<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Apple Ads- What you need to know" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Apple is adding more ad slots to App Store search results, creating new install opportunities while increasing competition for high-intent searches.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg" class="attachment-large size-large wp-post-image" alt="Apple Ads- What you need to know" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/Apple-Ads-What-you-need-to-know-in-2026-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Apple is expanding ads in App Store search results, giving advertisers more opportunities to reach users at the moment they’re looking to download apps.</p>



<p>Starting March 3rd, Apple Ads will begin showing additional ads per search query in the UK, followed by Japan. The expansion is expected to roll out to all Apple Ads markets by the end of March.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="488" height="960" src="https://searchengineland.com/wp-content/seloads/2026/01/0082-search-results.png" alt="" class="wp-image-467906"/></figure></div>


<p><strong>Why we care</strong>. More ad slots in App Store search results mean more chances to win installs—but also more competition for the same high-intent queries, which could push up costs. With no ability to choose placements, performance may vary by position, making creative relevance, keyword strategy, and conversion tracking more important than ever.</p>



<p><strong>What’s changing</strong>. Until now, Apple Ads search results featured a single sponsored placement at the top of the page. Beginning in March, multiple ad positions may appear for a single search query, including the existing top slot and new placements further down the results.</p>



<p>The new placements will be supported on devices running iOS and iPadOS 26.2 and later.</p>



<p><strong>How eligibility works</strong>. Advertisers don’t need to make any changes to access the new inventory. Any existing search results campaign will automatically be eligible to appear in all available positions.</p>



<p>However, advertisers can’t choose or bid for specific placements. Apple will decide where an ad appears within search results.</p>



<p><strong>Ad formats and pricing stay the same</strong>. Ads will look the same regardless of placement, using either a default product page or a custom product page. Optional deep links can send users directly to a specific in-app destination.</p>



<p>Billing remains unchanged, with advertisers paying on a cost-per-tap or cost-per-install basis.</p>



<p><strong>How ads are matched to searches</strong>. Search results ads continue to rely on keywords, either selected by advertisers or suggested by Apple. Apple says its relevance-based matching delivers more than a 60% average conversion rate for top-of-search ads.</p>



<p>Placement is determined by a combination of relevance and bid, but relevance is non-negotiable. Apple says ads won’t enter auctions if they aren’t a strong match for the user’s query — regardless of bid size.</p>



<p><strong>What advertisers should watch</strong>. More ad slots mean more opportunities — but also more competition within the same search results page. Advertisers may need to closely monitor performance by query, creative alignment, and conversion rates as the rollout expands globally.</p>



<p><strong>What’s next</strong>. The phased rollout will continue through March, bringing <a href="https://ads.apple.com/app-store/help/ad-placements/0082-search-results?cid=ads-app-store-em-c00376-M02485">additional App Store search ads</a> to all Apple Ads markets. For app marketers, it marks a meaningful shift in how search visibility — and competition — will work inside the App Store.</p>



<p></p>


Apple is expanding ads in App Store search results, giving advertisers more opportunities to reach users at the moment they’re looking to download apps.
Starting March 3rd, Apple Ads will begin showing additional ads per search query in the UK, followed by Japan. The expansion is expected to roll out to all Apple Ads markets by the end of March.

Why we care. More ad slots in App Store search results mean more chances to win installs—but also more competition for the same high-intent queries, which could push up costs. With no ability to choose placements, performance may vary by position, making creative relevance, keyword strategy, and conversion tracking more important than ever.
What’s changing. Until now, Apple Ads search results featured a single sponsored placement at the top of the page. Beginning in March, multiple ad positions may appear for a single search query, including the existing top slot and new placements further down the results.
The new placements will be supported on devices running iOS and iPadOS 26.2 and later.
How eligibility works. Advertisers don’t need to make any changes to access the new inventory. Any existing search results campaign will automatically be eligible to appear in all available positions.
However, advertisers can’t choose or bid for specific placements. Apple will decide where an ad appears within search results.
Ad formats and pricing stay the same. Ads will look the same regardless of placement, using either a default product page or a custom product page. Optional deep links can send users directly to a specific in-app destination.
Billing remains unchanged, with advertisers paying on a cost-per-tap or cost-per-install basis.
How ads are matched to searches. Search results ads continue to rely on keywords, either selected by advertisers or suggested by Apple. Apple says its relevance-based matching delivers more than a 60% average conversion rate for top-of-search ads.
Placement is determined by a combination of relevance and bid, but relevance is non-negotiable. Apple says ads won’t enter auctions if they aren’t a strong match for the user’s query — regardless of bid size.
What advertisers should watch. More ad slots mean more opportunities — but also more competition within the same search results page. Advertisers may need to closely monitor performance by query, creative alignment, and conversion rates as the rollout expands globally.
What’s next. The phased rollout will continue through March, bringing additional App Store search ads to all Apple Ads markets. For app marketers, it marks a meaningful shift in how search visibility — and competition — will work inside the App Store.

Apple is adding more ad slots to App Store search results, creating new install opportunities while increasing competition for high-intent searches.

Apple Ads adds more ad slots to App Store search results

<div><img width="1600" height="900" src="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png 1600w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-1536x864.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></div>One early-career PPC mistake nearly took campaigns offline on Black Friday, but it became a defining lesson in staying calm, &#038; owning errors.

<div><img width="1600" height="900" src="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5.png 1600w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/PLTP-Image-5-1536x864.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></div>
<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe title="The URL Mistake That Killed Black Friday ft Nick Handley" width="500" height="281" src="https://www.youtube.com/embed/IadRhqbz6ws?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p>On episode 338 of PPC Live The Podcast, I speak to Nick Handley Paid Media Lead at Impression, about one of the most formative mistakes of his career — and why those early errors often shape the strongest marketers.</p>



<p>The podcast series focuses on PPC professionals’ biggest “F-ups,” but never without exploring how they recovered, who helped them, and what lasting lessons came out the other side. Nick’s story is a textbook example of how a single mistake can permanently change how you work — for the better.</p>



<h2 class="wp-block-heading" id="h-the-black-friday-mistake-that-took-everything-down">The Black Friday mistake that took everything down</h2>



<p>Nick takes listeners back nearly ten years, to the very start of his career at <em>Tyres on the Drive</em> (now owned by Halfords). With only around seven months of PPC experience, he was left managing campaigns during the Black Friday period while a senior colleague was on holiday.</p>



<p>The task sounded simple: update URLs across multiple campaigns using Google Ads Editor. The execution, however, went very wrong.</p>



<p>Nick mistyped part of the landing page URL — a small error with massive consequences. Once uploaded, ads across the account were disapproved, effectively taking paid search offline during one of the most important trading periods of the year. At the time, PPC accounted for around 70% of the company’s conversions.</p>



<p>“It was full panic,” Nick admits. “I genuinely thought I was going to lose my job.”</p>



<h2 class="wp-block-heading" id="h-panic-makes-problems-worse">Panic makes problems worse</h2>



<p>What made the situation harder wasn’t just the typo — it was what came next. In a stressed state, Nick tried to fix the issue without properly re-syncing Google Ads Editor with the live account. Changes didn’t apply, errors stacked up, and confusion grew.</p>



<p>The turning point came when Max Hopkinson, a senior colleague, stepped in. Instead of blaming or escalating, Max calmly walked Nick through the fix: re-sync the account, undo the changes properly, re-upload, and get campaigns live again.</p>



<p>The downtime was resolved in about an hour, and the team worked strategically to recover performance by increasing spend later in the day. The Black Friday period ultimately performed well — but the emotional impact of the mistake stuck.</p>



<h2 class="wp-block-heading" id="h-the-real-lesson-de-escalate-yourself-first">The real lesson: de-escalate yourself first</h2>



<p>One of the biggest takeaways from Nick’s experience isn’t technical — it’s psychological.</p>



<p>When things go wrong, panic actively makes solutions harder to see. Nick stresses the importance of stepping away, calming yourself down, and then methodically identifying the issue. Five minutes away from the screen can prevent five hours of damage.</p>



<p>This mindset now underpins how he works — and how he manages others.</p>



<h2 class="wp-block-heading" id="h-from-junior-panic-to-leadership-principles">From junior panic to leadership principles</h2>



<p>As a leader today, Nick is intentional about building systems that reduce risk and pressure. At Impression, large changes go through a buddy-based QA system, where someone outside the immediate account team sense-checks major updates before they go live.</p>



<p>The goal isn’t mistrust — it’s safety. Fresh eyes catch errors tired ones miss, especially when working at speed.</p>



<p>Nick is clear that this approach isn’t just for agencies. In-house teams, freelancers, and solo marketers can adapt it using automation, AI checks, or structured workflows to ensure nothing slips through.</p>



<h2 class="wp-block-heading" id="h-ai-is-helpful-but-only-if-you-know-the-basics">AI is helpful — but only if you know the basics</h2>



<p>Nick also warns against leaning too heavily on AI without understanding fundamentals first. While automation and AI can help sense-check work, speed up QA, or manage budgets, they can’t replace foundational knowledge.</p>



<p>“If you don’t know what ‘right’ looks like,” he explains, “you won’t know when AI is wrong.”</p>



<p>This applies to everything from ad copy and keyword research to budget pacing and performance analysis. AI should amplify expertise — not replace it.</p>



<h2 class="wp-block-heading" id="h-accountability-beats-perfection">Accountability beats perfection</h2>



<p>Perhaps the most important message from the episode is that mistakes are inevitable — but hiding them is optional.</p>



<p>Nick emphasizes accountability over blame. When errors happen, the best response is to clearly explain what went wrong, what the impact was, and how it’s being fixed. Most clients and managers are far more understanding than people expect, especially when transparency comes early.</p>



<p>This culture of openness not only protects performance — it protects mental health.</p>



<h2 class="wp-block-heading" id="h-why-sharing-mistakes-makes-better-marketers">Why sharing mistakes makes better marketers</h2>



<p>Nick believes leaders should openly share their failures, not just their wins. Digital marketing already carries intense pressure, constant change, and unrealistic expectations of perfection. Hearing that respected experts still make mistakes — and survive them — normalizes the learning curve.</p>



<p>“We’re not robots,” he says. “We’re people doing complex work in fast-moving systems.”</p>



<h2 class="wp-block-heading" id="h-the-big-takeaway">The big takeaway</h2>



<p>Nick’s early-career mistake didn’t derail his career — it defined it. It shaped how he approaches QA, leadership, automation, and stress. More importantly, it reinforced a truth many PPC professionals need to hear:</p>



<p>Mistakes don’t end careers. Panic, silence, and lack of accountability do.</p>


