<div><img width="360" height="200" src="https://searchengineland.com/wp-content/seloads/2026/04/mt_360x200_smxnow_april.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" /></div>Join us May 6 for the second SMX Now, featuring Ameet Khabra on how to spot and stop PPC drift before it hurts performance.

<div><img width="360" height="200" src="https://searchengineland.com/wp-content/seloads/2026/04/mt_360x200_smxnow_april.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" /></div>
<p>Automation doesn’t fail on its own — it does exactly what it’s trained to do. The problem is that when Google Ads is fed incomplete, misaligned, or overly broad signals, it can optimize toward the wrong outcome faster than most advertisers realize.</p>



<p>In our second installment of SMX Now, our new monthly series, Ameet Khabra of Hop Skip Media will break down a real account where a 417% jump in conversions turned out to be the wrong kind of success. She’ll use that case study to explain the four key ways automation drift enters an account: signal drift, query drift, inventory drift, and creative drift.</p>



<p>You’ll leave with a practical framework for diagnosing drift early, understanding where human oversight matters most, and managing automation more deliberately so it works toward real business goals — not just platform-reported wins.</p>



<p>Join us May 6 at noon ET.</p>



<p class="has-text-align-center"><a href="https://www.bigmarker.com/third-door-media/the-automation-drift-and-how-to-correct-course?utm_bmcr_source=Editorial" type="link" id="https://www.bigmarker.com/third-door-media/the-automation-drift-and-how-to-correct-course?utm_bmcr_source=Editorial" target="_blank" rel="noopener"><strong>Save your spot</strong></a>


Automation doesn’t fail on its own — it does exactly what it’s trained to do. The problem is that when Google Ads is fed incomplete, misaligned, or overly broad signals, it can optimize toward the wrong outcome faster than most advertisers realize.
In our second installment of SMX Now, our new monthly series, Ameet Khabra of Hop Skip Media will break down a real account where a 417% jump in conversions turned out to be the wrong kind of success. She’ll use that case study to explain the four key ways automation drift enters an account: signal drift, query drift, inventory drift, and creative drift.
You’ll leave with a practical framework for diagnosing drift early, understanding where human oversight matters most, and managing automation more deliberately so it works toward real business goals — not just platform-reported wins.
Join us May 6 at noon ET.
Save your spot

Join us May 6 for the second SMX Now, featuring Ameet Khabra on how to spot and stop PPC drift before it hurts performance.

SMX Now: The automation drift and how to correct course

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Screenshot of Google Search Console" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>The data going forward should be correct but the 50 weeks or so of data in the past will not be fixed.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="Screenshot of Google Search Console" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2019/02/google-search-console-interface-ss-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google said it has &#8220;resolved&#8221; an issue with logging data within Google Search Console reporting. The logging issue happened between May 13, 2025 through April 27, 2026, about 50 weeks.  The resolution did not fix the past data, but it did fix the issue going forward.</p>



<p><strong>What Google said. </strong>Here is what Google <a href="https://support.google.com/webmasters/answer/6211453?hl=en#zippy=%2Cperformance-reports-search-results-discover-google-news">posted</a>:</p>



<p>&#8220;A logging error prevented Search Console from accurately reporting impressions from May 13, 2025 until April 27, 2026. This issue has been resolved. As a result, you may notice a decrease in impressions in the Search Console Performance report. Only impressions and related metrics &#8211; CTR and average position &#8211; were affected; clicks were not affected by the error, and this issue affected data logging only.&#8221;</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1556" height="880" src="https://searchengineland.com/wp-content/seloads/2026/05/google-data-issue-resolved-update-1777810799.png" alt="" class="wp-image-476443" srcset="https://searchengineland.com/wp-content/seloads/2026/05/google-data-issue-resolved-update-1777810799.png 1556w, https://searchengineland.com/wp-content/seloads/2026/05/google-data-issue-resolved-update-1777810799-768x434.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/google-data-issue-resolved-update-1777810799-1536x869.png 1536w" sizes="(max-width: 1556px) 100vw, 1556px" /></figure>



<p><strong>What was fixed. </strong>Just to be clear, Google has not fixed the data from May 13, 2025 through April 27, 2026 but just fixed the data going forward. So keep this in mind when reviewing the data in that date range.</p>



<p>John Mueller from Google confirmed on <a href="https://bsky.app/profile/johnmu.com/post/3mkx7smlf6c25">Bluesky</a> that this is only fixed going forward and the old data will not be fixed.</p>



<p><strong>Why we care. </strong>When reviewing your Search Console data, please note that for about 50 weeks, almost a year, the reports may be off and you may see a decrease in impressions, and thus click-through rate and average position data are also impacted.</p>


Google said it has “resolved” an issue with logging data within Google Search Console reporting. The logging issue happened between May 13, 2025 through April 27, 2026, about 50 weeks.  The resolution did not fix the past data, but it did fix the issue going forward.
What Google said. Here is what Google posted:
“A logging error prevented Search Console from accurately reporting impressions from May 13, 2025 until April 27, 2026. This issue has been resolved. As a result, you may notice a decrease in impressions in the Search Console Performance report. Only impressions and related metrics – CTR and average position – were affected; clicks were not affected by the error, and this issue affected data logging only.”




What was fixed. Just to be clear, Google has not fixed the data from May 13, 2025 through April 27, 2026 but just fixed the data going forward. So keep this in mind when reviewing the data in that date range.
John Mueller from Google confirmed on Bluesky that this is only fixed going forward and the old data will not be fixed.
Why we care. When reviewing your Search Console data, please note that for about 50 weeks, almost a year, the reports may be off and you may see a decrease in impressions, and thus click-through rate and average position data are also impacted.

The data going forward should be correct but the 50 weeks or so of data in the past will not be fixed.

Google fixes Search Console’s year-long data logging issue – well, kind of…

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Why-brand-authority-beats-topical-authority-in-AI-search.png" class="attachment-large size-large wp-post-image" alt="Why brand authority beats topical authority in AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Why-brand-authority-beats-topical-authority-in-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Why-brand-authority-beats-topical-authority-in-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Why-brand-authority-beats-topical-authority-in-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Why-brand-authority-beats-topical-authority-in-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>More content won’t make you an authority. AI search rewards brands with visibility, mentions, and real demand.


