<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform.png" class="attachment-large size-large wp-post-image" alt="OpenAI ChatGPT ad platform" style="margin-bottom: 15px;" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform.png 1920w, https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>OpenAI’s COO says ChatGPT ad rollout will be gradual and privacy-focused, as it tests monetization without compromising user trust.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform.png" class="attachment-large size-large wp-post-image" alt="OpenAI ChatGPT ad platform" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform.png 1920w, https://searchengineland.com/wp-content/seloads/2025/09/OpenAI-ChatGPT-ad-platform-768x432.png 768w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>OpenAI started <a href="https://searchengineland.com/openai-starts-testing-chatgpt-ads-468593">introducing ads</a> to free and Go-tier users of ChatGPT in the U.S., marking a significant shift in its monetization strategy — and drawing scrutiny from competitors.</p>



<p><strong>What’s happening</strong>. After signaling plans last month, OpenAI quietly rolled out ads to U.S.-based users earlier this month. The move comes amid rising competition, including high-profile marketing pushes from Anthropic.</p>



<p><strong>What OpenAI says</strong>. Speaking at the India AI summit, COO Brad Lightcap described the rollout as “iterative,” emphasizing user trust and privacy. He said ads, if done right, can be “additive” to the product experience — but acknowledged the company is still in early testing and will need time to refine the model.</p>



<p><strong>The backdrop</strong>. CEO Sam Altman recently sparred publicly with Anthropic over its Super Bowl ad campaign, defending OpenAI’s commitment to broad, free AI access. He argued that scale creates a “differently-shaped problem” for OpenAI compared to rivals with smaller user bases.</p>



<p><strong>The money angle</strong>. Reports suggest OpenAI is charging premium rates — as high as $60 CPM — with minimum commitments reportedly starting around $200,000. Meanwhile, partners like Shopify are enabling merchants to advertise inside ChatGPT through Shop Campaigns, alongside early testers including Target and Adobe.</p>



<p><strong>Between the lines</strong>. OpenAI is walking a tightrope: monetize its massive free user base without eroding trust — especially as privacy concerns and competitive pressures intensify.</p>



<p><strong>The bottom line</strong>. Ads are now part of ChatGPT’s future. The question isn’t whether OpenAI will monetize — it’s whether it can do so without compromising the product experience that fuelled its growth.</p>



<p><strong>Dig Deeper.</strong> <a href="https://techcrunch.com/2026/02/25/openai-coo-says-ads-will-be-an-iterative-process/">OpenAI COO says ads will be ‘an iterative process’</a></p>


OpenAI started introducing ads to free and Go-tier users of ChatGPT in the U.S., marking a significant shift in its monetization strategy — and drawing scrutiny from competitors.
What’s happening. After signaling plans last month, OpenAI quietly rolled out ads to U.S.-based users earlier this month. The move comes amid rising competition, including high-profile marketing pushes from Anthropic.
What OpenAI says. Speaking at the India AI summit, COO Brad Lightcap described the rollout as “iterative,” emphasizing user trust and privacy. He said ads, if done right, can be “additive” to the product experience — but acknowledged the company is still in early testing and will need time to refine the model.
The backdrop. CEO Sam Altman recently sparred publicly with Anthropic over its Super Bowl ad campaign, defending OpenAI’s commitment to broad, free AI access. He argued that scale creates a “differently-shaped problem” for OpenAI compared to rivals with smaller user bases.
The money angle. Reports suggest OpenAI is charging premium rates — as high as $60 CPM — with minimum commitments reportedly starting around $200,000. Meanwhile, partners like Shopify are enabling merchants to advertise inside ChatGPT through Shop Campaigns, alongside early testers including Target and Adobe.
Between the lines. OpenAI is walking a tightrope: monetize its massive free user base without eroding trust — especially as privacy concerns and competitive pressures intensify.
The bottom line. Ads are now part of ChatGPT’s future. The question isn’t whether OpenAI will monetize — it’s whether it can do so without compromising the product experience that fuelled its growth.
Dig Deeper. OpenAI COO says ads will be ‘an iterative process’

OpenAI’s COO says ChatGPT ad rollout will be gradual and privacy-focused, as it tests monetization without compromising user trust.

OpenAI COO says ChatGPT ad rollout will be “iterative”

<div><img width="800" height="462" src="https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-800x462.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-800x462.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-586x338.jpg 586w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-196x113.jpg 196w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-768x443.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-1536x886.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-150x87.jpg 150w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>Google’s new pacing update could increase monthly spend for ad-scheduled campaigns by pushing budgets harder within allowed run times.

<div><img width="800" height="462" src="https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-800x462.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-800x462.jpg 800w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-586x338.jpg 586w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-196x113.jpg 196w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-768x443.jpg 768w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-1536x886.jpg 1536w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920-150x87.jpg 150w, https://searchengineland.com/wp-content/seloads/2023/04/google-analytics-data-1920.jpg 1920w" sizes="(max-width: 800px) 100vw, 800px" /></div>
<p>Google is rolling out a significant update to how average daily budgets pace in campaigns that use ad scheduling — and it could materially change monthly spend totals.</p>



<p><strong>What’s happening</strong>. Starting March 1, 2026, Google Ads will begin proactively pacing budgets to spend up to the full 30.4x monthly limit, even if campaigns only run on specific days via ad scheduling.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1426" height="1520" src="https://searchengineland.com/wp-content/seloads/2026/02/google-ads-budget-pacing-for-ad-scheduling-update-email-1771541859.jpg" alt="" class="wp-image-470225" srcset="https://searchengineland.com/wp-content/seloads/2026/02/google-ads-budget-pacing-for-ad-scheduling-update-email-1771541859.jpg 1426w, https://searchengineland.com/wp-content/seloads/2026/02/google-ads-budget-pacing-for-ad-scheduling-update-email-1771541859-768x819.jpg 768w" sizes="(max-width: 1426px) 100vw, 1426px" /></figure>



<p><strong>How it works:</strong></p>



<ul class="wp-block-list">
<li>The 2x daily overspend rule stays in place.</li>



<li>The 30.4x average daily budget monthly cap remains unchanged.</li>



<li>Campaigns will not run outside scheduled hours.</li>



<li>But Google will now attempt to hit the full monthly ceiling within the allowed schedule.</li>
</ul>



<p><strong>Why we care</strong>. Until now, advertisers running limited schedules — like weekends only — effectively spent less per month because Google paced against active days. Campaigns using ad scheduling may start spending significantly more per month — even though daily budgets and billing caps haven’t changed. </p>



<p>Google will now push harder to hit the full 30.4x monthly limit within scheduled days, which could double spend for weekend-only or limited-hour campaigns. Without adjusting daily budgets, marketers risk unintentionally overshooting their intended monthly targets.</p>



<p><strong>Example</strong>. A campaign set to weekends only with a $100 daily budget previously spent about $800/month (roughly eight weekend days).</p>



<p>Under the new pacing logic, it could spend up to $1,600/month — hitting $200 (2x daily budget) on each scheduled day.</p>



<p><strong>What Google says</strong>. According to Google Ads Liaison Ginny Marvin, the goal is to better align pacing behavior with advertisers’ expectations around monthly spend limits. Spend will still be driven by campaign objectives like conversions or conversion value, and no campaign will exceed the existing billing caps.</p>



<p>Ginny <a href="https://www.linkedin.com/feed/update/urn:li:activity:7431716157981843456/?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7431716157981843456%2C7432156253277028353%29&amp;dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287432156253277028353%2Curn%3Ali%3Aactivity%3A7431716157981843456%29">also clarified</a> that only advertisers who received notifications about this update will be affected and the change will be slowly rolled out. </p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><a href="https://www.linkedin.com/feed/update/urn:li:activity:7431716157981843456/?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7431716157981843456%2C7432156253277028353%29&amp;dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287432156253277028353%2Curn%3Ali%3Aactivity%3A7431716157981843456%29"><img decoding="async" width="562" height="506" src="https://searchengineland.com/wp-content/seloads/2026/02/Budget-Pacing-update-Ginny.png" alt="" class="wp-image-470227"/></a></figure></div>


<p><strong>Between the lines</strong>. This is less about raising limits — and more about how aggressively Google uses existing ones. For advertisers relying on ad scheduling to naturally suppress spend, this could lead to unexpected increases unless daily budgets are recalibrated.</p>



<p><strong>What to do now:</strong></p>



<ul class="wp-block-list">
<li>Review campaigns using ad scheduling.</li>



<li>Recalculate daily budgets based on true monthly goals.</li>



<li>Lower daily budgets if you want to maintain previous monthly spend levels.</li>
</ul>



<p><strong>The bottom line</strong>. Google isn’t changing how much you can spend — it’s changing how quickly you will spend it. Flighted and part-time campaigns should adjust before March 2026.</p>



<p><strong>First spotted. </strong>This updated was mentioned by Jordan Fry who shared the Google message he got on <a href="https://www.linkedin.com/posts/jordan-fry_googleads-ppc-share-7430307861349511168-Xt8u/">LinkedIn</a>. </p>


Google is rolling out a significant update to how average daily budgets pace in campaigns that use ad scheduling — and it could materially change monthly spend totals.
What’s happening. Starting March 1, 2026, Google Ads will begin proactively pacing budgets to spend up to the full 30.4x monthly limit, even if campaigns only run on specific days via ad scheduling.




How it works:
The 2x daily overspend rule stays in place.
The 30.4x average daily budget monthly cap remains unchanged.
Campaigns will not run outside scheduled hours.
But Google will now attempt to hit the full monthly ceiling within the allowed schedule.
Why we care. Until now, advertisers running limited schedules — like weekends only — effectively spent less per month because Google paced against active days. Campaigns using ad scheduling may start spending significantly more per month — even though daily budgets and billing caps haven’t changed. 
Google will now push harder to hit the full 30.4x monthly limit within scheduled days, which could double spend for weekend-only or limited-hour campaigns. Without adjusting daily budgets, marketers risk unintentionally overshooting their intended monthly targets.
Example. A campaign set to weekends only with a $100 daily budget previously spent about $800/month (roughly eight weekend days).
Under the new pacing logic, it could spend up to $1,600/month — hitting $200 (2x daily budget) on each scheduled day.
What Google says. According to Google Ads Liaison Ginny Marvin, the goal is to better align pacing behavior with advertisers’ expectations around monthly spend limits. Spend will still be driven by campaign objectives like conversions or conversion value, and no campaign will exceed the existing billing caps.
Ginny also clarified that only advertisers who received notifications about this update will be affected and the change will be slowly rolled out. 

