
Just as supermarkets stock their own shelves with their best products, you should position your brand among the best available options.
Expand your owned ecosystem
Over time, you’ll find saturation points where every competitor appears in the same lists. 
At that stage, innovation and owned media become essential. 
Start your own publication, commission original research, and contribute to conversations in your category.
Create context that earns recommendations
Digital shelf space isn’t the problem. Credible context amplifies your fitness signals.
Efficient, data-led, and creative, this is GEO’s manufactured style. But its success depends entirely on having a brand worth recommending. 
That’s why GEO is the outcome of proper marketing. 
Still, it’s proper marketing with a specific focus: increasing the likelihood of being recommended by AI.
The future of visibility
SEO has always been about optimization. 
GEO is about promotion – building and distributing enough credible, distinctive information about your business that an AI can recognize it as a trusted source.
The techniques look familiar: PR, branding, copywriting, partnerships, directories, and reviews. 
The difference lies in intent. You’re not feeding a search engine – you’re training an intelligence.
This requires a new mindset. 
You’re no longer optimizing for human users who type short queries into Google. You’re optimizing for a probabilistic model that interprets human intent across millions of contexts. 
It doesn’t care about your title tags. It cares about whether you look like the right answer to a real problem.
GEO is both exciting and humbling. 
It reconnects brand marketing and search after years of false division, and reminds us that while the tools evolve, the fundamentals endure.
You still need to be known, available, and distinctive. 
And now your audience includes machines that think like humans but learn on their own terms.
Back to fundamentals, forward with AI
GEO is a return to marketing fundamentals seen through a new lens. 
Businesses still grow by increasing availability. 
Consumers still buy from the brands they notice and can easily access. 
What has changed is the mediator: AI has become the primary distributor of attention.
Your task as a marketer is to make your brand’s performance attributes, category entry points, and distinctive assets visible in the data that AI consumes. 
The goal hasn’t changed – to be chosen. Only the mechanics are new.
Because in the age of AI, the only brands that matter are the ones the machines remember.

GEO redefines visibility through AI availability – how likely your brand is to be recognized and recommended by AI systems.

Why AI availability is the new battleground for brands

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/google-reviews-local-seo-1920.png" class="attachment-large size-large wp-post-image" alt="Google reviews local SEO" style="margin-bottom: 15px;" decoding="async" /></div>Discover how keyword-rich Google reviews can boost your local visibility, engagement, and conversions – plus templates to help you. 

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/11/google-reviews-local-seo-1920.png" class="attachment-large size-large wp-post-image" alt="Google reviews local SEO" style="margin-bottom: 15px;" decoding="async" /></div>
<p>Keywords in reviews are generally believed to help local rankings, although their impact is still actively debated within the local SEO community.</p>



<p>Regardless of where the truth on ranking impact ultimately lands, keyword-rich reviews can still provide meaningful value for local SEO beyond pure rankings.</p>



<p>Below are seven reasons why you should still encourage keyword-rich reviews.</p>



<h2 class="wp-block-heading" id="h-1-review-justifications">1. Review justifications</h2>



<p>If your reviews consistently mention a keyword related to your business, the likelihood that your Profile will get a Review justification in search increases. </p>



<p>This visibility can boost click-through rates. Higher engagement may lead to a secondary improvement in search engine rankings.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1999" height="974" src="https://searchengineland.com/wp-content/seloads/2025/11/plumbing-google-review-justifications.png" alt="Plumbing Google review justifications" class="wp-image-464429" srcset="https://searchengineland.com/wp-content/seloads/2025/11/plumbing-google-review-justifications.png 1999w, https://searchengineland.com/wp-content/seloads/2025/11/plumbing-google-review-justifications-768x374.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/plumbing-google-review-justifications-1536x748.png 1536w" sizes="(max-width: 1999px) 100vw, 1999px" /></figure>