There’s a fundamental battle happening in search right now.
On one side is topical authority — the darling phrase of every SEO consultant who needs to sell more content. 
On the other is brand authority — something marketers have talked about for decades, while much of search treated it as optional, vague, or something the brand team could handle after the sitemap was fixed.
Now AI has walked into the room, kicked over the furniture, eaten half the traffic, and exposed the real problem. 
Search still matters. The global economy runs on people looking, comparing, buying, and solving problems through it. But the industry has a marketing problem.
And it shows. Too many SEOs have lost the plot on why people choose, remember, trust, search for, recommend, and buy from brands. AI search is making that ignorance harder to hide. That’s why brand authority wins — but not in the way most SEO dashboards suggest.
Topical authority was never supposed to mean content landfill
Before we get to AI, we need to define what topical authority was meant to be. At its best, it’s simple. 
You publish useful work, create evidence, and share expertise. Others cite you, journalists mention you, communities discuss you, and customers search for you. Over time, your brand becomes associated with the topic. That’s authority. It’s also brand building.
The problem is that much of the SEO industry hasn’t sold it that way. In practice, topical authority became a convenient commercial wrapper for content production.
SEO retainers were built around three pillars: technical, content, and links. Technical SEO became more specialized. Links were outsourced, packaged, renamed, earned through digital PR, or bought in one way or another. 
Content, meanwhile, remained the dependable agency engine — easy to sell, scope, and report. Think 4-8 blog posts a month, a topical map, a content hub, a cluster, a pillar page, and another 2,000 words on something nobody asked to read.
This wasn’t always wrong. In the pre-AI search world, content had real labor behind it. A decent article required research, writing, editing, optimization, internal linking, and promotion. That work had value. Good content could rank, attract links, build email lists, support commercial pages, and create some advertising effect through exposure.
Back in the day, we built what were often called power pages — strategic assets designed to earn links, rank, get shared, and pass equity to commercial pages. They had a purpose. They weren’t created just because the spreadsheet had another empty cell.
Topical authority changed that logic. It turned “let’s create something worth citing” into “let’s cover every possible keyword in the topic map and hope Google mistakes volume for expertise.” That was the original sin.
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Authority is what others say about you
Authority isn’t created by what you publish on your own site. It’s created when you become a recognized source.
Former Google engineer Jun Wu described this in terms of “mention information” — how search engines analyze natural language, identify topic phrases and sources, cluster related terms, and map associations between sources and topics. 
In plain English, they can recognize when certain brands, people, domains, and entities are repeatedly mentioned in relation to specific topics.
Today, SEOs call that brand co-occurrence. The idea isn’t new. When authoritative sites, journalists, communities, reviewers, experts, and customers consistently mention your brand in relation to a topic, you become associated with it — not because you published hundreds of near-identical articles, but because the wider web treats you as relevant.
Topical coverage is what you say about yourself. Authority is what the market says about you. AI search makes that difference hard to ignore.
The smash burger test
Suppose you want to become an authority in the smash burger industry. You probably don’t, but some topical authority consultant calling themselves a “semantic SEO” is likely pitching it to a fast food brand right now.
An SEO version of topical authority would probably begin with a map:
What is a smash burger?
Best meat for smash burgers.
History of smash burgers.
Smash burger recipes.
Smash burger toppings.
Smash burger glossary.
Best smash burger restaurants.
How to make a smash burger at home.
There’s nothing inherently wrong with that. If you run a serious smash burger publication, restaurant group, food brand, or equipment business, some of it might be useful. But authority doesn’t come from publishing those pages.
Real authority looks different. You create original data on the fastest-growing smash burger chains. You publish an index of the best-rated smash burger restaurants in the U.S. and U.K. You interview chefs, test meat blends, and produce videos people actually watch. 
You become a source journalists use when covering the category. Food creators reference your data. Restaurant owners subscribe to your newsletter. People search for your brand plus “smash burger report.”
That’s topical authority. It’s also brand authority.
The thin SEO version is publishing thousands of keyword pages and internally linking them until your CMS starts begging for death. The real version is becoming known.
AI has broken the old content economics
The old commercial defense of topical authority was traffic.
Brands didn’t hire search marketers because they had a deep spiritual yearning to become encyclopedias. They hired them for organic revenue growth — to appear when customers searched, and to drive clicks, leads, and sales.
Informational content was sold, in part, as advertising. Someone searches a question, lands on your article, and sees your brand. Maybe they join your email list, return later, or buy.
That model was always more fragile than the industry admitted. Most users don’t sit around thinking about your B2B SaaS platform, your dog food brand, or your running shoe category page. 
Ask someone to name 10 toothpaste brands, and they’ll struggle, despite a lifetime of exposure. Ask them to recall the last ten TikToks they watched, and watch their face collapse.
Advertising works through memory structures, distinctive assets, repeated exposure, and relevance. A single accidental visit to a generic “what is” article was never the brand-building miracle some content marketers claimed.
Now AI has made the economics worse. For many informational searches, answers are increasingly synthesized before the click. From the user’s point of view, that’s often a better experience.
My dad is in his 70s. He loves AI Overviews. He doesn’t want to click through three ad-infested recipe pages, dodge newsletter popups, reject cookies, scroll past a life story, and finally find how long to boil an egg. He wants the answer.
Users aren’t mourning your lost organic session. They’re getting on with their lives. That’s the uncomfortable truth.
If the click disappears, much of the supposed advertising effect of informational content disappears with it — no logo exposure, no distinctive assets, no remarketing pixel, no email capture, and no carefully designed journey. Just your content absorbed into a synthesized answer, and maybe a small source link on the side.
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AI citations aren’t the same as human citations
This brings us to another emerging industry obsession: AI citations. 
The small source boxes in ChatGPT, Gemini, Perplexity, AI Overviews, and other AI search experiences are being treated as the new holy metric. Agencies, tools, and consultants are already building around it.
The SEO industry loves a single metric — domain authority, traffic, keyword positions, share of voice, and now AI visibility. The problem is that an AI citation isn’t the same as a human citation.
An AI citation is often a helpful link — a reference, a retrieval artifact. It’s directionally useful. It can show what sources a system uses to support an answer, and whether your content is accessible, relevant, and being surfaced in certain contexts.
But it’s not the same as:
A journalist choosing to cite your research. 
A customer recommending you in a forum.
A creator reviewing your product.
A trade publication naming your brand as an expert source.
Human citations are evidence of market recognition. AI citations are evidence of machine retrieval. Don’t confuse the two.
The goal isn’t to be scraped. It’s to be recommended.
Brand search is the cleaner signal
If you want a better proxy for whether your authority is growing, look at brand search.
People search for brands they know, are considering, have bought from, or were recommended. Brand search isn’t perfect, but it’s much closer to commercial reality than counting how often a chatbot footnotes your blog post.
That’s why share of search matters. It gives you a directional view of market demand and mental availability. If more people are searching for your brand relative to competitors, something is happening. Your advertising, PR, product, reviews, word of mouth, content, partnerships, social presence, and customer experience are creating demand.
This is where the “but this is just SEO” crowd starts clearing its throat.
It’s not “just SEO.” Or rather, it’s only SEO if you define it so broadly that it includes every activity that might influence a search result. That’s strategic ambiguity. It lets everyone claim they were doing the future all along.
Most SEO retainers weren’t building brand fame. They were producing content, fixing technical issues, buying or earning links, and reporting rankings. Sometimes it worked — sometimes very well. But the average topical authority strategy wasn’t a sophisticated brand visibility program.
Traditional SEO still matters
None of this means you abandon traditional SEO. Buyer-intent rankings, category pages, product pages, local pages, technical SEO, internal linking, structured data, reviews, and crawlability matter. 
Search still works as a shelf. Many brands are discovered for the first time in supermarkets. The same is true in Google. If someone searches “emergency locksmith near me,” “best trail running shoes,” or “meeting intelligence software,” you want to appear.
Being found still matters, but it’s not the same as being recommended. Traditional SEO helps you get found, while brand authority drives recommendation. 
AI search shifts the balance toward the latter, synthesizing options, reducing uncertainty, and often naming brands, products, and solutions directly.
The new job is meaningful visibility
Semrush accidentally said the quiet part out loud with its April Fools’ “Brand Visibility Expert” stunt, where employees changed their titles on LinkedIn. It was a joke, but not entirely. 
The company later described AI visibility tools that track brand visibility, mentions, prompts, perception, and competitor presence in AI search. That’s where the market is going.
The future of search marketing isn’t just search engine optimization. It’s brand visibility across the network.
That means increasing meaningful visibility in the places where humans and AI systems encounter information: 
Search engines.
AI answers.
Review sites.
Communities.
YouTube. 
Reddit.
Trade media.
News sites.
Podcasts.
Influencers.
Comparison pages.
Customer reviews.
Social platforms.
Partner ecosystems.
Your own site.
The web is now the surface, and your website is just one part of it. This is the shift many SEOs don’t want to face. Many are used to optimizing owned pages for search engines. 
The next era is about optimizing a brand’s presence across the web. That requires different work.
Start with positioning
If you want to build brand authority in AI, start with positioning.
Who are you for?
What problem do you solve?
How do you solve it better?
What should the market associate with you?
What proof supports that claim?
These aren’t fluffy brand questions. They’re search questions now.
A locksmith isn’t only an emergency locksmith. They may install commercial locks, repair window locks, replace garage locks, secure doors, and provide security advice. 
A running shoe retailer may want to be known for trail running expertise, fast delivery, wide range, gait analysis, competitive pricing, or specialist advice. 
A SaaS platform may want to be known for extracting meeting intelligence that helps sales teams improve conversion.
These are performance attributes — the reasons people choose you. Your search strategy should reinforce them.
If your pet food brand specializes in sensitive stomachs, you need to be visible around dog dietary problems — not just on your blog, but in vet commentary, buyer guides, reviews, creator content, journalist coverage, customer stories, comparison pages, and data studies. 
These are the places where humans and AI systems learn what’s credible. That’s brand authority.
Create things worth being cited by humans
The rule for AI-era content is simple. Every piece of content should have real-world marketing value at publish.
If one person encounters it, they should understand your brand better, feel more positively about it, remember something useful, or be more likely to trust you.
If content only makes sense as an SEO asset after it ranks, it’s probably weak.
This means you stop creating “dead” content. Instead:
Create original research. 
Publish category data. 
Build useful tools. 
Share expert commentary. 
Produce strong product comparisons. 
Release reports journalists can cite. 
Create opinionated guides. 
Review products properly. 
Explain problems better than competitors. 
Make videos people want to watch. 
Turn internal data into public insight. 
Build assets that earn links and mentions.
Do fewer things. Make them better. Promote them harder.
Brands have limited budgets — smaller ones have even less room for waste. Spending thousands on a content library that repeats known information may be less effective than using the same budget to create one excellent data study, seed it with journalists, get creators talking, earn reviews, improve product pages, and run ads that make people search for your brand.
Ask yourself, “What use of this budget is most likely to increase brand search, links, mentions, reviews, and recommendations?”
Fitness times visibility equals success
A useful idea from network science applies here: success is driven by fitness multiplied by visibility.
Fitness is your ability to outperform alternatives — product, service, price, expertise, speed, range, design, convenience, proof, reviews, and customer experience.
Visibility is how often and how meaningfully the market encounters those signals.
Fitness without visibility is a brilliant brand nobody knows. Visibility without fitness is hype — and it usually collapses. 
That’s how preferential attachment starts. Brands that are talked about get talked about more. Brands that are searched get searched more. Brands that earn links earn more links. Brands that become default sources are cited more often. Brands that sell more get more reviews, more mentions, more data, and more presence.
AI accelerates this dynamic, consuming the web faster than humans and reinforcing those signals at scale. If your brand has dense, consistent, and credible associations with the problems you solve, you reduce uncertainty that you’re a good recommendation.
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What actually wins in AI search
Brand authority wins in AI — because real topical authority was always brand authority.
The version of topical authority that deserves to survive is the one where a brand becomes a genuine source in its category — creating useful information, earning mentions, building demand, getting searched, getting cited, and becoming associated with the problems it solves.
The version that deserves to die is the one where a brand publishes endless keyword-targeted sludge and calls the result authority.
AI hasn’t killed SEO. It’s killed the illusion that mediocrity deserves traffic.
The search marketers who win next won’t be the ones who publish the most. They’ll be the ones who make brands more meaningfully visible across the internet. They’ll understand positioning, PR, content, technical SEO, reviews, creators, category demand, links, mentions, and brand search as one connected system.
The goal isn’t to optimize for search engines, but for the network they use to understand the world.
Build the brand. Make it visible. Make it worth recommending. Everything else is just content with delusions of grandeur.

