Google Ads appears to be testing an automatic assignment of New Customer Value within New Customer Acquisition (NCA) campaigns — and it’s doing so without advertisers’ explicit consent.
The change, first spotted by performance marketer Bilal Yasin, has led to unexpected reporting shifts and frustration among advertisers.
“Without any heads-up, and without it being in the change history, a new customer value has suddenly been applied to a customer,” Yasin wrote on LinkedIn. “It was set to 200 DKK… One thing is that Google has assigned a value, but another is that I can’t remove it again!”
Why we care. Advertisers rely on New Customer Value settings to determine how campaigns optimize toward acquiring new users. When Google sets those values automatically, it can distort revenue reporting and campaign efficiency metrics.
Yasin noted several issues:
Google doesn’t know the true lifetime value of a new customer.
Many conversions are still classified as “unknown,” further clouding data.
What they’re saying. Google Ads Liaison Ginny Marvin confirmed the behavior is part of an experiment.
“This guidance is part of an experiment aimed at helping advertisers use settings that will improve results—specifically, to increase new customer ratios,” Marvin wrote.
She added that when the New Customer Value is too low—or not set—it can hinder campaign optimization.
What’s next. Google says it plans to roll out new customer reporting for all purchase conversion campaigns “in the next couple of quarters.”
The bottom line. While Google frames the test as a way to improve campaign performance, advertisers are raising alarms over transparency — especially when automatic value assignments alter reported revenue without clear notice or control.
A website redesign is essential for remaining competitive, but for multi-location businesses, the risks are much higher. Stripping away the local relevance that drives traffic to location pages can cause rankings and online visibility to plummet.
Using localized content on location pages resulted in a 107% rankings lift, something businesses risk losing if a redesign hurts these pages.
To mitigate the risk of fallen local rankings and to get the most from your website redesign, you need to maintain good multi-location local SEO and take key steps for a successful redesign.
Prioritizing SEO during a location page redesign helps multi-location businesses stay competitive.
Technical SEO pre-redesign audit checklist
Before launching a new website redesign, it’s essential to perform a comprehensive audit to ensure that your SEO foundation is retained. Thorough auditing before launch can help prevent common mistakes and preserve your rankings.
Manage inventory: Document all business locations, Google Business Profile IDs, current URLs, organic rankings, and highest-converting queries.
Identify issues: Use a site crawler to uncover duplicate/thin content, poor Core Web Vitals, slow loading, mobile responsiveness, or accessibility gaps.
Conduct a technical crawl audit: Confirm crawl budget, indexing, updated sitemaps, and hreflang configuration on multinational sites.
Audit and enhance structured data: Ensure LocalBusiness schema is present and NAP is perfectly consistent. Validate canonical tags for duplicate prevention.
Expand structured data: Consider implementing review, FAQ, and service schema types for additional SEO coverage.
Set up robust tracking: Implement UTM tagging, conversion tracking, and phone call analytics to precisely measure local and national SEO performance
PageSpeed Insights can let you know how fast your website loads and indicate potential performance issues.
How to optimize site architecture and your URL strate
Once your pre-redesign audit is complete and you’ve identified areas for improvement, it’s time to shift focus to your site architecture for SEO. A solid foundation in site architecture ensures both search engines and users can navigate your website with ease.
Common structures include:
Subfolders (/locations/city)
Subdomains (city.brand.com)
Multisite frameworks
Dedicated microsites
Subfolders generally work best for centralizing authority and scalability, with a primary website that branches out into many pages, including one for each location.
Note that it’s crucial to maintain consistency with your URL structure. If the existing site already has a URL for each location within a subfolder structure, do not change it! Ensuring that the URL structure remains identical between the existing and new website design is essential for retaining your SEO value and preventing any loss in rankings.
Here are some other key considerations:
Canonical URLs: Identify canonical URLs that help mitigate the risk of duplicate content.
Sitemap strategy: Determine whether your site should implement an XML sitemap or an HTML sitemap, with XML sitemaps being more explicitly effective for site crawlers and SEO, while HTML sitemaps could help with user navigation.
URL templates: Use static URLs, they’re cleaner and more optimization-friendly design (e.g., example.com/services/dentistry/location/).