Between the lines. This is less about raising limits — and more about how aggressively Google uses existing ones. For advertisers relying on ad scheduling to naturally suppress spend, this could lead to unexpected increases unless daily budgets are recalibrated.
What to do now:
Review campaigns using ad scheduling.
Recalculate daily budgets based on true monthly goals.
Lower daily budgets if you want to maintain previous monthly spend levels.
The bottom line. Google isn’t changing how much you can spend — it’s changing how quickly you will spend it. Flighted and part-time campaigns should adjust before March 2026.
First spotted. This updated was mentioned by Jordan Fry who shared the Google message he got on LinkedIn.

Google’s new pacing update could increase monthly spend for ad-scheduled campaigns by pushing budgets harder within allowed run times.

Google to change budget pacing for campaigns using ad scheduling

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions.png" class="attachment-large size-large wp-post-image" alt="What 13 months of data reveals about LLM traffic, growth, and conversions" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>An analysis of LLM referral traffic shows low volume, rapid growth, shifting citations, and an 18% conversion rate. 

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions.png" class="attachment-large size-large wp-post-image" alt="What 13 months of data reveals about LLM traffic, growth, and conversions" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/What-13-months-of-data-reveals-about-LLM-traffic-growth-and-conversions-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>LLMs and their influence on traffic to a brand’s website are a major topic in our client conversations. Everyone wants to know what’s happening, how they can do better, and what the best practices are.</p>



<p>My recommendation to brands right now is to start with the data and focus on what they can know for sure.</p>



<p>To glean insights into how LLM traffic is influencing key metrics, we analyzed our dataset of LLM prompt referral traffic in Google Analytics across our customer base over the last 13 months (Jan. 1, 2025 to Feb. 7, 2026).&nbsp;</p>



<p>We focused on traffic from various LLM models to brand sites and the conversion events closest to true business outcomes. In some cases, that’s a purchase. In others, it’s a generated lead.</p>



<p>When we look at this dataset, four major findings rise to the surface:</p>



<ul class="wp-block-list">
<li>LLM referral traffic is still small.</li>



<li>LLM traffic is growing fast.</li>



<li>The sources referenced in responses are shifting.</li>



<li>LLMs convert at a very high rate compared to other channels</li>
</ul>



<h2 class="wp-block-heading" id="h-llm-referral-traffic-is-still-small">LLM referral traffic is still small</h2>



<p>LLM referral traffic accounts for less than 2% of total referral traffic on average, according to our dataset. In other words, fewer than 2 out of 100 visitors to a site come from an LLM referring source.</p>



<p>The range is 0.15%-1.5% of referral traffic coming from various LLMs, including ChatGPT, Perplexity, Gemini, and Claude.</p>



<p>So while this is a major topic of conversation, it isn’t the highest priority for near-term bottom-line impact for many businesses.</p>



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<h2 class="wp-block-heading" id="h-llm-traffic-is-growing-fast">LLM traffic is growing fast</h2>



<p>LLMs, as a referral source, are growing quickly, according to our data. Comparing the first half of 2025 with the second half, we saw an average growth rate of 80% in LLM referral traffic.</p>



<p>There was a wide range across the dataset. Some companies saw just 10% growth, while others experienced 300% increases.</p>



<p>Below is the aggregate referral traffic by month in 2025. It shows a steady month-by-month increase, building to 3x referral traffic growth from January to December.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1600" height="449" src="https://searchengineland.com/wp-content/seloads/2026/02/LLM-traffic-is-growing-fast.png" alt="" class="wp-image-470119" srcset="https://searchengineland.com/wp-content/seloads/2026/02/LLM-traffic-is-growing-fast.png 1600w, https://searchengineland.com/wp-content/seloads/2026/02/LLM-traffic-is-growing-fast-768x216.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/LLM-traffic-is-growing-fast-1536x431.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></figure></div>


<p>That means it’s not enough to understand your volume of LLM traffic. You also need to monitor the velocity of that growth.</p>



<p>LLMs are expanding as consumer adoption grows, and prompt algorithms keep changing. Between those two variables, you can see dramatic swings that you need to monitor.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/llm-optimization-tracking-visibility-ai-discovery-463860">LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery</a></em></strong></p>



<h2 class="wp-block-heading" id="h-sources-referenced-in-responses-are-shifting">Sources referenced in responses are shifting</h2>



<p>The sources cited in LLM responses are changing quickly. </p>



<p>Here’s a look at our dataset since September of last year. The data comes from monitoring more than 5,000 prompts and their responses across various LLM APIs, including Gemini, ChatGPT, and Perplexity.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1252" height="606" src="https://searchengineland.com/wp-content/seloads/2026/02/Sources-referenced-in-responses-are-shifting.png" alt="Sources referenced in responses are shifting" class="wp-image-470120" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Sources-referenced-in-responses-are-shifting.png 1252w, https://searchengineland.com/wp-content/seloads/2026/02/Sources-referenced-in-responses-are-shifting-768x372.png 768w" sizes="(max-width: 1252px) 100vw, 1252px" /></figure></div>


<p>YouTube links and citations have increased over the last 30 days. Reddit saw similar growth, though that traffic recently leveled off.</p>



<p>These shifts in citations and links will affect the traffic that eventually reaches your site, and they may also influence your ad and content strategies. </p>



<p>If you don’t monitor this data, you won’t see these changes. LLMs don’t provide this information directly — you can only access it through a third-party tool.</p>



<h2 class="wp-block-heading" id="h-llms-convert-at-a-very-high-rate-compared-to-other-channels">LLMs convert at a very high rate compared to other channels</h2>



<p>This is likely the most interesting and important finding. When you compare conversion rates alongside the total percentage of traffic, the contrast becomes clear.</p>



<p>LLM referrals are the highest-converting traffic source across our customer base, with an approximate 18% conversion rate. That’s higher than any other tactic, including paid shopping, SEO, and PPC. </p>



<p>However, they account for the lowest percentage of total traffic to a brand’s website, about 25 times less than SEO or direct.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="946" height="507" src="https://searchengineland.com/wp-content/seloads/2026/02/LLMs-convert-at-a-very-high-rate-compared-to-other-channels.png" alt="" class="wp-image-470121" srcset="https://searchengineland.com/wp-content/seloads/2026/02/LLMs-convert-at-a-very-high-rate-compared-to-other-channels.png 946w, https://searchengineland.com/wp-content/seloads/2026/02/LLMs-convert-at-a-very-high-rate-compared-to-other-channels-768x412.png 768w" sizes="(max-width: 946px) 100vw, 946px" /></figure></div>


<p><strong><em>Dig deeper: <a href="https://searchengineland.com/measure-llm-visibility-464794">How to better measure LLM visibility and its impact</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-what-brands-should-do-next">What brands should do next</h2>



<p>Based on these findings, you should take the following actions to prepare for the evolving LLM landscape.</p>



<h3 class="wp-block-heading" id="h-1-establish-dedicated-monitoring">1. Establish dedicated monitoring</h3>



<p>While LLM traffic volume is still low, its growth rate and volatility, including shifts between sources like YouTube and Reddit, make monitoring essential.</p>



<ul class="wp-block-list">
<li><strong>Track velocity: </strong>Don’t just look at volume. Monitor the rate of growth in LLM referrals to understand when this channel crosses a meaningful threshold for your business.</li>



<li><strong>Monitor citation sources: </strong>Use available third-party tools to understand which LLMs and which types of platforms, including forums, videos, and news, are driving the most citations and subsequent traffic.</li>
</ul>



<h3 class="wp-block-heading" id="h-2-capitalize-on-high-value-traffic">2. Capitalize on high-value traffic</h3>



<p>An 18% conversion rate suggests LLM-referred users are highly qualified. They often arrive with clear intent or after their query has already been answered or validated by the LLM.</p>



<ul class="wp-block-list">
<li><strong>Analyze high-converting journeys: </strong>Review the user journey for LLM referrals. What content are they landing on? What queries are being answered that lead to conversion?</li>



<li><strong>Optimize for intent:</strong> Focus content and landing page optimization on the high-intent needs reflected in the LLM’s citation context. Treat this traffic as a premium audience.</li>
</ul>



<h3 class="wp-block-heading" id="h-3-plan-for-future-growth">3. Plan for future growth</h3>



<p>Given rapid LLM adoption, today’s low traffic volume won’t last.</p>



<ul class="wp-block-list">
<li><strong>Develop a content strategy for AI: </strong>Build a strategy that anticipates how LLMs summarize, cite, and reference your material. This isn’t traditional SEO. It’s about being the authoritative source LLMs choose to link to.</li>



<li><strong>Allocate budget: </strong>While this may not drive immediate bottom-line impact, dedicate a small budget to tools and resources focused on understanding and optimizing the LLM referral channel.</li>
</ul>



<p>This space is evolving fast. Hopefully, this dataset shows how things are progressing and motivates action within your organization.</p>



<p>This is a time of change. If you innovate, stay focused, and use data, you have a clear opportunity to outperform your competition.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/llm-consistency-recommendation-share-seo-kpi-469512">LLM consistency and recommendation share: The new SEO KPI</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-from-emerging-channel-to-strategic-signal">From emerging channel to strategic signal</h2>



<p>LLM referral traffic is still a small share of overall volume, but it’s growing fast, shifting where it cites, and driving strong conversions.</p>



<p>Don’t overreact. Monitor the trend lines, understand where citations come from, and watch how this audience behaves once it lands. This space is moving fast, and if you stay close to the data, you’ll be better positioned as it evolves.</p>

LLMs and their influence on traffic to a brand’s website are a major topic in our client conversations. Everyone wants to know what’s happening, how they can do better, and what the best practices are.
My recommendation to brands right now is to start with the data and focus on what they can know for sure.
To glean insights into how LLM traffic is influencing key metrics, we analyzed our dataset of LLM prompt referral traffic in Google Analytics across our customer base over the last 13 months (Jan. 1, 2025 to Feb. 7, 2026). 
We focused on traffic from various LLM models to brand sites and the conversion events closest to true business outcomes. In some cases, that’s a purchase. In others, it’s a generated lead.
When we look at this dataset, four major findings rise to the surface:
LLM referral traffic is still small.
LLM traffic is growing fast.
The sources referenced in responses are shifting.
LLMs convert at a very high rate compared to other channels
LLM referral traffic is still small
LLM referral traffic accounts for less than 2% of total referral traffic on average, according to our dataset. In other words, fewer than 2 out of 100 visitors to a site come from an LLM referring source.
The range is 0.15%-1.5% of referral traffic coming from various LLMs, including ChatGPT, Perplexity, Gemini, and Claude.
So while this is a major topic of conversation, it isn’t the highest priority for near-term bottom-line impact for many businesses.

