<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze.png" class="attachment-large size-large wp-post-image" alt="Bot detection maze" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Google has 21 days to amend part of its lawsuit after the court found its SearchGuard allegations were not sufficiently supported.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze.png" class="attachment-large size-large wp-post-image" alt="Bot detection maze" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/bot-detection-maze-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Google’s DMCA claims against SerpApi were dismissed July 20. Google now has 21 days to amend part of its complaint.</p>



<p class="wp-block-paragraph">The U.S. District Court for the Northern District of California granted SerpApi’s motion to dismiss Google’s two claims under the Digital Millennium Copyright Act. The court also stayed discovery until Google files an amended complaint, if any, and any resulting motion to dismiss is resolved.</p>



<p class="wp-block-paragraph"><strong>Claims split by content type</strong>. The court permanently dismissed the parts of Google’s claims based on Search results that didn&#8217;t include copyrighted content.</p>



<p class="wp-block-paragraph">The court dismissed the parts of Google’s claims involving Search results with copyrighted content, but gave Google a chance to revise them. The court said Google had not alleged facts showing that <a href="https://searchengineland.com/inside-google-searchguard-467676">SearchGuard</a>, Google’s anti-scraping system, was implemented and functioned “with the authority of the copyright owner.”</p>



<p class="wp-block-paragraph"><strong>Google gets another chance</strong>. Google may file an amended complaint within 21 days, provided it doesn&#8217;t contradict its original allegations. Information showing whether copyright owners authorized Google to use SearchGuard to protect licensed content should already be within Google&#8217;s possession, custody, or control, the court said.</p>



<p class="wp-block-paragraph"><strong>SerpApi responds. </strong>SerpApi CEO Julien Khaleghy said the ruling was “a win not just for SerpApi, but for all who depend on an open internet.”</p>



<ul class="wp-block-list">
<li>SerpApi said the court rejected Google’s attempt to expand the DMCA to control access to public pages. SerpApi said it would continue supporting developers, AI companies, researchers and businesses that rely on access to public search information.</li>
</ul>



<p class="wp-block-paragraph" id="h-serpapi-did-not-win-everything"><strong>SerpApi didn&#8217;t win everything.</strong> The court rejected SerpApi’s argument that Google lacked standing under the DMCA because Google didn&#8217;t allege that it owned or exclusively licensed the copyrighted material in search results. The court also said Google had alleged enough facts to support an inference that SerpApi circumvented SearchGuard.</p>



<p class="wp-block-paragraph" id="h-catch-up-quick-google-sued-serpapi-dec-19-alleging-the-company-bypassed-searchguard-and-scraped-google-search-results-for-resale"><strong>Catch up quick.</strong> <a href="https://searchengineland.com/google-sues-serpapi-466541">Google sued SerpApi Dec. 19</a>, alleging the company bypassed SearchGuard and scraped Google Search results for resale.</p>



<ul class="wp-block-list">
<li><a href="https://searchengineland.com/serpapi-motion-dismiss-google-scraping-lawsuit-469889">SerpApi moved to dismiss Feb. 20</a>, arguing Google was using the DMCA to restrict access to public search results. </li>



<li>SerpApi also argued Google didn&#8217;t own the underlying content displayed in search results and that public pages shouldn&#8217;t be treated as protected copyrighted works.</li>
</ul>



<p class="wp-block-paragraph"><strong>Why we care.</strong> Many search tools rely on automated access to public search results to monitor rankings, competitors, and AI visibility. This case could still shape how much third-party SERP data those tools can collect.</p>


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Google’s DMCA claims against SerpApi were dismissed July 20. Google now has 21 days to amend part of its complaint.
The U.S. District Court for the Northern District of California granted SerpApi’s motion to dismiss Google’s two claims under the Digital Millennium Copyright Act. The court also stayed discovery until Google files an amended complaint, if any, and any resulting motion to dismiss is resolved.
Claims split by content type. The court permanently dismissed the parts of Google’s claims based on Search results that didn’t include copyrighted content.
The court dismissed the parts of Google’s claims involving Search results with copyrighted content, but gave Google a chance to revise them. The court said Google had not alleged facts showing that SearchGuard, Google’s anti-scraping system, was implemented and functioned “with the authority of the copyright owner.”
Google gets another chance. Google may file an amended complaint within 21 days, provided it doesn’t contradict its original allegations. Information showing whether copyright owners authorized Google to use SearchGuard to protect licensed content should already be within Google’s possession, custody, or control, the court said.
SerpApi responds. SerpApi CEO Julien Khaleghy said the ruling was “a win not just for SerpApi, but for all who depend on an open internet.”
SerpApi said the court rejected Google’s attempt to expand the DMCA to control access to public pages. SerpApi said it would continue supporting developers, AI companies, researchers and businesses that rely on access to public search information.
SerpApi didn’t win everything. The court rejected SerpApi’s argument that Google lacked standing under the DMCA because Google didn’t allege that it owned or exclusively licensed the copyrighted material in search results. The court also said Google had alleged enough facts to support an inference that SerpApi circumvented SearchGuard.
Catch up quick. Google sued SerpApi Dec. 19, alleging the company bypassed SearchGuard and scraped Google Search results for resale.
SerpApi moved to dismiss Feb. 20, arguing Google was using the DMCA to restrict access to public search results. 
SerpApi also argued Google didn’t own the underlying content displayed in search results and that public pages shouldn’t be treated as protected copyrighted works.
Why we care. Many search tools rely on automated access to public search results to monitor rankings, competitors, and AI visibility. This case could still shape how much third-party SERP data those tools can collect.
before your competitors.
      
Start your free trial

Google has 21 days to amend part of its lawsuit after the court found its SearchGuard allegations were not sufficiently supported.

Google loses key DMCA claims against SerpApi in scraping lawsuit

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google launched video campaign groups, allowing advertisers to optimize YouTube reach and frequency across multiple campaigns.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-group-video-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google Ads is rolling out video campaign groups for YouTube reach and frequency campaigns, giving advertisers a new way to coordinate delivery across multiple video campaigns while optimizing toward a shared reach or frequency goal.</p>



<p class="wp-block-paragraph">The feature is designed to simplify campaign management while helping advertisers improve audience reach and avoid overexposure.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s new</strong>. Video campaign groups for YouTube reach and frequency campaigns are now available globally in Google Ads.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1087" height="586" src="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-grp.png" alt="" class="wp-image-483181" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Campaign-grp.png 1087w, https://searchengineland.com/wp-content/seloads/2026/07/Campaign-grp-768x414.png 768w" sizes="(max-width: 1087px) 100vw, 1087px" /></figure>



<p class="wp-block-paragraph">Advertisers can group multiple video campaigns under a single reach or frequency objective while still maintaining campaign-level controls, including budgets, creative assets, and other settings.</p>



<p class="wp-block-paragraph">The update also introduces unified reporting across grouped campaigns, providing visibility into metrics such as:</p>



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



<li>Average weekly impressions.</li>



<li>Reach and frequency performance across the entire campaign group.</li>
</ul>



<p class="wp-block-paragraph">Google says a Meridian marketing mix modeling (MMM) study found that an optimal frequency of 2.7 impressions per week resulted in a 19% increase in ROI.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Managing reach and frequency across multiple YouTube campaigns has traditionally required advertisers to monitor performance campaign by campaign. Video campaign groups centralize optimization and reporting, making it easier to control audience exposure while maintaining separate budgets and creative strategies. For brands running large awareness campaigns, the feature could improve media efficiency by reducing unnecessary overlap and helping maximize unique reach.</p>



<p class="wp-block-paragraph"><strong>Between the lines</strong>. Google continues to invest in cross-campaign optimization tools that automate media planning decisions without removing campaign-level flexibility. By coordinating delivery across campaigns, advertisers can focus more on overall audience strategy rather than manually balancing frequency across individual campaigns.</p>



<p class="wp-block-paragraph">The company also confirmed the feature will expand to Display &amp; Video 360, allowing advertisers to coordinate reach and frequency across multiple YouTube line items in the near future.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://blog.google/products/ads-commerce/video-campaign-groups/">Video campaign groups</a> give advertisers a centralized way to optimize YouTube reach and frequency across multiple campaigns, potentially improving media efficiency while simplifying campaign management and reporting.</p>



<p class="wp-block-paragraph"><strong>First spotted. </strong>The update was spotted by Paid Search Expert <a href="https://www.linkedin.com/in/arpan301/">Arpan Banerjee</a>, who shared the screenshot above. </p>


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Google Ads is rolling out video campaign groups for YouTube reach and frequency campaigns, giving advertisers a new way to coordinate delivery across multiple video campaigns while optimizing toward a shared reach or frequency goal.
The feature is designed to simplify campaign management while helping advertisers improve audience reach and avoid overexposure.
What’s new. Video campaign groups for YouTube reach and frequency campaigns are now available globally in Google Ads.




Advertisers can group multiple video campaigns under a single reach or frequency objective while still maintaining campaign-level controls, including budgets, creative assets, and other settings.
The update also introduces unified reporting across grouped campaigns, providing visibility into metrics such as:
Unique reach.
Average weekly impressions.
Reach and frequency performance across the entire campaign group.
Google says a Meridian marketing mix modeling (MMM) study found that an optimal frequency of 2.7 impressions per week resulted in a 19% increase in ROI.
Why we care. Managing reach and frequency across multiple YouTube campaigns has traditionally required advertisers to monitor performance campaign by campaign. Video campaign groups centralize optimization and reporting, making it easier to control audience exposure while maintaining separate budgets and creative strategies. For brands running large awareness campaigns, the feature could improve media efficiency by reducing unnecessary overlap and helping maximize unique reach.
Between the lines. Google continues to invest in cross-campaign optimization tools that automate media planning decisions without removing campaign-level flexibility. By coordinating delivery across campaigns, advertisers can focus more on overall audience strategy rather than manually balancing frequency across individual campaigns.
The company also confirmed the feature will expand to Display & Video 360, allowing advertisers to coordinate reach and frequency across multiple YouTube line items in the near future.
Bottom line. Video campaign groups give advertisers a centralized way to optimize YouTube reach and frequency across multiple campaigns, potentially improving media efficiency while simplifying campaign management and reporting.
First spotted. The update was spotted by Paid Search Expert Arpan Banerjee, who shared the screenshot above. 
a customer you lose.
      
See who’s stealing your traffic

Google launched video campaign groups, allowing advertisers to optimize YouTube reach and frequency across multiple campaigns.