Location page content considerations
Technical SEO components are important, but so is content. When redesigning your website, it’s crucial to prioritize the content elements that impact the SEO performance of your location pages.
A successful redesign should seamlessly integrate these elements to preserve and boost your SEO efforts.
Unique H1 on each location page with city intent that targets a relevant keyword, such as “housekeeping services in [city]”
Full name, address, and phone number that’s consistent across all directory listings
Link to each location’s corresponding GBP page.
Business hours that are up-to-date and unique to each location, further aligning with directory information
Local phone number, preferably static to maintain consistency with NAP data
Service-specific content, including details about each of your offerings, with locally optimized keywords for each
Staff and team photos showing the people behind your business, potentially at each location
Local testimonials from satisfied customers, including review and schema markup for aggregate ratings
h1 optimized for location and main keyword with custom text and clear CTAs. Source
As you incorporate these essential content elements into your location page redesign, it’s critical to ensure each page is unique and tailored to its specific location.
Each location page should include a designated content block section where you can add customized details about that individual location. This will additionally help reduce duplicate content across your location pages.
Location page with h1 and copy optimization Source
Top design elements to consider for a multi-location website
Redesigning location pages can be challenging because it requires balancing brand consistency with the unique identity of each location. Achieving this balance involves the strategic use of design elements that appeal to both local audiences and the overarching brand.
Top design elements include:
Location-specific imagery: For brick-and-mortar locations, use high-quality images of the storefronts. For service-based locations, showcase custom visuals that reflect the areas they serve.
Interactive maps or location finders: Adding Google Maps or a custom location finder helps users easily find the nearest store or service center. This feature not only enhances usability but also provides a tailored experience for visitors.
Social media feed integration: Integrating a live social media feed on location pages adds dynamic content and more localized imagery. It also provides a space to showcase promotions, events, and local engagement, keeping the page fresh and relevant.
Team photos: Featuring photos of local team members helps humanize the brand and create a personal connection with your audience. It’s a great way to reinforce the idea that your business is part of the local community, building trust and authenticity.
Example of an optimized H1 with custom images on the team page. Source
Complete multi-location redesign audit checklist
Website redesigns often require several months of planning and execution. However, before you push the new site live, it’s essential to ensure it passes the following key tests if you want to retain your traffic:
Brand consistency: Ensure that branding elements, such as colors, typography, logos, and tone, are consistent across all pages and location-specific content.
URL mapping: Double-check that all important URLs are correctly mapped to the new design and are still functional, preserving the SEO value of your existing pages.
No URL structure changes: If you’re maintaining a subfolder structure, confirm that no URL structures are altered to prevent any loss of SEO rankings or broken links.
Site performance: Test the website’s speed to ensure it meets performance standards, passes Core Web Vitals, is mobile-responsive, and is free of any accessibility issues.
Clear CTAs: Ensure that each page features clear, concise calls to action (CTAs) above the fold to encourage user engagement and conversions from the moment visitors land on the page.
Analytics setup: Verify that all necessary analytics and tracking codes (e.g., Google Analytics, conversion goals, UTM parameters) are properly implemented to monitor site performance and user behavior across all locations.
Mobile optimization: Check that the site is fully optimized for mobile users, with responsive design elements that scale and display well on all devices.
SEO-friendly content: Review content for SEO optimization, ensuring that each location page is targeted with local keywords, meta descriptions, and proper header tag hierarchy.
Structured data implementation: Verify that all relevant schema markup (e.g., LocalBusiness, Service, Review) is correctly applied to each location page to support search engines in indexing your content.
Internal linking: Ensure that all location pages have strong internal linking, guiding users through the site, and boosting SEO by connecting related content.
User testing and feedback: Conduct user testing or gather feedback from stakeholders to ensure the new design is intuitive, user-friendly, and aligns with business goals.
Content uniqueness: Confirm that all location pages have unique, location-specific content to avoid any potential issues with duplicate content.
Legal and compliance checks: Ensure that the website complies with any industry-specific regulations (e.g., ADA compliance, GDPR, HIPAA) before launch.
Cross-browser compatibility: Test the website across various browsers to ensure it functions smoothly for all users, regardless of their preferred browser.
