<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google says it is investigating reports of an issue affecting Merchant Center, but has not yet shared details on the cause or expected resolution.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-investigates-Merchant-Center-outage-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is investigating an issue affecting Google Merchant Center, though the company has not yet disclosed the cause or the impact on advertisers.</p>



<p class="wp-block-paragraph">The incident could affect merchants who rely on Merchant Center to manage product listings for Google Shopping and other commerce surfaces.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Google posted an incident notice stating that it is investigating reports of a problem with Merchant Center.</p>



<p class="wp-block-paragraph">The incident began on August 6 at 13:06 UTC, with Google publishing its first public update at 17:46 UTC, confirming it was investigating the issue and would provide more information as it became available.</p>



<p class="wp-block-paragraph">At the time of the update, Google had not shared details about the root cause, affected features or expected resolution timeline.</p>



<p class="wp-block-paragraph"><strong>Why we care:</strong> Merchant Center is a critical platform for retailers using Google Shopping, Performance Max and free product listings. Any disruption could impact product management or campaign operations, depending on the scope of the incident.</p>



<p class="wp-block-paragraph"><strong>Bottom line:</strong> <a href="https://merchants.google.com/status/incidents/cFVHBrBkwbAxFzEHjHwq">Google is investigating a Merchant Center incident</a> but has not yet confirmed what is affected or when the issue will be resolved.</p>


Google is investigating an issue affecting Google Merchant Center, though the company has not yet disclosed the cause or the impact on advertisers.
The incident could affect merchants who rely on Merchant Center to manage product listings for Google Shopping and other commerce surfaces.
What’s happening. Google posted an incident notice stating that it is investigating reports of a problem with Merchant Center.
The incident began on August 6 at 13:06 UTC, with Google publishing its first public update at 17:46 UTC, confirming it was investigating the issue and would provide more information as it became available.
At the time of the update, Google had not shared details about the root cause, affected features or expected resolution timeline.
Why we care: Merchant Center is a critical platform for retailers using Google Shopping, Performance Max and free product listings. Any disruption could impact product management or campaign operations, depending on the scope of the incident.
Bottom line: Google is investigating a Merchant Center incident but has not yet confirmed what is affected or when the issue will be resolved.

Google says it is investigating reports of an issue affecting Merchant Center, but has not yet shared details on the cause or expected resolution.

Google investigates Merchant Center outage

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>ChatGPT users can now reserve a table or join a Yelp waitlist without leaving the conversation, streamlining discovery to booking.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPTintegration-to-Yelp-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Yelp is deepening its partnership with OpenAI by bringing Reservations and Waitlist directly into ChatGPT, allowing users to book restaurant tables without leaving the conversation.</p>



<p class="wp-block-paragraph">The move expands ChatGPT from a discovery tool into a place where users can complete local actions, while giving restaurants another way to reach diners.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. ChatGPT users can now reserve a table or join a Yelp waitlist for thousands of restaurants across the U.S. and Canada directly within the chat experience.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Yelp-ChatGPt.png" alt="" class="wp-image-484555" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Yelp-ChatGPt.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Yelp-ChatGPt-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Yelp-ChatGPt-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Yelp-ChatGPt-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></figure>



<p class="wp-block-paragraph">After completing a booking, users can manage or modify their reservation through Yelp. The integration builds on Yelp&#8217;s existing partnership with OpenAI, which already surfaces Yelp reviews, ratings, photos and business details in ChatGPT responses.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The update shortens the path from recommendation to conversion. Instead of asking ChatGPT for restaurant suggestions and then switching to another app to book, users can now complete the entire journey in one conversation.</p>



<p class="wp-block-paragraph">For restaurants using Yelp Guest Manager, the integration also creates another discovery channel at the moment consumers are making dining decisions.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. Yelp is positioning itself as the infrastructure behind AI-powered local search rather than relying solely on traffic to its own website and app. Alongside ChatGPT, the company says its content and booking capabilities now power experiences across platforms including Apple Maps, Alexa+, Microsoft Bing, DuckDuckGo and Yahoo.</p>



<p class="wp-block-paragraph">The company also highlighted that Yelp remains one of the most frequently cited local business sources across major AI platforms, reinforcing its role as a trusted data provider for AI-powered recommendations.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://blog.yelp.com/news/yelp-chatgpt-integration/">By bringing reservations and waitlists into ChatGPT</a>, Yelp is making it easier for users to move from discovering a restaurant to securing a table, while strengthening its position in the growing AI search ecosystem.</p>


Yelp is deepening its partnership with OpenAI by bringing Reservations and Waitlist directly into ChatGPT, allowing users to book restaurant tables without leaving the conversation.
The move expands ChatGPT from a discovery tool into a place where users can complete local actions, while giving restaurants another way to reach diners.
What’s happening. ChatGPT users can now reserve a table or join a Yelp waitlist for thousands of restaurants across the U.S. and Canada directly within the chat experience.




After completing a booking, users can manage or modify their reservation through Yelp. The integration builds on Yelp’s existing partnership with OpenAI, which already surfaces Yelp reviews, ratings, photos and business details in ChatGPT responses.
Why we care. The update shortens the path from recommendation to conversion. Instead of asking ChatGPT for restaurant suggestions and then switching to another app to book, users can now complete the entire journey in one conversation.
For restaurants using Yelp Guest Manager, the integration also creates another discovery channel at the moment consumers are making dining decisions.
The bigger picture. Yelp is positioning itself as the infrastructure behind AI-powered local search rather than relying solely on traffic to its own website and app. Alongside ChatGPT, the company says its content and booking capabilities now power experiences across platforms including Apple Maps, Alexa+, Microsoft Bing, DuckDuckGo and Yahoo.
The company also highlighted that Yelp remains one of the most frequently cited local business sources across major AI platforms, reinforcing its role as a trusted data provider for AI-powered recommendations.
Bottom line. By bringing reservations and waitlists into ChatGPT, Yelp is making it easier for users to move from discovering a restaurant to securing a table, while strengthening its position in the growing AI search ecosystem.

ChatGPT users can now reserve a table or join a Yelp waitlist without leaving the conversation, streamlining discovery to booking.

Yelp brings restaurant reservations and waitlists to ChatGPT

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Technical-SEO-testing-How-to-build-a-stronger-experiment.png" class="attachment-large size-large wp-post-image" alt="Technical SEO testing: How to build a stronger experiment" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Technical-SEO-testing-How-to-build-a-stronger-experiment.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Technical-SEO-testing-How-to-build-a-stronger-experiment-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Technical-SEO-testing-How-to-build-a-stronger-experiment-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Technical-SEO-testing-How-to-build-a-stronger-experiment-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>The hardest part of an SEO test is knowing what caused the result. Choose comparisons and metrics that make your findings easier to defend.


Technical SEO changes are often evaluated with a simple before-and-after comparison. A change goes live, performance is measured over the following weeks, and any movement is attributed to the implementation.
The problem is that search performance rarely changes in isolation. Demand shifts, competitors move, Google updates roll out, and other site changes overlap with the same period. In many cases, Google hasn’t even recrawled enough of the affected pages before the test is called a success or failure.
That doesn’t make technical SEO experimentation impossible. It does mean the test needs to be designed around a stronger comparison than “what happened after launch.”
Define the hypothesis and the success criteria
Before choosing treatment and control groups, define the test precisely enough that the result can be interpreted.
Consider a multi-location site where location pages are connected primarily through a central locator and state-level pages. The team is considering a contextual internal-linking module that would connect each location to nearby locations and relevant service pages.
Define the test
The practical question is whether this specific module creates enough value to justify rolling it out across the full set of location pages.
That means the change needs to be clear and limited:
“Add a module to selected location pages containing links to three nearby locations and two relevant service pages. Keep the placement, design, number of links and selection logic consistent across the treatment group.”
Everything outside that change should remain as stable as possible. Rewriting the page content, changing the navigation, or updating the broader template at the same time would make it harder to separate the effect of the links from the rest of the implementation.
The test should also identify where the impact is expected to appear. The location pages receive the module, but the nearby locations and service pages receiving the links may be the pages that gain crawl activity, rankings, or traffic.
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Write the hypothesis
The hypothesis should connect the change to the expected result:
“Adding contextual links between related location and service pages will create stronger crawl paths and internal signals, improving the organic visibility of the linked destination pages compared with similar pages that retain the existing structure.”
This is more useful than predicting that traffic will increase. It explains why the change may work, identifies the pages expected to benefit, and establishes which signals should be measured.
Set success, failure, and inconclusive states
Define what would count as success, failure, or an inconclusive result before the data arrives.
At this stage, those definitions can remain high-level.
Success would show meaningful improvement in the areas the test was designed to influence, strong enough to justify rolling the change out at scale.
Failure would show no meaningful difference after enough crawl coverage and data had accumulated, or a decline in performance.
An inconclusive result would mean the comparison wasn’t clean enough or the available data wasn’t strong enough to support either conclusion.
The more complicated cases, including situations where technical signals improve but rankings don’t, can be addressed when interpreting the final result.
Dig deeper: Advanced technical SEO tips: 14 technical SEO issues you’re missing