Google Ads rolls out video campaign groups globally

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/How-semantics-and-topical-authority-improve-local-SEO.png" class="attachment-large size-large wp-post-image" alt="How semantics and topical authority improve local SEO" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/How-semantics-and-topical-authority-improve-local-SEO.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/How-semantics-and-topical-authority-improve-local-SEO-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/How-semantics-and-topical-authority-improve-local-SEO-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/How-semantics-and-topical-authority-improve-local-SEO-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Creating fewer, more purposeful pages can improve relevance, reduce duplication, and strengthen local search performance.


Creating fewer, more purposeful pages can improve relevance, reduce duplication, and strengthen local search performance.

How semantics and topical authority improve local SEO

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Does-topical-authority-matter-in-AI-Search-featured-image.png" class="attachment-large size-large wp-post-image" alt="Does topical authority matter in AI Search? - featured-image" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Does-topical-authority-matter-in-AI-Search-featured-image.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Does-topical-authority-matter-in-AI-Search-featured-image-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Does-topical-authority-matter-in-AI-Search-featured-image-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Does-topical-authority-matter-in-AI-Search-featured-image-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>New Semrush data shows topical authority still matters in AI search, helping brands earn and defend category ownership over time.

Some brands get away with broad topical focus. Forbes, for example, ranks well for everything from “bitcoin price” to “best pillows for neck pain.” But most brands are more visible in search when focusing their content strategy on core topics.
Topical authority is one of the most used concepts in SEO to justify content creation. It’s gone so far that swinging too far from the base can lead to algorithmic demotions (HubSpot and Clickup, to name a few significant ones). But does it translate to AI search? Or are LLMs such a new playing field that brands can really swing big?
Imagine a payroll software company planning its next 20 articles. It can chase broad, high-volume finance topics, or build out the payroll questions it wants to be known for: W-2 deadlines, contractor classification, payroll-tax errors, overtime rules, and state registration.
The topical-authority bet is to choose the second path, even when ChatGPT can answer some of those questions without sending a click. The goal is not traffic from every glossary page. It is to become a brand that appears consistently when people ask related questions, including the eventual “Which payroll software should I use?” question.
Topical authority matters in AI search, and the reason is durability. This study shows AI answers develop topic owners: Once a brand earns an outsized share of mentions in a category, it usually keeps it.
View embedded content



Method and limitations
To find out, the Semrush team gave me access to a big dataset based on the Semrush AI Visibility Toolkit.
Scope: 1,094 US categories, 5 prompts per category, and monthly snapshots from January through June 2026 in ChatGPT, USA only.
The study covers 220,000+ domains, 50,000+ brands, 600,000+ citations, and 220,000+ URLs
This study tracks which brands ChatGPT mentions most often across five prompts per category. It does not measure sentiment, recommendation quality, user trust, or purchase impact.
The study has no topic-level organic rankings, organic visibility, or SEO share-of-voice data.
Semrush’s export records whether a brand appears in an answer, not the surrounding text or sentiment. A mention can be positive, neutral, or negative.
Definitions:
Owner: The brand with the highest share of brand mentions, named in at least four of the category’s 5 prompts, and at least 5 percentage points ahead of the runner-up.
Emerging leader: The most-mentioned brand appears in at least three prompts but does not meet the clear-leader threshold.
Unsettled category: No leading brand appears in at least three prompts.
Important note: The definition for unsettled category makes sense based on the threshold we’ve seen in this specific study, but don’t treat it as a universal truth at this time.
While almost half of cited pages in the study were hard to classify (a mix of cryptic URLs like “examplesite.gov/0982349” that don’t have common/standard page types), we found that the most cited page types are product or service landing pages, followed by classic editorial content. Homepages were only cited 4% of the time.




1. Most categories have a leader, but some have an owner
Category owners dominate the category, of course. We defined them as +80% Share of Voice (available brand mentions in AI answers) and at least a 5 percentage point lead to the 2nd place.




Most categories that we analyzed in ChatGPT have not yet settled on an owner. In June 2026, only 15.2% of categories had a clear owner, while 53.7% were open fields with several contenders for the top. Over half of the +1,000 categories we analyzed have a leader that can be dethroned by a challenger. Plenty of opportunity, which I personally don’t think is true in classic Google Search.
When we look at AI (search) volume, which describes how many people might prompt in a given topic*, we find that the biggest categories by volume do not have an owner.
*Yes, I’m aware that AI (search) volume is not perfect, but when we abstract search keywords and prompts into topics and look at aggregate search volume, we can at least guess how big a topic in AI Search is.







In Semrush’s U.S. sample for our study, the biggest topics are the least likely to have an owner.
We ranked all 1,094 categories by AI-search volume and split them into 2 groups of 547. 
The top group holds 98% of all volume-based AI-search demand in the sample. It also has the lowest owner rate: 11.3%, versus 19.0% in the bottom group.
Stack those up, and 89.3% of estimated AI-search demand sits in categories with no clear owner. Demand concentrates, but in this dataset, ownership does not.




When we split the data out by quartiles or deciles, we see the same trend of top-heavy categories being more open-field opportunities than smaller ones.
A category with no owner is an open budget conversation waiting to happen. The AI SEO Budget Reallocation Planner generates 5 growth-priority scenarios and a screenshot-ready visual in under 7 minutes, so the categories you choose to attack come with a number attached. Find it in the Premium Subscribers Resource Library.



2. Owners win on brand mentions, not citations
This study counts whether a brand appears in an answer, not how prominently it appears or whether it is recommended. A category owner is therefore the brand named across the largest share of its tested prompts.
Previous Growth Memo user-behavior studies have repeatedly shown that users pay little attention to citations and most to brand mentions. In shortlists, users demonstrate strong preference for the top results for purchase decisions (75% of users pick the top brand). In other words, brand mentions are AEO gold. I applied this lens to this data as well.
From How Consumers Navigate High-Stakes Purchases in AI Mode:
“In classic search, 56% of participants built their own shortlist from multiple sources. In AI Mode, only 8 out of 147 codeable tasks produced a genuinely self-built shortlist. The user’s comparison process didn’t just shrink when using AI Mode. For most participants, it didn’t happen at all.
64% of AI Mode participants clicked nothing at all during their task. They read the AI’s text, sometimes scrolled through inline product snippets, and declared their finalists. The no-click rate varied by category.
Just like in classic search, the top answer carries outsized weight. 74% of participants chose the item ranked first in the AI’s response as their top pick. The mean rank of the final choice was 1.35. Only 10% chose something ranked third or lower.”
While citations influence the AI answer to a prompt, the relationship between citations and brand mentions is slightly negative (-0.229). In the study, the most-cited domain was rarely the most-mentioned (20.8%). But the most mentioned brand was often cited (69.9%) at least once.




All industries exhibit clear owners, except for legal. In retail, we see the highest owner rate with 61.6% (meaning 61 out of 99 categories we analyzed have a clear owner).




3. Characteristics of category owners
The available data lets us identify traits associated with ownership, but not prove how ownership was created. When compared to the 2nd place in a category, we do see that owners have:
Higher brand search volume (55.7%)
Higher organic traffic (48.4%)
Higher authority (52.5%, as measured by Semrush’s Authority Score) 




The branded-demand result means that, in 577 of 1,035 owner-runner-up pairs, the owner had higher branded search volume. 
It does not mean branded demand explains 55.7% of ownership. These are useful clues, but not a recipe. The better working hypothesis is:
Brand strength may help a domain enter the answer set. Category ownership is more likely determined by unmeasured topic-specific factors, including source relevance, cited content quality, reputation, and how well a domain fits the prompt.
4. Can a challenger win a category?
Category owners are defined by their position. They’re hard to dethrone. 
It’s not impossible to dethrone them, but the odds depend heavily on how settled the category is. A clear owner retained first place in 90.4% of next-month (or month over month, MoM) comparisons. Emerging and unsettled leaders change much more often.




Leaders switched in 1,950 of 5,470 MoM comparisons. But those changes were concentrated in categories where the initial lead was narrow: Switching leaders had a median 1.3-point lead, versus 2.9 points for leaders that retained first place.
Three examples where a clear leader was replaced by the previous month’s runner-up:












As you can see in the examples, you can trend up but reverse course (example 1), be flat and overtaken by a competitor (example 2), or grow and still be overtaken by a competitor that grows faster (example 3). Your trend line says little about your safety. You need a big enough margin (at least 5%).
We can’t say why these switches occurred from this dataset alone. They could reflect changes in sources, answer generation, prompt interpretation, or real changes in each brand’s underlying relevance. 
What the data does show is the condition for disruption: Narrow-lead categories are contestable; wide, sustained ownership is much harder to displace.



5. How to compete for category ownership
Use topical ownership to decide where to focus, not to declare that more content will make ChatGPT mention you:
Watchlist: List 10 to 20 commercially important categories for your brand. For each, track at least five representative prompts: a definition, comparison, alternatives, use case, and buying question. Read more about how to make your prompt tracking more accurate here.
Classify: A clear owner is the most-mentioned brand with a strong majority of prompts and a clear lead over the runner-up. Everything else is either an emerging-leader category or an unsettled category.
Invest: Prioritize commercially valuable categories with no clear owner, or a small gap between the leader and runner-up. Defend categories you already lead. Be more selective about attacking a category where an established brand leads across nearly every prompt.
Gaps: Close gaps across the prompts where competitors appear, and you don’t. That can mean clearer product positioning, comparison pages, documentation, expert guidance, proof points, and credible third-party coverage. The study does not show which of these creates ownership. It gives you a disciplined place to test them.
Measure: Track brand mentions as the ownership metric, citations as a source-authority metric, and referrals, self-reported pipeline, or revenue as the business metric. A monthly change in the most-mentioned brand is a reason to investigate, not proof that a competitive win created demand.
Topic focus is worth the “content constraint” because ownership compounds over time. A category you win in is a category you tend to keep, and the brands that spread their content creation across every topic that’s semi-adjacent to their core offering rarely reach the mention share that makes a lead stick.
The Semrush data shows that, currently, the window is open and it will not stay open. 89.3% of AI-search demand sits in categories with no owner (as defined by this study), which means the cost of picking the wrong 5 categories today is lower than it will be in 12 months. 
Pick the categories you want to be the answer to. Defend the ones you already lead. Skip the ones where an established brand appears in every prompt. Broad coverage still has a job in marketing, but it does not build the position that makes ChatGPT name you.
This post first appeared on the author’s website and is republished here with permission.

New Semrush data shows topical authority still matters in AI search, helping brands earn and defend category ownership over time.