  
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LLM traffic is growing fast
LLMs, as a referral source, are growing quickly, according to our data. Comparing the first half of 2025 with the second half, we saw an average growth rate of 80% in LLM referral traffic.
There was a wide range across the dataset. Some companies saw just 10% growth, while others experienced 300% increases.
Below is the aggregate referral traffic by month in 2025. It shows a steady month-by-month increase, building to 3x referral traffic growth from January to December.

That means it’s not enough to understand your volume of LLM traffic. You also need to monitor the velocity of that growth.
LLMs are expanding as consumer adoption grows, and prompt algorithms keep changing. Between those two variables, you can see dramatic swings that you need to monitor.
Dig deeper: LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery
Sources referenced in responses are shifting
The sources cited in LLM responses are changing quickly. 
Here’s a look at our dataset since September of last year. The data comes from monitoring more than 5,000 prompts and their responses across various LLM APIs, including Gemini, ChatGPT, and Perplexity.

YouTube links and citations have increased over the last 30 days. Reddit saw similar growth, though that traffic recently leveled off.
These shifts in citations and links will affect the traffic that eventually reaches your site, and they may also influence your ad and content strategies. 
If you don’t monitor this data, you won’t see these changes. LLMs don’t provide this information directly — you can only access it through a third-party tool.
LLMs convert at a very high rate compared to other channels
This is likely the most interesting and important finding. When you compare conversion rates alongside the total percentage of traffic, the contrast becomes clear.
LLM referrals are the highest-converting traffic source across our customer base, with an approximate 18% conversion rate. That’s higher than any other tactic, including paid shopping, SEO, and PPC. 
However, they account for the lowest percentage of total traffic to a brand’s website, about 25 times less than SEO or direct.

Dig deeper: How to better measure LLM visibility and its impact
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See terms.
What brands should do next
Based on these findings, you should take the following actions to prepare for the evolving LLM landscape.
1. Establish dedicated monitoring
While LLM traffic volume is still low, its growth rate and volatility, including shifts between sources like YouTube and Reddit, make monitoring essential.
Track velocity: Don’t just look at volume. Monitor the rate of growth in LLM referrals to understand when this channel crosses a meaningful threshold for your business.
Monitor citation sources: Use available third-party tools to understand which LLMs and which types of platforms, including forums, videos, and news, are driving the most citations and subsequent traffic.
2. Capitalize on high-value traffic
An 18% conversion rate suggests LLM-referred users are highly qualified. They often arrive with clear intent or after their query has already been answered or validated by the LLM.
Analyze high-converting journeys: Review the user journey for LLM referrals. What content are they landing on? What queries are being answered that lead to conversion?
Optimize for intent: Focus content and landing page optimization on the high-intent needs reflected in the LLM’s citation context. Treat this traffic as a premium audience.
3. Plan for future growth
Given rapid LLM adoption, today’s low traffic volume won’t last.
Develop a content strategy for AI: Build a strategy that anticipates how LLMs summarize, cite, and reference your material. This isn’t traditional SEO. It’s about being the authoritative source LLMs choose to link to.
Allocate budget: While this may not drive immediate bottom-line impact, dedicate a small budget to tools and resources focused on understanding and optimizing the LLM referral channel.
This space is evolving fast. Hopefully, this dataset shows how things are progressing and motivates action within your organization.
This is a time of change. If you innovate, stay focused, and use data, you have a clear opportunity to outperform your competition.
Dig deeper: LLM consistency and recommendation share: The new SEO KPI

  
complete picture of your search visibility.
      
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From emerging channel to strategic signal
LLM referral traffic is still a small share of overall volume, but it’s growing fast, shifting where it cites, and driving strong conversions.
Don’t overreact. Monitor the trend lines, understand where citations come from, and watch how this audience behaves once it lands. This space is moving fast, and if you stay close to the data, you’ll be better positioned as it evolves.

An analysis of LLM referral traffic shows low volume, rapid growth, shifting citations, and an 18% conversion rate.

What 13 months of data reveals about LLM traffic, growth, and conversions

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline.png" class="attachment-large size-large wp-post-image" alt="Google Discover pipeline" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>New SDK findings reveal why some pages never reach ranking, how pCTR predicts clicks, and why images and recency drive Discover traffic.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline.png" class="attachment-large size-large wp-post-image" alt="Google Discover pipeline" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/02/google-discover-pipeline-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Discover runs on a structured, multi-stage pipeline with hard publisher blocks, strict image requirements, freshness decay, and heavy experimentation shaping what users see, according to new SDK-level research by Metehan Yesilyurt.</p>



<p><strong>Why we care.</strong> Google Discover can drive massive traffic, but it often feels unpredictable. This research gives you a clearer view of how your content qualifies, gets ranked, or gets blocked — and where things can break before ranking even begins.</p>



<p><strong>The details.</strong> Yesilyurt analyzed observable signals in Google’s Discover app framework and mapped a nine-stage flow. Google:</p>



<ul class="wp-block-list">
<li>Crawls and understands your content.</li>



<li>Reads key meta tags like your image and title.</li>



<li>Classifies your content type (e.g., breaking news or evergreen).</li>



<li>Checks whether you’re blocked.</li>



<li>Matches your content to user interests.</li>



<li>Applies a server-side click-through rate prediction model.</li>



<li>Builds the feed layout.</li>



<li>Delivers your content.</li>



<li>Records user feedback.</li>
</ul>



<p><strong>One key finding.</strong> The publisher-level block happens before interest matching and ranking. If a user blocks you, your content never reaches the ranking stage.</p>



<ul class="wp-block-list">
<li>Publisher blocking is powerful. One “Don’t show content from this site” action can suppress your entire domain. There’s no similar sitewide “boost” mechanism.</li>
</ul>



<p><strong>The ranking model.</strong> Your title, image quality, and engagement history are part of the evaluation process. The system uses a predicted click-through rate (pCTR) model on Google’s servers to estimate how likely someone is to click. The model isn’t visible, but the app shows which signals are sent to Google before ranking decisions, including:</p>



<ul class="wp-block-list">
<li>Your page title (from og:title).</li>



<li>Your image size and quality.</li>



<li>How new your content is.</li>



<li>Past click and impression data for your URL.</li>



<li>Whether your images load successfully.</li>
</ul>



<p><strong>Freshness matters.</strong> Google Discover groups content into time windows:</p>



<ul class="wp-block-list">
<li><strong>1 to 7 days old:</strong> strongest boost.</li>



<li><strong>8 to 14 days:</strong> moderate visibility.</li>



<li><strong>15 to 30 days: </strong>limited visibility.</li>



<li><strong>30+ days:</strong> gradual decline.</li>
</ul>



<p>There’s a separate classification for strong evergreen content, but by default, newer content has an advantage.</p>



<p><strong>Image and meta tag requirements.</strong> Google Discover reads six key page-level tags, including og:image and og:title. No image means no card.</p>



<ul class="wp-block-list">
<li>To qualify for large, prominent cards, your images must be at least 1200px wide. Smaller images typically appear as thumbnails and often earn fewer clicks.</li>



<li>If certain tags are missing, Google Discover looks for backups — for example, it will try the Twitter title tag or the HTML title if og:title isn’t present.</li>



<li>Two specific meta tags — “nopagereadaloud” and “notranslate” — can stop your page from entering Google Discover entirely.</li>
</ul>



<p><strong>Personalization layers. </strong>Google Discover personalizes content using:</p>



<ul class="wp-block-list">
<li>Google’s broader interest data tied to user behavior.</li>



<li>Publisher signals, including Publisher Center registration.</li>



<li>Individual actions like follows, saves, and dismissals.</li>



<li>Engagement signals, such as time spent reading.</li>
</ul>



<p>If a user dismisses your story, the system stores that action permanently for that specific URL. It won’t resurface.</p>



<p><strong>Experiments everywhere. </strong>During one observed session, about 150 server-side experiments were running simultaneously. Another 50+ feature controls affected how cards were displayed.</p>



<ul class="wp-block-list">
<li>That means two similar users could see noticeably different feeds simply because they’re in different experiment groups.</li>
</ul>



<p><strong>Real-time feed updates.</strong> Google Discover isn’t static. The system can add, remove, or reorder content while someone is browsing, without a refresh.</p>



<p><strong>The big takeaways</strong>. Success in Google Discover depends less on tricks and more on eligibility, trust, strong visuals, and sustained engagement — in a system that can filter you out before ranking even starts.</p>



<ul class="wp-block-list">
<li>Publisher blocks happen before ranking.</li>



<li>Freshness is built into the system.</li>



<li>Strong images and clear titles are essential.</li>



<li>User dismissals are permanent.</li>



<li>Heavy experimentation makes volatility normal.</li>
</ul>



<p><strong>The research.</strong> <a href="https://metehan.ai/blog/google-discover-architecture/" target="_blank" rel="noopener">Google Discover Architecture: Clusters, Classifiers, OG Tags, NAIADES – What SDK Telemetry Reveals</a></p>