Choose the strongest comparison the site allows
In a perfect experiment, the treatment and control groups would be identical except for the change being tested. SEO rarely works that cleanly.
Pages differ in age, authority, demand, competition, link history, and search intent. They also influence one another through internal links, shared templates, and site architecture. Even on a large templated site, two pages that look nearly identical may behave very differently in search.
The goal isn’t to find a perfect control. It’s to build the strongest comparison the site can support and understand where that comparison is weak.
Some sites can support a true split test across large, stable page sets. Others may need matched page groups, a phased rollout, or a before-and-after analysis with more limited conclusions.
The testing method should reflect the level of control available, not the level of certainty the team wishes it had.
Split testing where possible
SEO split testing applies a change to one group of pages while a comparable group remains unchanged. Both groups are measured over the same period, which helps account for changes in demand, seasonality, algorithm updates, and broader site movement.
This is usually the strongest option when the site has a large set of similar pages and the implementation can be withheld safely from part of that set.
Ecommerce categories, product pages, editorial templates, and location pages can all create useful testing environments. The repeated structure makes it possible to change one portion of the site without changing everything at once.
But repeated templates don’t automatically create comparable pages.
Two location pages may use the same layout while serving markets with very different levels of demand, competition, and history. Two product categories may have similar page counts but completely different seasonal patterns. A random 50/50 split can still produce weak groups if one side contains stronger markets, categories, or page sets.
The split only helps if the groups were comparable before the test.
Matched page-group comparisons
When a clean split isn’t practical, matched page groups are often the next strongest option.
Instead of randomly assigning pages, the treatment group is compared with pages or sections that have shown similar historical behavior. The match may be based on clicks, impressions, rankings, crawl frequency, indexing, market size, page age, branded demand, or seasonality.
The groups don’t need to start at the same level.
A higher-traffic treatment group may still be useful if both groups have historically moved in similar ways. Two groups with similar current traffic may be a poor match if one has been growing for months while the other has been declining.
This is especially relevant on multi-location sites, where pages may share the same template but represent very different markets.
Matched page-group comparisons are less controlled than a well-designed split test, but they’re often more realistic. They can also be stronger than a random split with a small number of page groups that ignores how the pages actually perform.
Phased rollouts
Some changes are intended for the full site but can still be introduced in stages.
A first phase might include one group of markets, categories, or templates while comparable sections remain unchanged. Those untreated sections act as a temporary control.
This approach works well when a permanent control is unrealistic or when the team wants to reduce implementation risk before expanding the change. It creates time to validate the setup, look for unintended crawl or indexing effects, and confirm that the change is behaving as expected.
A phased rollout isn’t as clean as a carefully constructed split test. The groups may differ more, and the control may only remain available for a limited period.
It’s still much stronger than launching the change everywhere at once and relying only on a before-and-after chart.
Know what before-and-after testing can’t prove
Before-and-after analysis is the most common way technical SEO changes are evaluated because it’s the easiest.
A change launches in one month. The following month is compared with the previous one. If performance improves, the implementation is credited. If it declines, the change is questioned.
The weakness is built into the comparison. The two periods didn’t experience the same conditions.
Search demand may have changed. Competitors may have gained or lost visibility. Google may have rolled out an update. New content, links, promotions, or tracking changes may have overlapped with the same period. Existing growth or decline may have continued regardless of the implementation.
Before-and-after analysis may still be the only practical option. Smaller sites may not have enough comparable pages for useful treatment and control groups. Some changes affect shared infrastructure across the entire site. Others need to be fixed everywhere and shouldn’t be withheld for the sake of a cleaner test.
In those cases, treat the result as lower-confidence evidence. A change and a result that share a timeline aren’t proof that one caused the other.
Dig deeper: How to safely implement high-impact technical SEO changes




	
	
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Track the metrics that match the hypothesis
Once the test and comparison groups are defined, the next step is deciding what evidence to collect.
Crawl rate, indexing, rankings, and traffic answer different questions, and not every test should be expected to affect all four.
For the internal-linking example, crawl behavior can show whether Google is using the new paths. Indexing may matter if the destination pages were previously difficult to discover, but it may remain unchanged if those pages were already indexed. Rankings, traffic, clicks, and impressions show whether the change ultimately produced more visibility and value.
The metrics should follow the hypothesis, not the other way around.
Crawl rate
Crawl data can show whether the new internal links changed how Googlebot moved through the site.
For most teams, Search Console will only provide the broad view. Crawl Stats can show whether total crawl activity changed across the site or host, but it won’t cleanly separate the treatment, control, and destination-page groups.
For this test, the most useful crawl questions require server logs:
Did Googlebot crawl more of the destination pages?
Were those pages recrawled more frequently?
Did Googlebot reach them sooner after the module launched?
Those are the signals most closely tied to the hypothesis. They show whether the new links actually changed crawler behavior across the pages expected to benefit.
Without server logs, crawl analysis will be less precise. A smaller sample can be checked through URL Inspection, while Search Console can still show the broader crawl trend.
More crawling isn’t automatically better. The relevant result is whether Googlebot is reaching the intended destination pages more often or sooner.
Indexing
Indexing can be measured through Search Console and should be treated as a primary metric only when the test is expected to affect index coverage.
For this test, the most useful measures are:
Whether the affected destination pages remain indexed
Whether previously excluded pages enter the index
Whether new indexing exclusions appear
Whether Google selects unexpected canonicals
If the destination pages were already consistently indexed, flat indexing isn’t a failed result. In that case, indexing is a diagnostic or guardrail while crawl behavior and search visibility carry more weight.
Rankings and search visibility
Search Console and SEO tools answer slightly different questions.
Search Console is most useful for understanding how the affected pages are appearing across the full range of queries Google associates with them. Top metrics include:
Impressions.
Number of ranking queries.
Nonbranded query visibility.
Page-level changes across the treatment and control groups.
An SEO platform such as Semrush adds a more controlled view of rankings across a defined keyword set or page set.
Useful metrics here may include:
Position changes for the target keyword set.
Keyword rank changes for the target pages.
Share of keywords in top three, top 10, or top 20 positions.
Local or market-level rankings, where the tool supports them.
Traffic
Traffic is often the outcome stakeholders care about most, but it’s also the furthest metric from the technical change.
Useful measures include:
GSC clicks.
Organic sessions (GA).
Landing-page entrances (GA).
Leads.
Revenue or other conversions.
Traffic can move for reasons that have little to do with the test. Changes in search demand or the appearance and disappearance of SERP features may have a larger impact than the technical change itself.
Traffic should support the broader pattern, not serve as the only verdict.
Dig deeper: Why proving technical SEO ROI is so difficult



These aren’t four separate scorecards
Crawl rate, indexing, rankings, and traffic each tell you something different about the test. They should be interpreted together, but they shouldn’t be weighted equally in every experiment.
A change designed to improve discovery may be successful if more eligible pages are crawled and indexed, even if traffic doesn’t immediately follow. A change intended to strengthen rankings needs stronger visibility gains. If the goal is revenue or lead growth, technical improvements that never translate into traffic or conversions may not be enough to justify a wider rollout.
This is why success metrics need to be chosen before the test begins. Otherwise, it becomes too easy to focus on whichever number moved in the right direction.
The metrics can also pull in different directions. Rankings may improve while traffic declines because demand changed or new SERP features reduced clicks. 
More pages may enter the index while overall visibility falls because the newly indexed pages add little value. Crawl activity may shift toward the treatment pages while more important sections receive less attention.
None of those results can be judged from one metric alone. The right question is whether the overall result supports the hypothesis and the decision behind the test.
Dig deeper: A technical SEO blueprint for GEO: Optimize for AI-powered search



  
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Better methodology leads to better decisions
Technical SEO experiments rarely produce perfect controls. Pages differ, site sections overlap, and search performance continues to move while the test is running.
That makes it even more important to define the hypothesis clearly, choose the strongest comparison the site allows, and decide which signals matter before seeing the result.
The test may not remove every competing explanation. It should make the most likely explanation easier to defend.
That’s the difference between observing what happened after a change and having enough evidence to decide what to do next.