Does topical authority matter in AI search?

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns.png" class="attachment-large size-large wp-post-image" alt="Every content strategy has a point of diminishing returns" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Publishing more articles won't always improve SEO. Learn how indexing, crawl budget, and content pruning can drive better results.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns.png" class="attachment-large size-large wp-post-image" alt="Every content strategy has a point of diminishing returns" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Every-content-strategy-has-a-point-of-diminishing-returns-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Quality over quantity is a familiar saying, but it&#8217;s not always an easy sell to executives and decision-makers who still believe publishing more content leads to better results.</p>



<p class="wp-block-paragraph">That approach may still work in some areas of marketing and at specific, tested frequencies. But today&#8217;s content strategies often benefit more from a slower, data-backed production cadence guided by the law of diminishing returns.</p>



<h2 id="h-the-law-of-diminishing-returns-in-online-content" class="wp-block-heading">The law of diminishing returns in online content</h2>



<p class="wp-block-paragraph"><a href="https://blog.hubspot.com/marketing/blogging-frequency-benchmarks/" target="_blank" rel="noopener">Publishing more frequently</a> was associated with higher traffic, HubSpot found. But every content strategy eventually reaches a point of diminishing returns, where producing more content delivers smaller returns than improving what you already have.</p>



<p class="wp-block-paragraph">That point will vary by organization. You&#8217;ll also have &#8220;<a href="https://blog.hubspot.com/marketing/hubspot-blog-compounding-posts" target="_blank" rel="noopener">compounding articles</a>&#8221; (as HubSpot calls them) that generate most of your traffic, leads, and engagement. The goal is to identify your publishing threshold using your own performance data.</p>



<p class="wp-block-paragraph">Once you do, you can use that data to show your leadership team why publishing as much as possible doesn&#8217;t necessarily produce better results.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/more-content-unreliable-seo-475688">Why more content is no longer a reliable way to grow SEO</a></em></strong>


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<h3 id="h-but-are-your-articles-even-getting-indexed-nbsp" class="wp-block-heading">But are your articles even getting indexed?&nbsp;</h3>



<p class="wp-block-paragraph">A recent SEO client brought up an interesting point I hadn&#8217;t considered before. Among their high-quality content, researched, written by a human, and edited and reviewed by several people before publication, many articles were discovered by Google, but the search engine simply chose not to index them.</p>



<p class="wp-block-paragraph">This has been relatively rare until recently. Historically, Google indexed most pages it discovered on established, higher-quality sites. But as AI has accelerated site creation, we&#8217;re seeing more pages discovered by Google but left unindexed.</p>



<p class="wp-block-paragraph">Searching Reddit and other social forums shows that other SEOs are running into the same issue. Google has even <a href="https://www.youtube.com/watch?v=Q5kYrmzNhcU" target="_blank" rel="noopener">addressed it in a Search Central video</a>. SEO analyst Raghunath Sabat <a href="https://www.linkedin.com/posts/raghunath-sabat_%F0%9D%97%9A%F0%9D%97%A6%F0%9D%97%96-%F0%9D%97%A5%F0%9D%97%B2%F0%9D%97%BD%F0%9D%97%BC%F0%9D%97%BF%F0%9D%98%81-%F0%9D%97%A3%F0%9D%97%AE%F0%9D%97%B4%F0%9D%97%B2-%F0%9D%97%A1%F0%9D%97%BC%F0%9D%98%81-%F0%9D%97%9C%F0%9D%97%BB-activity-7374402679797784576-VKXT/?skipRedirect=true" target="_blank" rel="noopener">shared on LinkedIn</a> that this issue persists when one or more of the following exist:</p>



<ul class="wp-block-list">
<li>Crawl budget is limited.</li>



<li>There are too many URLs to crawl.</li>



<li>It&#8217;s a low-priority site (an authority issue).</li>



<li>The content is low quality.</li>



<li>There aren&#8217;t enough internal links.</li>
</ul>



<p class="wp-block-paragraph">In Raghunath&#8217;s case, he resolved the issue by republishing the article and linking to it from relevant articles. But the fundamentals still matter. Internal linking and crawl budget remain crucial to getting your high-quality content indexed and delivering value.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/guide/content-strategy-in-2026">Content strategy in 2026: What actually changed (and what didn’t)</a></em></strong>



<h2 id="h-why-crawl-budget-still-matters" class="wp-block-heading">Why crawl budget still matters</h2>



<p class="wp-block-paragraph">According to <a href="https://developers.google.com/crawling/docs/crawl-budget" target="_blank" rel="noopener">Google’s Developer documentation</a>: </p>



<ul class="wp-block-list">
<li>“The amount of time and resources that Google devotes to crawling a site is commonly called the site&#8217;s crawl budget, and it&#8217;s determined by two main elements: crawl capacity limit and crawl demand.” </li>
</ul>



<p class="wp-block-paragraph">When a site has too many pages to crawl, Google may decide not to crawl the entire site. That decision is typically based on dozens of factors, including site authority and what Google has already indexed.</p>



<h3 id="h-determine-a-content-pruning-strategy" class="wp-block-heading">Determine a content pruning strategy</h3>



<p class="wp-block-paragraph">Publishing less is only part of the equation. Optimizing the content you already have should become a core part of your content strategy and production workflow. </p>



<p class="wp-block-paragraph">One of the strongest examples comes from <a href="https://www.animalz.co/blog/content-pruning/" target="_blank" rel="noopener">Jimmy Daly&#8217;s post</a> on how QuickBooks deleted more than 2,000 pieces of content from its resource center. Within weeks, traffic increased 20%, leading to more than 70% more lead signups.</p>



<p class="wp-block-paragraph">Deleting content doesn&#8217;t guarantee success, but it can reduce crawl demand and help Google focus its crawl resources on the pages that matter most.</p>



<p class="wp-block-paragraph">Deleting content you&#8217;ve invested time, money, and effort into can feel risky. But in many cases, your lowest-performing content isn&#8217;t driving the results that matter most: conversions, leads, and sales. A Userpilot case study found that deleting <a href="https://www.linkedin.com/feed/update/urn:li:activity:7263650452741738497/?skipRedirect=true">nearly 25%</a> of its content led to its highest-trafficked month yet.</p>



<p class="wp-block-paragraph">Focusing your content on the topics where you have the deepest expertise, with one to four high-quality articles per topic instead of 50 or more, can improve crawl efficiency and help your team produce stronger content.</p>



<p class="wp-block-paragraph">While studies have observed a correlation between dwell time (the amount of time users spend consuming your content) and rankings, Google has never confirmed that dwell time is a ranking factor. </p>



<p class="wp-block-paragraph">Still, many experts have found that AI search citations disproportionately come from well-structured, substantive pages, and cited brands see meaningfully higher click-through rates than competitors that aren&#8217;t cited.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/guide/content-pruning-for-ai-search">Content pruning for AI search: When to remove, redirect, or consolidate pages</a></em></strong>



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<h2 id="h-how-to-make-the-case-for-less-content" class="wp-block-heading">How to make the case for less content</h2>



<p class="wp-block-paragraph">We&#8217;ve covered the benefits of producing fewer, higher-quality content pieces, from improved crawl efficiency and indexing to stronger engagement. But how do you turn those insights into an actionable plan that stakeholders can support? Start with these steps.</p>



<h3 id="h-run-a-content-audit" class="wp-block-heading">Run a content audit</h3>



<p class="wp-block-paragraph">Use a tool like Screaming Frog to generate a list of the content on your site you want to analyze. This could include blog articles, support articles, or other content assets. </p>



<p class="wp-block-paragraph">Pull not only the URLs, but also the data that will help inform your decisions, such as conversions, traffic, and ranked keywords over the past 12 months.</p>



<p class="wp-block-paragraph">Review each URL and decide whether to:</p>



<ul class="wp-block-list">
<li>Keep it as is.</li>



<li>Consolidate it with another article and redirect the current URL.</li>



<li>Refresh it with updated information and data.</li>



<li>Delete it and redirect the URL.</li>
</ul>



<p class="wp-block-paragraph">Then develop a plan for each category. Some tasks, such as deleting and redirecting content, can be completed in bulk. Others, such as content refreshes, are better handled in phases. Pair this work with a content gap analysis or other research to identify where new content still makes sense.</p>



<h3 id="h-reframe-your-kpis" class="wp-block-heading">Reframe your KPIs</h3>



<p class="wp-block-paragraph">The metrics you&#8217;ve traditionally used to measure content success may no longer capture the full impact of AI-driven search. </p>



<p class="wp-block-paragraph">Consider building an <a href="https://www.aleydasolis.com/en/ai-search/ai-search-prompt-library/" target="_blank" rel="noopener">AI search prompt library</a> that reflects how people discover your content, and track, when possible, whether your content generates conversions from AI summaries or other third-party experiences.</p>



<h3 id="h-set-a-review-date" class="wp-block-heading">Set a review date</h3>



<p class="wp-block-paragraph">If there&#8217;s still uncertainty about making a significant change to your publishing cadence, establish a review date to evaluate the results. Give the changes at least three to six months before deciding whether to continue or adjust your approach.</p>



<h3 id="h-stay-agile" class="wp-block-heading">Stay agile</h3>



<p class="wp-block-paragraph">Don&#8217;t treat any changes as permanent. As search and publishing continue to evolve, evaluate what&#8217;s working, such as content pruning, and what isn&#8217;t, such as changes to your publishing cadence.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/content-decay-types-fix-482486">4 types of content decay and how to fix each one</a></em></strong>



<h2 id="h-it-s-not-just-about-publishing-less" class="wp-block-heading">It&#8217;s not just about publishing less</h2>



<p class="wp-block-paragraph">Today&#8217;s content strategy isn&#8217;t about publishing more. It&#8217;s about making every article count. If your content isn&#8217;t driving meaningful business results, it isn&#8217;t the best use of your team&#8217;s time, budget, or resources. Every site has its own point of diminishing returns. Your job is to identify that threshold and adjust your production strategy accordingly.</p>



<p class="wp-block-paragraph">Refreshing existing content while creating new content remains essential. Don&#8217;t create content that can be easily summarized. Instead, publish substantive, informative content that offers depth beyond a quick overview. Depth and quality will attract more users and customers than high-volume publishing.</p>