More content won’t make you an authority. AI search rewards brands with visibility, mentions, and real demand.

Why brand authority beats topical authority in AI search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now.png" class="attachment-large size-large wp-post-image" alt="Tools for doing AEO right now" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>From AI assistants to analytics platforms, here’s how to use today’s tools to understand and work on your visibility in AI answers.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now.png" class="attachment-large size-large wp-post-image" alt="Tools for doing AEO right now" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Tools-for-doing-AEO-right-now-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The other day, I was putting together my version of a Lumascape of <a href="https://searchengineland.com/answer-engine-optimization-ai-models-453509">answer engine optimization</a> (AEO) tools — I’m kidding, my computer doesn’t have that kind of bandwidth.</p>



<p>Instead of mapping every tool — which would be outdated in minutes — I’m focusing on the ones I actually use to grow clients’ AI search presence.</p>



<p>This is a deliberately short list: four tools I rely on, plus three I’m testing before adding them to my team’s stack.</p>



<h2 class="wp-block-heading" id="h-1-ai-assistants-chatgpt-claude-perplexity">1. AI assistants (ChatGPT, Claude, Perplexity)</h2>



<p>Used thoughtfully, large language model (LLM) assistants are research and analysis tools in their own right. For AEO work specifically, they serve several distinct purposes:&nbsp;</p>



<ul class="wp-block-list">
<li>Competitive landscape research.</li>



<li>Content gap analysis.</li>



<li>Prompt testing.</li>



<li>Entity and topical coverage audits.</li>



<li>Structured content drafting. </li>
</ul>



<p>The key distinction from passive use is intentionality — using these tools with a defined AEO research methodology rather than ad hoc.</p>



<h3 class="wp-block-heading" id="h-why-they-re-essential">Why they’re essential</h3>



<p>AEO requires a fundamental understanding of how AI systems process and represent information. The most direct way to develop that understanding is to work regularly and analytically within those systems.&nbsp;</p>



<p>Querying AI assistants with the same prompts your target audience uses — and carefully analyzing what they return, what sources they cite, what entities they associate, and how they structure answers — gives you peerless ground-level intelligence.</p>



<h3 class="wp-block-heading" id="h-competitive-strengths">Competitive strengths</h3>



<p>Each platform has its own strengths worth noting:</p>



<ul class="wp-block-list">
<li>ChatGPT is widely used and offers broad general knowledge synthesis, making it useful for understanding how mainstream AI handles queries in your category.</li>



<li>Claude tends toward more nuanced, caveated responses and is strong for analytical tasks.</li>



<li>Perplexity is citation-heavy by design and particularly valuable for AEO research precisely because it surfaces its sources explicitly. You can see in real time which domains are being pulled and why.</li>
</ul>



<h3 class="wp-block-heading" id="h-what-you-can-t-do-without-them">What you can’t do without them</h3>



<p>Firsthand research on your brand’s current AEO status, which includes:</p>



<ul class="wp-block-list">
<li><strong>Manual prompt testing</strong>: See how your brand and content are being represented.</li>



<li><strong>Competitive research:</strong> Query AI systems with category-level questions to see which competitors appear and how they are framed.</li>



<li><strong>Topical gap analysis:</strong> Identify questions AI systems answer where your brand is absent.</li>



<li><strong>Structural content analysis:</strong> Understanding the answer formats (lists, definitions, comparisons, how-tos) that AI systems prefer for your query types.</li>
</ul>



<h3 class="wp-block-heading" id="h-caveats">Caveats</h3>



<p>AI assistant outputs are non-deterministic and vary by platform, model version, session context, and even time of day. Manual prompt testing is qualitative and difficult to scale. These tools are best used to build intuition and generate hypotheses, which should then be validated with quantitative data from platforms like Profound.&nbsp;</p>



<p>Also worth noting: querying AI systems for competitive research can quickly become a rabbit hole, so before you truly dig in, build a structured testing framework and stick to it.</p>



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<h2 class="wp-block-heading" id="h-2-profound-nbsp">2. Profound&nbsp;</h2>



<p>Profound is purpose-built AEO intelligence that monitors how AI platforms (ChatGPT, Perplexity, Google AI Overviews, Claude, etc.) discover, surface, and cite your brand and content.&nbsp;</p>



<p>It also tracks brand mention frequency and sentiment, competitors’ share of voice, and the specific prompts or query types that trigger your content to appear in AI-generated answers.</p>



<h3 class="wp-block-heading" id="h-why-it-s-essential">Why it’s essential</h3>



<p>If you want to understand where your brand stands in the AI answer ecosystem, it’s currently the most direct way to get that data. It shifts the question from “where do we rank?” to “when AI answers a question in our category, are we in the answer?”</p>



<h3 class="wp-block-heading" id="h-competitive-strengths-0">Competitive strengths</h3>



<p>The cross-platform coverage is the tool’s most distinctive feature. Rather than measuring a single AI engine in isolation, it provides a comparative view across the major platforms simultaneously. The competitive benchmarking functionality is particularly useful: you can see both your own AI citation share and how it stacks up against named competitors. It’s the kind of context that transforms data into strategy.</p>



<h3 class="wp-block-heading" id="h-what-you-can-t-do-without-it">What you can’t do without it</h3>



<p>Some fundamental capabilities, like:</p>



<ul class="wp-block-list">
<li>Quantifying your brand’s presence in AI-generated answers at scale.</li>



<li>Tracking citation share over time and across platforms.</li>



<li>Identifying which content types and topics drive AI mentions — and which competitors are winning the queries you’re losing.</li>
</ul>



<p>It’s a pretty expensive tool. If you want to justify the expense to your C-suite, tell them, “This will show us exactly where we’re losing to {most hated competitor}.”</p>



<h3 class="wp-block-heading" id="h-caveats-0">Caveats</h3>



<p>The tool is evolving quickly, which it needs to do as the AEO landscape morphs in real time. The data it surfaces reflects AI outputs at the time the query is made. Outputs are inherently variable because AI systems don’t return the same answer to the same prompt every time.</p>



<p>Treat metrics as directional signals and trend data rather than precise, static rankings. It also won’t tell you why you’re being cited or not. That’s on you and your team to analyze.</p>



<h2 class="wp-block-heading" id="h-3-google-trends-and-google-keyword-planner">3. Google Trends and Google Keyword Planner</h2>



<p>Google Trends tracks the relative search interest for queries over time, across geographies, and in comparison to related terms. Google Keyword Planner provides search volume estimates and demand forecasting, originally designed for paid search planning but equally useful for organic and AEO strategy.</p>



<h3 class="wp-block-heading" id="h-why-they-re-essential-0">Why they’re essential</h3>



<p>AEO strategy lives and dies by understanding demand signals. Before optimizing content to appear in AI answers, you need to know what questions people are actually asking, how that demand is trending, and whether the topic has enough volume to warrant investment.&nbsp;</p>



<p>Google’s tools remain the most reliable source of this data at scale — and crucially, they reflect the same underlying search behavior that feeds into AI engine training data and query patterns.</p>



<h3 class="wp-block-heading" id="h-competitive-strengths-1">Competitive strengths</h3>



<p>Google Trends is uniquely powerful for directional trend analysis. It doesn’t give you absolute volume, but it gives you relative momentum — which is often more strategically valuable when you’re trying to anticipate where audience interest is heading rather than just where it has been.</p>



<p>For AEO specifically, rising query trends can signal emerging answer opportunities for you to address before your competitors do.&nbsp;</p>



<p>In my experience, Keyword Planner’s forecasting features are underused. They can help you prioritize content investment based on projected demand rather than historical data alone.</p>



<h3 class="wp-block-heading" id="h-what-you-can-t-do-without-them-0">What you can’t do without them</h3>



<p>Build a truly dynamic AEO strategy in which you:</p>



<ul class="wp-block-list">
<li>Understand whether demand for a topic is growing, stable, or declining before building content around it.</li>



<li>Identify seasonal patterns that should shape content publishing calendars.</li>



<li>Surface related queries and rising breakout terms that expand your AEO content coverage.</li>



<li>Validate whether a topic has enough search demand to justify the content investment.</li>
</ul>



<h3 class="wp-block-heading" id="h-caveats-1">Caveats</h3>



<p>As you probably noticed when I recommended those tools, neither reflects AI-native query behavior directly. They measure traditional search, not prompts submitted to ChatGPT or Perplexity.&nbsp;</p>