<h2 class="wp-block-heading" id="h-2-place-topics">2. Place Topics</h2>



<p>Google creates clickable Place Topics from keywords in your reviews. These topics:</p>



<ul class="wp-block-list">
<li>Highlight your specialties.</li>



<li>Filter reviews for customers.</li>



<li>Can boost your Profile&#8217;s engagement.</li>
</ul>



<figure class="wp-block-image size-full"><img decoding="async" width="1290" height="509" src="https://searchengineland.com/wp-content/seloads/2025/11/google-place-topics.jpg" alt="Google place topics" class="wp-image-464426" srcset="https://searchengineland.com/wp-content/seloads/2025/11/google-place-topics.jpg 1290w, https://searchengineland.com/wp-content/seloads/2025/11/google-place-topics-768x303.jpg 768w" sizes="(max-width: 1290px) 100vw, 1290px" /></figure>



<h2 class="wp-block-heading" id="h-3-review-snippets">3. Review snippets</h2>



<p>Google bolds frequently mentioned terms in three review snippets on the Business Profile. This draws users searching for those terms to your Profile, hopefully increasing click-through rates.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="860" height="701" src="https://searchengineland.com/wp-content/seloads/2025/11/google-review-snippets.png" alt="Google review snippets" class="wp-image-464427" srcset="https://searchengineland.com/wp-content/seloads/2025/11/google-review-snippets.png 860w, https://searchengineland.com/wp-content/seloads/2025/11/google-review-snippets-768x626.png 768w" sizes="(max-width: 860px) 100vw, 860px" /></figure>



<h2 class="wp-block-heading" id="h-4-menu-highlights-restaurants">4. Menu Highlights (restaurants)</h2>



<p>The Menu Highlights are generated from customer reviews and photos, similar to Place Topics.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="332" height="720" src="https://searchengineland.com/wp-content/seloads/2025/11/maestro-pasta-menu.png" alt="Maestro Pasta menu" class="wp-image-464428"/></figure>



<p><a href="https://reputationarm.com/boost-your-rankings-with-menu-items-menu-highlights-reviews-and-photos/" target="_blank" rel="noopener">Recent analysis from Claudia Tomina</a> showed that:</p>



<ul class="wp-block-list">
<li>The menu highlights section impacts rankings.</li>



<li>Keywords in reviews impact the Menu Highlights section.</li>



<li>Therefore, when you get a menu highlight for a term mentioned in your reviews, you should rank better for that term.</li>
</ul>



<h2 class="wp-block-heading" id="h-5-ai-editorial-summaries">5. AI editorial summaries</h2>



<p>Google’s AI-generated business summaries pull concepts from reviews (e.g., &#8220;cozy”) to describe your business. </p>



<p>While Google&#8217;s AI summaries aren&#8217;t something you can edit, encouraging customers to include specific keywords in their reviews could influence the AI to emphasize aspects most beneficial to your business.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="923" height="1999" src="https://searchengineland.com/wp-content/seloads/2025/11/basta-pesta-ai-summary.png" alt="Basta Pesta AI summary" class="wp-image-464424" srcset="https://searchengineland.com/wp-content/seloads/2025/11/basta-pesta-ai-summary.png 923w, https://searchengineland.com/wp-content/seloads/2025/11/basta-pesta-ai-summary-768x1663.png 768w, https://searchengineland.com/wp-content/seloads/2025/11/basta-pesta-ai-summary-709x1536.png 709w" sizes="(max-width: 923px) 100vw, 923px" /></figure>



<h2 class="wp-block-heading" id="h-6-ai-review-summaries">6. AI review summaries</h2>



<p>Google&#8217;s AI generates review summaries by analyzing common sentiments and tips from customer feedback. </p>