On episode 338 of PPC Live The Podcast, I speak to Nick Handley Paid Media Lead at Impression, about one of the most formative mistakes of his career — and why those early errors often shape the strongest marketers.
The podcast series focuses on PPC professionals’ biggest “F-ups,” but never without exploring how they recovered, who helped them, and what lasting lessons came out the other side. Nick’s story is a textbook example of how a single mistake can permanently change how you work — for the better.
The Black Friday mistake that took everything down
Nick takes listeners back nearly ten years, to the very start of his career at Tyres on the Drive (now owned by Halfords). With only around seven months of PPC experience, he was left managing campaigns during the Black Friday period while a senior colleague was on holiday.
The task sounded simple: update URLs across multiple campaigns using Google Ads Editor. The execution, however, went very wrong.
Nick mistyped part of the landing page URL — a small error with massive consequences. Once uploaded, ads across the account were disapproved, effectively taking paid search offline during one of the most important trading periods of the year. At the time, PPC accounted for around 70% of the company’s conversions.
“It was full panic,” Nick admits. “I genuinely thought I was going to lose my job.”
Panic makes problems worse
What made the situation harder wasn’t just the typo — it was what came next. In a stressed state, Nick tried to fix the issue without properly re-syncing Google Ads Editor with the live account. Changes didn’t apply, errors stacked up, and confusion grew.
The turning point came when Max Hopkinson, a senior colleague, stepped in. Instead of blaming or escalating, Max calmly walked Nick through the fix: re-sync the account, undo the changes properly, re-upload, and get campaigns live again.
The downtime was resolved in about an hour, and the team worked strategically to recover performance by increasing spend later in the day. The Black Friday period ultimately performed well — but the emotional impact of the mistake stuck.
The real lesson: de-escalate yourself first
One of the biggest takeaways from Nick’s experience isn’t technical — it’s psychological.
When things go wrong, panic actively makes solutions harder to see. Nick stresses the importance of stepping away, calming yourself down, and then methodically identifying the issue. Five minutes away from the screen can prevent five hours of damage.
This mindset now underpins how he works — and how he manages others.
From junior panic to leadership principles
As a leader today, Nick is intentional about building systems that reduce risk and pressure. At Impression, large changes go through a buddy-based QA system, where someone outside the immediate account team sense-checks major updates before they go live.
The goal isn’t mistrust — it’s safety. Fresh eyes catch errors tired ones miss, especially when working at speed.
Nick is clear that this approach isn’t just for agencies. In-house teams, freelancers, and solo marketers can adapt it using automation, AI checks, or structured workflows to ensure nothing slips through.
AI is helpful — but only if you know the basics
Nick also warns against leaning too heavily on AI without understanding fundamentals first. While automation and AI can help sense-check work, speed up QA, or manage budgets, they can’t replace foundational knowledge.
“If you don’t know what ‘right’ looks like,” he explains, “you won’t know when AI is wrong.”
This applies to everything from ad copy and keyword research to budget pacing and performance analysis. AI should amplify expertise — not replace it.
Accountability beats perfection
Perhaps the most important message from the episode is that mistakes are inevitable — but hiding them is optional.
Nick emphasizes accountability over blame. When errors happen, the best response is to clearly explain what went wrong, what the impact was, and how it’s being fixed. Most clients and managers are far more understanding than people expect, especially when transparency comes early.
This culture of openness not only protects performance — it protects mental health.
Why sharing mistakes makes better marketers
Nick believes leaders should openly share their failures, not just their wins. Digital marketing already carries intense pressure, constant change, and unrealistic expectations of perfection. Hearing that respected experts still make mistakes — and survive them — normalizes the learning curve.
“We’re not robots,” he says. “We’re people doing complex work in fast-moving systems.”
The big takeaway
Nick’s early-career mistake didn’t derail his career — it defined it. It shaped how he approaches QA, leadership, automation, and stress. More importantly, it reinforced a truth many PPC professionals need to hear:
Mistakes don’t end careers. Panic, silence, and lack of accountability do.

One early-career PPC mistake nearly took campaigns offline on Black Friday, but it became a defining lesson in staying calm, & owning errors.

The URL mistake that killed Black Friday ft Nick Handley

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png" class="attachment-large size-large wp-post-image" alt="Dealing with Google Ads frustrations: Poor support, suspensions and rising costs" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>A Google Ads bug is causing the option to add account notes to disappear for some advertisers, complicating change tracking and documentation.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png" class="attachment-large size-large wp-post-image" alt="Dealing with Google Ads frustrations: Poor support, suspensions and rising costs" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-800x450.png 800w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-600x338.png 600w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-200x113.png 200w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2025/04/Dealing-with-Google-Ads-frustrations-Poor-support-suspensions-and-rising-costs.png 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Some Google Ads advertisers are seeing a bug that causes the option to add notes to disappear from the account change popup, making it harder to document optimizations and performance shifts.</p>



<p>The issue was flagged by paid search consultant Odi Caspi, who says the problem has appeared intermittently over the past couple of weeks.</p>



<p>What advertisers should be seeing:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1302" height="336" src="https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19.png" alt="" class="wp-image-467896" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19.png 1302w, https://searchengineland.com/wp-content/seloads/2026/01/Screenshot-2026-01-23-at-19.45.19-768x198.png 768w" sizes="(max-width: 1302px) 100vw, 1302px" /></figure>



<p>Caspi shares his view below:</p>



<figure class="wp-block-image size-full is-resized"><img decoding="async" width="800" height="362" src="https://searchengineland.com/wp-content/seloads/2026/01/1769187329142.jpeg" alt="" class="wp-image-467897" style="width:840px;height:auto" srcset="https://searchengineland.com/wp-content/seloads/2026/01/1769187329142.jpeg 800w, https://searchengineland.com/wp-content/seloads/2026/01/1769187329142-768x348.jpeg 768w" sizes="(max-width: 800px) 100vw, 800px" /></figure>



<p><strong>Why we care</strong>. Account notes are a key workflow tool for agencies and in-house teams tracking changes over time. Losing easy access to notes makes troubleshooting performance swings harder and weakens institutional memory across teams.</p>



<p><strong>What users are seeing</strong>. In affected accounts, the “Add note” option no longer appears in the standard popup where advertisers typically annotate changes. The issue appears to be <strong>sporadic</strong>, working normally at times and disappearing at others.</p>



<p><strong>Workarounds, for now</strong>. Caspi says one workaround is clicking on an existing note, which then reveals the option to add a new one. The downside: this only works if a note exists in the current date range.</p>



<p>Another option, shared by Paid Media Specialist, <strong>Dids Reeve</strong>, is to open the Notes panel from the “More” (burger) menu, where the add-note function may still be accessible.</p>



<p><strong>What’s next</strong>. Google has not publicly acknowledged the bug or shared a timeline for a fix. Until then, advertisers relying on notes may need to use alternative entry points — and double-check that important changes are being properly documented.</p>



<p><strong>First seen. </strong>This error was first spotted by Caspi who shared his view of camapign reports on <a href="https://www.linkedin.com/feed/update/urn:li:activity:7420509497137463296/">LinkedIn</a></p>


Some Google Ads advertisers are seeing a bug that causes the option to add notes to disappear from the account change popup, making it harder to document optimizations and performance shifts.
The issue was flagged by paid search consultant Odi Caspi, who says the problem has appeared intermittently over the past couple of weeks.
What advertisers should be seeing:




Caspi shares his view below:




Why we care. Account notes are a key workflow tool for agencies and in-house teams tracking changes over time. Losing easy access to notes makes troubleshooting performance swings harder and weakens institutional memory across teams.
What users are seeing. In affected accounts, the “Add note” option no longer appears in the standard popup where advertisers typically annotate changes. The issue appears to be sporadic, working normally at times and disappearing at others.
Workarounds, for now. Caspi says one workaround is clicking on an existing note, which then reveals the option to add a new one. The downside: this only works if a note exists in the current date range.
Another option, shared by Paid Media Specialist, Dids Reeve, is to open the Notes panel from the “More” (burger) menu, where the add-note function may still be accessible.
What’s next. Google has not publicly acknowledged the bug or shared a timeline for a fix. Until then, advertisers relying on notes may need to use alternative entry points — and double-check that important changes are being properly documented.
First seen. This error was first spotted by Caspi who shared his view of camapign reports on LinkedIn

A Google Ads bug is causing the option to add account notes to disappear for some advertisers, complicating change tracking and documentation.

Google Ads bug removes notes option for some advertisers

<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" style="margin-bottom: 15px;" 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 
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SEO Strategist ~ Ramp ~ $60,000-$80,000 ~ Hybrid (New York, NY/San Francisco, CA, United States)
January 23, 2026 
At Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it. Ramp is a financial operations platform designed to […]

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PPC/Google Ads Specialist ~ ITVibes, Inc. ~ $60,000-$80,000 ~ In-office (USA) ~ The Woodlands, TX, United States
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PPC/SEM & GOOGLE ADS SPECIALIST ITVibes, an SEO and digital marketing agency located in The Woodlands, TX, is seeking a PPC/SEM & Google Ads Specialist to become a part of our amazing team! The PPC/SEM & Google Ads Specialist position involves the management of digital advertising campaigns using various platforms including but not limited to […]

Associate Director, Paid Search (SEM) ~ Starcom ~ $95,950 – $137,865 ~ In-office (USA) ~ Chicago, IL, United States
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Paid Digital Media Specialist ~ Explore Industries USA, Inc. ~ $48,000 – $58,000 ~ In-office (USA) ~ Knoxville, TN, United States
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Digital Paid Media Specialist ~ ADI Global Distribution ~ $60,000-$80,000 ~ In-office (USA) ~ Irving, TX, United States
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<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend.png" class="attachment-large size-large wp-post-image" alt="7 Google Ads search term filters to cut wasted spend" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend.png 1920w, https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>A new Google Ads bug is preventing some advertisers from editing PMax asset groups, forcing teams to rely on Ads Editor as a workaround.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend.png" class="attachment-large size-large wp-post-image" alt="7 Google Ads search term filters to cut wasted spend" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend.png 1920w, https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2025/07/7-Google-Ads-search-term-filters-to-cut-wasted-spend-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>A new bug in Google Ads is preventing some advertisers from editing and saving existing Performance Max (PMAX) asset groups. Users report seeing error messages when attempting to make changes in the platform interface, blocking updates from being saved.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="960" height="540" src="https://searchengineland.com/wp-content/seloads/2026/01/pmax-asset-group-bug-edited.jpg" alt="" class="wp-image-467881" srcset="https://searchengineland.com/wp-content/seloads/2026/01/pmax-asset-group-bug-edited.jpg 960w, https://searchengineland.com/wp-content/seloads/2026/01/pmax-asset-group-bug-edited-768x432.jpg 768w" sizes="(max-width: 960px) 100vw, 960px" /></figure></div>


<p><strong>Why we care.</strong> Performance Max relies heavily on asset freshness and iteration. If advertisers can’t update asset groups, campaigns risk running with outdated creative, messaging, or offers — directly impacting performance and efficiency.</p>



<p><strong>What advertisers are seeing</strong>. Affected users encounter an error message reading, <em>“An error occurred. Please try again later. Value is required,”</em> when attempting to edit asset group details. The error appears in the Google Ads UI and prevents changes from being saved, even when required fields appear complete.</p>



<p><strong>Google’s response</strong>. Google has acknowledged the issue and says it is actively investigating. As of now, the company has not shared a timeline for a fix or provided additional guidance through official status channels.</p>



<p><strong>Temporary workaround</strong>. Advertisers can still make changes using Google Ads Editor, then upload updates directly to their accounts. While functional, the workaround adds friction for teams accustomed to managing PMAX exclusively in the web interface.</p>



<p><strong>What to do now</strong>. Advertisers running Performance Max campaigns should double-check recent asset group edits to confirm changes were successfully saved. Those planning creative updates may want to route edits through Ads Editor until the issue is resolved.</p>



<p><strong>What’s next</strong>. Until Google ships a fix, the bug adds another layer of uncertainty to Performance Max management — reinforcing the importance of version checks and alternative workflows for advertisers relying heavily on PMAX.</p>



<p><strong>First seen.</strong> The issue was flagged publicly by PPC professional Chelsea Harding and shared the error message she recieved on <a href="https://www.linkedin.com/posts/chelsea-h-google-ads-ecom-performance-freelancer_ppcupdates-googleadsupdates-activity-7419902009589452800-mTus/?utm_source=share&amp;utm_medium=member_desktop&amp;rcm=ACoAABU5RtAB1yM61HMd6Ska99csDVjiJlgRo6A">LinkedIn</a>.</p>


A new bug in Google Ads is preventing some advertisers from editing and saving existing Performance Max (PMAX) asset groups. Users report seeing error messages when attempting to make changes in the platform interface, blocking updates from being saved.