Backup and contingency plans: Create a backup of the current website before launching the redesign, and have a contingency plan in place in case issues arise post-launch.
By ensuring that these elements are in place, you can launch a multi-location website redesign that performs well across all locations and provides a seamless, user-friendly experience for your visitors.
Example of before website redesign and after a website redesign
The business case: search and revenue impact at scale
Partnering with a web design and development agency that truly understands the complexities of multi-location businesses, technical SEO, and CRO is essential.
Ignite Visibility is a prime example of this expertise. We implemented a performance-driven SEO strategy to help a home services franchise with over 60 locations across the U.S.
The team optimized city-specific landing pages, standardized keyword-rich updates across Google Business Profiles, and strategically matched high-intent keywords to local markets to maximize visibility.
The results speak for themselves. The Ignite Visibility approach doesn’t just maintain rankings – it creates massive growth opportunities.
If you’re ready to maximize the impact of your next website redesign and achieve measurable, scalable growth, reach out to Ignite Visibility. With our proven track record, we’ll help you stay ahead of the competition and deliver results that matter.
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Google is starting to roll out its new Text Guidelines feature in Google Ads, a tool first announced at the Think Retail event five weeks ago that gives advertisers more control over AI-generated ad copy.
Driving the news. The feature, now appearing in some accounts, lets marketers set campaign-level text parameters — guiding Google’s AI to stay within brand tone, language preferences, and compliance requirements when generating text assets.
Why we care. As Google Ads leans deeper into AI-powered creative, advertisers have been asking for stronger brand safety and message consistency controls. Text Guidelines offer a way to fine-tune AI output without sacrificing automation or performance.
How it works:
Found at the campaign level, Text Guidelines apply only when text customization is turned on.
Advertisers can define rules to steer AI-generated text assets toward specific brand or legal standards.
Designed to support “brand-safe creative” and improve asset quality.
The bottom line. Text Guidelines give brands a new lever to shape how Google’s AI writes for them — tightening control without slowing down automation.
First seen. This rollout was spotted by PPC Speacialist Arpan Banerjee
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/10/google-ads-text-guidelines-beta-1760877222-pPO2We.jpg?fit=1113%2C1058&ssl=110581113http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-20 16:31:512025-10-20 16:31:51Google Ads’ new text guidelines feature begins rolling out
Google is tightening its account retention policy — canceled Google Ads accounts will now be permanently deleted six months after cancellation, marking the end of indefinite account storage.
Driving the news. Under the new policy, Google will begin a cleanup of inactive accounts, sending a 30-day email warning before deletion. Previously, advertisers could reactivate canceled accounts at any time, preserving data and structure indefinitely.
Why we care. This change could impact advertisers who rely on historical performance data, conversion tracking, or campaign templates stored in inactive accounts. Once deleted, all account history and assets — including campaigns, reports, and settings — will be gone for good.
How it works:
Canceled accounts with no active campaigns will be deleted six months after cancellation.
A 30-day warning email will be sent before deletion.
Reactivating an account within the six-month window will prevent deletion.
Between the lines. The policy shift underscores Google’s broader effort to streamline its ad systems and purge unused data, mirroring similar moves across other Google services.
The bottom line. Advertisers who want to preserve old campaign data or structures should reactivate or export data from canceled accounts before the six-month clock runs out.
First seen. This update was spotted by PPC News Feed founder Hana Kobzová.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/10/Inside-Google-Ads-AI-powered-Shopping-ecosystem-Performance-Max-AI-Max-and-more-Hl9R7E.webp?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-20 16:12:482025-10-20 16:12:48Google Ads to permanently delete canceled accounts after six months
After years of delays and scaled-back ambitions, Google officially killed its Privacy Sandbox, the once-flagship initiative aimed at replacing third-party cookies with privacy-preserving ad technologies.
Driving the news. In a blog post Friday, Anthony Chavez, VP of Privacy Sandbox, confirmed that Google is retiring 10 remaining Sandbox APIs, including Attribution Reporting, Topics, and Protected Audience for both Chrome and Android. The move comes over a year after Google abandoned plans to phase out third-party cookies in Chrome altogether.