<p>If your customers mention the right keywords in their reviews, your review summary will appear more compelling.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1290" height="966" src="https://searchengineland.com/wp-content/seloads/2025/11/google-ai-review-summaries.jpg" alt="Google AI review summaries" class="wp-image-464425" srcset="https://searchengineland.com/wp-content/seloads/2025/11/google-ai-review-summaries.jpg 1290w, https://searchengineland.com/wp-content/seloads/2025/11/google-ai-review-summaries-768x575.jpg 768w" sizes="(max-width: 1290px) 100vw, 1290px" /></figure>



<h2 class="wp-block-heading" id="h-7-ask-maps-about-this-place-feature">7. <em>Ask Maps about this place</em> feature</h2>



<p>Google is phasing out the old Q&amp;A section and replacing it with an AI-powered feature that pulls answers from customer reviews. </p>



<p>This means reviews with detailed info (and the right keywords) are more valuable than ever.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1071" height="1496" src="https://searchengineland.com/wp-content/seloads/2025/11/skyway-roofing-ask-maps-about-this-place.jpg" alt="Skyway Roofing Ask Maps about this place" class="wp-image-464430" srcset="https://searchengineland.com/wp-content/seloads/2025/11/skyway-roofing-ask-maps-about-this-place.jpg 1071w, https://searchengineland.com/wp-content/seloads/2025/11/skyway-roofing-ask-maps-about-this-place-768x1073.jpg 768w" sizes="(max-width: 1071px) 100vw, 1071px" /></figure>



<h2 class="wp-block-heading" id="h-how-do-you-get-keywords-in-your-reviews">How do you get keywords in your reviews?</h2>



<p>It does not make sense to directly ask your customers, “Can you please add <em>[keyword] </em>to your review?” It’s unnatural and weird and will leave the customer wondering what your deal is.</p>



<p>But that doesn’t mean you have no options.</p>



<p>To encourage customers to naturally include relevant keywords in their reviews, begin by upgrading your review request templates.</p>



<p>Miriam Ellis recently wrote <a href="https://whitespark.ca/blog/the-ultimate-review-request-templates-for-maximizing-the-benefits-from-reviews/" target="_blank" rel="noopener nofollow">a helpful guide</a> all about how to get keyword-rich reviews, which also includes three review request templates to make it extra easy for every business owner.</p>



<p>These templates guide customers on what to say, encouraging longer, more detailed, keyword-rich reviews — and can even prompt them to add photos to their reviews.</p>



<p>Here are three of those templates:</p>



<h3 class="wp-block-heading" id="h-scenario-1-requesting-reviews-of-specific-products"><strong>Scenario 1: Requesting reviews of specific products</strong></h3>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td>Hi [customer name],<br>I’m [your name and job title] from [company name], and I’m writing to check in with you on your purchase of [product]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]?&nbsp;<br>I’m enclosing a photo of [product] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:<br>– The features of this product that stand out most to you– What you like or dislike about it– How you’ve been using the product since you purchased it&nbsp;&nbsp;&nbsp;<br>If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.<br>[review us here link or button]<br>Sincerely,[name, job title, business]</td></tr></tbody></table></figure>



<h3 class="wp-block-heading" id="h-scenario-2-requesting-reviews-of-specific-services"><strong>Scenario 2: Requesting reviews of specific services</strong></h3>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td>Hello [customer name],<br>This is [your name and job title] from [company name], and we were so happy to [service provided]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]?&nbsp;<br>I’m enclosing a photo of [the service that was provided] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:<br>– Whether the service met your expectations– What you like/dislike about the service– How we did with our customer service&nbsp;<br>If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied, and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.<br>[review us here link or button]<br>Sincerely,[name, job title, business]</td></tr></tbody></table></figure>



<h3 class="wp-block-heading" id="h-scenario-3-requesting-reviews-when-you-re-not-sure-what-a-customer-purchased"><strong>Scenario 3: Requesting reviews when you’re not sure what a customer purchased</strong></h3>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td>Email template</td></tr><tr><td>Hello [customer name],<br>Thank you for being our customer. I’m [your name and job title] from [company name], It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]?&nbsp;<br>I’m enclosing a photo of [the business premises] for your use in your review if you don’t have your own photo, and I’d love it if you could review:<br>– Whether you found our customer service helpful– What you like/dislike about our store– Why you chose our store&nbsp;<br>If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.<br>[review us here link or button]<br>Sincerely,[name, job title, business]</td></tr></tbody></table></figure>