Quality over quantity is a familiar saying, but it’s not always an easy sell to executives and decision-makers who still believe publishing more content leads to better results.
That approach may still work in some areas of marketing and at specific, tested frequencies. But today’s content strategies often benefit more from a slower, data-backed production cadence guided by the law of diminishing returns.
The law of diminishing returns in online content
Publishing more frequently was associated with higher traffic, HubSpot found. But every content strategy eventually reaches a point of diminishing returns, where producing more content delivers smaller returns than improving what you already have.
That point will vary by organization. You’ll also have “compounding articles” (as HubSpot calls them) that generate most of your traffic, leads, and engagement. The goal is to identify your publishing threshold using your own performance data.
Once you do, you can use that data to show your leadership team why publishing as much as possible doesn’t necessarily produce better results.
Dig deeper: Why more content is no longer a reliable way to grow SEO



  
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But are your articles even getting indexed? 
A recent SEO client brought up an interesting point I hadn’t considered before. Among their high-quality content, researched, written by a human, and edited and reviewed by several people before publication, many articles were discovered by Google, but the search engine simply chose not to index them.
This has been relatively rare until recently. Historically, Google indexed most pages it discovered on established, higher-quality sites. But as AI has accelerated site creation, we’re seeing more pages discovered by Google but left unindexed.
Searching Reddit and other social forums shows that other SEOs are running into the same issue. Google has even addressed it in a Search Central video. SEO analyst Raghunath Sabat shared on LinkedIn that this issue persists when one or more of the following exist:
Crawl budget is limited.
There are too many URLs to crawl.
It’s a low-priority site (an authority issue).
The content is low quality.
There aren’t enough internal links.
In Raghunath’s case, he resolved the issue by republishing the article and linking to it from relevant articles. But the fundamentals still matter. Internal linking and crawl budget remain crucial to getting your high-quality content indexed and delivering value.
Dig deeper: Content strategy in 2026: What actually changed (and what didn’t)



Why crawl budget still matters
According to Google’s Developer documentation: 
“The amount of time and resources that Google devotes to crawling a site is commonly called the site’s crawl budget, and it’s determined by two main elements: crawl capacity limit and crawl demand.” 
When a site has too many pages to crawl, Google may decide not to crawl the entire site. That decision is typically based on dozens of factors, including site authority and what Google has already indexed.
Determine a content pruning strategy
Publishing less is only part of the equation. Optimizing the content you already have should become a core part of your content strategy and production workflow. 
One of the strongest examples comes from Jimmy Daly’s post on how QuickBooks deleted more than 2,000 pieces of content from its resource center. Within weeks, traffic increased 20%, leading to more than 70% more lead signups.
Deleting content doesn’t guarantee success, but it can reduce crawl demand and help Google focus its crawl resources on the pages that matter most.
Deleting content you’ve invested time, money, and effort into can feel risky. But in many cases, your lowest-performing content isn’t driving the results that matter most: conversions, leads, and sales. A Userpilot case study found that deleting nearly 25% of its content led to its highest-trafficked month yet.
Focusing your content on the topics where you have the deepest expertise, with one to four high-quality articles per topic instead of 50 or more, can improve crawl efficiency and help your team produce stronger content.
While studies have observed a correlation between dwell time (the amount of time users spend consuming your content) and rankings, Google has never confirmed that dwell time is a ranking factor. 
Still, many experts have found that AI search citations disproportionately come from well-structured, substantive pages, and cited brands see meaningfully higher click-through rates than competitors that aren’t cited.
Dig deeper: Content pruning for AI search: When to remove, redirect, or consolidate pages




	
	
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How to make the case for less content
We’ve covered the benefits of producing fewer, higher-quality content pieces, from improved crawl efficiency and indexing to stronger engagement. But how do you turn those insights into an actionable plan that stakeholders can support? Start with these steps.
Run a content audit
Use a tool like Screaming Frog to generate a list of the content on your site you want to analyze. This could include blog articles, support articles, or other content assets. 
Pull not only the URLs, but also the data that will help inform your decisions, such as conversions, traffic, and ranked keywords over the past 12 months.
Review each URL and decide whether to:
Keep it as is.
Consolidate it with another article and redirect the current URL.
Refresh it with updated information and data.
Delete it and redirect the URL.
Then develop a plan for each category. Some tasks, such as deleting and redirecting content, can be completed in bulk. Others, such as content refreshes, are better handled in phases. Pair this work with a content gap analysis or other research to identify where new content still makes sense.
Reframe your KPIs
The metrics you’ve traditionally used to measure content success may no longer capture the full impact of AI-driven search. 
Consider building an AI search prompt library that reflects how people discover your content, and track, when possible, whether your content generates conversions from AI summaries or other third-party experiences.
Set a review date
If there’s still uncertainty about making a significant change to your publishing cadence, establish a review date to evaluate the results. Give the changes at least three to six months before deciding whether to continue or adjust your approach.
Stay agile
Don’t treat any changes as permanent. As search and publishing continue to evolve, evaluate what’s working, such as content pruning, and what isn’t, such as changes to your publishing cadence.
Dig deeper: 4 types of content decay and how to fix each one



It’s not just about publishing less
Today’s content strategy isn’t about publishing more. It’s about making every article count. If your content isn’t driving meaningful business results, it isn’t the best use of your team’s time, budget, or resources. Every site has its own point of diminishing returns. Your job is to identify that threshold and adjust your production strategy accordingly.
Refreshing existing content while creating new content remains essential. Don’t create content that can be easily summarized. Instead, publish substantive, informative content that offers depth beyond a quick overview. Depth and quality will attract more users and customers than high-volume publishing.

Publishing more articles won't always improve SEO. Learn how indexing, crawl budget, and content pruning can drive better results.

The data-backed case for publishing less content

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/A-4-step-health-check-for-your-target-ROAS-and-CPA.png" class="attachment-large size-large wp-post-image" alt="A 4-step health check for your target ROAS and CPA" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/A-4-step-health-check-for-your-target-ROAS-and-CPA.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/A-4-step-health-check-for-your-target-ROAS-and-CPA-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/A-4-step-health-check-for-your-target-ROAS-and-CPA-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/A-4-step-health-check-for-your-target-ROAS-and-CPA-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Your bidding strategy is only as good as the targets behind it. Validate them with practical formulas and real campaign data.


Target ROAS and CPA aren’t optimization settings. They’re business decisions.
Many accounts inherit a target from a previous agency, finance team, or account manager without questioning whether it still makes sense. Set it too aggressively, and you limit volume and lose auctions. Set it too loosely, and you sacrifice profit.
This four-step framework shows you how to calculate a defensible target, test whether it’s realistic, and confirm that your last advertising dollar is still making you money.
Why your target matters more than you think
Two companies sell the same product. One tells their agency to hold ROAS at 800%. The other is fine with 400% because they’d rather take market share than protect margin. Guess who wins more auctions, shows up more often, and slowly takes the category.
As my high school economics teacher would have said, ceteris paribus, the advertiser with the more aggressive target wins. In other words, all else being equal, including conversion rate and Quality Score. In real life, ceteris is rarely paribus. But for this example, we’ll pretend it is.
The first company isn’t being disciplined. It’s being outbid, and it probably doesn’t know it. Somewhere, a target was set, entered into Smart Bidding, and never questioned again.
That doesn’t make the second company the smart one, by the way. Trading margin for market share can be brilliant or reckless, depending on the business behind it. The difference between these two companies isn’t who has the lower target. It’s whether anyone chose it on purpose.
This is the quiet problem with target ROAS and CPA. Most practitioners treat the number as a given. It came from the client, finance, or whatever the account was doing when they inherited it. It rarely came from a calculation they were involved in. 
Now that most campaigns use a bid strategy based on target CPA or ROAS, that target is the main lever you still control. Get it wrong in either direction, and you’ll either leave growth on the table or quietly lose money on every sale.
The good news is that the right target isn’t a matter of opinion. You can calculate it two ways:
From the inside out, starting with your profit margin and how much of it you’re willing to spend to grow.
From the outside in, sanity-checking against what the auction and your current performance will actually allow.
Once you have your number, there’s one final check most accounts never run: whether your last dollar is still making you money. None of it requires more than arithmetic, and all of it should feed one conversation you ought to have at least once a year with whoever owns the number.
I’ll share every formula along the way so you can rebuild them in a spreadsheet and run your own numbers before you finish reading.
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1. Start with the floor: Your break-even target
Start with the part you can probably do in your head:
Break-even ROAS = 1 / profit margin




A 40% margin breaks even at 250% ROAS. Below that, every sale costs more than it makes.
CPA gets its own formula because you’re usually buying a lead, not a sale:
Break-even CPA = Average profit per customer within your payback period x Lead-to-sale conversion rate




The payback period is a decision in itself. Profit over the full customer lifetime is the most generous window, but lifetime value (LTV) can take years to materialize, and few businesses have the cash to prepay for it. That’s why many advertisers count only the profit that arrives within six or 12 months. Pick the window first. The formula is only as honest as that choice.
Say a customer delivers $1,000 in profit within your chosen window, and one in five leads becomes a customer. Your break-even CPA is $1,000 x 20% = $200. Pay more per lead, and you’re underwater.
Nothing new so far, I know. Here’s why the refresher matters: Most accounts feed these formulas the wrong numbers.
The number that belongs in the formula is your effective margin, not your headline gross margin. Effective margin is what’s left after everything it takes to fulfill the order: shipping you subsidize, payment fees, fulfillment, and, in some categories, the quiet killer: returns. 
A fashion retailer with a 40% gross margin and a 25% return rate isn’t operating at 40%. After those deductions, it might be in the low 30% range.
That gap isn’t academic. At a 40% effective margin, your break-even ROAS is 250%. Drop the effective margin to 30%, and it climbs to 333%. 
Base your target on the headline number, and you’ll end up with one that looks profitable in a spreadsheet but loses money on every order. Nobody notices until finance asks why a “profitable” account isn’t generating cash.
The CPA version of the same mistake is counting lifetime profit when the business actually needs its money back within six months. Same formula, wrong window, same quiet losses.
So step one isn’t the formula. It’s getting the right numbers into it. Agree on the true effective margin and the payback window with whoever owns the P&L before you calculate anything
Dig deeper: How to optimize for ROAS in Google Ads using LTV insights