The hardest part of an SEO test is knowing what caused the result. Choose comparisons and metrics that make your findings easier to defend.

Technical SEO testing: How to build a stronger experiment

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google is bringing automated dashboards and conversational reporting to Google Ads and Analytics for faster analysis.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Agentic-to-Ads-and-Analytics-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is expanding its AI assistant, <a href="https://searchengineland.com/google-launches-ask-advisor-across-ads-analytics-and-merchant-center-478114">Ask Advisor</a>, with new agentic capabilities across Google Ads and Google Analytics, aiming to help marketers uncover insights faster, automate analysis and make decisions without leaving the platform.</p>



<p class="wp-block-paragraph">The updates are designed to reduce the time spent interpreting data while keeping advertisers in control of campaign decisions.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening.</strong> Google Analytics is introducing AI Overviews on the homepage, providing a summary of key performance changes since a user last logged in. The feature highlights trends such as shifts in traffic or seasonal sales spikes, then recommends potential next steps.</p>



<figure class="wp-block-video"><video height="1566" width="2784" controls src="https://searchengineland.com/wp-content/seloads/2026/08/AI-Overviews-in-Google-Analytics.mp4"></video></figure>



<p class="wp-block-paragraph">Users can click directly into Ask Advisor to investigate a specific insight further, and they can opt in to receive these AI-generated summaries via email or mobile notifications.</p>



<p class="wp-block-paragraph">Google Ads is also getting a redesigned homepage with personalized AI-powered insight cards. Advertisers can ask natural-language questions—such as how competitors are affecting impression share or what trends could influence campaign performance—and Ask Advisor will generate tailored insights.</p>



<p class="wp-block-paragraph"><strong>Reporting gets smarter.</strong> Google is also introducing Dashboards in Google Ads, with support for Google Analytics coming soon.</p>



<figure class="wp-block-video"><video height="1458" width="2352" controls src="https://searchengineland.com/wp-content/seloads/2026/08/NEW-Google-Ads-Dashboard.mp4"></video></figure>



<p class="wp-block-paragraph">Using simple text prompts, marketers can generate visual reports from their data, while AI automatically creates real-time summaries explaining the performance trends behind the charts.</p>



<p class="wp-block-paragraph"><strong>Why we care. </strong>These updates move Google beyond simply surfacing data to actively helping advertisers interpret it. Rather than digging through reports and manually identifying trends, marketers can use AI to highlight important changes, answer business questions and create visual reports in a fraction of the time.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://blog.google/products/ads-commerce/google-ads-analytics-AI-updates">Google is giving Ads and Analytics users more AI-powered assistance through Ask Advisor</a>, introducing homepage summaries, conversational insights and automated reporting designed to simplify campaign analysis and speed up decision-making.</p>


Google is expanding its AI assistant, Ask Advisor, with new agentic capabilities across Google Ads and Google Analytics, aiming to help marketers uncover insights faster, automate analysis and make decisions without leaving the platform.
The updates are designed to reduce the time spent interpreting data while keeping advertisers in control of campaign decisions.
What’s happening. Google Analytics is introducing AI Overviews on the homepage, providing a summary of key performance changes since a user last logged in. The feature highlights trends such as shifts in traffic or seasonal sales spikes, then recommends potential next steps.




Users can click directly into Ask Advisor to investigate a specific insight further, and they can opt in to receive these AI-generated summaries via email or mobile notifications.
Google Ads is also getting a redesigned homepage with personalized AI-powered insight cards. Advertisers can ask natural-language questions—such as how competitors are affecting impression share or what trends could influence campaign performance—and Ask Advisor will generate tailored insights.
Reporting gets smarter. Google is also introducing Dashboards in Google Ads, with support for Google Analytics coming soon.




Using simple text prompts, marketers can generate visual reports from their data, while AI automatically creates real-time summaries explaining the performance trends behind the charts.
Why we care. These updates move Google beyond simply surfacing data to actively helping advertisers interpret it. Rather than digging through reports and manually identifying trends, marketers can use AI to highlight important changes, answer business questions and create visual reports in a fraction of the time.
Bottom line. Google is giving Ads and Analytics users more AI-powered assistance through Ask Advisor, introducing homepage summaries, conversational insights and automated reporting designed to simplify campaign analysis and speed up decision-making.

Google is bringing automated dashboards and conversational reporting to Google Ads and Analytics for faster analysis.

Google brings new AI agent capabilities to Ads and Analytics

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/Why-the-traditional-link-building-model-no-longer-works-for-AI-search.png" class="attachment-large size-large wp-post-image" alt="Why the traditional link building model no longer works for AI search" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Why-the-traditional-link-building-model-no-longer-works-for-AI-search.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/Why-the-traditional-link-building-model-no-longer-works-for-AI-search-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Why-the-traditional-link-building-model-no-longer-works-for-AI-search-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Why-the-traditional-link-building-model-no-longer-works-for-AI-search-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>High-DR links, paid mentions, and link exchanges can look authoritative without giving AI systems enough credibility to recommend your brand.

Traditional link building agencies had an incredible run. The pitch was easy to sell: “We build you links from high-DR sites with commercial anchor text, your rankings improve, and you get a spreadsheet every month that tallies up your backlink counts.”
SEO teams would report to their leadership: “We built X number of backlinks this month,” broken down by domain authority. The pricing model was simple: The higher the domain authority, the more expensive the backlink.
That supply chain link building model worked well for more than a decade. But the market has evolved beyond the service model.
Do backlinks still matter for SEO?
Yes. Links still matter because, without a certain baseline level of authority, competitive SEO thresholds become hard to clear.
But the outdated package of 500-word guest articles, link inserts, and high-volume link exchanges is becoming less effective for AI search.
If you’re still buying links, you’re paying for fake authority instead of building it. And if you’re paying a GEO agency for “LLM visibility campaigns,” you’re still buying fake authority, just wrapped in new marketing jargon.
Here’s why traditional link building is fundamentally broken, how AI search exposed it, and how to acquire real authority today.
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What a $500 backlink really buys you
Most traditional link building vendors sell a unit. That unit is a link insert or a guest article, and the pricing is almost always tied to domain authority.
Over the years, I’ve personally tested dozens of link building services and audited countless vendor proposals. If you look at a typical pricing sheet today, you’ll find flat rates of $400 to $500 per backlink, or rigid monthly retainers starting at $5,000.
But let’s look at the reality of what that $500 per link actually buys you.
A vendor might promise a placement with a Domain Rating of 70+ and 15,000 monthly organic visitors. On paper, it passes the test. But when you actually inspect the link placements, the cracks show immediately.
*Example below: I rejected 40+ link insertion pitches because they were completely irrelevant.*
Here’s what you typically find when you dig into those “high-quality” $500 links:
The link is shoved into completely irrelevant content that makes zero contextual sense.
The page traffic is generated entirely from countries outside the client’s target market.
The editing suggestion completely ignores the core topic of the client’s target URL.
The page is already stuffed with spammy, out-of-context external links.




Link building vendors hide behind Domain Authority
This exposes the core problem with traditional link building: It focuses on the wrong incentive. The agency is paid to produce a spreadsheet row, not to build real authority. The client receives proof of activity, not impact.
Link building vendors use Domain Authority as a crutch because it gives buyers an easy filter and sellers an easy pricing model.
But a high Domain Authority number is often just an illusion of authority. It doesn’t guarantee that the website is legitimate or that the referring page drives organic traffic.
And it certainly doesn’t guarantee that the content is editorially credible or that AI systems will consider that backlink as a source when deciding to recommend your brand.
AI search is harder to manipulate with one-off backlinks
Wil Reynolds said it best: 
“In the old days you could just muscle your way to the top of Google with zero receipts that you are “top 3” at XYZ thing. If you had enough domain authority you could rank. AI is 100x more likely to force you to have receipts to back up your claims.”
For years, the goal was to push a target URL higher up in the traditional rankings list. SEO teams achieved this through “ground and pound” link building to a specific target URL.
AI search forces a completely different and more complex question: Did we create enough credible context for an AI system to understand, trust, and recommend the brand?
That’s nearly impossible to fake with random, forced links.
AI models are looking for consensus, not random backlinks
AI answer engines analyze patterns of corroboration across the entire web. They don’t just crawl your backlinks. They synthesize the consensus around your entity. 
If your brand is mentioned across credible, topically relevant sources, the model encodes it as factual.
A random link doesn’t add to your brand consensus. It gets filtered out as noise.
Context is the new authority signal
In traditional SEO, a link was a form of digital vouching.
In the AI world, the co-occurrence of your brand name next to relevant industry terms, competitors, and specific use cases is the signal. AI systems map your brand’s entity footprint. They identify what you do, who you serve, and who you compete with.
A link stuffed into an irrelevant guest article provides zero entity context. It’s essentially invisible to the AI’s understanding of your brand.
AI mention building is just link building 2.0
As the industry shifts toward AI search, link builders are scrambling to adapt. Instead of evolving their underlying model, many are simply rebranding it. Enter the GEO grift.
Agencies that previously sold backlinks are now pitching “AI mention building” and “LLM visibility campaigns.” The sales pitch promises to engineer your brand into ChatGPT, Perplexity, and AI Overviews. Look under the hood, and it’s the exact same playbook wearing a new mask.
Take a look at the pitch below. The sender explicitly states, “We’re not asking for a backlink, just a mention,” but immediately follows it up with an offer to link back to you from a “partner site” in return.
It’s the exact same ABC link exchange scheme, just rebranded with AEO/GEO buzzwords.