<p>As information-seeking behavior shifts toward AI interfaces, these tools will increasingly undercount true demand. Use them as a strong proxy and directional guide, not as a complete picture.</p>



<p>Worth noting: Keyword Planner also requires an active Google Ads account, and volume estimates in low-competition or niche categories can be imprecise.</p>



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<h2 class="wp-block-heading" id="h-4-google-search-console-and-google-analytics">4. Google Search Console and Google Analytics</h2>



<p><a href="https://searchengineland.com/google-search-console-seo-guide-443942">Google Search Console</a> (GSC) provides direct data on how your site performs in Google Search: which queries trigger impressions, click-through rates, average positions, and indexing status.&nbsp;</p>



<p><a href="https://searchengineland.com/guide/how-to-use-google-analytics-4">Google Analytics 4</a> (GA4) tracks on-site behavior — how users arrive, what they do, how long they stay, and where they exit — including referral traffic sources that reveal whether visitors are arriving from AI-adjacent platforms.</p>



<h3 class="wp-block-heading" id="h-why-they-re-essential-1">Why they’re essential</h3>



<p>For AEO practitioners, these tools serve critical diagnostic functions.</p>



<p>GSC tells you whether the content you’re optimizing for AI citation is also performing in traditional search, which matters because Google AI Overviews and traditional organic results draw from overlapping content pools.</p>



<p>GA4’s referral traffic data is increasingly important for detecting direct traffic from AI platforms: as users click through citations in tools like Perplexity or ChatGPT’s browsing mode, that activity shows up as referral or direct traffic. That’s worth segmenting and monitoring, even if, given the scorching rise of zero-click activity, it paints a very incomplete picture of your AEO impact.</p>



<h3 class="wp-block-heading" id="h-competitive-strengths-nbsp">Competitive strengths&nbsp;</h3>



<p>GSC’s query data is irreplaceable. No third-party tool has access to the same level of Google-sourced search performance data. The ability to see exactly which queries are driving impressions (even without clicks) is foundational for identifying content that has topical authority but may not be converting visibility into AI citations.&nbsp;</p>



<p>GA4’s cross-channel attribution and audience analysis capabilities help you understand where AEO-driven traffic comes from and what that traffic does when it arrives — which is the commercial case for the discipline.</p>



<h3 class="wp-block-heading" id="h-what-you-can-t-do-without-them-1">What you can’t do without them</h3>



<p>Develop a true understanding of AEO business impact — and AEO blockers — by:</p>



<ul class="wp-block-list">
<li>Measuring whether your AEO content investments translate into actual traffic and engagement.</li>



<li>Identifying content with high impression share but low CTR — a common signal of AI Overview cannibalization.</li>



<li>Monitoring referral traffic from AI platforms as that ecosystem matures.</li>



<li>Diagnosing indexing or crawlability issues that prevent AI systems from accessing your content.</li>
</ul>



<h3 class="wp-block-heading" id="h-caveats-2">Caveats</h3>



<p>GSC data has well-documented limitations: it samples at scale, attribution can be murky, and data is typically available with a 48-72 hour lag. Critically, it only reflects Google. It tells you nothing about how you perform in Bing-powered AI search or standalone AI platforms.&nbsp;</p>



<p>GA4 still has UX rough edges, so you’ll need to confirm that your event tracking and conversion configuration is solid before drawing strategic conclusions from the data.</p>



<h2 class="wp-block-heading" id="h-rapid-fire-roundup-nbsp">Rapid-fire roundup&nbsp;</h2>



<p>That shortlist leaves, oh, thousands of tools left to consider. I recommend putting these on your radar and testing them to gauge their value as the AEO ecosystem develops.</p>



<h3 class="wp-block-heading" id="h-5-ai-trust-signals">5. AI Trust Signals</h3>



<p>AI Trust Signals focuses on the credibility and trustworthiness signals that influence whether AI systems choose to cite a source. </p>



<p>This is an emerging and underexplored dimension of AEO: it goes upstream from content relevance and helps brands understand whether an AI system “trusts” a domain enough to surface it as an authoritative reference. It’s worth monitoring as the understanding of AI citation mechanics matures.</p>



<h3 class="wp-block-heading" id="h-6-ahrefs">6. Ahrefs</h3>



<p>Ahrefs is a mature SEO platform with deep backlink analysis, content gap tooling, site auditing, and keyword research capabilities.&nbsp;</p>



<p>Its relevance to AEO is primarily indirect, but it’s significant: authority signals, including referring domain quality and topical authority depth, are widely believed to influence AI citation likelihood. Ahrefs is a benchmark tool for understanding and building that authority infrastructure.</p>



<p>Its Content Explorer is also a practical tool for identifying high-performing content in your category that AI systems are likely to draw from.</p>



<h3 class="wp-block-heading" id="h-7-roadway-ai">7. Roadway AI</h3>



<p>Roadway AI positions itself as an AI-native platform with a focus on scaling growth marketing activities. Where it helps is building agents that can help attribute AEO signals into revenue, so you can better understand impact.&nbsp;</p>



<p>As a newer entrant, it’s worth evaluating as part of a toolkit audit, especially if you’re looking for tooling built specifically for AEO use cases. The category is moving fast, and platforms like Roadway AI may gain significant mindshare within 12 months, which also means more competitors are coming soon.</p>



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<h2 class="wp-block-heading" id="h-the-reality-of-aeo-tools-fast-moving-and-imperfect">The reality of AEO tools: Fast-moving and imperfect</h2>



<p>AEO tooling is still catching up to AEO as a discipline, which will likely be the dynamic for the next few years, at least. </p>



<p>Everything is changing so fast, and AI-driven discovery is evolving as users adopt new behaviors that vary by vertical. What matters is consistently applied measurement, strong analysis, and testing that lead to actionable insights.</p>



<p>You won’t get your setup perfect. Like much of marketing, solidly directional is probably as good as you’re going to get. With any tool, if you can explain and measure how it improves your AEO efforts, that’s a great start.&nbsp;</p>



<p>Before you sign any contracts, see if you can find an industry colleague with real-life experience using the tool, and ask them for their take. Unless they’re staunch advocates, chances are you can either find an alternative that does the same thing better or cheaper, or you can wait another month for one to emerge.</p>