Why we care. The Privacy Sandbox was Google’s answer to growing privacy regulation and industry backlash against cross-site tracking — but its complexity, limited adoption, and regulatory scrutiny stalled momentum. At last, Google is no longer forcing a shift away from third-party cookies, preserving the familiar targeting and measurement tools that power much of digital advertising.
While this offers short-term stability and fewer disruptions to campaign performance, it also signals that true privacy-safe ad solutions are still unresolved, leaving the industry without a clear path forward as regulators and browsers continue tightening data rules. In short — advertisers get breathing room today, but more uncertainty tomorrow.
The details. Google will phase out:
Attribution Reporting API (Chrome and Android)
Topics API (Chrome and Android)
Protected Audience API (Chrome and Android)
IP Protection, On-Device Personalization, and others
What stays.
CHIPS (Cookies Having Independent Partitioned State) – isolates cookie data to prevent cross-site tracking.
Private State Tokens – helps verify legitimate traffic without tracking users.
Between the lines. Google’s retreat follows years of industry skepticism. Many advertisers and publishers viewed Sandbox tools as confusing, limited, and unlikely to preserve ad performance at scale. By contrast, maintaining cookies while adding optional privacy controls keeps Chrome aligned with user choice — and ad revenue stability.
What they’re saying. “We’ll continue our work to improve privacy across Chrome, Android and the web, but moving away from the Privacy Sandbox branding,” a Google spokesperson told Adweek.
The bottom line. After five years, countless tests, and intense debate, Google’s grand privacy experiment is over — and the web’s future looks a lot more like its past.
Anchor text, which is also known as link text, is the visible, clickable text of a hyperlink. It usually appears in a different color and is often underlined. Good anchor text tells readers what to expect when they click and gives search engines valuable context about the linked page. Getting your anchor text right helps users navigate your content more easily, improves your internal link structure, and provides search engines with clues about your page relationships, which can positively influence your SEO.
Anchor text enhances user navigation and provides context for search engines, improving SEO outcomes.
Good anchor text clearly describes the linked content and avoids misleading or over-optimized phrases.
Different types of anchor text exist, each with specific use cases; mix them for variety and clarity.
Yoast SEO offers tools to analyze competing links and improve anchor text for better search engine ranking.
To enhance anchor text, ensure it matches the linked content, flows naturally, and clearly signals clickable links.
What does an anchor text look like?
Anchor text is the part of a link that describes the linked page. It guides both readers and search engines toward relevant information. For example, if we link to our post about keyword research tools, the phrase “keyword research tools” is the anchor text.
In HTML, it looks like this:
<a href="https://yoast.com/keyword-research-tools/">keyword research tools</a>
The first part is the URL, while the second, the visible text, is the anchor text. Ideally, the words you choose should naturally describe the content on the linked page.
Why are link/anchor texts important?
Links are vital for SEO. They show how your pages connect and help search engines understand your site structure. The anchor text in those links provides extra context.
When Google crawls your site, it uses link text as a clue to what each linked page is about. If multiple links all use the same focus keyphrase, Google might not know which page should rank highest for that topic, leading to competition between your own pages.
That’s why thoughtful, descriptive anchor text matters. It helps search engines interpret your site and helps readers decide whether a link is worth clicking. Over-optimized or misleading link text can confuse both.
Tip: Avoid using your main focus keyphrase in multiple anchor texts within one post, as it can create competing links. Your linking should always feel natural and avoid over-optimization.
An example of internal links with good anchor texts
Different kinds of anchor text
Anchor text applies to both internal and external links. External sites can link to your content in various ways, and each type sends a different signal to search engines:
Branded links: Use your brand name as anchor text (e.g., Yoast)
If Yoast SEO detects that one of your links contains your focus keyphrase or a synonym of it, then Premium users get a warning. The reason? You don’t want multiple pages trying to rank for the same phrase.
For example, say your focus keyphrase is potato chips. If you link to another page using that exact phrase, Yoast SEO will flag it as a competing link. You’ll see a notification in your SEO analysis, so you can adjust it before publishing. If you have Yoast SEO Premium or Yoast SEO for Shopify, the check will also look for the synonyms of your keyphrase.