<h2 class="wp-block-heading" id="h-now-make-it-work-for-you">Now, make it work for you</h2>



<p>By implementing a few simple improvements in your review requests, you will receive more detailed reviews from your customers, and their enhanced feedback will provide numerous benefits.</p>



<p>You may even increase your Google rankings for additional keywords, but I can&#8217;t guarantee anything. With all the other benefits, rankings shouldn’t be your primary goal anyway.</p>


Keywords in reviews are generally believed to help local rankings, although their impact is still actively debated within the local SEO community.
Regardless of where the truth on ranking impact ultimately lands, keyword-rich reviews can still provide meaningful value for local SEO beyond pure rankings.
Below are seven reasons why you should still encourage keyword-rich reviews.
1. Review justifications
If your reviews consistently mention a keyword related to your business, the likelihood that your Profile will get a Review justification in search increases. 
This visibility can boost click-through rates. Higher engagement may lead to a secondary improvement in search engine rankings.




2. Place Topics
Google creates clickable Place Topics from keywords in your reviews. These topics:
Highlight your specialties.
Filter reviews for customers.
Can boost your Profile’s engagement.




3. Review snippets
Google bolds frequently mentioned terms in three review snippets on the Business Profile. This draws users searching for those terms to your Profile, hopefully increasing click-through rates.




4. Menu Highlights (restaurants)
The Menu Highlights are generated from customer reviews and photos, similar to Place Topics.




Recent analysis from Claudia Tomina showed that:
The menu highlights section impacts rankings.
Keywords in reviews impact the Menu Highlights section.
Therefore, when you get a menu highlight for a term mentioned in your reviews, you should rank better for that term.
5. AI editorial summaries
Google’s AI-generated business summaries pull concepts from reviews (e.g., “cozy”) to describe your business. 
While Google’s AI summaries aren’t something you can edit, encouraging customers to include specific keywords in their reviews could influence the AI to emphasize aspects most beneficial to your business.




6. AI review summaries
Google’s AI generates review summaries by analyzing common sentiments and tips from customer feedback. 
If your customers mention the right keywords in their reviews, your review summary will appear more compelling.




7. Ask Maps about this place feature
Google is phasing out the old Q&A section and replacing it with an AI-powered feature that pulls answers from customer reviews. 
This means reviews with detailed info (and the right keywords) are more valuable than ever.




How do you get keywords in your reviews?
It does not make sense to directly ask your customers, “Can you please add [keyword] to your review?” It’s unnatural and weird and will leave the customer wondering what your deal is.
But that doesn’t mean you have no options.
To encourage customers to naturally include relevant keywords in their reviews, begin by upgrading your review request templates.
Miriam Ellis recently wrote a helpful guide all about how to get keyword-rich reviews, which also includes three review request templates to make it extra easy for every business owner.
These templates guide customers on what to say, encouraging longer, more detailed, keyword-rich reviews — and can even prompt them to add photos to their reviews.
Here are three of those templates:
Scenario 1: Requesting reviews of specific products

Hi [customer name],
I’m [your name and job title] from [company name], and I’m writing to check in with you on your purchase of [product]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [product] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:
– The features of this product that stand out most to you– What you like or dislike about it– How you’ve been using the product since you purchased it   
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]





Scenario 2: Requesting reviews of specific services

Hello [customer name],
This is [your name and job title] from [company name], and we were so happy to [service provided]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [the service that was provided] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:
– Whether the service met your expectations– What you like/dislike about the service– How we did with our customer service 
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied, and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]





Scenario 3: Requesting reviews when you’re not sure what a customer purchased

Email template
Hello [customer name],
Thank you for being our customer. I’m [your name and job title] from [company name], It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [the business premises] for your use in your review if you don’t have your own photo, and I’d love it if you could review:
– Whether you found our customer service helpful– What you like/dislike about our store– Why you chose our store 
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]





Now, make it work for you
By implementing a few simple improvements in your review requests, you will receive more detailed reviews from your customers, and their enhanced feedback will provide numerous benefits.
You may even increase your Google rankings for additional keywords, but I can’t guarantee anything. With all the other benefits, rankings shouldn’t be your primary goal anyway.