The other day, I was putting together my version of a Lumascape of answer engine optimization (AEO) tools — I’m kidding, my computer doesn’t have that kind of bandwidth.
Instead of mapping every tool — which would be outdated in minutes — I’m focusing on the ones I actually use to grow clients’ AI search presence.
This is a deliberately short list: four tools I rely on, plus three I’m testing before adding them to my team’s stack.
1. AI assistants (ChatGPT, Claude, Perplexity)
Used thoughtfully, large language model (LLM) assistants are research and analysis tools in their own right. For AEO work specifically, they serve several distinct purposes: 
Competitive landscape research.
Content gap analysis.
Prompt testing.
Entity and topical coverage audits.
Structured content drafting. 
The key distinction from passive use is intentionality — using these tools with a defined AEO research methodology rather than ad hoc.
Why they’re essential
AEO requires a fundamental understanding of how AI systems process and represent information. The most direct way to develop that understanding is to work regularly and analytically within those systems. 
Querying AI assistants with the same prompts your target audience uses — and carefully analyzing what they return, what sources they cite, what entities they associate, and how they structure answers — gives you peerless ground-level intelligence.
Competitive strengths
Each platform has its own strengths worth noting:
ChatGPT is widely used and offers broad general knowledge synthesis, making it useful for understanding how mainstream AI handles queries in your category.
Claude tends toward more nuanced, caveated responses and is strong for analytical tasks.
Perplexity is citation-heavy by design and particularly valuable for AEO research precisely because it surfaces its sources explicitly. You can see in real time which domains are being pulled and why.
What you can’t do without them
Firsthand research on your brand’s current AEO status, which includes:
Manual prompt testing: See how your brand and content are being represented.
Competitive research: Query AI systems with category-level questions to see which competitors appear and how they are framed.
Topical gap analysis: Identify questions AI systems answer where your brand is absent.
Structural content analysis: Understanding the answer formats (lists, definitions, comparisons, how-tos) that AI systems prefer for your query types.
Caveats
AI assistant outputs are non-deterministic and vary by platform, model version, session context, and even time of day. Manual prompt testing is qualitative and difficult to scale. These tools are best used to build intuition and generate hypotheses, which should then be validated with quantitative data from platforms like Profound. 
Also worth noting: querying AI systems for competitive research can quickly become a rabbit hole, so before you truly dig in, build a structured testing framework and stick to it.
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2. Profound 
Profound is purpose-built AEO intelligence that monitors how AI platforms (ChatGPT, Perplexity, Google AI Overviews, Claude, etc.) discover, surface, and cite your brand and content. 
It also tracks brand mention frequency and sentiment, competitors’ share of voice, and the specific prompts or query types that trigger your content to appear in AI-generated answers.
Why it’s essential
If you want to understand where your brand stands in the AI answer ecosystem, it’s currently the most direct way to get that data. It shifts the question from “where do we rank?” to “when AI answers a question in our category, are we in the answer?”
Competitive strengths
The cross-platform coverage is the tool’s most distinctive feature. Rather than measuring a single AI engine in isolation, it provides a comparative view across the major platforms simultaneously. The competitive benchmarking functionality is particularly useful: you can see both your own AI citation share and how it stacks up against named competitors. It’s the kind of context that transforms data into strategy.
What you can’t do without it
Some fundamental capabilities, like:
Quantifying your brand’s presence in AI-generated answers at scale.
Tracking citation share over time and across platforms.
Identifying which content types and topics drive AI mentions — and which competitors are winning the queries you’re losing.
It’s a pretty expensive tool. If you want to justify the expense to your C-suite, tell them, “This will show us exactly where we’re losing to {most hated competitor}.”
Caveats
The tool is evolving quickly, which it needs to do as the AEO landscape morphs in real time. The data it surfaces reflects AI outputs at the time the query is made. Outputs are inherently variable because AI systems don’t return the same answer to the same prompt every time.
Treat metrics as directional signals and trend data rather than precise, static rankings. It also won’t tell you why you’re being cited or not. That’s on you and your team to analyze.
3. Google Trends and Google Keyword Planner
Google Trends tracks the relative search interest for queries over time, across geographies, and in comparison to related terms. Google Keyword Planner provides search volume estimates and demand forecasting, originally designed for paid search planning but equally useful for organic and AEO strategy.
Why they’re essential
AEO strategy lives and dies by understanding demand signals. Before optimizing content to appear in AI answers, you need to know what questions people are actually asking, how that demand is trending, and whether the topic has enough volume to warrant investment. 
Google’s tools remain the most reliable source of this data at scale — and crucially, they reflect the same underlying search behavior that feeds into AI engine training data and query patterns.
Competitive strengths
Google Trends is uniquely powerful for directional trend analysis. It doesn’t give you absolute volume, but it gives you relative momentum — which is often more strategically valuable when you’re trying to anticipate where audience interest is heading rather than just where it has been.
For AEO specifically, rising query trends can signal emerging answer opportunities for you to address before your competitors do. 
In my experience, Keyword Planner’s forecasting features are underused. They can help you prioritize content investment based on projected demand rather than historical data alone.
What you can’t do without them
Build a truly dynamic AEO strategy in which you:
Understand whether demand for a topic is growing, stable, or declining before building content around it.
Identify seasonal patterns that should shape content publishing calendars.
Surface related queries and rising breakout terms that expand your AEO content coverage.
Validate whether a topic has enough search demand to justify the content investment.
Caveats
As you probably noticed when I recommended those tools, neither reflects AI-native query behavior directly. They measure traditional search, not prompts submitted to ChatGPT or Perplexity. 
As information-seeking behavior shifts toward AI interfaces, these tools will increasingly undercount true demand. Use them as a strong proxy and directional guide, not as a complete picture.
Worth noting: Keyword Planner also requires an active Google Ads account, and volume estimates in low-competition or niche categories can be imprecise.
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4. Google Search Console and Google Analytics
Google Search Console (GSC) provides direct data on how your site performs in Google Search: which queries trigger impressions, click-through rates, average positions, and indexing status. 
Google Analytics 4 (GA4) tracks on-site behavior — how users arrive, what they do, how long they stay, and where they exit — including referral traffic sources that reveal whether visitors are arriving from AI-adjacent platforms.
Why they’re essential
For AEO practitioners, these tools serve critical diagnostic functions.
GSC tells you whether the content you’re optimizing for AI citation is also performing in traditional search, which matters because Google AI Overviews and traditional organic results draw from overlapping content pools.
GA4’s referral traffic data is increasingly important for detecting direct traffic from AI platforms: as users click through citations in tools like Perplexity or ChatGPT’s browsing mode, that activity shows up as referral or direct traffic. That’s worth segmenting and monitoring, even if, given the scorching rise of zero-click activity, it paints a very incomplete picture of your AEO impact.
Competitive strengths 
GSC’s query data is irreplaceable. No third-party tool has access to the same level of Google-sourced search performance data. The ability to see exactly which queries are driving impressions (even without clicks) is foundational for identifying content that has topical authority but may not be converting visibility into AI citations. 
GA4’s cross-channel attribution and audience analysis capabilities help you understand where AEO-driven traffic comes from and what that traffic does when it arrives — which is the commercial case for the discipline.
What you can’t do without them
Develop a true understanding of AEO business impact — and AEO blockers — by:
Measuring whether your AEO content investments translate into actual traffic and engagement.
Identifying content with high impression share but low CTR — a common signal of AI Overview cannibalization.
Monitoring referral traffic from AI platforms as that ecosystem matures.
Diagnosing indexing or crawlability issues that prevent AI systems from accessing your content.
Caveats
GSC data has well-documented limitations: it samples at scale, attribution can be murky, and data is typically available with a 48-72 hour lag. Critically, it only reflects Google. It tells you nothing about how you perform in Bing-powered AI search or standalone AI platforms. 
GA4 still has UX rough edges, so you’ll need to confirm that your event tracking and conversion configuration is solid before drawing strategic conclusions from the data.
Rapid-fire roundup 
That shortlist leaves, oh, thousands of tools left to consider. I recommend putting these on your radar and testing them to gauge their value as the AEO ecosystem develops.
5. AI Trust Signals
AI Trust Signals focuses on the credibility and trustworthiness signals that influence whether AI systems choose to cite a source. 
This is an emerging and underexplored dimension of AEO: it goes upstream from content relevance and helps brands understand whether an AI system “trusts” a domain enough to surface it as an authoritative reference. It’s worth monitoring as the understanding of AI citation mechanics matures.
6. Ahrefs
Ahrefs is a mature SEO platform with deep backlink analysis, content gap tooling, site auditing, and keyword research capabilities. 
Its relevance to AEO is primarily indirect, but it’s significant: authority signals, including referring domain quality and topical authority depth, are widely believed to influence AI citation likelihood. Ahrefs is a benchmark tool for understanding and building that authority infrastructure.
Its Content Explorer is also a practical tool for identifying high-performing content in your category that AI systems are likely to draw from.
7. Roadway AI
Roadway AI positions itself as an AI-native platform with a focus on scaling growth marketing activities. Where it helps is building agents that can help attribute AEO signals into revenue, so you can better understand impact. 
As a newer entrant, it’s worth evaluating as part of a toolkit audit, especially if you’re looking for tooling built specifically for AEO use cases. The category is moving fast, and platforms like Roadway AI may gain significant mindshare within 12 months, which also means more competitors are coming soon.
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The reality of AEO tools: Fast-moving and imperfect
AEO tooling is still catching up to AEO as a discipline, which will likely be the dynamic for the next few years, at least. 
Everything is changing so fast, and AI-driven discovery is evolving as users adopt new behaviors that vary by vertical. What matters is consistently applied measurement, strong analysis, and testing that lead to actionable insights.
You won’t get your setup perfect. Like much of marketing, solidly directional is probably as good as you’re going to get. With any tool, if you can explain and measure how it improves your AEO efforts, that’s a great start. 
Before you sign any contracts, see if you can find an industry colleague with real-life experience using the tool, and ask them for their take. Unless they’re staunch advocates, chances are you can either find an alternative that does the same thing better or cheaper, or you can wait another month for one to emerge.

From AI assistants to analytics platforms, here’s how to use today’s tools to understand and work on your visibility in AI answers.

7 tools for doing AEO right now

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/Why-AI-visibility-starts-before-search-and-ends-with-citations.png" class="attachment-large size-large wp-post-image" alt="Why AI visibility starts before search and ends with citations" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/Why-AI-visibility-starts-before-search-and-ends-with-citations.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/Why-AI-visibility-starts-before-search-and-ends-with-citations-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/Why-AI-visibility-starts-before-search-and-ends-with-citations-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/Why-AI-visibility-starts-before-search-and-ends-with-citations-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Most visibility is shaped before the query. Learn how influence, entity signals, and original data determine who AI systems cite.