Instead of building real authority, these vendors repackage the tired outreach model:
Selling brand mentions on the exact same low-quality websites.
Paying for sponsored listicles on external sites just to rank their clients at the top.
Pitching a Reddit strategy that’s actually just blatant astroturfing.
Buying fake brand mentions isn’t a modern AEO/GEO strategy. Third-party validation only matters when it comes from credible, topically relevant sources.
If a brand mention doesn’t come from a domain that buyers and AI engines already trust, it won’t influence a recommendation.
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What to do instead
GEO is a relevance engineering problem, not a tactical link building problem.
AI systems are trying to determine exactly what you do, who you serve, and where you sit in the competitive landscape. If you don’t intentionally shape that narrative, AI excludes your brand from the vendor selection process.
When buyers ask AI search platforms for a shortlist of vendor solutions, your brand needs to become an unavoidable, logical answer.
Here are some ways to achieve this.
Drive customer reviews to influential third-party sources
In this example for “best insider risk management solutions,” it’s clear that your brand must be represented on Gartner.
If your brand profile isn’t aligned to the correct Gartner category, and you aren’t driving credible and authentic customer reviews for this product line, your brand will likely be excluded from the vendor selection process.




Publish owned BOFU listicles for narrative control
This has become a hot topic in SEO, but there’s a way to do it right. 
John-Henry Scherck says that if your brand belongs in a category, it makes sense to build your own bottom-of-funnel comparison content.
But the goal isn’t to artificially rank your brand as “number one” in hopes of manipulating AI search. Instead, do it for brand narrative control.
By publishing objective comparisons on your own site (e.g., Your Brand vs. Competitor, Competitor Alternatives), you increase your chances of entering the citation pool. 
This helps the AI accurately understand your product features, use cases, and market position relative to your competitors, ultimately enabling it to better understand when it should recommend you.
Build proprietary content assets
Cyrus Shepard found in a recent study that 92% of sites that experience significant organic growth produce their own proprietary assets. 
Vince Nero also pointed out that owning a unique data asset on your own site allows you to run legitimate digital PR campaigns that earn real coverage, rather than paying vendors for forced insertions.
Focus your content budget on:
Original data studies and industry benchmarks.
Free interactive tools and calculators.
Multimodal assets like infographics and comparison charts that AI models can easily parse.
The bottom line is that you should strive to create assets that no competitor can copy.
Rely on founder-led PR and real relationships
Spamming out generic cold email templates for link exchanges doesn’t build trust. Most of it never even reaches a human being.




Irina Maltseva recommends shifting entirely to relationship-based marketing. You build true entity association by getting your founders and subject matter experts out into the market. This looks like:
Securing appearances on industry podcasts.
Co-marketing with non-competing SaaS companies that share your audience.
Earning mentions in private communities, newsletters, and dark social channels.
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Links are ultimately the result of a smart marketing strategy
Traditional link building agencies are struggling because the market no longer rewards raw link volume as a measure of success.
SEO teams need to abandon the tired publisher database model that forces links into irrelevant guest articles to hit a monthly quota.
If your brand is absent from the conversations that shape your category, no number of forced backlinks or brand mentions will fix the problem.
The best links don’t come from rows of a spreadsheet that need to be manually reviewed and approved. They’re the natural result of a good marketing strategy.

High-DR links, paid mentions, and link exchanges can look authoritative without giving AI systems enough credibility to recommend your brand.

Why the traditional link building model no longer works for AI search

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-to-run-ChatGPT-ads-A-step-by-step-guide-from-early-campaigns.png" class="attachment-large size-large wp-post-image" alt="How to run ChatGPT ads- A step-by-step guide from early campaigns" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-to-run-ChatGPT-ads-A-step-by-step-guide-from-early-campaigns.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-run-ChatGPT-ads-A-step-by-step-guide-from-early-campaigns-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-run-ChatGPT-ads-A-step-by-step-guide-from-early-campaigns-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-to-run-ChatGPT-ads-A-step-by-step-guide-from-early-campaigns-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>ChatGPT Ads work differently from other ad platforms. Here’s what early campaigns reveal about CPCs, targeting, measurement, and performance.

What could become one of the most important ad platforms of the next decade is live, and most advertisers still haven’t run a single campaign on it.
OpenAI’s self-serve ad platform opened to everyone in May 2026.
Advertisers can target ChatGPT user conversations that are relevant to their products or services and promote their brand at the very moment of interest, similar to Google Search ads.
This guide gives step-by-step instructions for launching your first ChatGPT Ads campaign, plus what we’ve learned spending our own and our clients’ money on the platform.
We won’t pretend to be ChatGPT Ads experts yet because the platform is simply too new and constantly evolving for anyone to accurately claim expertise.
Note: OpenAI frequently releases updates to the platform. This guide is accurate as of the time of writing.



Who can you target with ChatGPT Ads?
Your ads can only serve to users OpenAI believes are 18 or older, on the Free and Go tiers (including logged-out sessions).
You’ll have a hard time reaching your target audience if they’re primarily people who are paying for higher tiers of access to ChatGPT.
But if you’re looking for people who are using the tool cheaply or for free, ads could be a good fit.
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How much do ChatGPT Ads cost?
We’re seeing average CPCs in the $2-$5 range across industries.
If you set a max CPC lower than $3, the platform will tell you that your ad may not deliver. This appears to be a hard-coded threshold, not a dynamic assessment of competition or the strength of your creative and targeting.








Step 1: Confirm you’re eligible
Types of businesses allowed to advertise in ChatGPT



OpenAI restricts advertising in categories including adult content, alcohol, tobacco, financial services, gambling, and more. Read OpenAI’s ad policies to confirm your eligibility.
Some of the policies are self-contradictory. 
For example, the policy page says “ads for legal advice, representation, or legal services offered to individuals or businesses are not permitted,” but the changelog says that some legal ads are allowed. Ads for lawyers have been running since at least May 2026.
Minimum budget for ChatGPT Ads



You can run ads with a daily budget as low as $25, a far cry from the $200,000 minimum commitments required during the pilot phase.




What countries can you target?



You can target the United States, Australia, Canada, Japan, New Zealand, South Korea, and the United Kingdom, with more countries likely coming soon.
Step 2: Set up your ad account
Collect this information before you start:
Legal business name.
Business Tax ID (e.g., EIN).
Payment method (credit/debit card).
Favicon.
Create your account at ads.openai.com.
OpenAI says that agencies should not create accounts on behalf of clients. Advertisers can add agencies as users to ad accounts. OpenAI does not yet have an equivalent to Google Ads Manager Accounts or Meta Business Managers.
A single user can access multiple ChatGPT Ads accounts, but we’re not aware of a way for one user to create multiple accounts.
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Step 3: Structure your campaigns
You’ll instantly recognize the campaign structure options if you’ve used other major ad platforms such as Google or Meta Ads.
The structure is: Campaign > Ad group > Ad.