Why we care. Performance Max relies heavily on asset freshness and iteration. If advertisers can’t update asset groups, campaigns risk running with outdated creative, messaging, or offers — directly impacting performance and efficiency.
What advertisers are seeing. Affected users encounter an error message reading, “An error occurred. Please try again later. Value is required,” when attempting to edit asset group details. The error appears in the Google Ads UI and prevents changes from being saved, even when required fields appear complete.
Google’s response. Google has acknowledged the issue and says it is actively investigating. As of now, the company has not shared a timeline for a fix or provided additional guidance through official status channels.
Temporary workaround. Advertisers can still make changes using Google Ads Editor, then upload updates directly to their accounts. While functional, the workaround adds friction for teams accustomed to managing PMAX exclusively in the web interface.
What to do now. Advertisers running Performance Max campaigns should double-check recent asset group edits to confirm changes were successfully saved. Those planning creative updates may want to route edits through Ads Editor until the issue is resolved.
What’s next. Until Google ships a fix, the bug adds another layer of uncertainty to Performance Max management — reinforcing the importance of version checks and alternative workflows for advertisers relying heavily on PMAX.
First seen. The issue was flagged publicly by PPC professional Chelsea Harding and shared the error message she recieved on LinkedIn.

A new Google Ads bug is preventing some advertisers from editing PMax asset groups, forcing teams to rely on Ads Editor as a workaround.

Google Ads bug blocks edits to Performance Max asset groups

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-800x450.jpg" class="attachment-large size-large wp-post-image" alt="TikTok ban U.S." style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Majority U.S. ownership, Oracle-hosted data, and independent governance aim to end ban fears and give brands and creators a steadier outlook.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-800x450.jpg" class="attachment-large size-large wp-post-image" alt="TikTok ban U.S." style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2024/03/TIkTok-ban-in-the-united-states.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>TikTok announced a new U.S.-based joint venture to meet federal national security requirements and keep the app available to more than 200 million Americans.</p>



<p>The entity, TikTok USDS Joint Venture LLC, was established under an executive order signed by President Trump on Sept. 25.</p>



<p><strong>The big picture. </strong>TikTok USDS Joint Venture is majority American-owned and operates independently, with control over U.S. user data, content moderation, and algorithm security. </p>



<ul class="wp-block-list">
<li>ByteDance holds a 19.9% stake, below the threshold U.S. officials have often cited as a national security risk.</li>



<li>The joint venture expands TikTok’s existing U.S. Data Security program and is designed to isolate sensitive systems from foreign access.</li>
</ul>



<p><strong>Why we care.</strong> This joint venture could decide whether TikTok continues operating in the U.S. without bans or forced divestment. It moves control of U.S. user data, content moderation, and the recommendation algorithm to a majority American-owned, U.S.-governed entity, directly addressing long-standing national security concerns. For creators, advertisers, and rival platforms, it serves as a test case for how the U.S. may regulate foreign-owned technology going forward.</p>



<p><strong>How the safeguards work.</strong> U.S. user data will be stored and protected in Oracle’s U.S.-based cloud, supported by ongoing audits and third-party cybersecurity certifications. </p>



<ul class="wp-block-list">
<li>The joint venture says its security program meets federal and industry standards, including NIST, ISO 27001, and CISA requirements.</li>



<li>The recommendation algorithm for U.S. users will be retrained, tested, and updated using U.S. data, then secured entirely within Oracle’s U.S. environment. </li>



<li>The source code will undergo continuous review under formal software assurance protocols.</li>
</ul>



<p><strong>Trust, safety, and content moderation.</strong> Unlike earlier arrangements, the joint venture holds decision-making authority over trust and safety policies and content moderation for U.S. users. This control is designed to strengthen accountability and limit foreign influence over sensitive moderation decisions.</p>



<p><strong>Global reach, U.S. control. </strong>While the joint venture oversees U.S. security and safety functions, TikTok’s global U.S. entities will continue to manage interoperability and commercial operations, including advertising, marketing, and ecommerce.</p>



<ul class="wp-block-list">
<li>This structure keeps U.S. creators and businesses discoverable worldwide, TikTok said.</li>
</ul>



<p><strong>Who’s in charge. </strong>The joint venture is overseen by a seven-member board with a majority of American directors, including executives from Silver Lake, Oracle, Susquehanna International Group, and MGX.</p>



<ul class="wp-block-list">
<li>Adam Presser was appointed CEO, and Will Farrell was named chief security officer.</li>



<li>The board’s security committee is chaired by Raul Fernandez, CEO of DXC Technology.</li>
</ul>



<p><strong>Ownership structure.</strong> Silver Lake, Oracle, and MGX are the joint venture’s three managing investors, each holding 15%. </p>



<ul class="wp-block-list">
<li>Additional investors include firms affiliated with Michael Dell, General Atlantic, Dragoneer, and Xavier Niel. </li>



<li>The safeguards also extend to CapCut, Lemon8, and other TikTok-owned apps in the U.S.</li>
</ul>



<p><strong>What’s next. </strong>The announcement positions <a href="https://newsroom.tiktok.com/announcement-from-the-new-tiktok-usds-joint-venture-llc?lang=en" target="_blank" rel="noopener">TikTok USDS Joint Venture</a> as a long-term solution to U.S. regulatory pressure. Whether it fully satisfies lawmakers and national security agencies — and finally stabilizes TikTok’s U.S. future — will become clear as oversight and enforcement begin.</p>



<p><strong>Catch-up. </strong><a href="https://searchengineland.com/tiktok-us-deal-462607">$14 billion deal keeps TikTok alive in U.S.</a></p>


TikTok announced a new U.S.-based joint venture to meet federal national security requirements and keep the app available to more than 200 million Americans.
The entity, TikTok USDS Joint Venture LLC, was established under an executive order signed by President Trump on Sept. 25.
The big picture. TikTok USDS Joint Venture is majority American-owned and operates independently, with control over U.S. user data, content moderation, and algorithm security. 
ByteDance holds a 19.9% stake, below the threshold U.S. officials have often cited as a national security risk.
The joint venture expands TikTok’s existing U.S. Data Security program and is designed to isolate sensitive systems from foreign access.
Why we care. This joint venture could decide whether TikTok continues operating in the U.S. without bans or forced divestment. It moves control of U.S. user data, content moderation, and the recommendation algorithm to a majority American-owned, U.S.-governed entity, directly addressing long-standing national security concerns. For creators, advertisers, and rival platforms, it serves as a test case for how the U.S. may regulate foreign-owned technology going forward.
How the safeguards work. U.S. user data will be stored and protected in Oracle’s U.S.-based cloud, supported by ongoing audits and third-party cybersecurity certifications. 
The joint venture says its security program meets federal and industry standards, including NIST, ISO 27001, and CISA requirements.
The recommendation algorithm for U.S. users will be retrained, tested, and updated using U.S. data, then secured entirely within Oracle’s U.S. environment. 
The source code will undergo continuous review under formal software assurance protocols.
Trust, safety, and content moderation. Unlike earlier arrangements, the joint venture holds decision-making authority over trust and safety policies and content moderation for U.S. users. This control is designed to strengthen accountability and limit foreign influence over sensitive moderation decisions.
Global reach, U.S. control. While the joint venture oversees U.S. security and safety functions, TikTok’s global U.S. entities will continue to manage interoperability and commercial operations, including advertising, marketing, and ecommerce.
This structure keeps U.S. creators and businesses discoverable worldwide, TikTok said.
Who’s in charge. The joint venture is overseen by a seven-member board with a majority of American directors, including executives from Silver Lake, Oracle, Susquehanna International Group, and MGX.
Adam Presser was appointed CEO, and Will Farrell was named chief security officer.
The board’s security committee is chaired by Raul Fernandez, CEO of DXC Technology.
Ownership structure. Silver Lake, Oracle, and MGX are the joint venture’s three managing investors, each holding 15%. 
Additional investors include firms affiliated with Michael Dell, General Atlantic, Dragoneer, and Xavier Niel. 
The safeguards also extend to CapCut, Lemon8, and other TikTok-owned apps in the U.S.
What’s next. The announcement positions TikTok USDS Joint Venture as a long-term solution to U.S. regulatory pressure. Whether it fully satisfies lawmakers and national security agencies — and finally stabilizes TikTok’s U.S. future — will become clear as oversight and enforcement begin.
Catch-up. $14 billion deal keeps TikTok alive in U.S.

Majority U.S. ownership, Oracle-hosted data, and independent governance aim to end ban fears and give brands and creators a steadier outlook.

TikTok’s U.S. joint venture could reduce long-term uncertainty for brands

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting.png" class="attachment-large size-large wp-post-image" alt="Rubrics- The missing piece in AI prompting" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Prompts describe tasks. Rubrics define rules. Here’s how rubric-based prompting reduces hallucinations in search and content workflows.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting.png" class="attachment-large size-large wp-post-image" alt="Rubrics- The missing piece in AI prompting" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Rubrics-The-missing-piece-in-AI-prompting-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Generative AI has become a practical tool in search, content, and analytical workflows. </p>



<p>But, as adoption increases, so does a familiar and costly problem: confidently incorrect outputs.</p>



<p>Also called “<a href="https://searchengineland.com/guide/fix-your-brands-ai-hallucinations">hallucinations</a>,” the term implies that an AI model is malfunctioning. </p>



<p>But here’s the truth: This behavior is often predictable and results from unclear instructions. Or, more accurately, unclear <a href="https://searchengineland.com/guide/ai-prompts">prompts</a>.</p>



<p>For example, prompt AI for a “cookie recipe,” and nothing more. Don’t offer details about allergies, preferences, or constraints.&nbsp;</p>



<p>The result might be Christmas cookies in July, a peanut-packed option, or a recipe so bland and basic as to be unworthy of the name “sweet treat.” This lack of detail can lead to misaligned outputs.</p>



<p>It’s best to expect a model to misbehave and preempt this by creating explicit guardrails.&nbsp;</p>



<p>This can be done effectively with rubrics.</p>



<p>We’ll examine how rubric-based prompting works, why it improves factual reliability, and how you can apply it to AIs to produce more trustworthy results.&nbsp;</p>



<h2 class="wp-block-heading" id="h-fluency-vs-restraint-which-is-better">Fluency vs. restraint: Which is better?</h2>



<p>When AI is asked to produce complete, polished answers without specific instructions on how to handle uncertain information or missing data, it often prioritizes <strong>fluency </strong>over <strong>restraint</strong>.&nbsp;</p>



<p>That is, continuing the response smoothly (fluency) rather than pausing, qualifying, or declining to answer when information is missing (restraint).&nbsp;</p>



<p>This is the moment AI “makes stuff up” – because uncertainty was not established as a stopping point. The consequences can be financially costly and can also harm reputation, efficiency, and trust.</p>



<p>Professional service firm Deloitte was required to repay 440,000 Australian dollars after errors in an AI-assisted government report were found to include fabricated citations and a misattributed court quote, as <a href="https://apnews.com/article/australia-ai-errors-deloitte-ab54858680ffc4ae6555b31c8fb987f3" target="_blank" rel="noopener">reported by the Associated Press</a> in late 2025. </p>