2. Inside-out: The target your margin can actually support
Break-even tells you where you stop losing money. It says nothing about how much profit you keep. For that, you need one more input, and it’s a business decision, not a math one: 
How much of your margin are you willing to spend to win a customer?
My PPC friends and fellow Dutchmen Bob Meijer (no relation, excellent surname) and Miles McNair of PPC Mastery have a three-letter acronym for this number: PAR, or Profit-to-Acquisition Ratio, the percentage of profit reinvested in Google Ads for acquisition. Credit to them for coining it and for finding three letters PPC hadn’t already claimed.
For this article, I’ll simply call it your acquisition share. Spend none of your margin, and you grow nothing. Spend all of it, and you’re back at break-even. The share lives between those poles, and where you set it is the single most consequential number nobody on the account ever discusses.
For ecommerce, the formula folds margin and acquisition share into one line:
Target ROAS = 1 / (Profit margin x Acquisition share)




Take a 40% margin and decide to spend half of it on acquisition:
Target ROAS = 1 / (40% x 50%) = 500% (5.0)
So 500% is your target. At break-even, you were at 250%. Spending half your margin to grow doubles the efficiency you demand. 
Want to grow faster? Raise the acquisition share to 70%, and the target drops to 357%. You’re accepting thinner returns per sale to win more of them. Want to protect profit? Drop it to 30%, and the target jumps to 833%, fewer sales, and a fatter margin on each.
For lead gen, fold the acquisition share into the break-even formula from earlier:
Target CPA = Average profit per customer within your payback period x Acquisition share x Lead-to-sale conversion rate




Run the same numbers: $1,000 in profit per customer x 50% acquisition share x 20% lead-to-sale conversion rate = $100. That’s exactly half of the $200 break-even, as you’d expect when you spend half your margin on acquisition.
That lead-to-sale conversion rate does more work in this formula than most lead-gen accounts give it credit for. Halve it from 20% to 10%, and your target CPA halves with it, from $100 to $50, for the exact same customer. The campaign didn’t change. The sales team did. If your CPA target feels impossible, the problem may not be in the account. It may be two desks over, or at your client’s office, wherever the leads you deliver become customers.
For most companies, the profit-maximizing acquisition share sits between 50% and 70%.
That range comes from George Michie‘s math, not my gut. His square root rule puts the theoretical profit peak at spending exactly half your margin, and his studies of real accounts found the peak slightly higher, around 60% to 70%.
But profit maximization, on average, isn’t a law for your business. The right number depends on 
How aggressive the business wants to be.
How much competitors are willing to spend.
Whether this quarter is about growth or profit. 
That’s exactly why it shouldn’t be set once and forgotten.
Sit down with your client or manager at least once a year and decide it together. Not the ROAS or CPA target itself, but the thinking behind it: the margin, the share of it you’re betting on acquisition, and the trade-off you’re accepting. 
Done right, “we need 8x ROAS” stops being a demand handed down from finance and becomes a conversation about how much growth the business is willing to pay for. That single conversation prevents more poorly set targets than any optimization you’ll do all year.
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3. Outside-in: Sanity-check the target against the auction
The inside-out target tells you what your business needs. It says nothing about what the auction and your current performance will allow. 
I learned this the awkward way in my agency days: A client handed me a target, I ran the math below, and the number that came out was nowhere near the one they walked in with. The arithmetic takes about 30 seconds, and apparently nobody had ever spent them.
The outside-in math needs two or three metrics you either have or can estimate in minutes.
Achievable ROAS = (Conversion rate x Average order value) / CPC




For CPA, it’s even simpler. Two metrics:
Achievable CPA = CPC / Conversion rate




There are no weightings and no hidden variables. Each input moves the result one for one: Double your conversion rate or your average order value, and your achievable ROAS doubles. Halve your CPC, and the same thing happens. Fill in actuals from your account, or estimates if you’re sizing up a new market, and the number rolls out.
Say your account shows a $0.80 average CPC, a 2% conversion rate, and a $120 average order value:
Achievable ROAS = (2% x $120) / $0.80 = 300%
Now put that next to the 500% inside-out target from earlier. The business wants 500%. Reality offers 300%. That’s the health check: The target isn’t realistic right now. Sure, Smart Bidding can technically deliver 500% by retreating to the handful of auctions where the math works, but that’s hitting the target by giving up volume, which is rarely what anyone meant.
By the way, 300% still clears the 250% break-even point. You’re not losing money. You’re keeping less of your margin than the business planned, which is a different, much calmer conversation.
The CPA version works the same way. A $4.50 CPC and a 2.5% conversion rate yield an achievable CPA of $180 ($4.50 / 0.025). Against the $100 target from earlier, it’s not realistic right now either.
Now the two companies from the intro come back into the picture. Your CPC is only partly your metric. The auction sets the price level based on what your competitors are willing to accept.
Run the formula in reverse to see what a target does to your bidding power. With a 2% conversion rate and a $120 average order value, a 400% target lets you pay up to $0.60 per click. An 800% target caps you at $0.30. The company demanding 800% isn’t being outbid by better marketers. It’s being outbid by its own target.
So what do you do when the desired target fails the check? The same formula tells you exactly what passing would take.
To reach 500% on those metrics, you need one of the following:
Increase your conversion rate from 2% to 3.33%.
Decrease your CPC from $0.80 to $0.48.
Increase your average order value from $120 to $200.
Make smaller improvements across all three.
Now you have something better than a missed target: a shortlist. Improve your landing pages to increase conversion rate, reduce wasted spend, and improve Quality Score to lower CPC, or increase average order value with bundles or free shipping thresholds. 
Something on that list can always improve. Just don’t assume it will improve enough. Whatever gap remains is evidence for the target conversation from the inside-out section.
I won’t pretend the renegotiation is fun. Telling your manager, client, or prospect that the desired target isn’t feasible right now makes you the bearer of bad news, and I never learned to enjoy it. What you’re really asking them to accept is a feasible target today, a plan toward the one they want, and the trade-offs in between. But that conversation happens once.
Accept the fantasy target instead, and you’ll have a worse conversation every month explaining why volume keeps falling short of expectations. Awkward now beats awkward forever.
4. The last-dollar check: Where the profit-maximizing target hides
By now, you have a target your margin can defend and a verdict on whether current reality will allow it. Here’s the catch: Every number we’ve calculated describes your average sale. Profit doesn’t happen on average. It happens one incremental dollar at a time.
You already know the principle behind this. Every campaign picks its cheapest conversions first, and Smart Bidding is ruthless about it. Each extra dollar buys slightly worse auctions than the one before: pricier clicks and vaguer queries. So the last dollar you spend always earns less than your average dollar. Blame the law of diminishing returns, not Google.
How much less? You don’t have to guess, and you don’t need anyone else’s benchmark. Google will show you, campaign by campaign.
How to run the last-dollar check in Google Ads
The bid simulator shows what your campaign would have done at different targets over the past week. For each simulated target, it estimates cost and conversions or conversion value.
Google won’t calculate the incremental numbers for you (I wonder why), but they’re hiding in plain sight between any two rows.




Take two target levels and divide the differences between them. For ROAS, the extra conversion value divided by the extra cost equals the incremental ROAS for that step.
From the screenshot above, changing the target ROAS from 500% to 436% would add €7,218 in spend and €19,493 in conversion value. That step earns an incremental ROAS of 270%, just above the 250% break-even point. So it could still be worthwhile.
Once your incremental ROAS or CPA falls below your break-even point, it’s “like feeding money into a shredder,” as George Michie put it.
For CPA, use the same approach in reverse: Divide the extra cost by the extra conversions to calculate the incremental CPA. If raising your target from $100 to $120 adds $3,000 in cost and 12 conversions, those conversions cost $250 each. Against a $200 break-even point, that’s too expensive.
Walk the rows until the incremental number crosses the bar you’ve set. The last step that reaches the break-even point marks your profit-maximizing target. If you want every extra dollar to earn the full inside-out target instead, use that stricter bar. You’ll stop sooner and keep more margin per sale. Either way, your own data determines what’s acceptable.
That completes the health check: a break-even floor, an inside-out target your margin can defend, an outside-in verdict on what reality allows, and a last-dollar reading of where profit actually peaks, based on your own campaigns.
a customer you lose.
      
See who’s stealing your traffic
    
Make the target an annual conversation
The full health check takes four steps, one afternoon, and no math beyond arithmetic:
Step 1: Calculate the break-even floor

Agree on the effective margin with whoever owns the P&L, then run your break-even ROAS or CPA. Wrong margin in, wrong everything out.
Step 2: Set the target inside-out

Decide together how much of that margin buys growth. The acquisition share is the business decision. The formula simply converts it into a target.
Step 3: Check it outside-in

Compare the target against your actual (or estimated) CPC, conversion rate, and, for ROAS, average order value. If they can’t produce the number, you need a plan or a renegotiation, not a pep talk.
Step 4: Check your last dollar

Open the bid simulators and look at what your next dollar earns. Below break-even, tighten. Far above it, you’re leaving profit on the table.
The target conversation should happen at least once a year with whoever owns the number, whether that’s a client, CFO, or manager. Margins change, competitors change their appetite, sales teams close better or worse, and a target that made sense when someone set it can slowly turn into a number nobody can explain.
The last-dollar check runs on a faster clock. The bid simulator uses the past seven days of data, so it can show you a new curve every week, and it doesn’t require a meeting.
The formulas are what turn the yearly conversation from “we want more” into an actual discussion about trade-offs: this much growth, at this much margin, given this auction.
You don’t even need to build the spreadsheet. I’ve created free, ungated PPC calculators for every step, from the inside-out and outside-in formulas to the bid simulator analysis: enter your numbers, get your answer, and bring it to the meeting.
Remember the two companies from the beginning? The difference between them was never the number. It was that one of them chose theirs on purpose. Be that company.

Your bidding strategy is only as good as the targets behind it. Validate them with practical formulas and real campaign data.