Campaign

Type (Standard or product feed)
Objective (Reach, Clicks, or Conversions)
Locations to target and/or exclude (country, region, DMA, or postal code)
Custom audiences to target and/or exclude (first-party data upload)
Budget (daily or total)
Conversion event (optional)
Start date
End date (optional)





Ad group

Bid
Default Ad Destination URL
Context hints (more on this below)





Ad

Destination URL
Headline (50-character max, can be truncated)
Description (100-character max, can be truncated)
Image (PNG or JPG, square, at least 256 x 256 px)




Bidding strategies



You can choose to bid for Clicks, Reach, or Conversions.
Most advertisers will start with “Clicks.” You set a maximum bid, similar to Google’s Manual CPC bidding, and you’ll be charged per click.
If you’re trying to maximize the number of people who see your ads, you can choose “Reach,” and you’ll be charged per 1,000 impressions (CPM).
If you have set up conversion tracking using OpenAI’s pixel, you can choose to optimize towards conversions. You will still be charged per click, and can set a bid cap.
How the auction works



OpenAI uses a “relevance-weighted, second-price auction to select among eligible ads.” 
This works similarly to Google’s Ad Rank, which incorporates landing page relevance, ad quality, and bids to determine which ads win auctions.
There have also been reports of multiple ads serving at a single time.
Step 4: Choose your targeting (there are no keywords)
Advertisers coming from Google or Meta to ChatGPT Ads will have some adjustments to make when they think about targeting.
There are no keywords, no demographics, no in-market audiences.
Other than geography, first-party data, and the actual wording of your ad and landing page, the primary lever to control your ad targeting is called “context hints” and is at the ad group level.
You’ll see a freeform box where you can write whatever you want.
OpenAI gives this guidance:
“Describe the conversations, topics, or keywords where your products or services may be relevant; these hints guide matching but aren’t exact-match targeting rules.”
You can leave this field blank, dump keywords in it, or write a carefully crafted prompt as you might enter into a conversation with ChatGPT.
This feature is ripe for testing.
Case study: A list of keywords vs. a list of complete questions



We created a campaign with two ad groups.
We added a list of keywords to the “Keywords” ad group similar to what you might find in a Google Ads Search campaign.
We added a list of complete questions that people might ask ChatGPT to the “Conversational” ad group.
We created an ad in each ad group with the exact same content.




In this particular test, ChatGPT showed the ad from the “Keywords” ad group far more often and it had a slightly higher CTR and lower Avg. CPC than the “Conversational” ad group.
Example of keywords

Lumber yard near me
Buy 2x4s
Cedar planks for decking
Example of a list of questions

Where is the closest lumberyard?
What is the most cost-effective material to use for decking?
How long do cedar decks last?
Example of a conversational context hint

I want to target DIY homeowners in the San Antonio, Texas area who are looking for a source for high-quality cedar planks to use for decking projects.
First-party data



You can target or exclude audiences built from your first-party data (customer emails and phone numbers), but the minimum of 25,000 matched users limits this feature for most SMBs.
Step 5: Create ads
Ads in ChatGPT appear at the bottom of a conversation with a label saying “Sponsored.”
There are two ad formats: static and product.
Static ads
Here is the anatomy of a static ad:




Product ads
Advertisers can submit a product feed to ChatGPT and serve ads using product data from that feed.
Initially, these ads looked identical to static ads, but OpenAI announced on July 24 that it’s updating the product card format to feature prices and star ratings.
Here is the anatomy of a product ad:




Here are instructions for submitting a product feed to ChatGPT.
The process is clunky and time-consuming at the moment, and we’ve run into multiple glitches. Expect OpenAI to improve this over time.
Step 6: Set up measurement before you launch
OpenAI has a pixel that works similarly to the Google Ads and Meta Ads pixels.
You can install the base code directly on your website and fire events based on specific actions, such as button clicks and page loads. You can also set dynamic values to track metrics such as order revenue.
OpenAI reports conversions in your ad account at the campaign, ad group, and ad level, and you can optimize towards conversions.
We strongly recommend adding UTM parameters to your ad URLs to track ChatGPT Ads traffic in third-party systems, including GA4.
Some third-party platforms, such as the call-tracking software CTM, integrate directly with ChatGPT Ads.
In addition to conversions, ChatGPT reports impressions, clicks, spend, CTR, Avg. CPC, and Avg. CPM.
Step 7: How to optimize with limited data
The key levers for optimizing ChatGPT Ads are the ads themselves and how you structure your campaigns and ad groups.
There is very little data available to you about what is actually driving your performance.
If you want to test how your ads perform in different geographic areas, you’ll have to create separate campaigns for each area because reporting can only be segmented by country, even though you can target more granular locations.
OpenAI matches ads using the current conversation and, for users who have ads personalization enabled, signals from their broader ChatGPT activity. None of that information is shared with the advertiser.
You cannot see any conversation data or even the keywords or conversation themes that may have triggered your ad.
Using ChatGPT Ads feels like the early days of Google’s Performance Max campaigns, where we largely had to trust that the system was showing ads to relevant people in relevant situations.
Case study: How engaged is ChatGPT Ads traffic?



Here is data from GA4 covering around 1,500 users who reached the same website via Google Ads versus ChatGPT Ads.
Average engagement time per active user

Google Ads: 41 seconds
ChatGPT Ads: 17 seconds
Engaged sessions per active user

Google Ads: 1.13
ChatGPT Ads: 0.88
Conversion rate:

Google Ads: 3.71%
ChatGPT Ads: 0.21%
In this test, users coming via Google Ads were more engaged and converted at a significantly higher rate than users coming from ChatGPT Ads.
That said, we were able to reach people using ChatGPT Ads who weren’t necessarily searching for a solution on Google. While benchmarking against other channels is helpful, you should judge each channel by what it costs you to acquire a customer through it.
Where ChatGPT Ads fits in your channel mix
Because you’re serving ads to people while they’re researching and having a conversation with the LLM, ChatGPT Ads are more like Google Search ads than Facebook or Instagram ads.
If you are already getting good organic traffic to your website from ChatGPT, that’s a signal that ChatGPT Ads may be well worth testing.
That said, OpenAI makes it clear that running ads does not impact whether your brand will be mentioned organically, and vice versa.
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Should you test ChatGPT Ads?
Most advertisers should test ChatGPT Ads.
The cost of testing is relatively low and will only rise as the platform matures and more advertisers enter.
You should use in-platform and third-party tracking to understand how traffic converts.
Benchmark your ChatGPT Ads results against your Google search results, while factoring in that this is still a new platform and is constantly changing.
Because the platform is too new to have established best practices, be prepared to invest time and thought in testing a variety of approaches and creatives to find what works best for you.

ChatGPT Ads work differently from other ad platforms. Here’s what early campaigns reveal about CPCs, targeting, measurement, and performance.

How to run ChatGPT ads: A step-by-step guide from early campaigns

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey.png" class="attachment-large size-large wp-post-image" alt="How customers build confidence across the search journey" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>AI, Google, Reddit, YouTube, and brand sites help resolve different kinds of uncertainty. Here's what that means for your search strategy.

<div><img width="1920" height="1080" src="https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey.png" class="attachment-large size-large wp-post-image" alt="How customers build confidence across the search journey" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey.png 1920w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/How-customers-build-confidence-across-the-search-journey-1200x675.png 1200w" sizes="(max-width: 1920px) 100vw, 1920px" /></div>
<p class="wp-block-paragraph">Every week, there&#8217;s another headline about the future of search.</p>



<p class="wp-block-paragraph">Google is losing ground. ChatGPT is growing. Reddit is becoming the place people trust. TikTok is replacing Google for younger audiences. YouTube has become a search engine in its own right.</p>



<p class="wp-block-paragraph">From the outside, search looks increasingly fragmented. People are discovering brands in more places than ever before.</p>



<p class="wp-block-paragraph">We&#8217;re looking at the consequences through the wrong lens.</p>



<p class="wp-block-paragraph">Our latest SearchPulse research at Reflect Digital suggests the real shift is about confidence. <em>(</em><strong><em>Disclosure: </em></strong><em>I’m Reflect Digital’s founder and CEO.)</em>



<p class="wp-block-paragraph">The psychological reasons people search haven&#8217;t fundamentally changed. People still want to understand. They still want reassurance. They still want to fit in, avoid making mistakes, and feel confident they&#8217;re making the right decision.</p>



<p class="wp-block-paragraph">What&#8217;s changing is where they go to build that confidence.</p>



<h2 id="h-the-data-only-looks-contradictory-until-you-think-about-behavior" class="wp-block-heading">The data only looks contradictory until you think about behavior</h2>



<p class="wp-block-paragraph">At first glance, the research appears contradictory.</p>



<p class="wp-block-paragraph">We found that 56% of people now regularly use AI search, yet 57% still fall into our Traditional Searcher segment. How can both be true?</p>



<p class="wp-block-paragraph">People are expanding their search journey across more platforms. The clearest evidence comes from our behavioral segmentation. </p>



<p class="wp-block-paragraph">The fastest-growing audience is the &#8220;multi-platform searcher&#8221; — people who naturally move between search engines, AI, communities, creators, and brand websites before making a decision. They&#8217;re assembling confidence from multiple places.</p>