Google Discover runs on a structured, multi-stage pipeline with hard publisher blocks, strict image requirements, freshness decay, and heavy experimentation shaping what users see, according to new SDK-level research by Metehan Yesilyurt.
Why we care. Google Discover can drive massive traffic, but it often feels unpredictable. This research gives you a clearer view of how your content qualifies, gets ranked, or gets blocked — and where things can break before ranking even begins.
The details. Yesilyurt analyzed observable signals in Google’s Discover app framework and mapped a nine-stage flow. Google:
Crawls and understands your content.
Reads key meta tags like your image and title.
Classifies your content type (e.g., breaking news or evergreen).
Checks whether you’re blocked.
Matches your content to user interests.
Applies a server-side click-through rate prediction model.
Builds the feed layout.
Delivers your content.
Records user feedback.
One key finding. The publisher-level block happens before interest matching and ranking. If a user blocks you, your content never reaches the ranking stage.
Publisher blocking is powerful. One “Don’t show content from this site” action can suppress your entire domain. There’s no similar sitewide “boost” mechanism.
The ranking model. Your title, image quality, and engagement history are part of the evaluation process. The system uses a predicted click-through rate (pCTR) model on Google’s servers to estimate how likely someone is to click. The model isn’t visible, but the app shows which signals are sent to Google before ranking decisions, including:
Your page title (from og:title).
Your image size and quality.
How new your content is.
Past click and impression data for your URL.
Whether your images load successfully.
Freshness matters. Google Discover groups content into time windows:
1 to 7 days old: strongest boost.
8 to 14 days: moderate visibility.
15 to 30 days: limited visibility.
30+ days: gradual decline.
There’s a separate classification for strong evergreen content, but by default, newer content has an advantage.
Image and meta tag requirements. Google Discover reads six key page-level tags, including og:image and og:title. No image means no card.
To qualify for large, prominent cards, your images must be at least 1200px wide. Smaller images typically appear as thumbnails and often earn fewer clicks.
If certain tags are missing, Google Discover looks for backups — for example, it will try the Twitter title tag or the HTML title if og:title isn’t present.
Two specific meta tags — “nopagereadaloud” and “notranslate” — can stop your page from entering Google Discover entirely.
Personalization layers. Google Discover personalizes content using:
Google’s broader interest data tied to user behavior.
Publisher signals, including Publisher Center registration.
Individual actions like follows, saves, and dismissals.
Engagement signals, such as time spent reading.
If a user dismisses your story, the system stores that action permanently for that specific URL. It won’t resurface.
Experiments everywhere. During one observed session, about 150 server-side experiments were running simultaneously. Another 50+ feature controls affected how cards were displayed.
That means two similar users could see noticeably different feeds simply because they’re in different experiment groups.
Real-time feed updates. Google Discover isn’t static. The system can add, remove, or reorder content while someone is browsing, without a refresh.
The big takeaways. Success in Google Discover depends less on tricks and more on eligibility, trust, strong visuals, and sustained engagement — in a system that can filter you out before ranking even starts.
Publisher blocks happen before ranking.
Freshness is built into the system.
Strong images and clear titles are essential.
User dismissals are permanent.
Heavy experimentation makes volatility normal.
The research. Google Discover Architecture: Clusters, Classifiers, OG Tags, NAIADES – What SDK Telemetry Reveals

New SDK findings reveal why some pages never reach ranking, how pCTR predicts clicks, and why images and recency drive Discover traffic.

How Google Discover qualifies, ranks, and filters content: Research

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study.png" class="attachment-large size-large wp-post-image" alt="The AI writing tics that hurt engagement- A study" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>An analysis of 1,000+ URLs reveals which AI writing tics correlate with engagement. Some common “tells” don’t matter. A few might.


<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study.png" class="attachment-large size-large wp-post-image" alt="The AI writing tics that hurt engagement- A study" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/The-AI-writing-tics-that-hurt-engagement-A-study-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>The web has strong opinions about what “AI-written” content looks like, and even stronger ones about what’s supposedly wrong with it. Scroll any content marketer’s LinkedIn feed, and you’ll find confident claims that em dashes and other AI “tells” signal bad, automated writing.</p>



<p>The problem with these debates is that they often confuse taste with performance. What counts as “bad writing” will always be subjective. But if the goal for content marketers is to communicate clearly and compete in the information marketplace, the practical question should be: which LLM habits actually turn readers off?</p>



<p>To find out, we analyzed a large dataset of content marketing pages to identify which AI writing “tics” we see most often called out to understand which are turning off readers — and the ones we may be calling out for no reason.</p>



<h2 class="wp-block-heading" id="h-how-we-built-our-ai-tics-study">How we built our ‘AI tics’ study</h2>



<p>At this point, you’ve probably all seen them, too:</p>



<ul class="wp-block-list">
<li>“In today’s fast-paced digital landscape…”</li>



<li>“It’s important to note that…”</li>



<li>“Not only… but also” (repeated over, and over and over…)</li>



<li>“In conclusion” (even when nothing has been concluded)</li>
</ul>



<p>The second you notice them, it’s hard not to see them everywhere an LLM has helped produce copy. Many readers report <a href="https://www.nytimes.com/2025/12/03/magazine/chatbot-writing-style.html" target="_blank" rel="noopener">hating these LLM patterns</a>. But how exactly are they impacting user engagement?</p>



<p>To find out, we gathered a list of the most common AI writing tells we and others have noticed. These include:</p>



<ul class="wp-block-list">
<li><strong>“Not only… but also” constructions:</strong> “Not only does X do Y, but it also does Z.”</li>



<li><strong>Sentence starts with “then,” “this,” or” that”: </strong>“Then you should…” “Then the system…” “This shows…” “This means…”&nbsp;</li>



<li><strong>Introductory filler: </strong>“In this article,” “We’ll explore,” and “Let’s take a look”.&nbsp;</li>



<li><strong>“Conclusion” starters:</strong> “In conclusion,” or other AI equivalents of clearing your throat.</li>



<li><strong>Em dashes:</strong> The <a href="https://www.nytimes.com/2025/09/18/magazine/chatgpt-dash-hyphen-writing-communication.html">most infamous punctuation mark</a> in today’s content marketing.</li>
</ul>



<p>From there, we built a dataset of:</p>



<ul class="wp-block-list">
<li><strong>10 domains</strong> of varied site size and monthly traffic, in a wide array of industries including tech, ecommerce, healthcare, education, analytics, and more</li>



<li><strong>1,000+ content marketing URLs, </strong>built from a mix of workflows including posts that were either fully human-written, written collaboratively by humans and AI, or completely AI-generated.</li>
</ul>



<p>Then we standardized our dataset by:&nbsp;</p>



<ul class="wp-block-list">
<li><strong>Aligning shorter posts and cornerstone content by standardizing every writing tic as occurrences per 1,000 words.</strong> Since longer articles naturally contain more of, well, everything, a 3,000-word guide would otherwise look “worse” than a 600-word post simply because it has more sentences.</li>



<li><strong>Excluding any page under 500 words.</strong> Very short pages don’t give enough room for stylistic patterns to emerge, and their engagement metrics are likely driven more by intent than by engagement alone.</li>



<li><strong>Prioritizing engagement rate as the primary performance metric.</strong> Engagement rate best captures a reader’s first real decision: “Do I stay, or do I leave?” GA4 registers an engaged session as <a href="https://support.google.com/analytics/answer/12195621?hl=en" target="_blank" rel="noopener">any lasting 10 or more seconds</a>. While 10 seconds may sound brief to assess whether a post is AI, it’s long enough for a user to skim an introduction, notice awkward or repetitive writing patterns, and scan headings to decide whether the content feels worth continuing.</li>
</ul>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-prompting-rubrics-467813">A smarter way to approach AI prompting</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-why-tracking-total-ai-tics-wasn-t-enough">Why tracking total AI tics wasn’t enough</h2>



<p>Our first instinct was to average the number of AI tics per 1,000 words and compare the pages’ performance. </p>



<p>At a glance, this seemed like a clean way to separate human writing from AI-influenced writing. But the picture quickly got complicated by one tic in particular — the infamous em dash — which dominated the dataset and heavily skewed the averages.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1600" height="531" src="https://searchengineland.com/wp-content/seloads/2026/02/Content-marketing-across-10-domains.png" alt="Content marketing across 10 domains" class="wp-image-470097" srcset="https://searchengineland.com/wp-content/seloads/2026/02/Content-marketing-across-10-domains.png 1600w, https://searchengineland.com/wp-content/seloads/2026/02/Content-marketing-across-10-domains-768x255.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/Content-marketing-across-10-domains-1536x510.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></figure></div>


<p>The issue pointed to a larger problem: AI tics are messy by definition. AI is trained on human writing. So if certain patterns show up frequently, that doesn’t mean they’re uniquely “AI.” It may just mean they’re common in English prose. </p>



<p>To compare, we ran the same tic counter on two known controls: a novel I published in 2021 (which I could guarantee was written without ChatGPT, Grammarly, or other AI-assisted tools). This scored a startlingly above-average 6.9 tics per 1,000 words. </p>



<p>Next, we scored “Hamlet,” the famous Shakespearean play, which scored an even higher ≈11.4 tics per 1,000 words. Shakespeare, it turns out, is more “AI-coded” than many AI-generated blog posts.</p>



<p>Ultimately, we assessed that this is almost entirely due to the em dash, which is likely to appear in droves in many human writers’ prose as well as AI-produced copy. </p>



<p>With this in mind, we analyzed each “tell” individually, still standardizing per 1,000 words. The story became much clearer — and far more useful for writers trying to decide what’s actually worth avoiding.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/how-to-make-your-ai-generated-content-sound-more-human-437854">How to make your AI-generated content sound more human</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-the-ai-tics-impacting-performance">The AI tics impacting performance</h2>



<p>Not all posts are the same, and many different factors impact the success or failure of any page of content marketing. That’s perhaps why our data showed that most AI “tells” didn’t correlate strongly with performance or non-performance. </p>



<p>Anything smaller than plus/minus .1 correlation is statistically insignificant. However, there were a handful worth noting with a larger impact than others.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="794" height="491" src="https://searchengineland.com/wp-content/seloads/2026/02/image-147.png" alt="" class="wp-image-470052" srcset="https://searchengineland.com/wp-content/seloads/2026/02/image-147.png 794w, https://searchengineland.com/wp-content/seloads/2026/02/image-147-768x475.png 768w" sizes="(max-width: 794px) 100vw, 794px" /></figure>



<h3 class="wp-block-heading" id="h-not-only-and-not-just-structures-may-be-driving-users-away">‘Not only’ and ‘not just’ structures may be driving users away</h3>



<p>Phrases built around “not only…” or “not just…but also” stood out with larger-than-average negative correlations with engagement rate. While these constructions, when used occasionally, can add emphasis, the data shows that frequent use is associated with high user bounce rates.&nbsp;</p>



<p>AI-assisted writers and editors should take note, as many of the AI-generated posts we reviewed tripped over themselves with these constructions. In one instance, we found a single blog post that used “not only” and “but also” 12 separate times.</p>



<h3 class="wp-block-heading" id="h-starting-headers-with-conclusion-was-the-strongest-negative-signal">Starting headers with ‘conclusion’ was the strongest negative signal</h3>



<p>The strongest negative correlation in the entire dataset was observed in sentences beginning with “Conclusion,” typically section headers preceding a call to action. The clearest AI stylistic red flag we found, posts with headers starting with “Conclusion” had the largest negative correlation&nbsp; (≈ -0.118) with post engagement rate.</p>



<p>Since this tic traditionally comes at the conclusion of a post, it’s clear readers may quickly scroll down over the entirety of these posts before bouncing — or else that posts with these final headings tend to be lower-quality on average.</p>



<h3 class="wp-block-heading" id="h-em-dashes-correlated-slightly-positively">Em dashes correlated slightly positively</h3>



<p>Em dashes were by far the most common stylistic tic in the dataset. They also produced one of the most surprising results: a slight positive correlation with engagement rate.</p>



<p>Despite widespread online chatter treating em dashes as an “AI artifact,” this data suggests they’re not hurting performance, and they may even align with better engagement. (As someone who genuinely likes em dashes — this was deeply validating.)</p>