<p>One academic reviewer noted that it:&nbsp;</p>



<ul class="wp-block-list">
<li>“Misquoted a court case then made up a quotation from a judge… misstating the law to the Australian government in a report that they rely on.”</li>
</ul>



<p>Should Deloitte have skipped the use of AI?&nbsp;</p>



<p>Evaluating data and generating reports is an AI superpower. The lesson here is to keep AI in the workflow, but to constrain<strong> </strong>it – define, in advance, what a model must do when it doesn’t know something.</p>



<p>This is where rubrics enter the fray.</p>



<h2 class="wp-block-heading" id="h-the-role-of-rubrics-in-ai">The role of rubrics in AI</h2>



<p>It’s common for users to implement generic safeguards against potential patterns of hallucination, but they often don’t hold up in practice.&nbsp;</p>



<p>Why not? Because they usually describe an outcome and not a decision-making process. This leaves the AI model to make inferences when required information isn’t available.</p>



<p>This is where rubric-based prompting is essential.</p>



<p>A rubric – a scoring guide or set of criteria to evaluate work – can feel like an old-school, academic concept.&nbsp;</p>



<p>Think of a grid teachers traditionally used to grade papers, often shared ahead of time so students knew what “good,” “OK,” and “not acceptable” papers looked like.&nbsp;</p>



<p>AI rubrics rely on the same structural idea but serve a different purpose.&nbsp;</p>



<p>Rather than scoring answers after prompting, they shape decision-making during the response generation process. </p>



<p>They do this by defining what an AI model should do when the required criteria cannot be met.</p>



<p>By defining explicit criteria, rubrics set clear boundaries, priorities, and even failure behaviors, reducing the risk of hallucination.</p>



<h2 class="wp-block-heading" id="h-writing-better-prompts-is-not-enough">Writing better prompts is not enough</h2>



<p>Advice around prompting often focuses on better wording. Typically, this implies being more specific or issuing clearer instructions. It may even mean nudging a model toward a specific format or tone.&nbsp;</p>



<p>These are not useless steps, and techniques of this kind can improve surface-level quality. But they will not erase the underlying cause of hallucination.</p>



<p>Users frequently prompt AI models with outcomes rather than rules. </p>



<p>Prompt phrases like “be accurate,” “cite sources,” or “use only verified information” sound sensible but leave too much space for interpretation. </p>



<p>The model will remain stuck deciding substantial details for itself.</p>



<p>Long or complex prompts can also create competing goals. </p>



<p>A single prompt might demand clarity, completeness, confidence, and speed – conflicting goals that can lead models to default behaviors, causing them to produce fluent and “complete” responses. </p>



<p>Without a clear hierarchy of priorities, accuracy may be lost or diminished.&nbsp;</p>



<p>Whereas a prompt might be effective at describing tasks, a rubric governs the decision-making process within tasks.</p>



<p>AI rubrics do this by switching decision-making from <strong>inference </strong>to <strong>explicit instruction</strong>.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/advanced-ai-prompt-engineering-strategies-seo-436286">Advanced AI prompt engineering strategies for SEO</a></em></strong></p>



<h2 class="wp-block-heading" id="h-what-rubrics-do-that-prompts-can-t">What rubrics do that prompts can’t</h2>



<p>Prompts focus on tone, format, and level of detail. </p>



<p>They frequently fail to address uncertainty. Missing or ambiguous information forces an AI model to decide whether to stop, qualify a response, or infer an answer. </p>



<p>Without human guidance, inference usually is the victor.</p>



<p>Rubrics cut down on ambiguity through the use of clear decision boundaries. </p>



<p>A rubric formally defines what is required, optional, and unacceptable. These criteria supply the model with a concrete framework to evaluate all outputs generated.</p>



<p>Identifying priorities explicitly means AI models are less likely to fill in the blanks to maintain fluency. </p>



<p>The rubric that clarifies which constraints matter can allow factual accuracy to take precedence over “completeness” or narrative flow. </p>



<p>Most importantly, a rubric defines failure behavior, what the model needs to do if success is impossible.&nbsp;</p>



<p>Strong rubrics establish that a model can acknowledge missing information, return a partial response, or even decline to answer rather than making up a single word.</p>



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<h2 class="wp-block-heading" id="h-anatomy-of-an-effective-ai-rubric">Anatomy of an effective AI rubric</h2>



<p>There is an old adage about “too many chefs spoiling the soup,” and this is the perfect analogy for rubric creation.&nbsp;</p>



<p>Effective AI rubrics don’t need to fill pages or show up as heavily detailed queries. In the same way a recipe can be ruined by fussiness or too many competing flavors, so too can a prompt be overdone.</p>



<p>Too many details or demands can introduce confusion. Reliable rubrics are those that focus on a small set of enforceable criteria that directly address the risks of hallucination.</p>



<p>At a minimum, a well-written rubric should include:</p>



<ul class="wp-block-list">
<li><strong>Accuracy requirements:</strong> Clear rules about what must be supported, what counts as evidence, and whether approximation is unacceptable.</li>



<li><strong>Source expectations:</strong> Guidance on whether sources must be provided, whether they are to come from supplied materials, or how to handle conflicting information.</li>



<li><strong>Uncertainty handling:</strong> Explicit instructions for what the model must do when information is unavailable, ambiguous, or incomplete.</li>



<li><strong>Confidence/tone constraints:</strong> Limitations on tone to prevent speculative answers from being presented with certainty.</li>



<li><strong>Failure behavior:</strong> Permission and preference for stopping, qualifying, or deferring rather than guessing.</li>
</ul>



<h2 class="wp-block-heading" id="h-how-to-create-a-rubric-for-an-ai-model">How to create a rubric for an AI model</h2>



<p>A rubric doesn&#8217;t make an AI model smarter, it makes its decision-making process more reliable.</p>



<p>Here’s an example of a competitive analysis to explain the value of rubrics:</p>



<p>A team asks an Al model to explain why their competitors are outperforming them in search results, and what they can do about it. Their prompt is written like this:</p>



<ul class="wp-block-list">
<li>“Evaluate why [competitor] is outranking us for [specific topic]. Identify the keywords they rank for, the SERP features they win, and recommend changes to our content strategy.”</li>
</ul>



<p>On the surface, this seems reasonable. In practice, it is an invitation for hallucination.</p>



<p>The prompt lacks concrete inputs and the model has no constraints. The risk is high that the AI will invent plausible-sounding rankings, features, and strategic conclusions.</p>



<h3 class="wp-block-heading" id="h-writing-the-rubric">Writing the rubric</h3>



<p>In practice, your rubric is included directly within the prompt. It must be clearly separated from the task, which describes what to analyze or generate.&nbsp;</p>



<p>The rubric then defines the rules the model must follow to perform its task.&nbsp;</p>



<p>This is a critical distinction: prompts ask for outputs, while rubrics govern how that prompt is created.</p>



<p>Using the criteria in the section above, the prompt, followed by the rubric, would now read:</p>



<ul class="wp-block-list">
<li>“Analyze why [competitor] may be outperforming our site for [topic]. Provide insights and recommendations.
<ul class="wp-block-list">
<li>Do not claim rankings, traffic, or SERP features unless explicitly provided in the prompt.</li>



<li>If required data is missing, state what cannot be determined and list the inputs needed.</li>



<li>Frame recommendations as conditional when evidence is incomplete. Avoid definitive language without supporting data.</li>



<li>If analysis cannot be completed reliably, return a partial response rather than guessing.”</li>
</ul>
</li>
</ul>



<p>When the rubric is incorporated, the model can’t infer. Instead, it treats uncertainty as a constraint.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/proxies-for-prompts-466351">Proxies for prompts: Emulate how your audience may be looking for you</a></em></strong></p>



<h2 class="wp-block-heading" id="h-how-rubrics-and-prompts-work-together">How rubrics and prompts work together</h2>



<p>As seen in the example above, rubrics don’t replace the prompt. They add to and often come after the prompt. They should be viewed as a stabilizing layer.</p>



<p>The prompt is always responsible for defining the task: what is summarized, analyzed, or generated. Rubrics define the rules under which that task is performed.&nbsp;</p>



<p>In practice, prompts can vary, while rubrics remain relatively stable across similar types of work, regardless of the topic. Defining sourcing, uncertainty, and failure behavior stays consistent, reducing error rates over time.</p>



<p>For many workflows, a rubric can be embedded directly after the prompt. In others, they can be referenced or applied programmatically – for example, through reusable templates, automated checks, or system instructions. The format doesn’t matter, only the clarity of the criteria.</p>



<h2 class="wp-block-heading" id="h-avoid-overengineering">Avoid overengineering</h2>



<p>Despite their effectiveness, rubrics can be easy to misuse. A common mistake users make is <strong>overengineering</strong>.</p>



<p>The rubric that seeks to anticipate every possible scenario often results in an unwieldy, inconsistent one.&nbsp;</p>



<p>Another mistake involves adding conflicting criteria without clarifying which takes precedence.</p>



<p>Rubrics must be concise, prioritized, and explicit about failure behavior to reduce hallucinations.</p>



<h2 class="wp-block-heading" id="h-use-ai-rubrics-like-a-pro">Use AI rubrics like a pro</h2>



<p>Prompting like a pro is about anticipating where AI will be forced to guess, then defining and constraining how it operates.</p>



<p>Rubrics tell AI models to slow down, qualify, or stop when information is missing. In doing so, rubrics can help you leverage the power of AI for your work and create outputs that are accurate and trustworthy.</p>