The conversation has shifted. We’re spending less time optimizing for clicks and more time trying to fix the AI ROI story. AI now sits at the center of discovery, shaping what gets seen, summarized, and cited.
Here’s what’s working right now, what your peers are doing, and why SMX Advanced will feel different this year.
The SparkToro wake-up call: Influence happens everywhere
The foundation of any serious 2026 content strategy has to start with Rand Fishkin’s landmark March 2026 study, “Influence Happens Everywhere,” an analysis of the 5,000 most-visited sites on both mobile and desktop. 
The finding that rattled the industry: while Google still commands 73% of search traffic, search itself is merely a response to influence created elsewhere.
People don’t wake up and search for a brand in a vacuum. They read, watch, and listen across a fragmented web of news, social media, and niche communities before they ever hit a search bar. 
AI tools, despite their rapid growth, still account for a fraction of total web visits compared to the “big incumbents.” But the trajectory is unmistakable.
The fundamental problem with attribution in 2026 is that search gets over-credited because it captures demand at the finish line, while the fragmented channels — email, news, specialized content — get under-credited for creating that demand in the first place. 
When creating content, your job is to win the influence phase so thoroughly that when a user eventually turns to an AI assistant or a search bar, your brand is the only logical answer.
That framing is the strategic backbone behind sessions at the upcoming SMX Advanced in Boston, June 3-5, and the lens through which your entire editorial calendar should be rewritten.
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What your Search Engine Land colleagues are already doing
Before we discuss tactics, it’s worth pausing to note that this publication’s own contributor base has been sounding the alarm in complementary ways. Read them together and a clear picture emerges.
Dave Davies, principal SEO manager at Weights & Biases and a regular SMX Advanced speaker, published a rigorous piece in December 2025, “Mentions, citations, and clicks: Your 2026 content strategy.” 
Drawing on Siege Media’s two-year content performance study covering more than 7.2 million sessions, Grow and Convert’s conversion research, and Seer Interactive’s AI Overview findings, Davies made the case that the metrics we’ve lived by — impressions, sessions, CTR — “no longer tell the full story.” 
Mentions, citations, and structured visibility signals, he argued, are becoming the new levers of trust and the path to revenue. 
Carolyn Shelby, who appeared in a recent SMX Munich 2026 recap for her session “Inside Google’s Head,” crystallized what many of us have only half-articulated: AI doesn’t discover new brands — it selects from known entities. 
The implications are stark. If you haven’t built entity recognition across the web’s key reference points — Wikipedia, Reddit, LinkedIn, authoritative press coverage — you don’t get selected. 
My own October 2025 piece for this publication compared how ChatGPT, Perplexity, Gemini, Claude, and DeepSeek differ in their data sources, live web use, and citation rules. The conclusion I reached then is truer today: a single-platform AI strategy isn’t a strategy. Each model has different retrieval logic, different trust signals, and different recency weighting. 
Jordan Koene made the same point in January 2026, noting that different LLMs win different jobs. This heterogeneity is the fundamental reason why “write good content” is both correct and insufficient as advice.
What ‘full-stack content’ actually means
In 2024, we were impressed if an AI tool could write a decent 500-word blog post. Today, writing is the least interesting thing AI does.
Jasper’s 2026 Enterprise Suite is a useful illustration. It doesn’t just draft text, it:
Pulls real-time performance data from Google Search Console.
Identifies content gaps where competitors are gaining ground.
Generates a multimodal package: a 1,500-word deep dive, three vertical videos for YouTube Shorts, and custom infographics, all calibrated to a brand-voice model trained on your last five years of successful campaigns. 
We have moved from “Help me write this” to “Help me dominate this topic.”
But tools don’t solve strategy problems. The harder question is “what should the content actually say?” AI can’t produce the original research, the proprietary case study, or the hard-won perspective that makes an LLM choose you over a dozen lookalike alternatives.
This is why the most interesting SMX Advanced session on content this year may be the one by Purna Virji of LinkedIn, who opens the conference with a keynote on fixing the broken AI ROI story before budgets get cut. 
Her argument — that AI investment must generate measurable business outcomes “at the P&L level,” not just activity, efficiency, or content volume — is a direct challenge to teams that have been celebrating output metrics while their revenue dashboards flatline.
Google Vids and the democratization of video: A genuine inflection point
Perhaps the most significant platform shift for content creators in 2026 was Google moving Google Vids out of its Workspace-only silo. You can now create, edit, and share videos at no cost directly within the Google ecosystem, powered by the Veo 3 generative model.
For years, video production was protected by a high barrier to entry: expensive tools, specialist skills, and days of editing time. Google Vids collapses that barrier. Drop a Google Doc or a URL into the “Help me create” prompt, and you get a full-motion storyboard with AI-generated voiceovers, licensed music, and transitions in minutes.
The practical consequences are arriving fast:
Small agencies are now producing video-first content calendars that previously required five-figure budgets. The “if only we had video” excuse has expired.
Hyper-localization is becoming a baseline expectation. Using Vids’ automated dubbing and visual swapping, a single “hero” video can be localized for 20 different markets in an afternoon.
AI-generated summaries are already threatening video metadata. YouTube recently tested swapping video titles for AI-generated summaries. Brands that have not invested in clear entity signals and structured descriptions may soon find their video content renamed by an algorithm — not a person.
The strategic implication is the same as it was for text: AI tools lower the floor but raise the bar. Every competitor now has access to cheap video. But who has something worth saying in that video?
GEO, AEO, and the language problem
Depending on which Search Engine Land article you read in the past few weeks, the dominant framework for surviving this shift is either generative engine optimization (GEO) or answer engine optimization (AEO).
A growing number of contributors argue these terms are marketing noise for what is, at bottom, just good search everywhere optimization plus structured data plus earned media.
That debate is genuinely worth having, and it will be had at SMX Advanced. But for the practitioner who needs to make decisions next week, here’s what the evidence actually supports:
eMarketer’s Nate Elliott put it plainly in a recent FAQ: “Almost every GEO response is different from every other GEO response.” Between 40% and 60% of cited sources change month-to-month across Google AI Mode and ChatGPT, making AI visibility far less stable than organic search rankings. That volatility is the real risk, not the terminology debate.
Similarweb’s 2026 GenAI Brand Visibility Index, reported by Digiday, found that major publishers like Reuters and The Guardian receive less than 1% of referral traffic from AI platforms despite being frequently cited. Yet, The Washington Post found that visitors arriving from AI platforms convert to subscriptions at four to five times the rate of traditional search visitors. The volume-versus-value tension has never been more acute.
The practical translation of all of this:
In 2006, we optimized press releases for keyword density: In 2026, optimize for entity association: linking your brand to specific solutions in the AI’s knowledge graph.
Long-form blogs become modular content: Snippets, FAQs, and data tables designed for “chunk-level” ingestion by fetcher bots.
Gated white papers become open data: Making unique research crawlable so AI credits you as the source in an overview, not a competitor who summarized your findings.
Your robots.txt file now has strategic consequences: Allowing OAI-SearchBot but blocking GPTBot is a choice — one that determines whether you show up in real-time AI search citations versus model training data.
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The human premium isn’t a platitude
As AI-generated content reaches its peak volume, the value of the human voice has skyrocketed — but not for the reasons most think-piece writers suggest.
The standard argument runs like this: 
Audiences can smell AI slop.
Authentic human writing wins. 
That’s partially true, but it understates the mechanism. The deeper reason human-authored content is winning in AI-mediated search is structural. 
Human authors who’ve built genuine reputations across years of bylined, cited, and cross-referenced work have, in effect, built entity graphs that AI systems can navigate. That isn’t something a prompt can replicate.
The classic example: an AI-generated 2026 review of a new electric vehicle might be factually flawless, listing every spec and battery range. But it loses to a human-authored piece that says, “I drove this through a New England blizzard and the door handle froze shut.” 
AI can’t freeze. It can’t feel frustration. It can’t have a bad morning. Those human frictions are now genuinely valuable SEO assets — not because they’re charming, but because no language model can fabricate them with any credibility.
Readers, trained by years of exposure to AI content, have developed a reliable instinct for the difference.
The Siege Media data Davies cited adds a quantitative dimension: across 7.2 million sessions, the content that earned sustained citations and conversions shared a consistent profile — original data, expert voice, and clear structure that an AI system could extract and attribute. Volume without those properties is, as the headline puts it, just noise.
What to watch at SMX Advanced 2026 — and what it tells us about where this is going
The SMX Advanced agenda is the clearest available signal of where the practitioner community thinks the critical problems are right now. A few sessions deserve particular attention from anyone focused on content creation.
Virji’s keynote, “Your AI ROI story is broken: How to fix it before budgets get cut,” opens Day 2. Virji isn’t arguing that AI investment is wrong. She’s arguing that almost every organization is measuring it incorrectly — and that the correction required is organizational, not tactical.
Davies’ session, “Predicting and influencing AI citations with retrieval signals,” on June 4, is the direct technical counterpart to the strategic framing above. If Virji is asking “what does success mean,” Davies is asking “how do you engineer it.” 
SMX Master Classes ran in April, and SMX Next follows in November. If there’s a throughline across the entire 2026 SMX calendar, it’s this: the search marketing community has collectively decided that the era of isolated channel optimization is over. Content, paid, technical, and brand are now one discipline, or they are failing disciplines.
What you need to actually do in the second half of 2026
Broad strategic advice is easy to nod at and ignore. Here is the specific and uncomfortable version:
Audit your AI visibility before you touch your content: Query ChatGPT, Claude, Copilot, Gemini, and Perplexity with the prompts your customers actually use. Note which brands appear. Note which sources get cited. If you’re not among them, adding more content isn’t the first fix — fixing your entity signals is.
Stop treating your unique research as a lead-generation gate: Crawlable, citable original data earns AI attribution. A PDF behind a form wall earns nothing except a diminishing number of direct downloads as discovery migrates to AI interfaces.
Invest in community platforms as a first-party strategy, not an afterthought: LLMs pull heavily from Reddit, YouTube, and Wikipedia. eMarketer’s Max Willens has noted that Reddit alone has 100 million daily active users generating brand conversations. Your brand’s absence from those conversations isn’t neutral. It creates a vacuum that your competitors or your critics will fill.
Optimize for citatability, not just rankability: The new KPI isn’t the visit — it’s the attribution. If an AI Overview uses your data but doesn’t name your brand, you’ve been mined, not cited. Use clear entity markup, structured FAQ sections, and “quotable” conclusions that make it easy for an LLM to attribute rather than anonymize.
Diversify your robots.txt strategy intentionally: Different bots serve different purposes. Allowing OAI-SearchBot (real-time citation) while blocking GPTBot (model training) is a legitimate strategic choice. Most organizations have not made it deliberately. Make it deliberately.
Measure differently: The eMarketer-recommended framework allocates 40% of your optimization budget to core SEO fundamentals, 25% to digital PR, 20% to data and reporting, 10% to training, and 5% to experimentation. If your current allocation looks nothing like that, the gap explains more about your AI visibility struggles than any content audit will. So, combining SEO and PR is even more important today than it was back in the old days when I started speaking and writing about search.
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The bots are crawling: Are you worth citing?
The age of the proxy is over. You can no longer hide behind a ghostwriter or a simple prompt and expect to build a brand. But the deeper truth — the one that doesn’t make it into most AI content trend pieces — is that this transformation benefits people who’ve been doing the hard work all along.
If you’ve been building genuine expertise, publishing original data, earning bylines in authoritative publications, and cultivating real presence in the communities where your customers actually talk — then you already have most of what you need. The AI infrastructure of 2026 is, in many ways, a system that rewards exactly the things good content has always required.
The difference is that the competition is now generating plausible-sounding content on a scale that would have been impossible to imagine four years ago. Being good isn’t enough to stand out. 
You have to be citable, structured, and present in all the right places at precisely the right time — which is a harder, more interesting, and ultimately more durable strategic problem than keyword density ever was.
See you in Boston.