The 4-step health check for your target ROAS and CPA

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif 1920w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-768x432.avif 768w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1536x864.avif 1536w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1200x675.avif 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Centralized, tagged, governed. And still slow. Here's what your DAM was never designed to do.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif 1920w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-768x432.avif 768w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1536x864.avif 1536w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1200x675.avif 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div><div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif" alt="Illustration of the content activation cycle, showing an organized DAM connected to omnichannel asset delivery through asset activation workflows." class="wp-image-482034" srcset="https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage.avif 1920w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-768x432.avif 768w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1536x864.avif 1536w, https://searchengineland.com/wp-content/seloads/2026/07/ImageKit-FeaturedImage-1200x675.avif 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>
</div>


<p class="wp-block-paragraph">Your DAM is working.</p>



<p class="wp-block-paragraph">Assets are centralized. Metadata is applied. Roles and permissions are in place. By every standard measure of a <a href="https://imagekit.io/guides/digital-asset-management/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">digital asset management</a> (DAM) implementation, you succeeded.</p>



<p class="wp-block-paragraph">And yet, campaigns still launch late. Engineering is still fielding requests to resize hero images. The regional team in APAC is re-uploading files into the local CMS because they can&#8217;t easily pull from the DAM. The DAM isn&#8217;t broken; the assumption is that a functioning DAM means your content is ready to work.</p>



<h3 class="wp-block-heading" id="h-a-library-and-a-supply-chain-are-not-the-same-thing">A library and a supply chain are not the same thing</h3>



<p class="wp-block-paragraph">The original promise of DAM was organization: one place for assets, consistent metadata, and governance over which ones are approved and current. That&#8217;s a library problem, and modern DAMs solve it well. Assets are searchable, versions are controlled, and expired content doesn’t go live by accident.&nbsp;</p>



<p class="wp-block-paragraph">But activation is a supply chain problem. An asset has to reach a campaign page, a product detail page, a social post, an email, and a partner&#8217;s CMS, in the right format, at the right quality, at the right moment. And the systems running that chain are increasingly AI agents and automations, not humans. Libraries were not built to run supply chains.</p>



<p class="wp-block-paragraph"><a href="https://business.adobe.com/blog/71-percent-of-marketers-say-content-demand-to-increase-5x" target="_blank" rel="noopener sponsored nofollow">Adobe&#8217;s 2025 research</a> surveyed more than 1,600 marketers and found that 62% say content demand has already increased 5x or more over the last two years. At the same time, <a href="https://learn.g2.com/ai-in-digital-asset-management" target="_blank" rel="noopener sponsored nofollow">G2&#8217;s 2026 DAM report</a> found eight out of 10 DAM vendors now cite exponential asset growth as their primary operational pressure. More content, multiplied by more channels, equals more strain on the activation side. And yet, content activation workflows are stuck where they were five years ago.</p>



<p class="wp-block-paragraph">The distance between an asset sitting in your DAM and that asset arriving in front of a customer —&nbsp; in the right state, at the right moment — is the Content Activation Gap. Closing it requires five specific shifts that most DAM implementations haven&#8217;t made:</p>



<h3 class="wp-block-heading" id="h-from-portal-navigation-to-headless-integration">From portal navigation to headless integration</h3>



<p class="wp-block-paragraph">Most DAMs were built with a portal in mind. A user logs in, navigates a folder structure, finds an asset, downloads it, and uploads it into the next system. Every interaction is manual, in both directions.&nbsp;</p>



<p class="wp-block-paragraph">That model breaks at scale. Content moves in and out of systems faster than any portal can mediate. <a href="https://imagekit.io/solutions/headless-dam/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">Headless</a> API access lets any authorized system write to or read from the DAM directly. An ecommerce platform pulls product images from the DAM at the moment a webpage is rendered. A video production tool uploads rendered files to the DAM the moment a job completes.  </p>



<p class="wp-block-paragraph">Native integrations bring the DAM into the tools teams already use. A Figma plugin pushes designs straight into the campaign folder. A Slack integration shares assets and approval status directly in the channel where the team already talks.&nbsp;</p>



<p class="wp-block-paragraph">A DAM disconnected from the stack becomes a workaround.&nbsp;</p>



<h3 class="wp-block-heading" id="h-from-stored-exports-to-on-demand-variants-and-versions">From stored exports to on-demand variants and versions</h3>



<p class="wp-block-paragraph">Every time a new channel, size, or format is needed, the same asset gets downloaded, resized, and re-uploaded. A <a href="https://digitalassetmanagementnews.org/features/designers-extremely-frustrated-with-resizing-process/" target="_blank" rel="noopener sponsored nofollow">2023 survey by Santa Cruz Software</a> found that 76% of designers spend at least 20 hours per week resizing graphics. That isn&#8217;t a design capacity problem. It&#8217;s a file architecture problem.</p>



<p class="wp-block-paragraph">The alternative is URL-based <a href="https://imagekit.io/solutions/publish-assets-digital-asset-management/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">transformations</a> that work in real time. Add parameters for size, format, or edits, and the variant comes back without anyone pre-generating it. A 6MB original at 4000×3000 serves a 1920×1080 hero image, a 400×400 thumbnail, a 1200×630 social preview card, and a 750×1000 mobile variant, all from the same asset. And with AI, transformations go further. The same source file delivers background swaps, generative fill, prompt-based edits, and AI-generated variations on demand.</p>



<p class="wp-block-paragraph"><a href="https://imagekit.io/docs/dam/asset-versioning?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">Versioning</a> works on the same principle. The URL stays stable, the file behind it changes, and one update reaches every system that references it. Update once. Reflect everywhere. This is the model DAM platforms like <a href="https://imagekit.io/digital-asset-management/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">ImageKit</a> are built on.</p>



<h3 class="wp-block-heading" id="h-from-manual-upkeep-to-autonomous-ai-agents">From manual upkeep to autonomous AI agents </h3>



<p class="wp-block-paragraph">A growing library doesn&#8217;t stay clean on its own. Tags drift as people leave, metadata grows inconsistent, and file formats sneak in that shouldn&#8217;t. Manual housekeeping doesn&#8217;t scale with volume.</p>



<p class="wp-block-paragraph">Autonomous <a href="https://imagekit.io/blog/introducing-dam-agent-ai-powered-media-management/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">AI agents</a> change that. They run <a href="https://imagekit.io/solutions/digital-asset-management-governance/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">quality control</a> on every upload, apply controlled vocabulary against business-specific taxonomies, enforce format and metadata requirements, and hold drafts unpublished until approved. The library stays clean without anyone scheduling a cleanup sprint.</p>



<p class="wp-block-paragraph">This becomes essential when downstream consumers are themselves agents. An AI agent retrieving an asset for a product page needs the file to be correctly tagged, in an approved format, and published rather than still a draft. If autonomous agents have already done the upkeep, the retrieving agent finds a folder where the rules have already been applied.</p>



<h3 class="wp-block-heading" id="h-from-hopeful-search-to-ai-powered-discovery">From hopeful search to AI-powered discovery</h3>



<p class="wp-block-paragraph">At scale, <a href="https://imagekit.io/solutions/digital-asset-management-organize-search/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">search</a> in a DAM becomes a gamble. One team tags a product image &#8220;T-shirt.&#8221; Another tags it &#8220;TShirt.&#8221; A third uses a different tag entirely. Search for any one term and you&#8217;ll find a fraction of what the library actually holds.</p>



<p class="wp-block-paragraph">AI agents are now searching alongside humans, and that changes what a missed match costs. A wrong result used to mean another search. Now it can mean a wrong asset shipping into production.&nbsp;</p>



<p class="wp-block-paragraph">AI-powered discovery closes the gap. Natural-language queries return results based on meaning, not keyword match. Visual search surfaces similar assets regardless of how they were named. The same approach extends to video, where AI can index visual content and spoken dialogue rather than depending on a manually-typed title. Discovery isn&#8217;t about better keywords anymore. It&#8217;s about a library queryable by what assets contain.</p>



<h3 class="wp-block-heading" id="h-from-a-standalone-dam-to-an-mcp-connected-stack">From a standalone DAM to an MCP-connected stack</h3>



<p class="wp-block-paragraph">A modern DAM doesn&#8217;t sit on its own. Creative apps, AI coding assistants, marketing copilots, and campaign automation agents all need to interact with the asset library directly.</p>



<p class="wp-block-paragraph"><a href="https://imagekit.io/docs/build-with-ai?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">MCP</a> (Model Context Protocol) servers make this possible. They expose the DAM as a service that any compliant AI tool can call. A developer in Cursor pulls approved product images without leaving their IDE. A marketer in Claude pulls brand-cleared hero images mid-conversation. An automation agent building a product launch email pulls the right assets without anyone selecting them. The DAM stops being a destination people switch to. It becomes a layer that the rest of the stack reaches into.</p>



<h3 class="wp-block-heading" id="h-the-question-has-changed">The question has changed</h3>



<p class="wp-block-paragraph">For years, content operations revolved around one question. Where do we store our assets? Building a DAM was the answer.</p>



<p class="wp-block-paragraph">That question is largely settled. Most enterprise teams have a functioning library. The next question is harder. How fast can those assets reach customers, formatted for every channel, correctable at the source, and ready for both human teams and AI agents to act on?</p>



<p class="wp-block-paragraph">Together, the five shifts answer it. They turn the DAM from a tool that teams visit into infrastructure that the rest of the stack runs on. <a href="https://imagekit.io/solutions/ai-imagekit-dam/?utm_source=MarTech&amp;utm_medium=referral&amp;utm_campaign=Your-DAM-Solved-the-Library-Problem" target="_blank" rel="noopener sponsored nofollow">AI</a> compounds the change: agents handle the upkeep, drive the discovery, and cut the time between a finished asset and a live channel.</p>



<p class="wp-block-paragraph">The next generation of DAM won&#8217;t be judged by how well it stores and organizes assets. It will be judged by how quickly those assets move across channels, teams, and AI workflows. The library was the foundation. Activation is the building on top of it.</p>