Generative AI has become a practical tool in search, content, and analytical workflows. 
But, as adoption increases, so does a familiar and costly problem: confidently incorrect outputs.
Also called “hallucinations,” the term implies that an AI model is malfunctioning. 
But here’s the truth: This behavior is often predictable and results from unclear instructions. Or, more accurately, unclear prompts.
For example, prompt AI for a “cookie recipe,” and nothing more. Don’t offer details about allergies, preferences, or constraints. 
The result might be Christmas cookies in July, a peanut-packed option, or a recipe so bland and basic as to be unworthy of the name “sweet treat.” This lack of detail can lead to misaligned outputs.
It’s best to expect a model to misbehave and preempt this by creating explicit guardrails. 
This can be done effectively with rubrics.
We’ll examine how rubric-based prompting works, why it improves factual reliability, and how you can apply it to AIs to produce more trustworthy results. 
Fluency vs. restraint: Which is better?
When AI is asked to produce complete, polished answers without specific instructions on how to handle uncertain information or missing data, it often prioritizes fluency over restraint. 
That is, continuing the response smoothly (fluency) rather than pausing, qualifying, or declining to answer when information is missing (restraint). 
This is the moment AI “makes stuff up” – because uncertainty was not established as a stopping point. The consequences can be financially costly and can also harm reputation, efficiency, and trust.
Professional service firm Deloitte was required to repay 440,000 Australian dollars after errors in an AI-assisted government report were found to include fabricated citations and a misattributed court quote, as reported by the Associated Press in late 2025. 
One academic reviewer noted that it: 
“Misquoted a court case then made up a quotation from a judge… misstating the law to the Australian government in a report that they rely on.”
Should Deloitte have skipped the use of AI? 
Evaluating data and generating reports is an AI superpower. The lesson here is to keep AI in the workflow, but to constrain it – define, in advance, what a model must do when it doesn’t know something.
This is where rubrics enter the fray.
The role of rubrics in AI
It’s common for users to implement generic safeguards against potential patterns of hallucination, but they often don’t hold up in practice. 
Why not? Because they usually describe an outcome and not a decision-making process. This leaves the AI model to make inferences when required information isn’t available.
This is where rubric-based prompting is essential.
A rubric – a scoring guide or set of criteria to evaluate work – can feel like an old-school, academic concept. 
Think of a grid teachers traditionally used to grade papers, often shared ahead of time so students knew what “good,” “OK,” and “not acceptable” papers looked like. 
AI rubrics rely on the same structural idea but serve a different purpose. 
Rather than scoring answers after prompting, they shape decision-making during the response generation process. 
They do this by defining what an AI model should do when the required criteria cannot be met.
By defining explicit criteria, rubrics set clear boundaries, priorities, and even failure behaviors, reducing the risk of hallucination.
Writing better prompts is not enough
Advice around prompting often focuses on better wording. Typically, this implies being more specific or issuing clearer instructions. It may even mean nudging a model toward a specific format or tone. 
These are not useless steps, and techniques of this kind can improve surface-level quality. But they will not erase the underlying cause of hallucination.
Users frequently prompt AI models with outcomes rather than rules. 
Prompt phrases like “be accurate,” “cite sources,” or “use only verified information” sound sensible but leave too much space for interpretation. 
The model will remain stuck deciding substantial details for itself.
Long or complex prompts can also create competing goals. 
A single prompt might demand clarity, completeness, confidence, and speed – conflicting goals that can lead models to default behaviors, causing them to produce fluent and “complete” responses. 
Without a clear hierarchy of priorities, accuracy may be lost or diminished. 
Whereas a prompt might be effective at describing tasks, a rubric governs the decision-making process within tasks.
AI rubrics do this by switching decision-making from inference to explicit instruction.
Dig deeper: Advanced AI prompt engineering strategies for SEO
What rubrics do that prompts can’t
Prompts focus on tone, format, and level of detail. 
They frequently fail to address uncertainty. Missing or ambiguous information forces an AI model to decide whether to stop, qualify a response, or infer an answer. 
Without human guidance, inference usually is the victor.
Rubrics cut down on ambiguity through the use of clear decision boundaries. 
A rubric formally defines what is required, optional, and unacceptable. These criteria supply the model with a concrete framework to evaluate all outputs generated.
Identifying priorities explicitly means AI models are less likely to fill in the blanks to maintain fluency. 
The rubric that clarifies which constraints matter can allow factual accuracy to take precedence over “completeness” or narrative flow. 
Most importantly, a rubric defines failure behavior, what the model needs to do if success is impossible. 
Strong rubrics establish that a model can acknowledge missing information, return a partial response, or even decline to answer rather than making up a single word.
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See terms.
Anatomy of an effective AI rubric
There is an old adage about “too many chefs spoiling the soup,” and this is the perfect analogy for rubric creation. 
Effective AI rubrics don’t need to fill pages or show up as heavily detailed queries. In the same way a recipe can be ruined by fussiness or too many competing flavors, so too can a prompt be overdone.
Too many details or demands can introduce confusion. Reliable rubrics are those that focus on a small set of enforceable criteria that directly address the risks of hallucination.
At a minimum, a well-written rubric should include:
Accuracy requirements: Clear rules about what must be supported, what counts as evidence, and whether approximation is unacceptable.
Source expectations: Guidance on whether sources must be provided, whether they are to come from supplied materials, or how to handle conflicting information.
Uncertainty handling: Explicit instructions for what the model must do when information is unavailable, ambiguous, or incomplete.
Confidence/tone constraints: Limitations on tone to prevent speculative answers from being presented with certainty.
Failure behavior: Permission and preference for stopping, qualifying, or deferring rather than guessing.
How to create a rubric for an AI model
A rubric doesn’t make an AI model smarter, it makes its decision-making process more reliable.
Here’s an example of a competitive analysis to explain the value of rubrics:
A team asks an Al model to explain why their competitors are outperforming them in search results, and what they can do about it. Their prompt is written like this:
“Evaluate why [competitor] is outranking us for [specific topic]. Identify the keywords they rank for, the SERP features they win, and recommend changes to our content strategy.”
On the surface, this seems reasonable. In practice, it is an invitation for hallucination.
The prompt lacks concrete inputs and the model has no constraints. The risk is high that the AI will invent plausible-sounding rankings, features, and strategic conclusions.
Writing the rubric
In practice, your rubric is included directly within the prompt. It must be clearly separated from the task, which describes what to analyze or generate. 
The rubric then defines the rules the model must follow to perform its task. 
This is a critical distinction: prompts ask for outputs, while rubrics govern how that prompt is created.
Using the criteria in the section above, the prompt, followed by the rubric, would now read:
“Analyze why [competitor] may be outperforming our site for [topic]. Provide insights and recommendations.

Do not claim rankings, traffic, or SERP features unless explicitly provided in the prompt.
If required data is missing, state what cannot be determined and list the inputs needed.
Frame recommendations as conditional when evidence is incomplete. Avoid definitive language without supporting data.
If analysis cannot be completed reliably, return a partial response rather than guessing.”
When the rubric is incorporated, the model can’t infer. Instead, it treats uncertainty as a constraint.
Dig deeper: Proxies for prompts: Emulate how your audience may be looking for you
How rubrics and prompts work together
As seen in the example above, rubrics don’t replace the prompt. They add to and often come after the prompt. They should be viewed as a stabilizing layer.
The prompt is always responsible for defining the task: what is summarized, analyzed, or generated. Rubrics define the rules under which that task is performed. 
In practice, prompts can vary, while rubrics remain relatively stable across similar types of work, regardless of the topic. Defining sourcing, uncertainty, and failure behavior stays consistent, reducing error rates over time.
For many workflows, a rubric can be embedded directly after the prompt. In others, they can be referenced or applied programmatically – for example, through reusable templates, automated checks, or system instructions. The format doesn’t matter, only the clarity of the criteria.
Avoid overengineering
Despite their effectiveness, rubrics can be easy to misuse. A common mistake users make is overengineering.
The rubric that seeks to anticipate every possible scenario often results in an unwieldy, inconsistent one. 
Another mistake involves adding conflicting criteria without clarifying which takes precedence.
Rubrics must be concise, prioritized, and explicit about failure behavior to reduce hallucinations.
Use AI rubrics like a pro
Prompting like a pro is about anticipating where AI will be forced to guess, then defining and constraining how it operates.
Rubrics tell AI models to slow down, qualify, or stop when information is missing. In doing so, rubrics can help you leverage the power of AI for your work and create outputs that are accurate and trustworthy.

Prompts describe tasks. Rubrics define rules. Here’s how rubric-based prompting reduces hallucinations in search and content workflows.

A smarter way to approach AI prompting

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management.png" class="attachment-large size-large wp-post-image" alt="Agentic AI and vibe coding: The next evolution of PPC management" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Agentic AI and custom-built tools are changing how PPC accounts are run – and what marketers need to focus on next.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management.png" class="attachment-large size-large wp-post-image" alt="Agentic AI and vibe coding: The next evolution of PPC management" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/Agentic-AI-and-vibe-coding-The-next-evolution-of-PPC-management-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Automation has been reshaping <a href="https://searchengineland.com/guide/what-is-paid-search">PPC</a> account management for years, from rules, <a href="https://searchengineland.com/google-ads-scripts-everything-you-need-to-know-450294">scripts</a>, and API-driven workflows inside Google Ads.&nbsp;</p>



<p>Most marketers are already comfortable with <a href="https://searchengineland.com/automated-bidding-google-ads-best-results-450204">automated bidding</a>, data-driven optimization, and <a href="https://searchengineland.com/when-to-trust-google-ads-ai-and-when-you-shouldnt-461668">other AI-powered enhancements</a>.</p>



<p>The next shift goes further. Two developments in particular are changing how PPC campaigns are managed and optimized: <a href="https://searchengineland.com/ai-agents-ppc-what-to-know-build-457318">AI agents</a> and <a href="https://searchengineland.com/vibe-coding-with-ai-tools-a-marketers-guide-455134">vibe coding</a>.</p>



<p>Together, they point to a more autonomous way of working, where execution increasingly moves to AI – while marketers focus on strategy, systems, and creative direction.&nbsp;</p>



<p>This shift unlocks new levels of efficiency and flexibility, but it also changes what effective PPC management looks like.</p>



<h2 class="wp-block-heading" id="h-agentic-ai-google-ads-has-its-own-agentic-ai-integrated">Agentic AI: Google Ads has its own agentic AI integrated</h2>



<p>Google <a href="https://searchengineland.com/google-launches-ai-powered-advisors-464571">released its Agentic Ads Advisor</a> in November 2025.&nbsp;</p>



<p>The tool uses the latest Gemini models to help advertisers surface insights and improve campaign performance.</p>



<figure class="wp-block-video aligncenter"><video controls src="https://storage.googleapis.com/gweb-uniblog-publish-prod/original_videos/Advisor_Hero_1_BThomrB.mp4#t=0.001"></video></figure>



<p>Google describes Ads Advisor as:&nbsp;</p>



<ul class="wp-block-list">
<li>“[Y]our AI partner that helps you proactively manage campaigns directly within Google Ads. It helps you understand your business context and simplifies your work by learning from your interactions to improve campaign results.”</li>
</ul>



<p>The goal is to help advertisers analyze and optimize campaigns more efficiently.&nbsp;</p>



<p>But it raises an important question: what should an agentic AI tool actually do?</p>



<p>An agentic AI should function as an autonomous agent.&nbsp;</p>



<p>It should surface information when needed, but it should also be able to operate independently when appropriate.&nbsp;</p>



<p>That includes identifying opportunities to improve campaign setup, assets and ad copy, search terms, and other inputs.&nbsp;</p>



<p>More importantly, it should be capable of implementing certain changes, not just recommending them.</p>



<p>That is where agentic AI needs to go. As <a href="https://searchengineland.com/author/jyll-saskin-gales">Jyll Saskin Gales</a> <a href="https://searchengineland.com/googles-new-ads-advisor-ai-is-put-to-the-test-464663">noted after testing the tool</a>, Google’s Ads Advisor is useful in places but not yet capable of acting autonomously.</p>



<h3 class="wp-block-heading" id="h-how-agentic-ai-can-be-used-in-ppc-workflows">How agentic AI can be used in PPC workflows</h3>



<p>AI agents are meant to be autonomous.&nbsp;</p>



<p>They should be able to make decisions without constant human input, actively managing, adjusting, and optimizing campaigns in real time.&nbsp;</p>



<p>If an agentic AI only provides advice or reporting, much of its potential is lost.</p>



<p>In practical terms, agentic AI can handle bidding strategies, ad placements, audience targeting, and creative testing.&nbsp;</p>



<p>Instead of simply adjusting bids or budgets, it can make decisions on the fly, optimizing campaigns based on live performance data, seasonality, competitive activity, and user behavior trends.</p>



<p>This represents a fundamental shift in how PPC accounts are managed.&nbsp;</p>



<p>As agentic AI takes on more operational work, PPC professionals can spend more time on strategic decision-making.</p>



<p>Over time, it is likely that many advertisers will rely on the same algorithms, campaign types, and AI agents.&nbsp;</p>



<p>When that happens, competitive advantage will depend less on tooling and more on strategy.&nbsp;</p>



<p>Differentiation will come from classic marketing fundamentals:&nbsp;</p>



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



<li>Value propositions.</li>



<li>Offers.</li>



<li>Website quality.</li>



<li>Brand awareness.</li>



<li>Creative assets.&nbsp;</li>
</ul>



<p>Those are the areas where marketers can still outpace competitors using the same AI-driven systems.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/agentic-ppc-what-performance-marketing-could-look-like-in-2030-463419">Agentic PPC: What performance marketing could look like in 2030</a></em></strong></p>