Discover how keyword-rich Google reviews can boost your local visibility, engagement, and conversions – plus templates to help you.

7 local SEO wins you get from keyword-rich Google reviews

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more.png" class="attachment-large size-large wp-post-image" alt="Inside Google Ads’ AI-powered Shopping ecosystem: Performance Max, AI Max and more" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more.png 1920w, https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Advertisers will soon get deeper visibility into how each Display creative performs, enabling smarter optimization decisions.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more.png" class="attachment-large size-large wp-post-image" alt="Inside Google Ads’ AI-powered Shopping ecosystem: Performance Max, AI Max and more" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more.png 1920w, https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/06/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is rolling out asset-level reporting for Display campaigns, giving advertisers a clearer view of how individual creative assets perform — a move that brings Display closer to the visibility already seen in Performance Max campaigns.</p>



<p><strong>Why we care</strong>. Until now, Display campaign insights have been limited to overall ad performance. With this update, advertisers can analyze results at the asset level — images, headlines, descriptions — to pinpoint what’s driving engagement and what’s not. </p>



<p><strong>How it works</strong>. A new Assets tab in Google Ads will let users:</p>



<ul class="wp-block-list">
<li>Compare performance of each creative asset.</li>



<li>View when assets were last updated to track iteration history.</li>



<li>Decide which assets to keep, refresh, or remove based on data.</li>
</ul>



<p><strong>The details</strong>. A new Google support page, “About asset reporting in Display,” outlines the update with links to:</p>



<ul class="wp-block-list">
<li><em>Get started</em></li>



<li><em>How it works</em></li>



<li><em>Asset reporting for your Display campaigns</em></li>



<li><em>Evaluating asset performance</em></li>
</ul>



<p><strong>Between the lines</strong>. This upgrade mirrors reporting tools available in Performance Max, signaling Google’s continued effort to unify insights across campaign types and improve transparency in automated advertising.</p>



<p><strong>What’s next</strong>. <a href="https://support.google.com/google-ads/answer/16713821">The feature </a>hasn’t been spotted live yet, but its appearance on Google’s help center — first noticed by PPC News Feed founder Hana Kobzová — suggests a wider rollout is imminent.</p>


Google is rolling out asset-level reporting for Display campaigns, giving advertisers a clearer view of how individual creative assets perform — a move that brings Display closer to the visibility already seen in Performance Max campaigns.
Why we care. Until now, Display campaign insights have been limited to overall ad performance. With this update, advertisers can analyze results at the asset level — images, headlines, descriptions — to pinpoint what’s driving engagement and what’s not. 
How it works. A new Assets tab in Google Ads will let users:
Compare performance of each creative asset.
View when assets were last updated to track iteration history.
Decide which assets to keep, refresh, or remove based on data.
The details. A new Google support page, “About asset reporting in Display,” outlines the update with links to:
Get started
How it works
Asset reporting for your Display campaigns
Evaluating asset performance
Between the lines. This upgrade mirrors reporting tools available in Performance Max, signaling Google’s continued effort to unify insights across campaign types and improve transparency in automated advertising.
What’s next. The feature hasn’t been spotted live yet, but its appearance on Google’s help center — first noticed by PPC News Feed founder Hana Kobzová — suggests a wider rollout is imminent.

Advertisers will soon get deeper visibility into how each Display creative performs, enabling smarter optimization decisions.

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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