Your DAM is working.
Assets are centralized. Metadata is applied. Roles and permissions are in place. By every standard measure of a digital asset management (DAM) implementation, you succeeded.
And yet, campaigns still launch late. Engineering is still fielding requests to resize hero images. The regional team in APAC is re-uploading files into the local CMS because they can’t easily pull from the DAM. The DAM isn’t broken; the assumption is that a functioning DAM means your content is ready to work.
A library and a supply chain are not the same thing
The original promise of DAM was organization: one place for assets, consistent metadata, and governance over which ones are approved and current. That’s a library problem, and modern DAMs solve it well. Assets are searchable, versions are controlled, and expired content doesn’t go live by accident. 
But activation is a supply chain problem. An asset has to reach a campaign page, a product detail page, a social post, an email, and a partner’s CMS, in the right format, at the right quality, at the right moment. And the systems running that chain are increasingly AI agents and automations, not humans. Libraries were not built to run supply chains.
Adobe’s 2025 research surveyed more than 1,600 marketers and found that 62% say content demand has already increased 5x or more over the last two years. At the same time, G2’s 2026 DAM report found eight out of 10 DAM vendors now cite exponential asset growth as their primary operational pressure. More content, multiplied by more channels, equals more strain on the activation side. And yet, content activation workflows are stuck where they were five years ago.
The distance between an asset sitting in your DAM and that asset arriving in front of a customer —  in the right state, at the right moment — is the Content Activation Gap. Closing it requires five specific shifts that most DAM implementations haven’t made:
From portal navigation to headless integration
Most DAMs were built with a portal in mind. A user logs in, navigates a folder structure, finds an asset, downloads it, and uploads it into the next system. Every interaction is manual, in both directions. 
That model breaks at scale. Content moves in and out of systems faster than any portal can mediate. Headless API access lets any authorized system write to or read from the DAM directly. An ecommerce platform pulls product images from the DAM at the moment a webpage is rendered. A video production tool uploads rendered files to the DAM the moment a job completes.  
Native integrations bring the DAM into the tools teams already use. A Figma plugin pushes designs straight into the campaign folder. A Slack integration shares assets and approval status directly in the channel where the team already talks. 
A DAM disconnected from the stack becomes a workaround. 
From stored exports to on-demand variants and versions
Every time a new channel, size, or format is needed, the same asset gets downloaded, resized, and re-uploaded. A 2023 survey by Santa Cruz Software found that 76% of designers spend at least 20 hours per week resizing graphics. That isn’t a design capacity problem. It’s a file architecture problem.
The alternative is URL-based transformations that work in real time. Add parameters for size, format, or edits, and the variant comes back without anyone pre-generating it. A 6MB original at 4000×3000 serves a 1920×1080 hero image, a 400×400 thumbnail, a 1200×630 social preview card, and a 750×1000 mobile variant, all from the same asset. And with AI, transformations go further. The same source file delivers background swaps, generative fill, prompt-based edits, and AI-generated variations on demand.
Versioning works on the same principle. The URL stays stable, the file behind it changes, and one update reaches every system that references it. Update once. Reflect everywhere. This is the model DAM platforms like ImageKit are built on.
From manual upkeep to autonomous AI agents 
A growing library doesn’t stay clean on its own. Tags drift as people leave, metadata grows inconsistent, and file formats sneak in that shouldn’t. Manual housekeeping doesn’t scale with volume.
Autonomous AI agents change that. They run quality control on every upload, apply controlled vocabulary against business-specific taxonomies, enforce format and metadata requirements, and hold drafts unpublished until approved. The library stays clean without anyone scheduling a cleanup sprint.
This becomes essential when downstream consumers are themselves agents. An AI agent retrieving an asset for a product page needs the file to be correctly tagged, in an approved format, and published rather than still a draft. If autonomous agents have already done the upkeep, the retrieving agent finds a folder where the rules have already been applied.
From hopeful search to AI-powered discovery
At scale, search in a DAM becomes a gamble. One team tags a product image “T-shirt.” Another tags it “TShirt.” A third uses a different tag entirely. Search for any one term and you’ll find a fraction of what the library actually holds.
AI agents are now searching alongside humans, and that changes what a missed match costs. A wrong result used to mean another search. Now it can mean a wrong asset shipping into production. 
AI-powered discovery closes the gap. Natural-language queries return results based on meaning, not keyword match. Visual search surfaces similar assets regardless of how they were named. The same approach extends to video, where AI can index visual content and spoken dialogue rather than depending on a manually-typed title. Discovery isn’t about better keywords anymore. It’s about a library queryable by what assets contain.
From a standalone DAM to an MCP-connected stack
A modern DAM doesn’t sit on its own. Creative apps, AI coding assistants, marketing copilots, and campaign automation agents all need to interact with the asset library directly.
MCP (Model Context Protocol) servers make this possible. They expose the DAM as a service that any compliant AI tool can call. A developer in Cursor pulls approved product images without leaving their IDE. A marketer in Claude pulls brand-cleared hero images mid-conversation. An automation agent building a product launch email pulls the right assets without anyone selecting them. The DAM stops being a destination people switch to. It becomes a layer that the rest of the stack reaches into.
The question has changed
For years, content operations revolved around one question. Where do we store our assets? Building a DAM was the answer.
That question is largely settled. Most enterprise teams have a functioning library. The next question is harder. How fast can those assets reach customers, formatted for every channel, correctable at the source, and ready for both human teams and AI agents to act on?
Together, the five shifts answer it. They turn the DAM from a tool that teams visit into infrastructure that the rest of the stack runs on. AI compounds the change: agents handle the upkeep, drive the discovery, and cut the time between a finished asset and a live channel.
The next generation of DAM won’t be judged by how well it stores and organizes assets. It will be judged by how quickly those assets move across channels, teams, and AI workflows. The library was the foundation. Activation is the building on top of it.

Centralized, tagged, governed. And still slow. Here's what your DAM was never designed to do.

Your DAM solved the library problem. The activation problem is next. by ImageKit

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership.png" class="attachment-large size-large wp-post-image" alt="ChatGPT brand topic ownership" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Mentions matter more than citations, and narrow leads often change, revealing the instability of AI search brand authority, Semrush finds.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership.png" class="attachment-large size-large wp-post-image" alt="ChatGPT brand topic ownership" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership.png 1920w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/chatgpt-brand-topic-ownership-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">Only 15.2% of ChatGPT topic categories had a clear brand owner across related buyer questions, according to a Semrush analysis.</p>
</blockquote>



<p class="wp-block-paragraph">That means about 85% of categories had no dominant brand. Appearing in one prompt didn&#8217;t mean a brand appeared consistently across related questions in the same topic.</p>



<p class="wp-block-paragraph"><strong>How ownership was defined.</strong> Semrush defined a category owner as the brand with the highest share of mentions, appearing in at least four of five related prompts and leading the runner-up by at least 5 percentage points.</p>



<ul class="wp-block-list">
<li>Only 15.2% of the 1,094 categories met that standard.</li>



<li>Another 31.2% had an emerging leader, with one brand appearing in at least three prompts but without the required lead.</li>



<li>The remaining 53.7% were unsettled, with no brand appearing in at least three of five prompts.</li>
</ul>



<p class="wp-block-paragraph"><strong>Popular topics</strong>,<strong> few clear owners. </strong>Semrush split categories into two groups by AI search demand. Only 11.3% of topics in the top half had a clear owner, compared with 19% in the bottom half.</p>



<ul class="wp-block-list">
<li>The top half accounted for 98% of the AI search volume in the sample.</li>



<li>Most ChatGPT demand Semrush tracked was in categories without a clear brand owner.</li>
</ul>



<p class="wp-block-paragraph"><strong>Broad SEO metrics had limited predictive value</strong>. Traditional SEO strength didn&#8217;t reliably predict which brands owned ChatGPT topics. “Traditional SEO metrics aren&#8217;t enough to explain who owns a topic. While they play their role, there’s more to it,” wrote Kevin Indig, founder of Growth Memo. </p>



<ul class="wp-block-list">
<li>Semrush compared category owners with runners-up across branded search volume, organic traffic, and Authority Score.</li>



<li>Owners had higher branded search volume in 55.7% of comparisons, higher organic traffic in 48.4%, and a higher Authority Score in 52.5%. Branded search volume was the only metric that reached statistical significance.</li>
</ul>



<p class="wp-block-paragraph"><strong>Most-cited rarely meant most-mentioned.</strong> Semrush measured ownership by brand mentions in ChatGPT’s answer text, not by the links cited below.</p>



<ul class="wp-block-list">
<li>Mentions and citations often didn&#8217;t align. Only 21% of the most-cited domains in a category were also the most-mentioned brand.</li>
</ul>


<a href="https://www.semrush.com/ai-seo/overview?utm_campaign=ic_sel_0102ai&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>
    
    <div>
      
      <div id="semrush-one-headline" class="headline-responsive">
        If AI can’t find you, <span>customers won’t either</span>.
      </div>
      <p id="semrush-one-subhead">
       Track your visibility across AI search, uncover missed opportunities, and grow your presence where customers are asking questions.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta">See your AI visibility</span>
    </div>
    </div>
    </a>




<p class="wp-block-paragraph"><strong>Why we care</strong>. Semrush found that prompt-level visibility didn&#8217;t always carry across related buyer questions. That suggests topic-level visibility is more useful for assessing whether ChatGPT consistently associates a brand with a category.</p>



<p class="wp-block-paragraph"><strong>Brands that owned a topic usually kept it.</strong> Clear category owners stayed in first place in 90.4% of month-over-month comparisons. Weaker leaders changed more often, with the top brand switching in 1,950 of 5,470 comparisons across emerging and unsettled categories.</p>



<p class="wp-block-paragraph"><strong>Narrow leads were less stable. </strong>When a top brand later lost first place, its typical lead was just 1.3 percentage points. When it stayed on top, its typical lead was 2.9 points, more than twice as large.</p>



<ul class="wp-block-list">
<li>Semrush said the data didn&#8217;t explain why leaders changed. It showed only that brands with smaller leads were more likely to lose first place.</li>
</ul>



<p class="wp-block-paragraph"><strong>About the data.</strong> Semrush and Kevin Indig analyzed 1,094 U.S. categories in ChatGPT from January through June 2026 using the Semrush AI Visibility Toolkit. The dataset covered more than 50,000 brands, 220,000 domains, 600,000 citations, and 220,000 URLs. Each category included five prompts tied to common buyer questions, including definitions, comparisons, alternatives, use cases, and buying decisions.</p>



<p class="wp-block-paragraph"><strong>The study.</strong> <a href="https://www.semrush.com/blog/chatgpt-topic-authority-study/" target="_blank" rel="noopener">AI visibility is a topic-level game: A study of 50,000 brands in ChatGPT [Study]</a>


Only 15.2% of ChatGPT topic categories had a clear brand owner across related buyer questions, according to a Semrush analysis.
That means about 85% of categories had no dominant brand. Appearing in one prompt didn’t mean a brand appeared consistently across related questions in the same topic.
How ownership was defined. Semrush defined a category owner as the brand with the highest share of mentions, appearing in at least four of five related prompts and leading the runner-up by at least 5 percentage points.
Only 15.2% of the 1,094 categories met that standard.
Another 31.2% had an emerging leader, with one brand appearing in at least three prompts but without the required lead.
The remaining 53.7% were unsettled, with no brand appearing in at least three of five prompts.
Popular topics, few clear owners. Semrush split categories into two groups by AI search demand. Only 11.3% of topics in the top half had a clear owner, compared with 19% in the bottom half.
The top half accounted for 98% of the AI search volume in the sample.
Most ChatGPT demand Semrush tracked was in categories without a clear brand owner.
Broad SEO metrics had limited predictive value. Traditional SEO strength didn’t reliably predict which brands owned ChatGPT topics. “Traditional SEO metrics aren’t enough to explain who owns a topic. While they play their role, there’s more to it,” wrote Kevin Indig, founder of Growth Memo. 
Semrush compared category owners with runners-up across branded search volume, organic traffic, and Authority Score.
Owners had higher branded search volume in 55.7% of comparisons, higher organic traffic in 48.4%, and a higher Authority Score in 52.5%. Branded search volume was the only metric that reached statistical significance.
Most-cited rarely meant most-mentioned. Semrush measured ownership by brand mentions in ChatGPT’s answer text, not by the links cited below.
Mentions and citations often didn’t align. Only 21% of the most-cited domains in a category were also the most-mentioned brand.
customers won’t either.
      