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<h2 id="h-search-behavior-doesn-t-follow-the-funnel" class="wp-block-heading">Search behavior doesn&#8217;t follow the funnel</h2>



<p class="wp-block-paragraph">Marketing has spent years trying to understand customer journeys. We&#8217;ve built funnels, embraced the messy middle, and mapped touchpoints. All of that still has value.</p>



<p class="wp-block-paragraph">Traditional journey mapping misses something important. People don&#8217;t consciously move from awareness to consideration to purchase, nor do they think, &#8220;Now I&#8217;m going to Google,&#8221; or &#8220;Now I&#8217;m entering the evaluation stage.&#8221;</p>



<p class="wp-block-paragraph">They simply keep resolving uncertainty until they feel confident enough to act. Every interaction fills a different confidence gap. That subtle shift changes how we should think about modern search.</p>



<h2 id="h-different-platforms-serve-different-needs" class="wp-block-heading">Different platforms serve different needs</h2>



<p class="wp-block-paragraph">We identified four consistent psychological drivers behind search behavior:</p>



<ul class="wp-block-list">
<li><strong>Fact finding</strong>: &#8220;I need accurate, trustworthy information.&#8221;</li>



<li><strong>Crowdsourcing</strong>: &#8220;What do people like me think?&#8221;</li>



<li><strong>Taste tuning</strong>: &#8220;Does this feel right for me?&#8221;</li>



<li><strong>Autopilot</strong>: &#8220;Help me get this done.&#8221;</li>
</ul>



<p class="wp-block-paragraph">Those motivations haven&#8217;t changed because AI arrived. They&#8217;ve always existed. What&#8217;s changing is how different platforms satisfy them.</p>



<p class="wp-block-paragraph">YouTube isn&#8217;t successful simply because people like watching videos. Watching something removes uncertainty in a way that text often can&#8217;t.</p>



<p class="wp-block-paragraph">Reddit isn&#8217;t valuable because it&#8217;s another search engine. Communities provide reassurance through shared experience.</p>



<p class="wp-block-paragraph">AI excels at helping people understand a topic quickly. Google still plays an important role in verification. Brand websites provide reassurance that you&#8217;re buying from the right company.</p>



<p class="wp-block-paragraph">Platforms are increasingly specializing in different confidence needs.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/search-users-outsource-decisions-ai-479505">Delegation search: Why users outsource decisions to AI</a></em></strong>



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<h2 id="h-the-challenge-is-understanding-confidence" class="wp-block-heading">The challenge is understanding confidence</h2>



<p class="wp-block-paragraph">Most marketing teams are still organized around channels:</p>



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



<li>Paid search.</li>



<li>Social.</li>



<li>PR.</li>



<li>Content.</li>
</ul>



<p class="wp-block-paragraph">Customers don&#8217;t think like that. They move between confidence signals until they&#8217;re ready to make a decision.</p>



<p class="wp-block-paragraph">The challenge for marketers isn&#8217;t deciding which channel matters most. It&#8217;s understanding which confidence gaps their audience still has and making sure they help close them.</p>



<h2 id="h-how-to-identify-and-close-confidence-gaps" class="wp-block-heading">How to identify and close confidence gaps</h2>



<p class="wp-block-paragraph">Campaign planning should start with confidence.</p>



<h3 id="h-1-what-confidence-does-this-audience-need-before-they-ll-buy" class="wp-block-heading">1. What confidence does this audience need before they&#8217;ll buy?</h3>



<p class="wp-block-paragraph">The answer will vary. A first-time customer needs different reassurance than an existing one. A CFO needs different proof than a marketing manager.</p>



<p class="wp-block-paragraph">Someone making a $20 purchase has different needs than someone choosing a strategic B2B partner.</p>



<h3 id="h-2-what-confidence-assets-do-we-already-have" class="wp-block-heading">2. What confidence assets do we already have?</h3>



<p class="wp-block-paragraph">These pieces of content serve as evidence that reduces uncertainty.</p>



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



<li>Case studies.</li>



<li>Original research.</li>



<li>Expert opinion.</li>



<li>Product demonstrations.</li>



<li>Industry recognition.</li>



<li>Community recommendations.</li>



<li>Founder expertise.</li>
</ul>



<p class="wp-block-paragraph">Each one answers a different confidence gap.</p>



<h3 id="h-3-where-will-people-naturally-discover-those-confidence-assets" class="wp-block-heading">3. Where will people naturally discover those confidence assets?</h3>



<p class="wp-block-paragraph">This is where platforms come back into the conversation. Different audiences naturally look in different places for different types of reassurance.</p>



<p class="wp-block-paragraph">The same Trustpilot review can influence someone through a Google search result, an AI answer, your own website, or a direct visit to Trustpilot.</p>



<p class="wp-block-paragraph">The confidence asset stays the same. The discovery point changes.</p>



<h3 id="h-4-how-will-we-know-we-re-building-confidence" class="wp-block-heading">4. How will we know we&#8217;re building confidence?</h3>



<p class="wp-block-paragraph">This is where marketing needs to evolve. Some confidence is directly observable:</p>



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



<li>Leads.</li>



<li>Sales.</li>



<li>Conversions.</li>
</ul>



<p class="wp-block-paragraph">Increasingly, some confidence is built in places we&#8217;ll never fully attribute.</p>



<p class="wp-block-paragraph">Someone reads Reddit before searching your brand. They watch a YouTube review. They ask ChatGPT to compare suppliers. They see your research cited by an AI assistant.</p>



<p class="wp-block-paragraph">Those moments influence decisions, even if they never appear in your analytics platform. They still matter, which means we need to stop judging every confidence-building activity by performance marketing metrics alone.</p>



<p class="wp-block-paragraph">Some assets exist to generate clicks. Others exist to reduce uncertainty. Both contribute to growth.</p>



<p class="wp-block-paragraph"><strong><em>Dig deeper: <a href="https://searchengineland.com/search-everywhere-new-seo-reality-472134">Why ‘search everywhere’ is the new reality for SEO</a></em></strong>


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<h2 id="h-the-future-of-search-isn-t-just-about-visibility" class="wp-block-heading">The future of search isn&#8217;t just about visibility</h2>



<p class="wp-block-paragraph">As AI and zero-click experiences continue to grow, marketers will lose visibility over parts of the customer journey. We can still understand <strong>how</strong> confidence is built.</p>



<p class="wp-block-paragraph">That means shifting our thinking from:</p>



<ul class="wp-block-list">
<li>&#8220;Which channel drove the conversion?&#8221;</li>
</ul>



<p class="wp-block-paragraph">to:</p>



<ul class="wp-block-list">
<li>&#8220;Which confidence gaps did our marketing help close?&#8221;</li>
</ul>



<p class="wp-block-paragraph">Search is fragmenting across platforms, but the questions people are trying to answer remain the same. They&#8217;re assembling those answers from more places than ever before.</p>



<p class="wp-block-paragraph">The brands that succeed will understand how confidence is built and make sure they&#8217;re present wherever their customers need it.</p>

Every week, there’s another headline about the future of search.
Google is losing ground. ChatGPT is growing. Reddit is becoming the place people trust. TikTok is replacing Google for younger audiences. YouTube has become a search engine in its own right.
From the outside, search looks increasingly fragmented. People are discovering brands in more places than ever before.
We’re looking at the consequences through the wrong lens.
Our latest SearchPulse research at Reflect Digital suggests the real shift is about confidence. (Disclosure: I’m Reflect Digital’s founder and CEO.)