<p>A plausible explanation may be that writers who use em dashes tend to write more explanatory, nuanced sentences rather than short, flat declarations. Those kinds of sentences often appear in longer, more thoughtful content that many readers actually engage with.</p>



<p>That said, this doesn’t mean em dashes cause engagement. Too much of a good thing is still too much of a good thing. But it does challenge the idea that em dashes are the bugbear content marketers make them out to be.&nbsp;</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/ai-assisted-content-process-459054">An AI-assisted content process that outperforms human-only copy</a></em></strong></p>



<h2 class="wp-block-heading" id="h-3-practical-takeaways-for-content-teams">3 practical takeaways for content teams</h2>



<p>Here’s what content marketers can act on today.</p>



<h3 class="wp-block-heading" id="h-1-don-t-over-optimize-for-ai-detection">1. Don’t over-optimize for AI detection</h3>



<p>Google doesn’t issue <a href="https://searchengineland.com/guide/what-is-seo">SEO</a> rankings like a monotonic punishment score for “AI style.” Most phrases we looked at didn’t correlate with engagement at all. </p>



<p>Don’t rewrite content just because someone declared a phrase “AI writing.” Write for reader usefulness and clarity above all.</p>



<h3 class="wp-block-heading" id="h-2-be-mindful-of-how-you-wrap-up">2. Be mindful of how you wrap up</h3>



<p>Explicit conclusion blocks aren’t bad — but generic, formulaic patterns are likely turning readers away. </p>



<p>Consider blending conclusions into analysis, using subtler transitions, or adding new value with headers, instead of signposting obvious structure. </p>



<h3 class="wp-block-heading" id="h-3-use-the-punctuation-that-makes-sense-nbsp">3. Use the punctuation that makes sense&nbsp;</h3>



<p>If your style calls for em-dashes? In this dataset, they were actually associated with better reader engagement. Use them.</p>



<h2 class="wp-block-heading" id="h-don-t-miss-the-forest-for-fake-plastic-trees">Don’t miss the forest for fake plastic trees</h2>



<p>AI is likely here to stay in content workflows. But the issues with “bad” AI writing aren’t limited to linguistic tics and punctuation. While we all have our stylistic opinions, we should be careful about turning stylistic hot takes into editorial law.&nbsp;</p>



<p>Write valuable writing. Think about readers first. And don’t panic every time someone on Twitter or LinkedIn decrees that “X phrase = AI.”</p>

The web has strong opinions about what “AI-written” content looks like, and even stronger ones about what’s supposedly wrong with it. Scroll any content marketer’s LinkedIn feed, and you’ll find confident claims that em dashes and other AI “tells” signal bad, automated writing.
The problem with these debates is that they often confuse taste with performance. What counts as “bad writing” will always be subjective. But if the goal for content marketers is to communicate clearly and compete in the information marketplace, the practical question should be: which LLM habits actually turn readers off?
To find out, we analyzed a large dataset of content marketing pages to identify which AI writing “tics” we see most often called out to understand which are turning off readers — and the ones we may be calling out for no reason.
How we built our ‘AI tics’ study
At this point, you’ve probably all seen them, too:
“In today’s fast-paced digital landscape…”
“It’s important to note that…”
“Not only… but also” (repeated over, and over and over…)
“In conclusion” (even when nothing has been concluded)
The second you notice them, it’s hard not to see them everywhere an LLM has helped produce copy. Many readers report hating these LLM patterns. But how exactly are they impacting user engagement?
To find out, we gathered a list of the most common AI writing tells we and others have noticed. These include:
“Not only… but also” constructions: “Not only does X do Y, but it also does Z.”
Sentence starts with “then,” “this,” or” that”: “Then you should…” “Then the system…” “This shows…” “This means…” 
Introductory filler: “In this article,” “We’ll explore,” and “Let’s take a look”. 
“Conclusion” starters: “In conclusion,” or other AI equivalents of clearing your throat.
Em dashes: The most infamous punctuation mark in today’s content marketing.
From there, we built a dataset of:
10 domains of varied site size and monthly traffic, in a wide array of industries including tech, ecommerce, healthcare, education, analytics, and more
1,000+ content marketing URLs, built from a mix of workflows including posts that were either fully human-written, written collaboratively by humans and AI, or completely AI-generated.
Then we standardized our dataset by: 
Aligning shorter posts and cornerstone content by standardizing every writing tic as occurrences per 1,000 words. Since longer articles naturally contain more of, well, everything, a 3,000-word guide would otherwise look “worse” than a 600-word post simply because it has more sentences.
Excluding any page under 500 words. Very short pages don’t give enough room for stylistic patterns to emerge, and their engagement metrics are likely driven more by intent than by engagement alone.
Prioritizing engagement rate as the primary performance metric. Engagement rate best captures a reader’s first real decision: “Do I stay, or do I leave?” GA4 registers an engaged session as any lasting 10 or more seconds. While 10 seconds may sound brief to assess whether a post is AI, it’s long enough for a user to skim an introduction, notice awkward or repetitive writing patterns, and scan headings to decide whether the content feels worth continuing.
Dig deeper: A smarter way to approach AI prompting
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Why tracking total AI tics wasn’t enough
Our first instinct was to average the number of AI tics per 1,000 words and compare the pages’ performance. 
At a glance, this seemed like a clean way to separate human writing from AI-influenced writing. But the picture quickly got complicated by one tic in particular — the infamous em dash — which dominated the dataset and heavily skewed the averages.

The issue pointed to a larger problem: AI tics are messy by definition. AI is trained on human writing. So if certain patterns show up frequently, that doesn’t mean they’re uniquely “AI.” It may just mean they’re common in English prose. 
To compare, we ran the same tic counter on two known controls: a novel I published in 2021 (which I could guarantee was written without ChatGPT, Grammarly, or other AI-assisted tools). This scored a startlingly above-average 6.9 tics per 1,000 words. 
Next, we scored “Hamlet,” the famous Shakespearean play, which scored an even higher ≈11.4 tics per 1,000 words. Shakespeare, it turns out, is more “AI-coded” than many AI-generated blog posts.
Ultimately, we assessed that this is almost entirely due to the em dash, which is likely to appear in droves in many human writers’ prose as well as AI-produced copy. 
With this in mind, we analyzed each “tell” individually, still standardizing per 1,000 words. The story became much clearer — and far more useful for writers trying to decide what’s actually worth avoiding.
Dig deeper: How to make your AI-generated content sound more human
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See terms.
The AI tics impacting performance
Not all posts are the same, and many different factors impact the success or failure of any page of content marketing. That’s perhaps why our data showed that most AI “tells” didn’t correlate strongly with performance or non-performance. 
Anything smaller than plus/minus .1 correlation is statistically insignificant. However, there were a handful worth noting with a larger impact than others.




‘Not only’ and ‘not just’ structures may be driving users away
Phrases built around “not only…” or “not just…but also” stood out with larger-than-average negative correlations with engagement rate. While these constructions, when used occasionally, can add emphasis, the data shows that frequent use is associated with high user bounce rates. 
AI-assisted writers and editors should take note, as many of the AI-generated posts we reviewed tripped over themselves with these constructions. In one instance, we found a single blog post that used “not only” and “but also” 12 separate times.
Starting headers with ‘conclusion’ was the strongest negative signal
The strongest negative correlation in the entire dataset was observed in sentences beginning with “Conclusion,” typically section headers preceding a call to action. The clearest AI stylistic red flag we found, posts with headers starting with “Conclusion” had the largest negative correlation  (≈ -0.118) with post engagement rate.
Since this tic traditionally comes at the conclusion of a post, it’s clear readers may quickly scroll down over the entirety of these posts before bouncing — or else that posts with these final headings tend to be lower-quality on average.
Em dashes correlated slightly positively
Em dashes were by far the most common stylistic tic in the dataset. They also produced one of the most surprising results: a slight positive correlation with engagement rate.
Despite widespread online chatter treating em dashes as an “AI artifact,” this data suggests they’re not hurting performance, and they may even align with better engagement. (As someone who genuinely likes em dashes — this was deeply validating.)
A plausible explanation may be that writers who use em dashes tend to write more explanatory, nuanced sentences rather than short, flat declarations. Those kinds of sentences often appear in longer, more thoughtful content that many readers actually engage with.
That said, this doesn’t mean em dashes cause engagement. Too much of a good thing is still too much of a good thing. But it does challenge the idea that em dashes are the bugbear content marketers make them out to be. 
Dig deeper: An AI-assisted content process that outperforms human-only copy
3 practical takeaways for content teams
Here’s what content marketers can act on today.
1. Don’t over-optimize for AI detection
Google doesn’t issue SEO rankings like a monotonic punishment score for “AI style.” Most phrases we looked at didn’t correlate with engagement at all. 
Don’t rewrite content just because someone declared a phrase “AI writing.” Write for reader usefulness and clarity above all.
2. Be mindful of how you wrap up
Explicit conclusion blocks aren’t bad — but generic, formulaic patterns are likely turning readers away. 
Consider blending conclusions into analysis, using subtler transitions, or adding new value with headers, instead of signposting obvious structure. 
3. Use the punctuation that makes sense 
If your style calls for em-dashes? In this dataset, they were actually associated with better reader engagement. Use them.
Don’t miss the forest for fake plastic trees
AI is likely here to stay in content workflows. But the issues with “bad” AI writing aren’t limited to linguistic tics and punctuation. While we all have our stylistic opinions, we should be careful about turning stylistic hot takes into editorial law. 
Write valuable writing. Think about readers first. And don’t panic every time someone on Twitter or LinkedIn decrees that “X phrase = AI.”

An analysis of 1,000+ URLs reveals which AI writing tics correlate with engagement. Some common “tells” don’t matter. A few might.