The competing links check in Yoast SEO helps you improve your linking
How to improve your anchor link texts
If Yoast SEO alerts you about competing links, or if you simply want to improve the quality of your link text, here are some best practices to follow.
1. Create a natural flow
Your writing should feel effortless. If a link feels awkward or forced into a sentence, it probably doesn’t belong there. Always prioritize readability, as a smooth flow improves both engagement and SEO. For more advice on writing content that feels natural while still ranking well, read our SEO copywriting guide.
2. Match the link text to the linked content
Readers should immediately understand what to expect when they click on a link. For example, a link that says meta description should lead to a post explaining what a meta description is and how to optimize it. Clear, logical linking builds trust and helps users navigate your content with ease.
3. Don’t trick your readers
Never mislead readers with inaccurate or confusing link text. If your link text says, “potato chips,” it shouldn’t lead to a page about cars. Consistent and honest linking keeps readers engaged and signals quality to search engines.
4. Make it clear that the link is clickable
Use visual cues such as color contrast or underlining, so it’s easy to tell when text is a link. This not only improves usability but also helps people using assistive technology to navigate your content. To see more on writing accessible, well-structured posts, visit our blogging guide.
5. Bonus tip: put your entire keyphrase in quotes
When using long tail keyphrases, you might see a warning about links that include parts of your focus keyphrase. To avoid this, put your full keyphrase in quotes, for example, “learning how to knit.” This tells Yoast SEO to look for the entire phrase rather than matching individual words.
If you’d like to learn more about writing effective link text and improving your content for SEO, take our SEO copywriting course, which is included with Yoast SEO Premium.
Go Premium and get free access to our SEO courses!
Learn how to write great content for SEO and unlock lots of features with Yoast SEO Premium:
But internal links work best when you write good anchor text for them. Each link should serve a clear purpose and guide readers naturally to related topics. Avoid adding unnecessary or irrelevant links just for the sake of having more connections.
Thoughtful internal linking improves the user experience and helps search engines understand your site’s structure, which is essential for strong SEO performance.
This is anchor text
Anchor text remains a small but powerful element of SEO. It helps users decide whether to click, gives search engines valuable context, and supports a logical site structure.
Keep your anchor text relevant, natural, and transparent and avoid manipulative or over-optimized linking practices. Search engines are now smarter than ever at spotting unnatural links, especially in the era of AI and semantic understanding.
So stay genuine, link with intent, and use Yoast SEO to guide you along the way.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-20 12:00:002025-10-20 12:00:00What is anchor text, and how can you improve your link texts?
Have you noticed that your site analytics feel a little, well, off lately? It’s not just your imagination. We’ve found a subtle growing issue popping up across multiple clients, and it might be hitting your site, too.
It comes down to GTM tag priority and how these tags fire in relation to consent management. If tags load out of order or before the user gives proper consent, your tracking can break. This means lost sessions, broken attribution, and inaccurate conversion data.
We’ve seen this firsthand, but we’ve taken steps to fix it. Let’s break down what tag sequencing is and why it matters. In addition, we’ll give you some tips to help make sure your data stays clean and compliant without sacrificing its usefulness.
Key Takeaways
Poor tag sequencing can lead to missing data, inflated conversion rates, and inaccurate attribution.
Tag priority matters, especially when consent management platforms are in play.
We’ve seen clients lose up to 20% of reported traffic due to sequencing issues.
Fixes include loading the consent script first, mapping tags to categories, and blocking tags until consent is confirmed.
Regular audits are non-negotiable. One misstep in your CMP or tag manager setup can break your entire funnel.
What is Tag Sequencing And Why Is It Important?
Tag sequencing is the order in which tracking tags, like analytics, advertising, or personalization, fire on your website. While it sounds simple, it plays a big role in the accuracy of your data.
When you use a consent management platform (CMP), sequencing these tags becomes even more important. Some tags aren’t allowed to fire if users don’t give specific consent. Others rely on earlier tags to work correctly. If the order’s off or a critical tag doesn’t fire, your tracking capabilities break down, and so does your reporting. CMP triggers or blocks tags in the right sequence so only authorized data collection occurs. This preserves regulatory compliance and performance accuracy.