<h3 class="wp-block-heading" id="h-why-agentic-ai-is-relevant-for-advanced-ppc-marketers">Why agentic AI is relevant for advanced PPC marketers</h3>



<p>For experienced PPC marketers, the appeal of agentic AI lies in its ability to scale campaigns without sacrificing strategic control.&nbsp;</p>



<p>That is where it becomes a true game-changer.</p>



<ul class="wp-block-list">
<li><strong>Real-time optimization:</strong> Instead of waiting a full day for bid adjustments to take effect, agentic AI can respond within minutes, allowing campaigns to adapt quickly to changing market conditions.</li>



<li><strong>Data-driven creativity:</strong> Agentic AI is not limited to performance metrics. It can analyze creative elements and audience interactions, testing combinations of visuals, copy, and CTAs to identify top-performing ads.</li>



<li><strong>Reduced human error:</strong> With less manual intervention, the risk of mistakes or missed opportunities declines. This allows PPC professionals to spend more time on higher-level strategy rather than execution.</li>
</ul>



<p>Despite the potential, agentic AI still requires informed oversight.&nbsp;</p>



<p>PPC professionals must understand how to evaluate and apply AI outputs, especially when aligning decisions with broader marketing objectives.</p>



<p>That matters because current tools are still limited. Google’s own agentic AI implementation still has limitations.&nbsp;</p>



<p>In addition, many advertisers want tools that operate according to their own rules and priorities.</p>



<p>That is where vibe coding comes in.</p>



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<h2 class="wp-block-heading" id="h-vibe-coding-how-to-build-your-own-tools">Vibe coding: How to build your own tools</h2>



<p>In parallel with the rise of agentic AI, another concept is gaining traction in marketing: <a href="https://searchengineland.com/scaling-ppc-ai-automation-scripts-data-custom-tools-461503">vibe coding</a>.&nbsp;</p>



<p>At its core, vibe coding is a way of working with AI-powered platforms to build more personalized, intuitive, and data-driven campaigns, tools, landing pages, or other systems.&nbsp;</p>



<p>In short, vibe coding lets you act as a developer, even if you are not one.</p>



<p>With tools such as Cursor, Lovable, and AI Studio, you can describe what you need and let the system build it.&nbsp;</p>



<p>By refining prompts over time, you can end up with a personalized tool that does exactly what you want, in your own style.</p>



<p>Vibe coding has been especially valuable in my own work.&nbsp;</p>



<p>Professionally, I have built tools such as:</p>



<ul class="wp-block-list">
<li>An SEO schema markup generator.</li>



<li>A campaign and SEO audit tool.</li>



<li>A system that generates marketing ideas by simply entering a website URL.&nbsp;</li>
</ul>



<p>It has also extended beyond work, including:</p>



<ul class="wp-block-list">
<li>A tool that tracks daily calorie and nutrition intake.</li>



<li>Another that creates custom CrossFit workouts based on Garmin and Strava data.&nbsp;</li>
</ul>



<p>Once you start building this way, it becomes easy to keep expanding what you create.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/vibe-coding-search-marketing-workflows-466661">How vibe coding is changing search marketing workflows</a></em></strong></p>



<h3 class="wp-block-heading" id="h-applying-vibe-coding-to-ppc-workflows">Applying vibe coding to PPC workflows</h3>



<p>Beyond building standalone tools, vibe coding becomes more powerful when combined with agentic AI.&nbsp;</p>



<p>That combination allows marketers to build their own AI agents for PPC work.</p>



<p><a href="https://searchengineland.com/author/frederick-vallaeys">Frederick Vallaeys</a> has shown <a href="https://searchengineland.com/ppc-vibe-coding-seasonality-analysis-tool-460968">how to build custom tools for PPC campaigns</a>, though his example relies on manually entering data before the tool can operate.&nbsp;</p>



<p>By adding an AI agent layer, that step can be automated.</p>



<p>Instead of manual inputs, the agent can pull data through the Google Ads API, process and format it as needed, and then execute specific tasks.&nbsp;</p>



<p>In Vallaeys’ example, that task is seasonality analysis.</p>



<p>From there, the possibilities expand.&nbsp;</p>



<p>You can build:</p>



<ul class="wp-block-list">
<li>A keyword agent to identify new opportunities.</li>



<li>An ad copy agent that generates creative based on performance data.</li>



<li>A creative agent that produces new image assets.&nbsp;</li>
</ul>



<p>Data agents, video agents, and other specialized agents can be connected into a single system, resulting in a custom agentic AI tool built through vibe coding.</p>



<h2 class="wp-block-heading" id="h-the-future-where-agentic-ai-and-vibe-coding-will-take-ppc">The future: Where agentic AI and vibe coding will take PPC</h2>



<p>The rise of these technologies brings both challenges and opportunities.&nbsp;</p>



<p>By embracing agentic AI and vibe coding, PPC marketers can streamline operations, improve campaign performance, and stay competitive while also standing out from peers.</p>



<p>The future of PPC is autonomous, data-driven, and more personalized than ever.&nbsp;</p>



<p>Embracing agentic AI and vibe coding creates a clear advantage for marketers who understand how to apply them effectively.&nbsp;</p>



<p>That advantage benefits internal teams and, ultimately, customers.</p>



<p>These technologies are not here to replace PPC professionals.&nbsp;</p>



<p>They are designed to extend capabilities, reduce manual effort, and enable better results with less friction.&nbsp;</p>



<p>PPC is becoming increasingly AI-powered, and adapting to that shift is no longer optional.</p>



<p>For practical examples of how AI agents and vibe coding are already being applied, follow <a href="https://www.linkedin.com/in/alfred-simon/">Alfred Simon</a>, <a href="https://au.linkedin.com/in/mikerhodesideas">Mike Rhodes</a>, and <a href="https://nl.linkedin.com/in/alessturala/">Ales Sturala</a>.</p>

Automation has been reshaping PPC account management for years, from rules, scripts, and API-driven workflows inside Google Ads. 
Most marketers are already comfortable with automated bidding, data-driven optimization, and other AI-powered enhancements.
The next shift goes further. Two developments in particular are changing how PPC campaigns are managed and optimized: AI agents and vibe coding.
Together, they point to a more autonomous way of working, where execution increasingly moves to AI – while marketers focus on strategy, systems, and creative direction. 
This shift unlocks new levels of efficiency and flexibility, but it also changes what effective PPC management looks like.
Agentic AI: Google Ads has its own agentic AI integrated
Google released its Agentic Ads Advisor in November 2025. 
The tool uses the latest Gemini models to help advertisers surface insights and improve campaign performance.




Google describes Ads Advisor as: 
“[Y]our AI partner that helps you proactively manage campaigns directly within Google Ads. It helps you understand your business context and simplifies your work by learning from your interactions to improve campaign results.”
The goal is to help advertisers analyze and optimize campaigns more efficiently. 
But it raises an important question: what should an agentic AI tool actually do?
An agentic AI should function as an autonomous agent. 
It should surface information when needed, but it should also be able to operate independently when appropriate. 
That includes identifying opportunities to improve campaign setup, assets and ad copy, search terms, and other inputs. 
More importantly, it should be capable of implementing certain changes, not just recommending them.
That is where agentic AI needs to go. As Jyll Saskin Gales noted after testing the tool, Google’s Ads Advisor is useful in places but not yet capable of acting autonomously.
How agentic AI can be used in PPC workflows
AI agents are meant to be autonomous. 
They should be able to make decisions without constant human input, actively managing, adjusting, and optimizing campaigns in real time. 
If an agentic AI only provides advice or reporting, much of its potential is lost.
In practical terms, agentic AI can handle bidding strategies, ad placements, audience targeting, and creative testing. 
Instead of simply adjusting bids or budgets, it can make decisions on the fly, optimizing campaigns based on live performance data, seasonality, competitive activity, and user behavior trends.
This represents a fundamental shift in how PPC accounts are managed. 
As agentic AI takes on more operational work, PPC professionals can spend more time on strategic decision-making.
Over time, it is likely that many advertisers will rely on the same algorithms, campaign types, and AI agents. 
When that happens, competitive advantage will depend less on tooling and more on strategy. 
Differentiation will come from classic marketing fundamentals: 
Positioning.
Value propositions.
Offers.
Website quality.
Brand awareness.
Creative assets. 
Those are the areas where marketers can still outpace competitors using the same AI-driven systems.
Dig deeper: Agentic PPC: What performance marketing could look like in 2030
Why agentic AI is relevant for advanced PPC marketers
For experienced PPC marketers, the appeal of agentic AI lies in its ability to scale campaigns without sacrificing strategic control. 
That is where it becomes a true game-changer.
Real-time optimization: Instead of waiting a full day for bid adjustments to take effect, agentic AI can respond within minutes, allowing campaigns to adapt quickly to changing market conditions.
Data-driven creativity: Agentic AI is not limited to performance metrics. It can analyze creative elements and audience interactions, testing combinations of visuals, copy, and CTAs to identify top-performing ads.
Reduced human error: With less manual intervention, the risk of mistakes or missed opportunities declines. This allows PPC professionals to spend more time on higher-level strategy rather than execution.
Despite the potential, agentic AI still requires informed oversight. 
PPC professionals must understand how to evaluate and apply AI outputs, especially when aligning decisions with broader marketing objectives.
That matters because current tools are still limited. Google’s own agentic AI implementation still has limitations. 
In addition, many advertisers want tools that operate according to their own rules and priorities.
That is where vibe coding comes in.
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See terms.
Vibe coding: How to build your own tools
In parallel with the rise of agentic AI, another concept is gaining traction in marketing: vibe coding. 
At its core, vibe coding is a way of working with AI-powered platforms to build more personalized, intuitive, and data-driven campaigns, tools, landing pages, or other systems. 
In short, vibe coding lets you act as a developer, even if you are not one.
With tools such as Cursor, Lovable, and AI Studio, you can describe what you need and let the system build it. 
By refining prompts over time, you can end up with a personalized tool that does exactly what you want, in your own style.
Vibe coding has been especially valuable in my own work. 
Professionally, I have built tools such as:
An SEO schema markup generator.
A campaign and SEO audit tool.
A system that generates marketing ideas by simply entering a website URL. 
It has also extended beyond work, including:
A tool that tracks daily calorie and nutrition intake.
Another that creates custom CrossFit workouts based on Garmin and Strava data. 
Once you start building this way, it becomes easy to keep expanding what you create.
Dig deeper: How vibe coding is changing search marketing workflows
Applying vibe coding to PPC workflows
Beyond building standalone tools, vibe coding becomes more powerful when combined with agentic AI. 
That combination allows marketers to build their own AI agents for PPC work.
Frederick Vallaeys has shown how to build custom tools for PPC campaigns, though his example relies on manually entering data before the tool can operate. 
By adding an AI agent layer, that step can be automated.
Instead of manual inputs, the agent can pull data through the Google Ads API, process and format it as needed, and then execute specific tasks. 
In Vallaeys’ example, that task is seasonality analysis.
From there, the possibilities expand. 
You can build:
A keyword agent to identify new opportunities.
An ad copy agent that generates creative based on performance data.
A creative agent that produces new image assets. 
Data agents, video agents, and other specialized agents can be connected into a single system, resulting in a custom agentic AI tool built through vibe coding.
The future: Where agentic AI and vibe coding will take PPC
The rise of these technologies brings both challenges and opportunities. 
By embracing agentic AI and vibe coding, PPC marketers can streamline operations, improve campaign performance, and stay competitive while also standing out from peers.
The future of PPC is autonomous, data-driven, and more personalized than ever. 
Embracing agentic AI and vibe coding creates a clear advantage for marketers who understand how to apply them effectively. 
That advantage benefits internal teams and, ultimately, customers.
These technologies are not here to replace PPC professionals. 
They are designed to extend capabilities, reduce manual effort, and enable better results with less friction. 
PPC is becoming increasingly AI-powered, and adapting to that shift is no longer optional.
For practical examples of how AI agents and vibe coding are already being applied, follow Alfred Simon, Mike Rhodes, and Ales Sturala.