The AI writing tics that hurt engagement: A study

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots.png" class="attachment-large size-large wp-post-image" alt="Anthropic bots" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Anthropic explains how its bots handle AI training, live queries, and search results, and what opting out means for visibility.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots.png" class="attachment-large size-large wp-post-image" alt="Anthropic bots" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/02/anthropic-bots-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Anthropic updated its crawler documentation this week, clarifying how its Claude bots access websites and how you can block them.</p>



<ul class="wp-block-list">
<li>Anthropic&#8217;s document explains what each bot does, how it affects AI training and search visibility, and how to opt out through robots.txt.</li>
</ul>



<p><strong>Why we care.</strong> If you publish or own content, you want control over how AI systems use it. Anthropic separates training crawlers, user-triggered fetches, and search indexing. Blocking one bot doesn’t block the others. Each choice carries different visibility and training trade-offs.</p>



<p><strong>The robots.</strong> Anthropic uses three separate user agents:</p>



<ul class="wp-block-list">
<li><strong>ClaudeBot</strong> collects public web content that may be used to train and improve Anthropic’s generative AI models. If you block ClaudeBot in robots.txt, Anthropic said it will exclude your site’s future content from AI training datasets.</li>



<li><strong>Claude-User</strong> retrieves content when a user asks Claude a question that requires access to a webpage. If you block Claude-User, Anthropic can’t fetch your pages in response to user queries. The company says this may reduce your visibility in user-directed search responses.</li>



<li><strong>Claude-SearchBot</strong> crawls content to improve the quality and relevance of Claude’s search results. If you block Claude-SearchBot, Anthropic won’t index your content for search optimization, which may reduce visibility and accuracy in Claude-powered search answers.</li>
</ul>



<p><strong>How to block them.</strong> The bots respect standard robots.txt directives, including “Disallow” rules and the non-standard “Crawl-delay” extension, Anthropic said. To block a bot across your entire site:</p>



<p>User-agent: ClaudeBot<br>Disallow: /</p>



<ul class="wp-block-list">
<li>You must add directives for each bot and each subdomain you want to restrict.</li>



<li>IP blocking may not work reliably because its bots use public cloud provider IP addresses, Anthropic said. Blocking those ranges could prevent the bot from accessing robots.txt. The company doesn’t publish IP ranges.</li>
</ul>



<p><strong>The document.</strong> <a href="https://privacy.claude.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler" target="_blank" rel="noopener">Does Anthropic crawl data from the web, and how can site owners block the crawler?</a></p>


Anthropic updated its crawler documentation this week, clarifying how its Claude bots access websites and how you can block them.
Anthropic’s document explains what each bot does, how it affects AI training and search visibility, and how to opt out through robots.txt.
Why we care. If you publish or own content, you want control over how AI systems use it. Anthropic separates training crawlers, user-triggered fetches, and search indexing. Blocking one bot doesn’t block the others. Each choice carries different visibility and training trade-offs.
The robots. Anthropic uses three separate user agents:
ClaudeBot collects public web content that may be used to train and improve Anthropic’s generative AI models. If you block ClaudeBot in robots.txt, Anthropic said it will exclude your site’s future content from AI training datasets.
Claude-User retrieves content when a user asks Claude a question that requires access to a webpage. If you block Claude-User, Anthropic can’t fetch your pages in response to user queries. The company says this may reduce your visibility in user-directed search responses.
Claude-SearchBot crawls content to improve the quality and relevance of Claude’s search results. If you block Claude-SearchBot, Anthropic won’t index your content for search optimization, which may reduce visibility and accuracy in Claude-powered search answers.
How to block them. The bots respect standard robots.txt directives, including “Disallow” rules and the non-standard “Crawl-delay” extension, Anthropic said. To block a bot across your entire site:
User-agent: ClaudeBot
Disallow: /
You must add directives for each bot and each subdomain you want to restrict.
IP blocking may not work reliably because its bots use public cloud provider IP addresses, Anthropic said. Blocking those ranges could prevent the bot from accessing robots.txt. The company doesn’t publish IP ranges.
The document. Does Anthropic crawl data from the web, and how can site owners block the crawler?

Anthropic explains how its bots handle AI training, live queries, and search results, and what opting out means for visibility.

Anthropic clarifies how Claude bots crawl sites and how to block them

<div><img width="1920" height="1082" src="https://searchengineland.com/wp-content/seloads/2026/02/How-ChatGPT-uses-SEO-to-drive-growth-and-revenue.png" class="attachment-large size-large wp-post-image" alt="How ChatGPT uses SEO to drive growth and revenue" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/How-ChatGPT-uses-SEO-to-drive-growth-and-revenue.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/How-ChatGPT-uses-SEO-to-drive-growth-and-revenue-768x433.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/How-ChatGPT-uses-SEO-to-drive-growth-and-revenue-1536x866.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>An SEO audit of ChatGPT, Claude, and Perplexity reveals how the platforms use technical optimization, content, and conversions to scale.

Generative search engines like ChatGPT have successfully used SEO as part of their growth strategy, even as the echo chambers of the web claim they’re killing this powerful marketing channel.
Let’s take a look at how ChatGPT, Perplexity, and Claude fare in SEO, and why ChatGPT’s investment in the strategy is paying off.
Directional SEO ROI forecast
A $600,000 annual SEO investment could generate outsized returns for generative AI platforms.
Using Semrush-reported monthly organic traffic — 76.5 million visits for ChatGPT, 908,000 for Claude, and 1.7 million for Perplexity — plus a conservative 0.5% conversion rate and a $20/month entry price, projected returns range from approximately $92 million in annual revenue for ChatGPT (15,200% ROI) to 82%-240% ROI for Claude and Perplexity.
OpenAI’s investment in SEO and content for ChatGPT’s growth
OpenAI understands the value of SEO to drive growth. It was offering $310,000-$393,000 to hire a content strategist with SEO experience.

It then launched a second job search for a growth role focused on SEO, CRO, and web strategy. 

Looking at SEO-focused growth role salaries in the U.S. ($100,000 to $295,000), we can estimate OpenAI invested between $410,000 and $600,000 for two SEO roles, not including benefits and other expenses.
SEO has more lives than an agile alley cat because it leverages human behavior. Searching is core to our survival. When we were cave dwellers needing food or shelter, we searched for it. Search engines amplify this behavior.

ChatGPT is expanding search behavior and increasing Google searches in certain use cases. However, there’s a 20% decline in overall Google search volume from 2024 to 2025. 
That shift makes visibility even more critical. As the search landscape evolves — and as Google’s AI Overviews take clicks away — increasing your website’s ability to be found through SEO becomes more important, not less.
The OpenAI team understands this. That’s why it built SEO into ChatGPT’s foundation and continues investing in it.

  
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Evaluating the SEO foundations of ChatGPT, Claude, and Perplexity
I conducted a brief analysis of how ChatGPT, Perplexity, and Claude use SEO to grow. The goal was to uncover the good, the bad, and the ugly so brands can apply what works and discard the rest.
Using Semrush for competitive keyword analysis, I examined domain authority, brand versus non-brand keyword distribution, and total keyword rankings.

Brand authority and demand
ChatGPT’s website has an authority score of 99, followed by Perplexity’s 81 and Claude’s 75. Building a strong product and brand, then leveraging public relations, news, and social media, is the best way to grow your website’s authority. 
The branded term “ChatGPT” gets 45.5 million searches monthly, while Perplexity gets 1 million and Claude gets 500,000. That’s an enormous demand; they use SEO to convert into traffic, signups, and revenue.
Paid and organic search
All brands spend money on Google Ads, but SEO drives most of their search traffic. None are integrating search, which is a big opportunity. 
Integrated search is the practice of targeting highly valuable, often expensive, keywords with both SEO and PPC. It increases conversions, lowers Google Ads cost per click, and helps you take up more real estate on the search engine results pages, pushing competitors lower.
Keyword rankings
ChatGPT: ~287,800 keywords.
Perplexity: ~184,800 keywords.
Claude: ~36,000 keywords.

ChatGPT leveraged user-generated content to build a massive indexable surface area. 
Perplexity focused on financial, stock-driven content pages. Claude uses blog articles targeting high-intent professional audiences.
Neither can match ChatGPT’s kinetic energy from branding efforts and SEO built into its technical foundation.
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The 3Cs SEO and AI optimization framework

Below, I applied our agency’s 3Cs SEO and AI optimization approach: code (technical foundation), content strategy and optimization, and conversions.
Code
For this section, I focused on indexability, or how well search engines can find important website content. This is important to rank in traditional search, including Google and Bing, and LLMs like ChatGPT.
Robots.txt
ChatGPT has a highly optimized robots.txt file that includes multiple sitemaps, location recommendations, and blocks for certain crawlers while allowing others.

Perplexity’s robots.txt file isn’t as optimized or detailed. Claude was missing a robots.txt but added it recently. Not having a robots.txt file or having it return a 404 can be detrimental to your rankings. 
Note that ChatGPT and Claude block each other from crawling their websites via robots.txt.

Recommendation: Optimize your robots.txt, include all sitemaps, block pages you don’t want indexed, and allow LLM crawlers like ChatGPT to crawl your site.
URL structure
According to Google representative John Mueller, keywords in a URL are a “very, very small ranking factor.” That said, we can see a clear performance difference between ChatGPT, Claude, and Perplexity because they include keywords in their URLs.
Including keywords in a URL is an important way to give search engines, LLMs, and users information about what the page is about.
Imagine you went to a restaurant and wanted a burger. You say, “I want a burger,” and you’ll get a burger. If you said, “I want 2387d2e3,” you’d only get frustration from your waiter. That’s what happens with LLMs and traditional search engines. 
Yes, search engines can look at other elements of the page to understand what it’s about, but you win when you check all the boxes. That’s the difference between ChatGPT and Claude’s URLs below.
ChatGPT uses the name of what a user creates and shares in the URL, which helps it rank better for those words.

Claude doesn’t. Its public artifacts don’t have words built into them.


Recommendation: Use short URLs with keywords in them. I’ve seen this have major ranking impacts, even though Google and others say it’s a minor ranking factor. Changing this is hard after the fact. Semantic URLs are also important to rank in LLMs like ChatGPT.
Content
All of the LLM websites use content for marketing, including use cases, partnerships, target industries, and more.

Claude’s blog has highly targeted articles for professionals.

Perplexity has a discovery hub with timely, useful content.




However, the content isn’t optimized for SEO. Meta titles, descriptions, URLs, and canonical tags aren’t optimized, which confuses search engines. 

Some pages aren’t even indexed on Google as a result.

Their blogs don’t optimize images either. Image names should be descriptive, like “perplexity-deep-research.webp,” to improve ranking ability.

Perplexity is giving itself death by a thousand optimization cuts. 
Even though Claude and Perplexity target highly relevant keywords, an analysis of the top 50,000 keywords each website ranks for shows ChatGPT winning with sustained month-over-month growth.

Recommendation: Build SEO into your technical foundation. Fully optimize blog articles. Leverage user-generated content through forums or community hubs.
Conversions
All these brands understand SEO needs to drive conversions, not just traffic and rankings. There are two types of conversions: free conversions for people not ready to buy and paid conversions for people ready to buy. 
ChatGPT, Perplexity, and Claude all give users a trial of their product, then ask them to convert or sign in.