Tags load in the right area (keeping your data clean)
Your campaigns see proper attribution (keeping your ROI real)
If you ignore tag sequencing, you risk bad data. Even worse, you can lose conversions and break your customer insights.
The Impact of Tag Sequencing on Data Quality (and the bottom line)
When you fail to set your GTM tag priority correctly, it can distort your data (sometimes massively). We’ve seen this across major brands in finance, hospitality, and automotive industries. In each case, the same issue kept popping up: the first page of a user’s visit wasn’t being tracked.
That doesn’t sound like a big deal, but it is. That one misstep led to a massive ripple effect:
Traffic was underreported by as much as 10 to 20 percent.
Here’s why that’s a problem: broken data could also lead to broken strategies. You could be pulling budget from channels that are working or double down on content that doesn’t actually convert. Either way, your decisions are off base.
The scary part is that this isn’t always obvious unless someone digs into the tags and sequencing logic; if you’re not actively spending time in the sequence, you may not notice an issue.
The Causes Behind Tag Sequencing Issues We’ve Found
Most tag sequencing issues come down to one of five things, which are often more common than you’d expect. If you’ve noticed attribution issues, you might have the following issues:
Consent misconfiguration. Tags aren’t properly mapped to categories like analytics, marketing, or performance. Even if a user opts in, the right tags may not fire.
Network latency. If your consent platform loads too slowly, it could delay or block tags entirely.
Script placement. Tags placed above the consent script in the site header will run before user choices are processed.
Direct-to-page scripts. It’s important to note that not all scripts necessarily sit in GTM, for a variety of reasons. If the consent banner configuration on the site doesn’t fire before these scripts and the GTM tags, it will cause issues. This applies whether you implement tags directly in GTM or the site itself.
When these problems stack up, you can often get missing data or broken attribution. This skews performance and could impact your decisions surrounding future resource allocation.
How To Fix Your Tag Sequencing Before It Impacts Data Quality
Fixing tag sequencing isn’t complicated, but it is important. We’ve helped our clients clean up their setup and reclaim accurate tracking with the following best practices:
Load your consent script first. This should be the very first script in your header. Put it before any analytics, marketing, or tracker tags.
Use your CMP to block everything else until the user’s choice is known. See below for an example of how to use OneTrust CMP to create active group triggers.
Assign consent categories to every tag. These categories ensure your platform knows what to load and when.
Audit your tags regularly. Site updates, script changes, and even CMP updates can reset sequencing logic without any warning. These screenshots are from our partner, ObservePoint, that we utilize for scaled audits. This tool can help scale up consent audits and can help us validate user consent selections. The below example shows what categories of tags fire when a user opts in vs. opts out and can be a quick way to determine whether further investigation is needed – for example, if we expect zero analytics tags to fire when consent is not given, and we see analytics tags firing on 4% of pages scanned that are opt out, that would flag to us that there is an issue with configuration.
How does this work in action? Take a look at the below examples to show how we utilize OneTrust CMP and create groupings based on cookie types: ( Performance, Marketing, Analytics, etc.). Mapping cookie types to their corresponding cookie groups and then assigning them to appropriate tags within GTM so the users cookie choices map with what tags fire once consent is given.
Below, by assigning that active group trigger as an And statement to an existing tag, this ensures both values are present before the tag fires, avoiding the issue we’ve been seeing.
Failure to fix tag sequencing means you break your compliance and your data, which will inevitably trickle into every marketing decision you make.
FAQs
What is tag sequencing in GTM?
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It’s the order in which tags are triggered on your site. When using consent management, this sequence determines which tags fire—and when—based on user permissions.
How can bad tag sequencing affect my data?
If tags fire too early (or not at all), you’ll miss sessions, inflate conversion rates, and get unreliable channel attribution.
Can I manage tag sequencing without a developer?
Yes—tools like Google Tag Manager and modern CMPs make it easy to handle sequencing logic without code, as long as they’re set up properly.
How often should I check my tag sequencing setup?
Audit it quarterly, or anytime you update your website, CMP, or launch a new campaign. One misplaced script can throw off everything.