Most visibility is shaped before the query. Learn how influence, entity signals, and original data determine who AI systems cite.

Why AI visibility starts before search and ends with citations

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>The turn down web page says, "Jeeves’ spirit endures."

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2014/09/ask-com-logo2-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Ask.com, formerly Ask Jeeves, which launched 29 years ago on June 3, 1996, before Google launched, shut down on May 1, 2026. </p>



<p>Ask.com now has a turn down page that reads:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Every great search<br>must come to an end.<br>As IAC continues to sharpen its focus, we have made the decision to discontinue our search business, which includes Ask.com. After 25 years of answering the world&#8217;s questions, Ask.com officially closed on May 1, 2026.</p>



<p>&#8220;To the millions who asked…&#8221;<br>We are deeply grateful to the brilliant engineers, designers, and teams who built and supported Ask over the decades. And to you—the millions of users who turned to us for answers in a rapidly changing world—thank you for your endless curiosity, your loyalty, and your trust.</p>



<p>Jeeves’ spirit endures.</p>
</blockquote>



<figure class="wp-block-image size-full"><img decoding="async" width="1574" height="1466" src="https://searchengineland.com/wp-content/seloads/2026/05/ask-dot-com-closes-down-1777809779.png" alt="" class="wp-image-476305" srcset="https://searchengineland.com/wp-content/seloads/2026/05/ask-dot-com-closes-down-1777809779.png 1574w, https://searchengineland.com/wp-content/seloads/2026/05/ask-dot-com-closes-down-1777809779-768x715.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/ask-dot-com-closes-down-1777809779-1536x1431.png 1536w" sizes="(max-width: 1574px) 100vw, 1574px" /></figure>



<p>Ask.com has been known as an answer engine, the Jeeves butler was who you spoke to in the early days.  With AI and all these new answer engines, Ask.com could have deployed its own unique taste for its answer engine.  But I guess with all the competition and the market being harder, IAC, Ask.com&#8217;s parent company, decided to turn it down.</p>



<p>Ask.com will always have a place in the search marketing industry and Ask, including Jeeves, will be missed.</p>


Ask.com, formerly Ask Jeeves, which launched 29 years ago on June 3, 1996, before Google launched, shut down on May 1, 2026. 
Ask.com now has a turn down page that reads:
Every great search
must come to an end.
As IAC continues to sharpen its focus, we have made the decision to discontinue our search business, which includes Ask.com. After 25 years of answering the world’s questions, Ask.com officially closed on May 1, 2026.
“To the millions who asked…”
We are deeply grateful to the brilliant engineers, designers, and teams who built and supported Ask over the decades. And to you—the millions of users who turned to us for answers in a rapidly changing world—thank you for your endless curiosity, your loyalty, and your trust.
Jeeves’ spirit endures.




Ask.com has been known as an answer engine, the Jeeves butler was who you spoke to in the early days.  With AI and all these new answer engines, Ask.com could have deployed its own unique taste for its answer engine.  But I guess with all the competition and the market being harder, IAC, Ask.com’s parent company, decided to turn it down.
Ask.com will always have a place in the search marketing industry and Ask, including Jeeves, will be missed.

The turn down web page says, "Jeeves’ spirit endures."

Ask.com shuts down after over 25 years

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

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



Digital Marketing Manager (SEO/SEM)
April 28, 2026 
Job Description Attention: Kapitus is aware that individuals posing as recruiters may be communicating with job seekers about supposed positions with Kapitus. Kapitus has received reports that the content and method of communication can vary, but messages may contain requests for payment (e.g., fees for equipment or training) and/or for sensitive financial information. Kapitus will […]

Digital Marketing Specialist (Local SEO)
April 27, 2026 
Job Description Benefits: Competitive salary Health insurance Opportunity for advancement Paid time off Training & development Digital Marketing Specialist (SEO Focus) Company: Direct Clicks Inc. Job Type: Full-Time or Hourly Based on Experience Location: Remote Candidates must be located within driving distance of Roseville, Minnesota for occasional in-person team meetups. About Direct Clicks Inc. Direct […]

SEO Account Manager
April 24, 2026 
Remote (Canada-wide) · Full-time · $75,000–$90,000 CAD About Webserv Webserv is a digital marketing agency that helps mission-driven businesses — particularly in behavioral health — grow through SEO, paid media, and conversion-focused web strategy. We’re a tight-knit team that values curiosity, ownership, and the kind of work that actually moves the needle for our clients. […]

Sr. SEO/AEO Manager (B2B SaaS – US or Canada Based)
April 21, 2026 
The Basics: Growth Plays is hiring a Senior SEO/AEO Manager based in the US, Canada or LATAM, to support and manage ongoing customer engagements and relationships. You’ll act as the main point of contact for your clients, and focus on building relationships and trust while driving strategy-aligned growth for the long term. This role is […]

Independent Outbound Sales Representative
April 20, 2026 
Company: Local Leads DigitalLocation: RemoteJob Type: Contract, 1099Compensation: 100% Commission, Uncapped Job SummaryLocal Leads Digital is hiring an Independent Sales Representative to help grow adoption of the L.O.C.A.L. Tool, our local SEO fulfillment solution. This is a fully remote, 1099 independent contractor opportunity for someone who is confident in outbound sales and comfortable building their […]

Growth Strategist (SEO/AEO)
April 20, 2026 
We Are: NoGood is an award-winning, tech-enabled growth consultancy that has fueled the success of some of the most iconic brands. We are a team of growth leads, creatives, engineers and data scientists who help unlock rapid measurable growth for some of the world’s category-defining brands. We bring together the art and science of strategy, […]

Intermediate Search Specialist
April 17, 2026 
We are seeking an intermediate-level SEO Specialist for Hive Digital, a cutting-edge and award-winning agency that prides itself on helping change the world for the better. We offer a highly collaborative team that works together to deliver the best possible outcomes for our clients in a fast-paced, fun work environment. Are you ready to bring […]

Director, Global Digital Marketing (SEO/SEM/Email)
April 15, 2026 
Director, Global Digital Marketing, Integrated Marketing Communication (IMC) Team Position Overview The Director of Digital Marketing is at the center of 10x Genomics’ digital marketing engine, delivering measurable business impact and innovating across channels to ensure leadership in scientific markets. This position reports to the Vice President of Integrated Marketing Communications as is responsible for […]

Senior SEO Analyst
April 14, 2026 
This role offers you the opportunity to deepen your SEO expertise and develop your leadership skills within a tight-knit agency team. Sr. SEO Analysts lead our client relationships and bring our outcome-driven strategies to life. They are responsible for delivering value and results to our clients through their high-quality work, commitment to building deep SEO […]

Content Marketing Specialist
April 13, 2026 
Job Description This position is a Full-time remote position The Entrust Group is a pioneer in the world of self-direction. For over 40 years, we’ve provided administration services for self-directed retirement accounts and tax‑advantaged plans. As a self-directed IRA administrator, Entrust enables clients to invest their retirement funds in alternative assets not typically available through […]

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







Paid Search Manager, Partnerships
May 4, 2026 
At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package – this is Total Rewards. Employees enjoy multiple wealth‑building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access […]

Paid Media Strategist (Remote UK)
May 4, 2026 
Directive Consulting is the leading B2B marketing agency for companies that are done optimizing for metrics that don’t move the business. With over a decade of expertise and 420+ B2B brands behind us, we know what real results look like. We operate through 3 divisions: Performance, Communications, and Commerce, each built to share intelligence and […]

Senior Paid Media Strategist (Remote US)
May 4, 2026 
Directive Consulting is the performance marketing agency for SaaS and Tech companies. We use Customer Generation (a marketing methodology developed by us) which focuses on SQLs and Customers instead of traditional metrics like MQLs. We offer Paid Media, SEO/Content, CRO, and Video to our clients by creating comprehensive digital marketing strategies that allow our clients […]

Programmatic Specialist
April 30, 2026 
Are you excited to leverage your expertise in programmatic advertising to drive client success? Do you thrive on analyzing and optimizing digital campaigns to not only meet but exceed performance goals? As our Programmatic Specialist, your ability to navigate the complexities of display, CTV/OTT, audio, and digital-out-of-home advertising will be key. If you’re passionate about […]

Paid Media Manager
April 30, 2026 
Job Description Job Description Paid Media Manager$250K+/mo Budget | Hybrid | Northwest Austin, TX (78750)Come build and scale a digital marketing performance engineWhat You’ll Own:You’ll run our paid acquisition engine—$250K+ monthly spend across Google Ads, Microsoft Ads, and Meta, scaling toward $500K. This is a hands-on role: you’re in the platforms daily, building campaigns, writing […]

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Manage senior analysts and help analysts grow into the next level of their career.
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Note: We update this post weekly. So make sure to bookmark this page and check back.