Agentic AI and custom-built tools are changing how PPC accounts are run – and what marketers need to focus on next.

Agentic AI and vibe coding: The next evolution of PPC management

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google warns that a court-ordered ad syndication could expose its ad algorithms, increase click fraud, and deliver less relevant traffic.

<div><img width="800" height="450" src="https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-800x450.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-800x450.jpg 800w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-600x338.jpg 600w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-200x113.jpg 200w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-1536x864.jpg 1536w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465-150x84.jpg 150w, https://searchengineland.com/wp-content/seloads/2022/07/Shutterstock_2020736465.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google is asking a federal judge to pause the DOJ’s antitrust remedies, warning that forced search and ad syndication would expose its proprietary technology and hurt advertisers.</p>



<p>The argument appears in a new affidavit from Jesse Adkins, Google’s director of product management for search and ads syndication, filed Jan. 16 in support of the company’s motion to pause Judge Amit Mehta’s final judgment while it appeals.</p>



<p><strong>The big picture</strong>. Adkins’ affidavit centers on damage that can&#8217;t be undone. It warns of forced exposure of proprietary ad technology, harm to advertisers, and loss of control over query and pricing data.</p>



<ul class="wp-block-list">
<li>Mehta’s final judgment would require Google to license its search results, features, and search text ads to any “qualified competitor” for five years, on terms no worse than its current deals.</li>



<li>Google argues that enforcing these remedies before the appeal is resolved would trigger immediate and irreversible harm.</li>
</ul>



<p><strong>Risk to Google’s ad technology</strong>. At the core of Google’s warning is the risk of exposing its search ads auction, built through decades of research and development by thousands of engineers.</p>



<ul class="wp-block-list">
<li>Large-scale syndication would allow competitors or third parties to reverse-engineer Google’s ad targeting, relevance signals, and auction mechanics, Adkins argued.</li>



<li>Data could then be used to train rival ad systems, eroding its competitive advantage, Google said.</li>
</ul>



<p><strong>Sub-syndication amplifies risk</strong>. The judgment allows competitors to redistribute Google ads to third parties, creating multiple layers where scraping and misuse are harder to detect.</p>



<ul class="wp-block-list">
<li>Even compliant partners would have little incentive to police downstream actors, effectively turning its ad system into a quasi-open utility with limited safeguards, Google said.</li>
</ul>



<p><strong>Advertisers could face fraud</strong>. Advertisers are caught in the crossfire, according to Adkins. The affidavit details “trick-to-click” tactics and query manipulation designed to drive accidental clicks or inflate costs.</p>



<ul class="wp-block-list">
<li>One example describes a syndicator appending high-income country names to queries while routing low-cost foreign traffic to the ads, generating tens of millions of dollars in click fraud over just two months. </li>



<li>Users may see less relevant ads, advertisers still pay, and conversion rates could collapse.</li>
</ul>



<p><strong>Pricing uncertainty</strong>. The final judgment also requires Google to offer syndication terms “no worse than” existing deals. Those arrangements are highly bespoke, tailored to each partner’s traffic quality and technical setup, Adkins noted.</p>



<ul class="wp-block-list">
<li>Applying these terms broadly could force below-market pricing and create financial uncertainty tied to unpredictable query volumes.</li>
</ul>



<p><strong>Irreversibility is key</strong>. Throughout the affidavit, Adkins emphasizes that the potential harm is irreversible. Once proprietary ad signals are exposed, they can&#8217;t be recovered.</p>



<ul class="wp-block-list">
<li>Once advertisers lose trust, it cannot be restored. </li>



<li>Once competitors build products on Google’s systems, the market impact becomes permanent. </li>



<li>Google argues that even a successful appeal would come too late to undo the damage.</li>
</ul>



<p><strong>Why we care.</strong> Court-ordered ad syndication could weaken Google’s control over ad placement and targeting, leading to less relevant ads and lower conversion rates. In short, the affidavit warns of higher costs, lower ROI, and less predictable campaign performance.</p>



<p><strong>What’s next</strong>. The court will decide whether to pause enforcement of the syndication remedies during Google’s appeal. Without a stay, Google would have to begin licensing search ads and results to qualified competitors under the new rules, reshaping the search advertising ecosystem in ways the company says would reach far beyond its own operations.</p>



<p><strong>Dig deeper.</strong> &nbsp;</p>



<ul class="wp-block-list">
<li><a href="https://www.courtlistener.com/docket/18552824/1471/3/united-states-of-america-v-google-llc/">Affidavit of Jesse Adkins — Document #1471, Attachment #3</a></li>



<li><a href="https://searchengineland.com/google-elizabeth-reid-affidavit-antitrust-467838">Google outlines risks of exposing its search index, rankings, and live results</a></li>



<li><a href="https://searchengineland.com/google-keep-chrome-exclusive-search-deals-end-461517">Google can keep Chrome, but exclusive search deals must end</a></li>
</ul>


Google is asking a federal judge to pause the DOJ’s antitrust remedies, warning that forced search and ad syndication would expose its proprietary technology and hurt advertisers.
The argument appears in a new affidavit from Jesse Adkins, Google’s director of product management for search and ads syndication, filed Jan. 16 in support of the company’s motion to pause Judge Amit Mehta’s final judgment while it appeals.
The big picture. Adkins’ affidavit centers on damage that can’t be undone. It warns of forced exposure of proprietary ad technology, harm to advertisers, and loss of control over query and pricing data.
Mehta’s final judgment would require Google to license its search results, features, and search text ads to any “qualified competitor” for five years, on terms no worse than its current deals.
Google argues that enforcing these remedies before the appeal is resolved would trigger immediate and irreversible harm.
Risk to Google’s ad technology. At the core of Google’s warning is the risk of exposing its search ads auction, built through decades of research and development by thousands of engineers.
Large-scale syndication would allow competitors or third parties to reverse-engineer Google’s ad targeting, relevance signals, and auction mechanics, Adkins argued.
Data could then be used to train rival ad systems, eroding its competitive advantage, Google said.
Sub-syndication amplifies risk. The judgment allows competitors to redistribute Google ads to third parties, creating multiple layers where scraping and misuse are harder to detect.
Even compliant partners would have little incentive to police downstream actors, effectively turning its ad system into a quasi-open utility with limited safeguards, Google said.
Advertisers could face fraud. Advertisers are caught in the crossfire, according to Adkins. The affidavit details “trick-to-click” tactics and query manipulation designed to drive accidental clicks or inflate costs.
One example describes a syndicator appending high-income country names to queries while routing low-cost foreign traffic to the ads, generating tens of millions of dollars in click fraud over just two months. 
Users may see less relevant ads, advertisers still pay, and conversion rates could collapse.
Pricing uncertainty. The final judgment also requires Google to offer syndication terms “no worse than” existing deals. Those arrangements are highly bespoke, tailored to each partner’s traffic quality and technical setup, Adkins noted.
Applying these terms broadly could force below-market pricing and create financial uncertainty tied to unpredictable query volumes.
Irreversibility is key. Throughout the affidavit, Adkins emphasizes that the potential harm is irreversible. Once proprietary ad signals are exposed, they can’t be recovered.
Once advertisers lose trust, it cannot be restored. 
Once competitors build products on Google’s systems, the market impact becomes permanent. 
Google argues that even a successful appeal would come too late to undo the damage.
Why we care. Court-ordered ad syndication could weaken Google’s control over ad placement and targeting, leading to less relevant ads and lower conversion rates. In short, the affidavit warns of higher costs, lower ROI, and less predictable campaign performance.
What’s next. The court will decide whether to pause enforcement of the syndication remedies during Google’s appeal. Without a stay, Google would have to begin licensing search ads and results to qualified competitors under the new rules, reshaping the search advertising ecosystem in ways the company says would reach far beyond its own operations.
Dig deeper.  
Affidavit of Jesse Adkins — Document #1471, Attachment #3
Google outlines risks of exposing its search index, rankings, and live results
Google can keep Chrome, but exclusive search deals must end

Google warns that a court-ordered ad syndication could expose its ad algorithms, increase click fraud, and deliver less relevant traffic.

Google: Forced syndication would permanently expose its ad systems

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam.png" class="attachment-large size-large wp-post-image" alt="Google index spam" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Elizabeth Reid’s affidavit warns that court-ordered data sharing would expose Google's IP, invite spam abuse, and put user privacy at risk.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam.png" class="attachment-large size-large wp-post-image" alt="Google index spam" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam.png 1920w, https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/google-index-spam-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google’s head of Search warned a federal court that forcing the company to share its search index, ranking data, and live results with competitors would cause &#8220;immediate and irreparable harm&#8221; to Google, its users, and the open web.</p>



<p>The warning appears in a filed affidavit from Elizabeth Reid, Google’s vice president and head of Search, submitted with Google’s motion to pause key <a href="https://searchengineland.com/google-keep-chrome-exclusive-search-deals-end-461517">antitrust remedies</a> while it appeals the final judgment in the <a href="https://searchengineland.com/federal-judge-rules-google-violated-antitrust-law-444756">DOJ search monopoly case</a>.</p>



<p>The filing spells out what Google sees as its most sensitive Search assets and why sharing them would expose proprietary systems, enable reverse engineering, and fuel spam.</p>



<h2 class="wp-block-heading" id="h-disclosure-of-google-s-web-search-index">Disclosure of Google’s web search index</h2>



<p><strong>The fight:</strong> Section IV of the final judgment would force Google to give “qualified competitors” a one-time dump of its core web index data at marginal cost. That data would include:</p>



<ul class="wp-block-list">
<li>Every URL in Google’s web search index</li>



<li>A DocID-to-URL map</li>



<li>Crawl timing data</li>



<li>Spam scores</li>



<li>Device-type flags</li>
</ul>



<p><strong>Google’s argument:</strong> This would hand competitors the output and the accumulated insight of more than 25 years of indexing work.</p>



<p>Reid described the index as the product of proprietary crawling, annotation, and tiering systems that decide which pages enter Google Search:</p>



<ul class="wp-block-list">
<li>“The selection of webpages in Google’s search index is the result of more than twenty-five years of sustained investments and exhaustive engineering efforts.”</li>
</ul>



<p>She warned that simply knowing which URLs Google indexes would allow rivals to skip large portions of crawling and analysis altogether:</p>



<ul class="wp-block-list">
<li>“Receiving the list of URLs in Google’s index will enable Qualified Competitors to forgo crawling and analyzing the larger web, and to instead focus their efforts on crawling only the fraction of pages Google has included in its index.”</li>
</ul>



<p>Metadata such as crawl frequency would reveal how Google prioritizes freshness and demand, she added:</p>



<ul class="wp-block-list">
<li>“Information regarding Google’s crawl schedule will provide rivals with insight into Google’s proprietary freshness signals and index tiering structure.”</li>
</ul>