Conclusion
Tag sequencing may seem like a simple technical skill, but it’s so much more than that. It creates a backbone for reliable data that underpins many of your marketing decisions. Tags that fire out of order can break tracking, skew analytics, and cause you to miss valuable opportunities.
But it’s a fixable issue, and a few key adjustments to your GTM setup and consent platform can get things back on track and keep them there.
If you want to dive deeper into clean data, consider performing a technical SEO audit and explore how your site’s structure can impact your results. But if you’re still unsure whether your tag setup costs you conversions, let’s talk. Fixing it now can save you wasted spend (and effort) down the line.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-16 07:00:002025-10-16 07:00:00How Tag Sequencing Is Affecting Website Data Quality When Utilizing Consent Management
When someone asks ChatGPT for a product in your category, it doesn’t always crawl websites in real-time.
Its first move is to pull from what it already knows about you and your competitors from its existing knowledge.
Clear and recognizable entities in AI training data are just as important as having the most authoritative and optimized website.
This shift means your webpage might rank #1 in classic search, but if your brand isn’t well-structured for entities, AI might overlook you entirely in the answer.
The rules we’ve relied on for decades don’t fully apply when machines create answers. They draw on their own knowledge and real-time data from sites, including yours.
You’re about to learn what this means, why it matters, and what you can do about it.
What Are Entities in AI Search?
An entity is a “thing” that search engines and AI models can recognize, understand, and connect to other things.
Think of entities as the building blocks that AI uses to construct answers. In other words, gigantic relational databases.
Let’s use email marketing company Omnisend as an example.
Through the lens of a database, Omnisend isn’t just a website with pages about email marketing. It’s a network of connected entities:
Use cases: “welcome series,” “abandoned cart recovery”
Here’s what the entities look (hypothetically ) like to a large language model (LLM):
These records become the foundation for AI answers.
LLMs do more than just find keywords on your page. They also retrieve entities, place them in vector space, and choose the ones that best answer your question.
Vector space explained: It’s a mathematical method that AI models use to understand relationships between concepts. Imagine a 3D map where similar items group together. For example, “Apple,” the company, is close to “iPhone” and “Tim Cook.” Meanwhile, “apple,” the fruit, is near “banana” and “orchard.”
For example, ask Google: “What’s the best email marketing tool for my Shopify store?”
You’ll see brand entities like Klaviyo, Omnisend, Brevo, Mailchimp, Privy, and MailerLite mentioned. This makes sense because the entities are closely related in the AI’s understanding.
Notice: the brand mentions aren’t linked to the websites. It’s just building the answer and then linking to the brand SERP on Google.
Why Entities Matter More Than Websites
AI models are constantly mapping relationships between entities when serving up answers.
When someone types “best email marketing tool for Shopify,” LLMs spread out the query. They turn that one question into multiple related searches.
Think of AI doing lots of Google searches at the same time.
The system simultaneously explores “What integrates with Shopify?”, “Which tools handle abandoned carts?” and “What do ecommerce stores actually use?”
Your brand can appear through any of these paths, even if you didn’t optimize for the original query.
Classic SEO relied a lot on keyword density and page authority.
But AI uses dense retrieval, where it’s looking for semantic meaning across the web, not just word matches on your page.
Dense retrieval explained: AI systems focus on meaning, not just exact keywords. They find related content, even if different words are used.
A Reddit comment that clearly explains “We switched from Klaviyo to Omnisend because the Shopify integration actually works” carries more signal (assuming the model prioritizes authentic discussions) than a page stuffed with “best email marketing Shopify” keywords.
The AI understands the relationship between the entities (Klaviyo, Omnisend, Shopify) and the context (switching, integration quality).
PR folks have been fighting for this moment: mentions without links still count.
For the longest time, we’ve obsessed over backlinks as the currency of SEO.
But AI systems recognize when brands get mentioned alongside relevant topics, using these as relationship signals.
So when Patagonia appears in climate articles without a hyperlink, when Notion shows up in productivity discussions on Reddit, when your brand gets name-dropped in a podcast transcript — these all strengthen your entity in AI’s understanding.
Here’s a real example that clarified this for me:
Microsoft OneNote often shows up high in AI recommendations for “note-taking tools.”