Recommendation: Convert as much website traffic as possible. Use AI coding platforms to build interactive content for conversion, as Google AI Overviews take traffic away.
If OpenAI bets on SEO, should you?
OpenAI is spending up to $600,000 on SEO talent to grow ChatGPT, not including staff benefits and other costs. This analysis breaks down how ChatGPT, Perplexity, and Claude use SEO to fuel growth. 
If disruptive technology companies like OpenAI are doubling down on SEO and content to drive growth, you should include it in your growth strategy as well. It works.

An SEO audit of ChatGPT, Claude, and Perplexity reveals how the platforms use technical optimization, content, and conversions to scale.

How ChatGPT uses SEO to drive growth and revenue

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard.png" class="attachment-large size-large wp-post-image" alt="How to read Meta Ads metrics like a system, not a scoreboard" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>Stop toggling off “losers” based on surface metrics. Analyze relationships between KPIs to pinpoint bottlenecks and drive sustainable growth.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard.png" class="attachment-large size-large wp-post-image" alt="How to read Meta Ads metrics like a system, not a scoreboard" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard.png 1920w, https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/02/How-to-read-Meta-Ads-metrics-like-a-system-not-a-scoreboard-1536x864.png 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Every week, thousands of media buyers perform the same ritual, opening Meta Ads Manager, scanning metrics, and deciding which campaigns and ads were winners and which were losers. If ROAS is positive, they’re pleased. If not, the mouse quickly heads toward the toggle button to disable the asset. This is the scoreboard trap some advertisers fall into.</p>



<p>When you treat metrics like a scoreboard, you’re looking at the outcome without understanding the full picture or how to improve going forward. The score of the game doesn’t include the fact that your strikers aren’t getting any passes from midfield.&nbsp;</p>



<p>To scale performance, it’s important to move from reporting to diagnosing the issues at hand. Start looking at your metrics as independent KPIs and as a system of interdependent signals to better tell the story of what’s happening in your account and accurately inform your next optimization steps.</p>



<h2 class="wp-block-heading" id="h-the-dashboard-illusion">The dashboard illusion</h2>



<p>Meta’s interface is designed as a linear grid, which can create a false sense of clarity. It may suggest that a high CPM is the problem in one column and, in another, that a low CTR is the culprit. In reality, these metrics are deeply intertwined.&nbsp;</p>



<p>A high CPM might not mean your audience is expensive. It may indicate your creative is low quality, so Meta is charging you more for a poor user experience on its platform.&nbsp;</p>



<p>Conversely, a high CTR might look like a win at first glance, but if your CVR is plummeting, it’s not a win, and you’re paying for high-intent customers your landing page can’t close.&nbsp;</p>



<p>The dashboard tells you what happened, and the system tells you why.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="873" height="321" src="https://searchengineland.com/wp-content/seloads/2026/02/A-visual-of-an-example-of-Meta-Ads-Manager-CTR-and-CPM-reporting-columns.png" alt="A visual of an example of Meta Ads Manager CTR and CPM reporting columns." class="wp-image-470067" srcset="https://searchengineland.com/wp-content/seloads/2026/02/A-visual-of-an-example-of-Meta-Ads-Manager-CTR-and-CPM-reporting-columns.png 873w, https://searchengineland.com/wp-content/seloads/2026/02/A-visual-of-an-example-of-Meta-Ads-Manager-CTR-and-CPM-reporting-columns-768x282.png 768w" sizes="(max-width: 873px) 100vw, 873px" /><figcaption class="wp-element-caption"><em><em>A visual of an example of Meta Ads Manager CTR and CPM reporting columns.</em></em></figcaption></figure></div>


<p><strong><em>Dig deeper: <a href="https://searchengineland.com/meta-ai-driven-advertising-system-andromeda-gem-468020">Inside Meta’s AI-driven advertising system: How Andromeda and GEM work together</a></em></strong></p>



<h2 class="wp-block-heading" id="h-the-team-metrics-framework">The team metrics framework</h2>



<p>To better understand the system, let’s think of metrics as a sports team. Each player has a specific role. If the team loses, you don’t bench the whole team. You review the play to see what happened so you can improve your chances of winning next time.</p>



<h3 class="wp-block-heading" id="h-the-scouts-cpm-and-reach">The scouts: CPM and reach</h3>



<p>CPM is the auction’s feedback on your total value. It’s a combination of your bid, estimated action rates, and value to the user. Together, their role is market resonance.&nbsp;</p>



<p>If CPM spikes relative to your historical average, these metrics signal the market is either too crowded or your creative isn’t effective enough to maintain volume.</p>



<h3 class="wp-block-heading" id="h-the-midfielders-ctr-and-hook-rate">The midfielders: CTR and hook rate</h3>



<p>Their role is to move the ball from the ad placement in Meta’s ecosystem to your website. If you have a high hook rate but a low CTR, your ad is great at getting attention but terrible at passing the ball. You’re stopping the scroll effectively, but your content isn’t enticing people to click.</p>



<h3 class="wp-block-heading" id="h-the-strikers-cvr-and-aov">The strikers: CVR and AOV</h3>



<p>These metrics are the final step in the journey and rely on your website. If CTR is high and CPC is low, but ROAS is low, something is amiss. Your ad did its job well, but your landing page or offer didn’t because people aren’t converting.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/meta-ads-ai-best-practices-better-results-455324">Rethinking Meta Ads AI: Best practices for better results</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-diagnosing-system-gaps">Diagnosing system gaps</h2>



<p>The real diagnosis happens between the columns you see in Ads Manager.</p>



<h3 class="wp-block-heading" id="h-hook-vs-hold-rates">Hook vs. hold rates</h3>



<p>Quickly diagnose creative fatigue before it impacts ROAS by looking at the ratio between hook rate and hold rate. </p>



<ul class="wp-block-list">
<li>If you have a high hook rate and a low hold rate, your ad is successfully grabbing attention but then losing interest. This is a good opportunity to adjust the latter portion of your ad, make it more compelling, and end it with a clear, strong CTA.</li>



<li>If you have a low hook rate but a high hold rate, you’re losing most people at the beginning, but those who stay are likely to convert. This presents a good opportunity to test new hooks that fit with the rest of your video to grab more attention up front and help drive more conversions.</li>
</ul>



<h3 class="wp-block-heading" id="h-link-clicks-vs-landing-page-views">Link clicks vs. landing page views</h3>



<p>The gap between these two metrics is important and often overlooked. If you have 1,000 clicks but only 450 landing page views, you may have a technical leak somewhere. Check your page speed and whether your tracking is working properly.&nbsp;</p>



<p>It’s unlikely this is a creative issue, as a significant drop-off rate like this is likely caused by a slow server. People expect a site to load quickly. If it doesn’t, they’ll bounce, and your budget will be wasted.</p>



<h3 class="wp-block-heading" id="h-cpa-vs-frequency">CPA vs. frequency</h3>



<p>If a rising CPA feels like a mystery, look at frequency. If both metrics are increasing, your audience is likely seeing the same ad too often and getting fatigued.&nbsp;</p>



<p>A tired audience and system need something fresh, not just a bid or budget increase. Swap out creative assets or expand your targeting if it’s too narrow.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="727" height="317" src="https://searchengineland.com/wp-content/seloads/2026/02/A-visual-of-an-example-of-Meta-Ads-Manager-reporting-columns.png" alt="A visual of an example of Meta Ads Manager reporting columns." class="wp-image-470068"/><figcaption class="wp-element-caption"><em><em>A visual of an example of Meta Ads Manager reporting columns.</em></em></figcaption></figure></div>


<p><strong><em>Dig deeper: <a href="https://searchengineland.com/meta-ads-lead-gen-what-you-need-to-know-456269">Meta Ads for lead gen: What you need to know</a></em></strong></p>



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<h2 class="wp-block-heading" id="h-from-reporting-to-diagnosing">From reporting to diagnosing</h2>



<p>When a campaign or creative underperforms, ask yourself:</p>



<ul class="wp-block-list">
<li><strong>Is volume constant? </strong>Has spend or impressions decreased? The system may have devalued or rejected your ad, specifically the creative.</li>



<li><strong>Where is the friction taking place? </strong>Follow the ball down the field. Is it hook rate, CTR, or CVR?</li>
</ul>



<p>Once you identify the bottleneck, change only that variable. If you change too many variables, you won’t clearly understand which part was broken. If CVR is low, don’t change the ad. Instead, improve the landing page experience.&nbsp;</p>



<p>Are you sending people to a product detail page while showcasing numerous products in a single creative? Remove the friction and create a product collection landing page instead, so everyone interested in a component of your ad can seamlessly and intuitively shop once they click.</p>



<h2 class="wp-block-heading" id="h-becoming-a-media-architect">Becoming a media architect</h2>



<p>With Meta’s AI taking the lead in targeting, it’s now our job as media buyers to evolve into system architects. </p>



<p>A scoreboard tells you something isn’t winning. A system map tells the full story, like when site speed is tanking ROAS or creative is hooking the wrong people.</p>



<p>Next time you look at your account, ignore the ROAS column at first glance. Instead, look at the ratios, trace the user’s path through your metrics, and unlock the story of the journey from ad to website. When you stop looking for winners and start looking for friction points, you’ll begin engineering more meaningful growth.</p>



<p><strong><em>Dig deeper: <a href="https://searchengineland.com/facebook-ad-templates-examples-467942">4 Facebook ad templates that still work in 2026 (with real examples)</a></em></strong></p>

Every week, thousands of media buyers perform the same ritual, opening Meta Ads Manager, scanning metrics, and deciding which campaigns and ads were winners and which were losers. If ROAS is positive, they’re pleased. If not, the mouse quickly heads toward the toggle button to disable the asset. This is the scoreboard trap some advertisers fall into.
When you treat metrics like a scoreboard, you’re looking at the outcome without understanding the full picture or how to improve going forward. The score of the game doesn’t include the fact that your strikers aren’t getting any passes from midfield. 
To scale performance, it’s important to move from reporting to diagnosing the issues at hand. Start looking at your metrics as independent KPIs and as a system of interdependent signals to better tell the story of what’s happening in your account and accurately inform your next optimization steps.
The dashboard illusion
Meta’s interface is designed as a linear grid, which can create a false sense of clarity. It may suggest that a high CPM is the problem in one column and, in another, that a low CTR is the culprit. In reality, these metrics are deeply intertwined. 
A high CPM might not mean your audience is expensive. It may indicate your creative is low quality, so Meta is charging you more for a poor user experience on its platform. 
Conversely, a high CTR might look like a win at first glance, but if your CVR is plummeting, it’s not a win, and you’re paying for high-intent customers your landing page can’t close. 
The dashboard tells you what happened, and the system tells you why.
A visual of an example of Meta Ads Manager CTR and CPM reporting columns.
Dig deeper: Inside Meta’s AI-driven advertising system: How Andromeda and GEM work together
The team metrics framework
To better understand the system, let’s think of metrics as a sports team. Each player has a specific role. If the team loses, you don’t bench the whole team. You review the play to see what happened so you can improve your chances of winning next time.
The scouts: CPM and reach
CPM is the auction’s feedback on your total value. It’s a combination of your bid, estimated action rates, and value to the user. Together, their role is market resonance. 
If CPM spikes relative to your historical average, these metrics signal the market is either too crowded or your creative isn’t effective enough to maintain volume.
The midfielders: CTR and hook rate
Their role is to move the ball from the ad placement in Meta’s ecosystem to your website. If you have a high hook rate but a low CTR, your ad is great at getting attention but terrible at passing the ball. You’re stopping the scroll effectively, but your content isn’t enticing people to click.
The strikers: CVR and AOV
These metrics are the final step in the journey and rely on your website. If CTR is high and CPC is low, but ROAS is low, something is amiss. Your ad did its job well, but your landing page or offer didn’t because people aren’t converting.
Dig deeper: Rethinking Meta Ads AI: Best practices for better results