See your AI visibility
    
Why we care. Semrush found that prompt-level visibility didn’t always carry across related buyer questions. That suggests topic-level visibility is more useful for assessing whether ChatGPT consistently associates a brand with a category.
Brands that owned a topic usually kept it. Clear category owners stayed in first place in 90.4% of month-over-month comparisons. Weaker leaders changed more often, with the top brand switching in 1,950 of 5,470 comparisons across emerging and unsettled categories.
Narrow leads were less stable. When a top brand later lost first place, its typical lead was just 1.3 percentage points. When it stayed on top, its typical lead was 2.9 points, more than twice as large.
Semrush said the data didn’t explain why leaders changed. It showed only that brands with smaller leads were more likely to lose first place.
About the data. Semrush and Kevin Indig analyzed 1,094 U.S. categories in ChatGPT from January through June 2026 using the Semrush AI Visibility Toolkit. The dataset covered more than 50,000 brands, 220,000 domains, 600,000 citations, and 220,000 URLs. Each category included five prompts tied to common buyer questions, including definitions, comparisons, alternatives, use cases, and buying decisions.
The study. AI visibility is a topic-level game: A study of 50,000 brands in ChatGPT [Study]

Mentions matter more than citations, and narrow leads often change, revealing the instability of AI search brand authority, Semrush finds.

ChatGPT topic ownership is rare, and SEO alone doesn’t explain it

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google Ads' new beta estimates the clicks, conversions, and revenue you may be missing due to limited budgets and low bids.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-recommendation-tab-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google Ads is bringing its &#8220;Missed Growth Opportunity&#8221; insights into the main Recommendations tab as a new beta, giving advertisers a clearer view of the traffic, conversions, and revenue they may be missing because of budget constraints or low bids.</p>



<p class="wp-block-paragraph">The move makes these opportunity estimates more visible, surfacing them directly alongside Google&#8217;s existing optimization recommendations.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s new</strong>. A new beta recommendation estimates the potential impact of increasing budgets or raising bids.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="565" height="431" src="https://searchengineland.com/wp-content/seloads/2026/07/Screenshot-2026-07-21-at-18.55.09.png" alt="" class="wp-image-482918"/></figure>



<p class="wp-block-paragraph">The feature highlights:</p>



<ul class="wp-block-list">
<li>Estimated clicks left on the table.</li>



<li>Missed conversions.</li>



<li>Unrealized conversion value.</li>



<li>Whether those missed opportunities were primarily caused by budget limitations or low bids.</li>
</ul>



<p class="wp-block-paragraph">Previously, these insights were available as the &#8220;Missed Growth Opportunity&#8221; tool within Google Ads Labs. They&#8217;re now being integrated into the Recommendations section for eligible advertisers.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Budget allocation and bid adjustments are among the biggest levers advertisers have for driving growth. By quantifying the potential impact of budget or bid constraints, Google is giving advertisers another data point to prioritize where additional spend could deliver the greatest return. That said, these are still modeled estimates—not guarantees. Advertisers should treat them as directional insights and validate them against their own performance data before increasing budgets or bids.</p>



<p class="wp-block-paragraph"><strong>What they&#8217;re seeing</strong>. The beta displays estimated missed performance directly within the Recommendations tab, breaking down unrealized results by whether they were caused by insufficient budgets or bids.</p>



<p class="wp-block-paragraph">The update was spotted by PPC expert Thomas Eccel, who noted that the feature is essentially a rebranded version of the former <a href="https://www.linkedin.com/posts/thomaseccel_ppc-googleads-share-7484255810085269504-42wP/">&#8220;Missed Growth Opportunity&#8221; tool from Google Ads Labs</a>.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. Google is giving advertisers a more prominent way to evaluate the cost of budget and bid constraints. If the underlying estimates are reliable, the new beta could become a useful planning tool for identifying untapped growth opportunities—but advertisers should verify the recommendations before acting on them.</p>


<a href="https://www.semrush.com/analytics/traffic/paid-search?utm_campaign=ic_sel_0102ppc&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>
    
    <div>
      
      <div id="semrush-one-headline" class="headline-responsive">
        Every click they win is <span>a customer you lose</span>.
      </div>
      <p id="semrush-one-subhead">
        See where competitors are investing, which keywords drive their results, and how to capture more of the market.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta">See who’s stealing your traffic</span>
    </div>
    </div>
    </a>



Google Ads is bringing its “Missed Growth Opportunity” insights into the main Recommendations tab as a new beta, giving advertisers a clearer view of the traffic, conversions, and revenue they may be missing because of budget constraints or low bids.
The move makes these opportunity estimates more visible, surfacing them directly alongside Google’s existing optimization recommendations.
What’s new. A new beta recommendation estimates the potential impact of increasing budgets or raising bids.




The feature highlights:
Estimated clicks left on the table.
Missed conversions.
Unrealized conversion value.
Whether those missed opportunities were primarily caused by budget limitations or low bids.
Previously, these insights were available as the “Missed Growth Opportunity” tool within Google Ads Labs. They’re now being integrated into the Recommendations section for eligible advertisers.
Why we care. Budget allocation and bid adjustments are among the biggest levers advertisers have for driving growth. By quantifying the potential impact of budget or bid constraints, Google is giving advertisers another data point to prioritize where additional spend could deliver the greatest return. That said, these are still modeled estimates—not guarantees. Advertisers should treat them as directional insights and validate them against their own performance data before increasing budgets or bids.
What they’re seeing. The beta displays estimated missed performance directly within the Recommendations tab, breaking down unrealized results by whether they were caused by insufficient budgets or bids.
The update was spotted by PPC expert Thomas Eccel, who noted that the feature is essentially a rebranded version of the former “Missed Growth Opportunity” tool from Google Ads Labs.
Bottom line. Google is giving advertisers a more prominent way to evaluate the cost of budget and bid constraints. If the underlying estimates are reliable, the new beta could become a useful planning tool for identifying untapped growth opportunities—but advertisers should verify the recommendations before acting on them.
a customer you lose.
      
See who’s stealing your traffic

Google Ads' new beta estimates the clicks, conversions, and revenue you may be missing due to limited budgets and low bids.

Google Ads adds missed growth estimates to the Recommendations tab

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google Ads now lets advertisers bulk link multiple accounts to a single GA4 property reducing manual account management.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup.png 1672w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/07/Google-Ads-GA4-setup-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is rolling out a new way for advertisers to link multiple Google Ads accounts to a single Google Analytics 4 (GA4) property, making it easier to manage data sharing across accounts from one place.</p>



<p class="wp-block-paragraph">The update is particularly useful for advertisers and agencies that oversee multiple Google Ads accounts tied to the same GA4 property, reducing the need to link each account individually.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s new</strong>. A new bulk linking option has been added under Data Manager &gt; Google Analytics 4 &gt; Link Setup in Google Ads.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="569" height="403" src="https://searchengineland.com/wp-content/seloads/2026/07/Screenshot-2026-07-21-at-18.31.03.png" alt="" class="wp-image-482910"/></figure>



<p class="wp-block-paragraph">Advertisers can use a drop-down menu to select or deselect multiple Google Ads accounts they want connected to a GA4 property. Once linked, the selected accounts can share data with the chosen analytics property, streamlining account management.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. For advertisers managing multiple Google Ads accounts, this update removes a tedious administrative task and makes it easier to keep measurement setups consistent across campaigns. Agencies, franchises, and enterprise marketing teams can quickly update account links as clients are added or removed, reducing the risk of missing conversion data or creating reporting gaps.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. Google&#8217;s latest update simplifies the relationship between Google Ads and GA4 by allowing advertisers to manage multiple account links from a single interface, saving time and making data integration easier at scale.</p>



<p class="wp-block-paragraph"><strong>First spotted.</strong> This update was spotted by Paid Search expert Thomas Eccel, who shared spotting the update on <a href="https://www.linkedin.com/posts/thomaseccel_ppc-googleads-share-7483127201417162752-wxZ4/">LinkedIn</a>.</p>


<a href="https://www.semrush.com/analytics/traffic/paid-search?utm_campaign=ic_sel_0101ppc&#038;utm_source=searchengineland.com&#038;utm_medium=overlay&#038;onboarding=off" target="_blank">
  <div>
    
    <div>
      
      <div id="semrush-one-headline" class="headline-responsive">
        See exactly how <span>your competitors win</span>.
      </div>
      <p id="semrush-one-subhead">
        Uncover the keywords, ads, landing pages, and strategies driving your competitors&#8217; paid search success—and find your next opportunity to outperform them.
      </p>
    </div>
    <div>
      <span id="semrush-one-cta">Analyze your competitors</span>
    </div>
    </div>
    </a>



Google is rolling out a new way for advertisers to link multiple Google Ads accounts to a single Google Analytics 4 (GA4) property, making it easier to manage data sharing across accounts from one place.
The update is particularly useful for advertisers and agencies that oversee multiple Google Ads accounts tied to the same GA4 property, reducing the need to link each account individually.
What’s new. A new bulk linking option has been added under Data Manager > Google Analytics 4 > Link Setup in Google Ads.




Advertisers can use a drop-down menu to select or deselect multiple Google Ads accounts they want connected to a GA4 property. Once linked, the selected accounts can share data with the chosen analytics property, streamlining account management.
Why we care. For advertisers managing multiple Google Ads accounts, this update removes a tedious administrative task and makes it easier to keep measurement setups consistent across campaigns. Agencies, franchises, and enterprise marketing teams can quickly update account links as clients are added or removed, reducing the risk of missing conversion data or creating reporting gaps.
Bottom line. Google’s latest update simplifies the relationship between Google Ads and GA4 by allowing advertisers to manage multiple account links from a single interface, saving time and making data integration easier at scale.
First spotted. This update was spotted by Paid Search expert Thomas Eccel, who shared spotting the update on LinkedIn.
your competitors win.
      
Analyze your competitors

Google Ads now lets advertisers bulk link multiple accounts to a single GA4 property reducing manual account management.

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