<p>Included in the affidavit is this image, &#8220;Google&#8217;s Web Crawling and Indexing Process: The Results,&#8221; showing that Google labels the great majority of webpages as &#8220;Spam, Duplicates, &amp; Low Quality Pages.&#8221; </p>



<figure class="wp-block-image size-full"><img decoding="async" width="1584" height="916" src="https://searchengineland.com/wp-content/seloads/2026/01/google-web-crawling-indexing-process-result.png" alt="" class="wp-image-467842" srcset="https://searchengineland.com/wp-content/seloads/2026/01/google-web-crawling-indexing-process-result.png 1584w, https://searchengineland.com/wp-content/seloads/2026/01/google-web-crawling-indexing-process-result-768x444.png 768w, https://searchengineland.com/wp-content/seloads/2026/01/google-web-crawling-indexing-process-result-1536x888.png 1536w" sizes="(max-width: 1584px) 100vw, 1584px" /></figure>



<ul class="wp-block-list">
<li>Google has crawled a redacted number of pages in the trillions. As of 2020, Google’s index contained roughly <a href="https://searchengineland.com/how-google-search-ranking-works-pandu-nayak-435395">400 billion documents</a>, according to testimony from Pandu Nayak, a Google executive.</li>
</ul>



<h2 class="wp-block-heading" id="h-risk-of-spam-abuse-and-reputational-damage">Risk of spam, abuse, and reputational damage</h2>



<p><strong>The concern:</strong> Google argues that exposing spam scores, even indirectly, would weaken its ability to fight webspam.</p>



<p>Effective spam fighting depends on secrecy, Reid stressed:</p>



<ul class="wp-block-list">
<li>“Fighting spam depends on obscurity, as external knowledge of spam-fighting mechanisms or signals eliminates the value of those mechanisms and signals.”</li>
</ul>



<p>If spam scores leaked or were breached, bad actors could use them to bypass Google’s defenses, Reid warned:</p>



<ul class="wp-block-list">
<li>“Spammers &#8230; could bypass Google’s spam detection technologies and hamstring Google in its efforts to combat spam.”</li>
</ul>



<p>That would push more low-quality and misleading content into search results, with users ultimately blaming Google:</p>



<ul class="wp-block-list">
<li>“The compelled disclosures are likely to cause more spam and misleading content to surface in response to user queries, compromising user safety and undermining Google’s reputation as a trustworthy search engine.”</li>
</ul>



<h2 class="wp-block-heading" id="h-disclosure-of-user-side-search-data-glue-and-rankembed">Disclosure of user-side search data (Glue and RankEmbed)</h2>



<p><strong>What the judgment requires:</strong> Ongoing sharing of “user-side data” used to run Google’s Glue and RankEmbed models. Reid says that data includes:</p>



<ul class="wp-block-list">
<li>Queries</li>



<li>Location</li>



<li>Time of search</li>



<li>Clicks, hovers, and other interactions</li>



<li>Every result and search feature shown, and their order</li>
</ul>



<p>Glue captures 13 months of U.S. search logs, according to the affidavit.</p>



<p><strong>Google’s argument:</strong> This would amount to a massive, ongoing disclosure of Google’s ranking output at scale.</p>



<ul class="wp-block-list">
<li>“The disclosure of Glue training data amounts to the disclosure of Google’s intellectual property, because it reveals the output of Google’s Search technologies in response to every query issued by a user located in the United States over a 13-month period.”</li>
</ul>



<p>She also warned that the data could be reused directly.</p>



<ul class="wp-block-list">
<li>“Qualified Competitors could also readily use the disclosed Glue and RankEmbed data as training data for a large language model.”</li>
</ul>



<p>On privacy, Reid emphasizes that Google would not control the final anonymization decisions.</p>



<ul class="wp-block-list">
<li>“Google will not have final decision-making authority over the anonymization and privacy-enhancing techniques to be applied to the user data before it is shared.”</li>
</ul>



<p>Users would still hold Google responsible for any fallout, Reid predicted.</p>



<ul class="wp-block-list">
<li>“Google users are nonetheless likely to fault Google for any privacy or security issues that arise from the data disclosures.”</li>
</ul>



<h2 class="wp-block-heading" id="h-syndication-of-google-s-search-results-and-features">Syndication of Google’s search results and features</h2>



<p><strong>What’s required:</strong> Section V would force Google to license and syndicate core search outputs to competitors for up to five years, including:</p>



<ul class="wp-block-list">
<li>Organic web results (“ten blue links”)</li>



<li>Query rewriting</li>



<li>Local, Maps, Images, Video, and Knowledge Panels</li>
</ul>



<p><strong>Google’s warning:</strong> This would expose the live output of its search systems to competitors—and beyond.</p>



<ul class="wp-block-list">
<li>“The search results and features required to be syndicated to Qualified Competitors are the product of decades of sustained engineering effort and innovation and many billions of dollars of investment.”</li>
</ul>



<p>Even with contractual limits, Google would lose control, Reid said:</p>



<ul class="wp-block-list">
<li>“Google does not have the ability (as it does in the ordinary course) to decline to syndicate to a Qualified Competitor.”</li>
</ul>



<p>Competitors could store, analyze, or leak the data — and that third parties could scrape it as well, Reid warned.</p>



<ul class="wp-block-list">
<li>“Any third party could ‘scrape’ the syndicated results and features from Qualified Competitors’ sites and thereby also avail themselves of Google’s results and features.”</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><strong>The document.</strong> <a href="https://www.courtlistener.com/docket/18552824/1471/2/united-states-of-america-v-google-llc/" target="_blank" rel="noopener">Read it here</a>.</p>



<ul class="wp-block-list">
<li><strong>What it is:</strong> Affidavit of Elizabeth Reid (Document #1471, Attachment #2)</li>



<li><strong>Filed:</strong> Jan. 16 at 3:46 p.m. ET</li>



<li><strong>Case:</strong> United States of America v. Google LLC, No. 1:20-cv-03010 (D.D.C.)</li>



<li><strong>Purpose:</strong> Supports Google’s motion to partially stay antitrust remedies pending appeal</li>
</ul>



<p>Reid testified previously at the remedies hearing and said the affidavit reflects her personal knowledge as the executive responsible for all of Google Search.</p>
</blockquote>


Google’s head of Search warned a federal court that forcing the company to share its search index, ranking data, and live results with competitors would cause “immediate and irreparable harm” to Google, its users, and the open web.
The warning appears in a filed affidavit from Elizabeth Reid, Google’s vice president and head of Search, submitted with Google’s motion to pause key antitrust remedies while it appeals the final judgment in the DOJ search monopoly case.
The filing spells out what Google sees as its most sensitive Search assets and why sharing them would expose proprietary systems, enable reverse engineering, and fuel spam.
Disclosure of Google’s web search index
The fight: Section IV of the final judgment would force Google to give “qualified competitors” a one-time dump of its core web index data at marginal cost. That data would include:
Every URL in Google’s web search index
A DocID-to-URL map
Crawl timing data
Spam scores
Device-type flags
Google’s argument: This would hand competitors the output and the accumulated insight of more than 25 years of indexing work.
Reid described the index as the product of proprietary crawling, annotation, and tiering systems that decide which pages enter Google Search:
“The selection of webpages in Google’s search index is the result of more than twenty-five years of sustained investments and exhaustive engineering efforts.”
She warned that simply knowing which URLs Google indexes would allow rivals to skip large portions of crawling and analysis altogether:
“Receiving the list of URLs in Google’s index will enable Qualified Competitors to forgo crawling and analyzing the larger web, and to instead focus their efforts on crawling only the fraction of pages Google has included in its index.”
Metadata such as crawl frequency would reveal how Google prioritizes freshness and demand, she added:
“Information regarding Google’s crawl schedule will provide rivals with insight into Google’s proprietary freshness signals and index tiering structure.”
Included in the affidavit is this image, “Google’s Web Crawling and Indexing Process: The Results,” showing that Google labels the great majority of webpages as “Spam, Duplicates, & Low Quality Pages.” 





Google has crawled a redacted number of pages in the trillions. As of 2020, Google’s index contained roughly 400 billion documents, according to testimony from Pandu Nayak, a Google executive.
Risk of spam, abuse, and reputational damage
The concern: Google argues that exposing spam scores, even indirectly, would weaken its ability to fight webspam.
Effective spam fighting depends on secrecy, Reid stressed:
“Fighting spam depends on obscurity, as external knowledge of spam-fighting mechanisms or signals eliminates the value of those mechanisms and signals.”
If spam scores leaked or were breached, bad actors could use them to bypass Google’s defenses, Reid warned:
“Spammers … could bypass Google’s spam detection technologies and hamstring Google in its efforts to combat spam.”
That would push more low-quality and misleading content into search results, with users ultimately blaming Google:
“The compelled disclosures are likely to cause more spam and misleading content to surface in response to user queries, compromising user safety and undermining Google’s reputation as a trustworthy search engine.”
Disclosure of user-side search data (Glue and RankEmbed)
What the judgment requires: Ongoing sharing of “user-side data” used to run Google’s Glue and RankEmbed models. Reid says that data includes:
Queries
Location
Time of search
Clicks, hovers, and other interactions
Every result and search feature shown, and their order
Glue captures 13 months of U.S. search logs, according to the affidavit.
Google’s argument: This would amount to a massive, ongoing disclosure of Google’s ranking output at scale.
“The disclosure of Glue training data amounts to the disclosure of Google’s intellectual property, because it reveals the output of Google’s Search technologies in response to every query issued by a user located in the United States over a 13-month period.”
She also warned that the data could be reused directly.
“Qualified Competitors could also readily use the disclosed Glue and RankEmbed data as training data for a large language model.”
On privacy, Reid emphasizes that Google would not control the final anonymization decisions.
“Google will not have final decision-making authority over the anonymization and privacy-enhancing techniques to be applied to the user data before it is shared.”
Users would still hold Google responsible for any fallout, Reid predicted.
“Google users are nonetheless likely to fault Google for any privacy or security issues that arise from the data disclosures.”
Syndication of Google’s search results and features
What’s required: Section V would force Google to license and syndicate core search outputs to competitors for up to five years, including:
Organic web results (“ten blue links”)
Query rewriting
Local, Maps, Images, Video, and Knowledge Panels
Google’s warning: This would expose the live output of its search systems to competitors—and beyond.
“The search results and features required to be syndicated to Qualified Competitors are the product of decades of sustained engineering effort and innovation and many billions of dollars of investment.”
Even with contractual limits, Google would lose control, Reid said:
“Google does not have the ability (as it does in the ordinary course) to decline to syndicate to a Qualified Competitor.”
Competitors could store, analyze, or leak the data — and that third parties could scrape it as well, Reid warned.
“Any third party could ‘scrape’ the syndicated results and features from Qualified Competitors’ sites and thereby also avail themselves of Google’s results and features.”
The document. Read it here.
What it is: Affidavit of Elizabeth Reid (Document #1471, Attachment #2)
Filed: Jan. 16 at 3:46 p.m. ET
Case: United States of America v. Google LLC, No. 1:20-cv-03010 (D.D.C.)
Purpose: Supports Google’s motion to partially stay antitrust remedies pending appeal
Reid testified previously at the remedies hearing and said the affidavit reflects her personal knowledge as the executive responsible for all of Google Search.

Elizabeth Reid’s affidavit warns that court-ordered data sharing would expose Google's IP, invite spam abuse, and put user privacy at risk.

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