The psychological reasons people search haven’t fundamentally changed. People still want to understand. They still want reassurance. They still want to fit in, avoid making mistakes, and feel confident they’re making the right decision.
What’s changing is where they go to build that confidence.
The data only looks contradictory until you think about behavior
At first glance, the research appears contradictory.
We found that 56% of people now regularly use AI search, yet 57% still fall into our Traditional Searcher segment. How can both be true?
People are expanding their search journey across more platforms. The clearest evidence comes from our behavioral segmentation. 
The fastest-growing audience is the “multi-platform searcher” — people who naturally move between search engines, AI, communities, creators, and brand websites before making a decision. They’re assembling confidence from multiple places.
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Search behavior doesn’t follow the funnel
Marketing has spent years trying to understand customer journeys. We’ve built funnels, embraced the messy middle, and mapped touchpoints. All of that still has value.
Traditional journey mapping misses something important. People don’t consciously move from awareness to consideration to purchase, nor do they think, “Now I’m going to Google,” or “Now I’m entering the evaluation stage.”
They simply keep resolving uncertainty until they feel confident enough to act. Every interaction fills a different confidence gap. That subtle shift changes how we should think about modern search.
Different platforms serve different needs
We identified four consistent psychological drivers behind search behavior:
Fact finding: “I need accurate, trustworthy information.”
Crowdsourcing: “What do people like me think?”
Taste tuning: “Does this feel right for me?”
Autopilot: “Help me get this done.”
Those motivations haven’t changed because AI arrived. They’ve always existed. What’s changing is how different platforms satisfy them.
YouTube isn’t successful simply because people like watching videos. Watching something removes uncertainty in a way that text often can’t.
Reddit isn’t valuable because it’s another search engine. Communities provide reassurance through shared experience.
AI excels at helping people understand a topic quickly. Google still plays an important role in verification. Brand websites provide reassurance that you’re buying from the right company.
Platforms are increasingly specializing in different confidence needs.
Dig deeper: Delegation search: Why users outsource decisions to AI




	
	
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The challenge is understanding confidence
Most marketing teams are still organized around channels:
SEO.
Paid search.
Social.
PR.
Content.
Customers don’t think like that. They move between confidence signals until they’re ready to make a decision.
The challenge for marketers isn’t deciding which channel matters most. It’s understanding which confidence gaps their audience still has and making sure they help close them.
How to identify and close confidence gaps
Campaign planning should start with confidence.
1. What confidence does this audience need before they’ll buy?
The answer will vary. A first-time customer needs different reassurance than an existing one. A CFO needs different proof than a marketing manager.
Someone making a $20 purchase has different needs than someone choosing a strategic B2B partner.
2. What confidence assets do we already have?
These pieces of content serve as evidence that reduces uncertainty.
Customer reviews.
Case studies.
Original research.
Expert opinion.
Product demonstrations.
Industry recognition.
Community recommendations.
Founder expertise.
Each one answers a different confidence gap.
3. Where will people naturally discover those confidence assets?
This is where platforms come back into the conversation. Different audiences naturally look in different places for different types of reassurance.
The same Trustpilot review can influence someone through a Google search result, an AI answer, your own website, or a direct visit to Trustpilot.
The confidence asset stays the same. The discovery point changes.
4. How will we know we’re building confidence?
This is where marketing needs to evolve. Some confidence is directly observable:
Traffic.
Leads.
Sales.
Conversions.
Increasingly, some confidence is built in places we’ll never fully attribute.
Someone reads Reddit before searching your brand. They watch a YouTube review. They ask ChatGPT to compare suppliers. They see your research cited by an AI assistant.
Those moments influence decisions, even if they never appear in your analytics platform. They still matter, which means we need to stop judging every confidence-building activity by performance marketing metrics alone.
Some assets exist to generate clicks. Others exist to reduce uncertainty. Both contribute to growth.
Dig deeper: Why ‘search everywhere’ is the new reality for SEO



  
before your competitors.
      
Start your free trial
    
The future of search isn’t just about visibility
As AI and zero-click experiences continue to grow, marketers will lose visibility over parts of the customer journey. We can still understand how confidence is built.
That means shifting our thinking from:
“Which channel drove the conversion?”
to:
“Which confidence gaps did our marketing help close?”
Search is fragmenting across platforms, but the questions people are trying to answer remain the same. They’re assembling those answers from more places than ever before.
The brands that succeed will understand how confidence is built and make sure they’re present wherever their customers need it.

AI, Google, Reddit, YouTube, and brand sites help resolve different kinds of uncertainty. Here's what that means for your search strategy.

How customers build confidence across the search journey

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>ChatGPT ads now allows for conversion-optimized product feed campaigns, expanded measurement integrations and carousel ads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/ChatGPT-Ads-oCPC-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">OpenAI is expanding ChatGPT Ads&#8217; conversion capabilities with new campaign types, broader measurement integrations and enhanced optimization tools, while preparing to launch the platform in two new markets.</p>



<p class="wp-block-paragraph">The latest updates are aimed at helping advertisers improve conversion tracking, automate campaign creation and scale ecommerce advertising.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. OpenAI has rolled out several new features centered on conversion optimization.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="722" height="1520" src="https://searchengineland.com/wp-content/seloads/2026/08/OpenAI-updates.png" alt="" class="wp-image-484495"/></figure>



<p class="wp-block-paragraph">Product feed campaigns now support <strong>conversion-optimized cost-per-click (oCPC)</strong> campaigns in beta, allowing advertisers to optimize toward conversions while continuing to pay per click. Advertisers can also clone existing CPC campaigns into oCPC campaigns or create them in bulk, simplifying campaign migration.</p>



<p class="wp-block-paragraph">The platform is also introducing dynamic URL parameters, enabling advertisers to automatically append campaign, ad group and ad IDs to landing page URLs for easier attribution and analytics.</p>


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<p class="wp-block-paragraph"><strong>Measurement gets a boost</strong>. OpenAI continues to expand its measurement ecosystem with new integrations.</p>



<p class="wp-block-paragraph">Advertisers can now connect Triple Whale to measure ChatGPT Ads performance alongside other marketing channels, while Sonar Optimize can send stronger conversion signals back to OpenAI. Hightouch now supports sending conversion events directly into ChatGPT Ads for measurement and optimization.</p>



<p class="wp-block-paragraph">Ads Manager has also gained more detailed Pixel validation diagnostics, helping advertisers identify why conversion events were rejected and providing recommendations for fixing implementation issues.</p>



<p class="wp-block-paragraph">Meanwhile, Automatic Advanced Matching (AAM) will become the default for all new web pixels immediately and will automatically be enabled for existing pixels on August 17, unless advertisers choose to opt out beforehand.</p>



<p class="wp-block-paragraph"><strong>New markets and ad formats</strong>. OpenAI says ChatGPT Ads will launch in Brazil and Mexico in the coming week, expanding advertiser access in Latin America.</p>



<p class="wp-block-paragraph">The company has also begun testing a multi-product carousel format for product feed campaigns, allowing multiple products to appear within a single ad unit.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The updates givies advertisers better tools to optimize for conversions, improve measurement, and scale campaigns more efficiently. New integrations with platforms like Triple Whale and Hightouch, enhanced pixel diagnostics, and Automatic Advanced Matching should lead to more accurate attribution and stronger optimization signals.</p>



<p class="wp-block-paragraph"><strong>Bottom line:</strong> OpenAI is doubling down on performance advertising with expanded conversion optimization, richer measurement integrations, new ecommerce formats and continued international expansion for ChatGPT Ads.</p>


OpenAI is expanding ChatGPT Ads’ conversion capabilities with new campaign types, broader measurement integrations and enhanced optimization tools, while preparing to launch the platform in two new markets.
The latest updates are aimed at helping advertisers improve conversion tracking, automate campaign creation and scale ecommerce advertising.
What’s happening. OpenAI has rolled out several new features centered on conversion optimization.




Product feed campaigns now support conversion-optimized cost-per-click (oCPC) campaigns in beta, allowing advertisers to optimize toward conversions while continuing to pay per click. Advertisers can also clone existing CPC campaigns into oCPC campaigns or create them in bulk, simplifying campaign migration.
The platform is also introducing dynamic URL parameters, enabling advertisers to automatically append campaign, ad group and ad IDs to landing page URLs for easier attribution and analytics.
AI recommends.
      
See your AI visibility
    
Measurement gets a boost. OpenAI continues to expand its measurement ecosystem with new integrations.
Advertisers can now connect Triple Whale to measure ChatGPT Ads performance alongside other marketing channels, while Sonar Optimize can send stronger conversion signals back to OpenAI. Hightouch now supports sending conversion events directly into ChatGPT Ads for measurement and optimization.
Ads Manager has also gained more detailed Pixel validation diagnostics, helping advertisers identify why conversion events were rejected and providing recommendations for fixing implementation issues.
Meanwhile, Automatic Advanced Matching (AAM) will become the default for all new web pixels immediately and will automatically be enabled for existing pixels on August 17, unless advertisers choose to opt out beforehand.
New markets and ad formats. OpenAI says ChatGPT Ads will launch in Brazil and Mexico in the coming week, expanding advertiser access in Latin America.
The company has also begun testing a multi-product carousel format for product feed campaigns, allowing multiple products to appear within a single ad unit.
Why we care. The updates givies advertisers better tools to optimize for conversions, improve measurement, and scale campaigns more efficiently. New integrations with platforms like Triple Whale and Hightouch, enhanced pixel diagnostics, and Automatic Advanced Matching should lead to more accurate attribution and stronger optimization signals.
Bottom line: OpenAI is doubling down on performance advertising with expanded conversion optimization, richer measurement integrations, new ecommerce formats and continued international expansion for ChatGPT Ads.