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

The latest jobs in search marketing

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Microsoft Advertising now adds conversion and spend data to PMax placement reports, giving clearer insight into performance.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920.jpg" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/11/microsoft-search-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Microsoft Advertising is expanding its Performance Max reporting with publisher-level conversion and spend data — giving advertisers more visibility into where results are actually coming from</p>



<p><strong>What’s happening</strong>. According to Microsoft Ads Product liaison Navah Hopkins, the PMax Website Publisher URL report now includes conversion and spend metrics, moving beyond basic placement visibility into actionable performance data.</p>



<p>This gives advertisers clearer insight into which placements are driving real outcomes — not just impressions or clicks.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1476" height="294" src="https://searchengineland.com/wp-content/seloads/2026/05/1777477808889.jpeg" alt="" class="wp-image-476290" srcset="https://searchengineland.com/wp-content/seloads/2026/05/1777477808889.jpeg 1476w, https://searchengineland.com/wp-content/seloads/2026/05/1777477808889-768x153.jpeg 768w" sizes="(max-width: 1476px) 100vw, 1476px" /></figure>



<p><strong>Why we care.</strong> This update gives advertisers visibility into which placements are actually driving conversions and spend — not just impressions. That means better optimisation decisions, from scaling winning inventory to cutting wasted spend. It also makes it easier to trust and justify Performance Max performance with concrete data, rather than relying on aggregated reporting.</p>



<p><strong>How advertisers can use it</strong>. The update opens up several practical use cases. High-performing placements can now inform Audience Ads strategies, such as building remarketing campaigns or impression-based audiences from winning inventory.</p>



<p>At the same time, advertisers can identify poor-fit placements and exclude them using account-level URL exclusion lists, helping protect brand safety and improve efficiency.</p>



<p><strong>Between the lines</strong>. This is another step toward making automated campaigns more transparent. Rather than replacing control entirely, platforms are starting to give advertisers clearer signals on what’s working — and where to act.</p>



<p><strong>What to watch:</strong>



<ul class="wp-block-list">
<li>Whether this level of transparency expands further across PMax reporting</li>



<li>How advertisers balance automation with manual optimisation</li>



<li>If similar reporting features roll out across other platforms</li>
</ul>



<p><strong>Bottom line</strong>. With conversion and spend data now visible at the placement level, <a href="https://www.linkedin.com/posts/navahhopkins_im-so-excited-about-this-microsoft-advertising-activity-7455282287002218496-590z/?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAAAAOXwgBGvKJ5PG5kuwaTmFUJWimyBar5pw">Microsoft is making Performance Max a little less of a black box</a> — and a lot more actionable.</p>


Microsoft Advertising is expanding its Performance Max reporting with publisher-level conversion and spend data — giving advertisers more visibility into where results are actually coming from
What’s happening. According to Microsoft Ads Product liaison Navah Hopkins, the PMax Website Publisher URL report now includes conversion and spend metrics, moving beyond basic placement visibility into actionable performance data.
This gives advertisers clearer insight into which placements are driving real outcomes — not just impressions or clicks.




Why we care. This update gives advertisers visibility into which placements are actually driving conversions and spend — not just impressions. That means better optimisation decisions, from scaling winning inventory to cutting wasted spend. It also makes it easier to trust and justify Performance Max performance with concrete data, rather than relying on aggregated reporting.
How advertisers can use it. The update opens up several practical use cases. High-performing placements can now inform Audience Ads strategies, such as building remarketing campaigns or impression-based audiences from winning inventory.
At the same time, advertisers can identify poor-fit placements and exclude them using account-level URL exclusion lists, helping protect brand safety and improve efficiency.
Between the lines. This is another step toward making automated campaigns more transparent. Rather than replacing control entirely, platforms are starting to give advertisers clearer signals on what’s working — and where to act.
What to watch:




Whether this level of transparency expands further across PMax reporting
How advertisers balance automation with manual optimisation
If similar reporting features roll out across other platforms
Bottom line. With conversion and spend data now visible at the placement level, Microsoft is making Performance Max a little less of a black box — and a lot more actionable.

Microsoft Advertising now adds conversion and spend data to PMax placement reports, giving clearer insight into performance.

Microsoft Ads adds deeper reporting to Performance Max placements

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="6 mistakes that hurt ecommerce campaigns on Google Ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google Ads API v20 will stop working on June 10, requiring advertisers to upgrade or risk disruptions.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png" class="attachment-large size-large wp-post-image" alt="6 mistakes that hurt ecommerce campaigns on Google Ads" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads.png 1920w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/04/6-mistakes-that-hurt-ecommerce-campaigns-on-Google-Ads-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google is enforcing a hard cutoff for older API versions, meaning advertisers and developers who don’t upgrade risk losing access to critical campaign management tools.</p>



<p><strong>What’s happening.</strong> Google Ads API v20 will officially sunset on June 10, 2026. From that date onward, all requests to v20 will fail, requiring migration to a newer version to maintain uninterrupted API access.</p>



<p><strong>Why we care. </strong>If you rely on the Google Ads API and don’t upgrade in time, automated workflows — including reporting, bidding and campaign management — could suddenly stop working. This could lead to data gaps, performance issues and operational disruption. Migrating early ensures continuity and avoids last-minute fixes that can impact campaign performance.</p>



<p><strong>What to do.</strong> Google is urging users to upgrade as soon as possible and provides resources like release notes and upgrade guides to support the transition. Developers can also use the Google Cloud Console to review recent API activity, including which methods and versions their projects are calling.</p>



<p><strong>Between the lines. </strong>API sunsets are routine, but the impact can be significant for advertisers relying on custom scripts, tools or third-party platforms. Missing the deadline could disrupt reporting, bidding or campaign automation workflows.</p>



<p id="h-the-bottom-line-this-is-a-firm-deadline-with-real-consequences-upgrade-to-a-newer-google-ads-api-version-before-june-10-or-risk-losing-access-entirely"><strong>The bottom line. </strong>This is a firm deadline with real consequences: <a href="https://ads-developers.googleblog.com/2026/04/google-ads-api-v20-sunset-reminder.html">upgrade to a newer Google Ads API version before June 10</a> or risk losing access entirely.</p>


Google is enforcing a hard cutoff for older API versions, meaning advertisers and developers who don’t upgrade risk losing access to critical campaign management tools.
What’s happening. Google Ads API v20 will officially sunset on June 10, 2026. From that date onward, all requests to v20 will fail, requiring migration to a newer version to maintain uninterrupted API access.
Why we care. If you rely on the Google Ads API and don’t upgrade in time, automated workflows — including reporting, bidding and campaign management — could suddenly stop working. This could lead to data gaps, performance issues and operational disruption. Migrating early ensures continuity and avoids last-minute fixes that can impact campaign performance.
What to do. Google is urging users to upgrade as soon as possible and provides resources like release notes and upgrade guides to support the transition. Developers can also use the Google Cloud Console to review recent API activity, including which methods and versions their projects are calling.
Between the lines. API sunsets are routine, but the impact can be significant for advertisers relying on custom scripts, tools or third-party platforms. Missing the deadline could disrupt reporting, bidding or campaign automation workflows.
The bottom line. This is a firm deadline with real consequences: upgrade to a newer Google Ads API version before June 10 or risk losing access entirely.

Google Ads API v20 will stop working on June 10, requiring advertisers to upgrade or risk disruptions.

Google Ads API v20 sunset set for June 10

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/05/SEO-agent-skills.png" class="attachment-large size-large wp-post-image" alt="SEO agent skills" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/05/SEO-agent-skills.png 1920w, https://searchengineland.com/wp-content/seloads/2026/05/SEO-agent-skills-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/05/SEO-agent-skills-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/05/SEO-agent-skills-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Most AI SEO “skills” are just prompts. Learn the system behind reliable agents: tools, memory, templates, and a built-in review layer.

Most AI SEO “skills” are just prompts. Learn the system behind reliable agents: tools, memory, templates, and a built-in review layer.

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