  
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Diagnosing system gaps
The real diagnosis happens between the columns you see in Ads Manager.
Hook vs. hold rates
Quickly diagnose creative fatigue before it impacts ROAS by looking at the ratio between hook rate and hold rate. 
If you have a high hook rate and a low hold rate, your ad is successfully grabbing attention but then losing interest. This is a good opportunity to adjust the latter portion of your ad, make it more compelling, and end it with a clear, strong CTA.
If you have a low hook rate but a high hold rate, you’re losing most people at the beginning, but those who stay are likely to convert. This presents a good opportunity to test new hooks that fit with the rest of your video to grab more attention up front and help drive more conversions.
Link clicks vs. landing page views
The gap between these two metrics is important and often overlooked. If you have 1,000 clicks but only 450 landing page views, you may have a technical leak somewhere. Check your page speed and whether your tracking is working properly. 
It’s unlikely this is a creative issue, as a significant drop-off rate like this is likely caused by a slow server. People expect a site to load quickly. If it doesn’t, they’ll bounce, and your budget will be wasted.
CPA vs. frequency
If a rising CPA feels like a mystery, look at frequency. If both metrics are increasing, your audience is likely seeing the same ad too often and getting fatigued. 
A tired audience and system need something fresh, not just a bid or budget increase. Swap out creative assets or expand your targeting if it’s too narrow.
A visual of an example of Meta Ads Manager reporting columns.
Dig deeper: Meta Ads for lead gen: What you need to know
Get the newsletter search marketers rely on.
 
				
								
					MktoForms2.loadForm("https://app-sj02.marketo.com", "727-ZQE-044", 16298, function(form) {
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						// });
						
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						// });
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See terms.
From reporting to diagnosing
When a campaign or creative underperforms, ask yourself:
Is volume constant? Has spend or impressions decreased? The system may have devalued or rejected your ad, specifically the creative.
Where is the friction taking place? Follow the ball down the field. Is it hook rate, CTR, or CVR?
Once you identify the bottleneck, change only that variable. If you change too many variables, you won’t clearly understand which part was broken. If CVR is low, don’t change the ad. Instead, improve the landing page experience. 
Are you sending people to a product detail page while showcasing numerous products in a single creative? Remove the friction and create a product collection landing page instead, so everyone interested in a component of your ad can seamlessly and intuitively shop once they click.
Becoming a media architect
With Meta’s AI taking the lead in targeting, it’s now our job as media buyers to evolve into system architects. 
A scoreboard tells you something isn’t winning. A system map tells the full story, like when site speed is tanking ROAS or creative is hooking the wrong people.
Next time you look at your account, ignore the ROAS column at first glance. Instead, look at the ratios, trace the user’s path through your metrics, and unlock the story of the journey from ad to website. When you stop looking for winners and start looking for friction points, you’ll begin engineering more meaningful growth.
Dig deeper: 4 Facebook ad templates that still work in 2026 (with real examples)

Stop toggling off “losers” based on surface metrics. Analyze relationships between KPIs to pinpoint bottlenecks and drive sustainable growth.

How to read Meta Ads metrics like a system, not a scoreboard

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>This seems like it was a brief outage over night.

<div><img width="1920" height="1097" src="https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920.jpg" class="attachment-large size-large wp-post-image" alt="" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920-768x439.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/10/google-broken-logo-1920-1536x878.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google confirmed it had an issue serving search results earlier this morning at around 1:30 am ET on Wednesday, February 25th. The issue seemed to be fixed very quickly and we didn&#8217;t see a huge number of complaints about the issue.</p>



<p>Google <a href="https://status.search.google.com/incidents/TZF4pLmbzFdoBPP6o3iv">posted</a> a notice saying, &#8220;We fixed the issue with serving search results. There will be no more updates.&#8221;</p>



<p><strong>Why we care. </strong>If your website noticed a drop in traffic around midnight last night, it may be related to this serving issue.  </p>



<p>Again, it seems the serving issue was discovered and fixed very quickly but just because Google posted the issue and resolved it within a minute, it does not mean the serving issue was only a minute. Rather, this is when Google posted the notices.  Google did say the issue lasted about 15 minutes.</p>



<p>Here is a screenshot of the status dashboard notice:</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1186" height="654" src="https://searchengineland.com/wp-content/seloads/2026/02/google-serving-issue-1772017445.png" alt="" class="wp-image-470164" srcset="https://searchengineland.com/wp-content/seloads/2026/02/google-serving-issue-1772017445.png 1186w, https://searchengineland.com/wp-content/seloads/2026/02/google-serving-issue-1772017445-768x424.png 768w" sizes="(max-width: 1186px) 100vw, 1186px" /></figure>


Google confirmed it had an issue serving search results earlier this morning at around 1:30 am ET on Wednesday, February 25th. The issue seemed to be fixed very quickly and we didn’t see a huge number of complaints about the issue.
Google posted a notice saying, “We fixed the issue with serving search results. There will be no more updates.”
Why we care. If your website noticed a drop in traffic around midnight last night, it may be related to this serving issue.  
Again, it seems the serving issue was discovered and fixed very quickly but just because Google posted the issue and resolved it within a minute, it does not mean the serving issue was only a minute. Rather, this is when Google posted the notices.  Google did say the issue lasted about 15 minutes.
Here is a screenshot of the status dashboard notice:

This seems like it was a brief outage over night.

Google fixed a serving issue with search results

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns.jpg" class="attachment-large size-large wp-post-image" alt="How to tell if Google Ads automation helps or hurts your campaigns" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>You can now tie ad spend to foot traffic, aligning bids with in-person visits across Maps and local search placements.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns.jpg" class="attachment-large size-large wp-post-image" alt="How to tell if Google Ads automation helps or hurts your campaigns" style="margin-bottom: 15px;" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns.jpg 1920w, https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns-768x432.jpg 768w, https://searchengineland.com/wp-content/seloads/2025/08/How-to-tell-if-Google-Ads-automation-helps-or-hurts-your-campaigns-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p>Google Ad Grants accounts can now optimize for real-world foot traffic. If you use the nonprofit program, you can set “shop visits” as an account-level goal, allowing your campaigns to optimize for in-person visits.</p>



<p><strong>Driving the news</strong>. Previously, if you tried to mark shop visits as a goal in Ad Grants, you’d get an error. That restriction appears to be lifted, allowing eligible accounts to include store visit conversions in their primary goal configuration.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1280" height="720" src="https://searchengineland.com/wp-content/seloads/2026/02/google-ad-grants-shop-visit-goal.jpg" alt="" class="wp-image-470133" srcset="https://searchengineland.com/wp-content/seloads/2026/02/google-ad-grants-shop-visit-goal.jpg 1280w, https://searchengineland.com/wp-content/seloads/2026/02/google-ad-grants-shop-visit-goal-768x432.jpg 768w" sizes="(max-width: 1280px) 100vw, 1280px" /></figure>



<ul class="wp-block-list">
<li>This update lets you align bidding and optimization with physical visits — especially for visibility in Maps placements and location-driven search results.</li>
</ul>



<p><strong>Why we care.</strong> If you run a nonprofit, museum, place of worship, community center, or other location-based organization, digital engagement doesn’t always translate into mission impact. Optimizing for shop visits bridges that gap, tying ad performance directly to foot traffic.</p>



<p><strong>What to do</strong>. If you use Ad Grants, review your account-level goals and confirm shop visits are enabled where eligible. Optimizing for foot traffic could materially improve your local impact — especially if you rely on in-person engagement.</p>



<p><strong>Between the lines</strong>. As Google continues to emphasize local intent and Maps-based discovery, bringing store visit optimization to Ad Grants expands your ability to compete for nearby audiences. It shifts the focus from clicks and website traffic to measurable offline action.</p>



<p><strong>First seen</strong>. Google Ads expert Jason King spotted this update and shared it on <a href="https://www.linkedin.com/posts/kingjason_quick-tip-for-google-ad-grant-users-putting-activity-7429157455219089409-_jHU/?utm_source=share&amp;utm_medium=member_android&amp;rcm=ACoAABU5RtAB1yM61HMd6Ska99csDVjiJlgRo6A">LinkedIn</a>.</p>


Google Ad Grants accounts can now optimize for real-world foot traffic. If you use the nonprofit program, you can set “shop visits” as an account-level goal, allowing your campaigns to optimize for in-person visits.
Driving the news. Previously, if you tried to mark shop visits as a goal in Ad Grants, you’d get an error. That restriction appears to be lifted, allowing eligible accounts to include store visit conversions in their primary goal configuration.





This update lets you align bidding and optimization with physical visits — especially for visibility in Maps placements and location-driven search results.
Why we care. If you run a nonprofit, museum, place of worship, community center, or other location-based organization, digital engagement doesn’t always translate into mission impact. Optimizing for shop visits bridges that gap, tying ad performance directly to foot traffic.
What to do. If you use Ad Grants, review your account-level goals and confirm shop visits are enabled where eligible. Optimizing for foot traffic could materially improve your local impact — especially if you rely on in-person engagement.
Between the lines. As Google continues to emphasize local intent and Maps-based discovery, bringing store visit optimization to Ad Grants expands your ability to compete for nearby audiences. It shifts the focus from clicks and website traffic to measurable offline action.
First seen. Google Ads expert Jason King spotted this update and shared it on LinkedIn.

You can now tie ad spend to foot traffic, aligning bids with in-person visits across Maps and local search placements.

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Read the Latest Trends and Headlines in Digital Marketing.

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

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