ChatGPT ads now allows for conversion-optimized product feed campaigns, expanded measurement integrations and carousel ads

ChatGPT Ads rolls out oCPC campaigns, AAM and product carousels

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Google is introducing new qualification criteria based on trust signals, verification and account history.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Google-Limited-Ad-serving-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Google is expanding its Limited Ad Serving policy to cover all Google Ads, giving qualified advertisers unrestricted impressions while limiting ad delivery for accounts it considers higher risk.</p>



<p class="wp-block-paragraph">The updated policy begins rolling out in August and will be implemented gradually through 2028.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s changing</strong>. Under the revised policy, Google will limit impressions—not disapprove ads—for advertisers it determines are unqualified in certain ad-serving scenarios that are more likely to result in poor user experiences.</p>



<p class="wp-block-paragraph">Google says qualification is based on a range of signals, including account maturity, advertiser verification status, policy compliance history, user reports, ad format usage, industry and other account attributes. Advertisers with strong trust signals won&#8217;t be affected by impression limits.</p>



<p class="wp-block-paragraph">Accounts that are limited will receive an in-account notification and can appeal the decision through Google&#8217;s Limited Ad Serving Appeals Form.</p>



<p class="wp-block-paragraph"><strong>What advertisers should do</strong>. Google is encouraging advertisers to build trust by completing advertiser verification, complying with advertising policies and maintaining clear branding across ads and landing pages.</p>



<p class="wp-block-paragraph">For Search campaigns, Google also recommends avoiding generic ad copy, clearly identifying your business and, where available, pinning your domain to the first headline position to reinforce brand identity.</p>



<p class="wp-block-paragraph">On YouTube, Gmail, Discover and the Play Store, advertisers are advised to continue building campaigns that generate positive user engagement while Google evaluates account quality.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. The update formalises how Google determines which advertisers can serve ads without restrictions. Rather than focusing solely on policy violations, Google is placing greater emphasis on trust, account history and user experience when deciding how broadly ads can be shown.</p>



<p class="wp-block-paragraph"><strong>Bottom line.</strong> <a href="https://support.google.com/adspolicy/answer/17344822?hl=en">Google&#8217;s expanded Limited Ad Serving policy</a> gives trusted advertisers unrestricted delivery while encouraging newer or less-established advertisers to build credibility through verification, policy compliance and consistent branding before gaining full access to inventory.</p>


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Google is expanding its Limited Ad Serving policy to cover all Google Ads, giving qualified advertisers unrestricted impressions while limiting ad delivery for accounts it considers higher risk.
The updated policy begins rolling out in August and will be implemented gradually through 2028.
What’s changing. Under the revised policy, Google will limit impressions—not disapprove ads—for advertisers it determines are unqualified in certain ad-serving scenarios that are more likely to result in poor user experiences.
Google says qualification is based on a range of signals, including account maturity, advertiser verification status, policy compliance history, user reports, ad format usage, industry and other account attributes. Advertisers with strong trust signals won’t be affected by impression limits.
Accounts that are limited will receive an in-account notification and can appeal the decision through Google’s Limited Ad Serving Appeals Form.
What advertisers should do. Google is encouraging advertisers to build trust by completing advertiser verification, complying with advertising policies and maintaining clear branding across ads and landing pages.
For Search campaigns, Google also recommends avoiding generic ad copy, clearly identifying your business and, where available, pinning your domain to the first headline position to reinforce brand identity.
On YouTube, Gmail, Discover and the Play Store, advertisers are advised to continue building campaigns that generate positive user engagement while Google evaluates account quality.
Why we care. The update formalises how Google determines which advertisers can serve ads without restrictions. Rather than focusing solely on policy violations, Google is placing greater emphasis on trust, account history and user experience when deciding how broadly ads can be shown.
Bottom line. Google’s expanded Limited Ad Serving policy gives trusted advertisers unrestricted delivery while encouraging newer or less-established advertisers to build credibility through verification, policy compliance and consistent branding before gaining full access to inventory.
your competitors win.
      
Analyze your competitors

Google is introducing new qualification criteria based on trust signals, verification and account history.

Google expands Limited Ad Serving policy across all Ads

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>Microsoft's now lets advertisers appeal multiple disapproved text &#038; image assets at once, reducing time spent resolving policy issues.

<div><img width="1672" height="941" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png" class="attachment-large size-large wp-post-image" alt="" decoding="async" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal.png 1672w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-768x432.png 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1536x864.png 1536w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-appeal-1200x675.png 1200w" sizes="(max-width: 1672px) 100vw, 1672px" /></div>
<p class="wp-block-paragraph">Microsoft Advertising launched bulk editing and appeals for disapproved assets, making it faster for advertisers to resolve policy issues without updating assets one at a time.</p>



<p class="wp-block-paragraph">The feature is now available in all accounts and supports both text and image assets.</p>



<p class="wp-block-paragraph"><strong>What&#8217;s happening</strong>. Announced by Microsoft Ads Product Liaison Navah Hopkins, the new tool lets advertisers bulk edit or appeal disapproved assets directly within Microsoft Advertising.</p>



<figure class="wp-block-image size-full"><img decoding="async" width="2048" height="961" src="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit.jpeg" alt="" class="wp-image-484484" srcset="https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit.jpeg 2048w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit-768x360.jpeg 768w, https://searchengineland.com/wp-content/seloads/2026/08/Microsoft-bulk-edit-1536x721.jpeg 1536w" sizes="(max-width: 2048px) 100vw, 2048px" /></figure>



<p class="wp-block-paragraph">There are a few important limitations. Because Microsoft reviews assets individually, appeals must be submitted for all disapproved assets within an ad. This allows approved assets to continue serving during the review process, provided the ad&#8217;s final URL remains approved.</p>



<p class="wp-block-paragraph">For image assets, advertisers can&#8217;t simply edit an existing creative—they&#8217;ll need to upload a replacement image. In some cases, Microsoft also recommends requesting a policy exception instead of modifying the asset. Advertisers can submit up to 5,000 ad exception requests.</p>



<p class="wp-block-paragraph"><strong>Why we care</strong>. Bulk editing removes one of the more time-consuming parts of campaign management, especially for advertisers managing large numbers of assets. Instead of reviewing and appealing each disapproval individually, teams can resolve policy issues much more efficiently.</p>



<p class="wp-block-paragraph"><strong>The bigger picture</strong>. Microsoft continues to invest in workflow improvements alongside new AI-powered campaign features. While not a headline-grabbing launch, updates like this reduce operational friction and make it easier for advertisers and agencies to manage campaigns at scale.</p>



<p class="wp-block-paragraph"><strong>Bottom line</strong>. <a href="https://www.linkedin.com/posts/navahhopkins_thrilled-to-share-that-microsoft-advertising-share-7491122041186566144-s7A4/">Microsoft Advertising&#8217;s new bulk edit and appeal tool</a> simplifies policy management by allowing advertisers to update or challenge multiple disapproved assets at once.</p>


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Microsoft Advertising launched bulk editing and appeals for disapproved assets, making it faster for advertisers to resolve policy issues without updating assets one at a time.
The feature is now available in all accounts and supports both text and image assets.
What’s happening. Announced by Microsoft Ads Product Liaison Navah Hopkins, the new tool lets advertisers bulk edit or appeal disapproved assets directly within Microsoft Advertising.




There are a few important limitations. Because Microsoft reviews assets individually, appeals must be submitted for all disapproved assets within an ad. This allows approved assets to continue serving during the review process, provided the ad’s final URL remains approved.
For image assets, advertisers can’t simply edit an existing creative—they’ll need to upload a replacement image. In some cases, Microsoft also recommends requesting a policy exception instead of modifying the asset. Advertisers can submit up to 5,000 ad exception requests.
Why we care. Bulk editing removes one of the more time-consuming parts of campaign management, especially for advertisers managing large numbers of assets. Instead of reviewing and appealing each disapproval individually, teams can resolve policy issues much more efficiently.
The bigger picture. Microsoft continues to invest in workflow improvements alongside new AI-powered campaign features. While not a headline-grabbing launch, updates like this reduce operational friction and make it easier for advertisers and agencies to manage campaigns at scale.
Bottom line. Microsoft Advertising’s new bulk edit and appeal tool simplifies policy management by allowing advertisers to update or challenge multiple disapproved assets at once.
a customer you lose.
      
See who’s stealing your traffic

Microsoft's now lets advertisers appeal multiple disapproved text & image assets at once, reducing time spent resolving policy issues.

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