In ChatGPT:
In Perplexity:
And in Google AI Overviews:
But EverNote dominates Google’s number one ranking spot for “note taking tools”.
Why?
OneNote’s integration with the Microsoft ecosystem means it gets mentioned constantly in productivity discussions, enterprise software comparisons, and Office tutorials. This creates dense entity relationships in AI training data.
Evernote, by contrast, has focused on SEO and earned strong backlinks that dominate traditional search rankings.
How Entities Get Recognized
So how does Google (and other AI systems) actually know that Omnisend is an email marketing platform and not, say, a meditation app?
The answer sits at the intersection of structured data, human conversation, and pattern recognition…at massive scale.
Entity Databases and Product Catalogs
Google maintains what they call Knowledge Graphs and Shopping Graphs.
Other AI systems have similar entity databases, just with different names.
The idea is the same: huge databases that map every product, company, and person along with their attributes and relationships.
When Nike releases the Pegasus 41, it doesn’t just become a new product page on Nike.com. It becomes an entity in Google’s Shopping Graph, connected to “running shoes,” “Nike,” “marathon training,” and hundreds of other nodes.
The system knows it’s a shoe before anyone optimizes a single keyword.
Human Conversation as Training Data
AI systems learn just as much from informal mentions as they do from structured markup.
When an Outdoor Gear Lab review casually mentions testing Patagonia’s Torrentshell 3L against the expensive Arc’teryx Beta SL, that relationship gets encoded.
When a podcast guest says, “I moved from Asana to Notion for task and project management,” this competitive link adds to the training data.
Reddit and Quora have become unexpectedly powerful for entity recognition. (Google explicitly stated they’re prioritizing “authentic discussion forums” in their ranking systems.)
A single comment on why someone picked Obsidian over Notion for knowledge management matters more than you might realize.
These platforms capture what websites struggle to do: real people sharing real decisions with real context.
Multimodal Recognition
AI systems extract entities from audio and video. They do this by turning speech into text through transcription.
Every mention in a transcript, every product on screen, and every comparison in a talking-head segment is processed.
A 10-minute YouTube review of project management tools turns into structured data that compares ClickUp, Notion, and Asana. It includes feature comparisons and maps out use cases.
The New SEO Power Dynamic
You can’t game entity recognition the way you could game PageRank.
You can’t manufacture authentic Reddit discussions. You can’t fake your way into natural podcast mentions. The system rewards genuine presence in genuine conversations, not optimized anchor text.
Think about what this means:
Your engineering team’s conference talk that mentions your product’s architecture? That’s entity building.
Your customer’s YouTube walkthrough of their workflow? Entity building.
That heated Hacker News thread where someone defends your approach to data privacy? Entity building.
We’ve spent the longest time optimizing for robots. Now the robots are optimized to recognize authentic human discussion. (Ironic.)
5 Ways to Optimize Your Brand for Entities (Not Just a Website)
Using Omnisend as an example, here are five approaches for evaluating and optimizing entity presence in AI-powered search results.
1. Assess Your Entity Foundation
To start, you need a baseline understanding of your current entity relationships.
For Omnisend, this means mapping how AI systems currently categorize them relative to competitors.
Begin by verifying schema markup across key pages.
Testing Omnisend’s homepage with the Schema Markup Validator shows they use Organization and VideoObject schema.
And the Organization schema is relatively basic.
Omnisends competitor, Klaviyo, uses Organization schema as a container for multiple software offerings.
Klaviyo’s approach maintains brand-level authority while declaring specific software categories and capabilities. This potentially gives them stronger entity associations for queries about email marketing, SMS marketing, and marketing automation.
Next, check your entity presence in major knowledge sources like Wikidata and Crunchbase.
On Wikidata, Omnisend’s records are OKAY.
There’s basic info, like what Omnisend does, the industry, inception date, URL, and social media profiles.
But Klaviyo, again, is all over it. They have multiple properties for industry, entity type, URLs, offerings, and even partnerships.
There’s a clear opportunity for Omnisend to update its Wikidata with more details.
2. Test Query Decomposition
AI systems break down queries into entities and relationships. Then, they may try multiple retrievals.
For example, in Google Chrome, I prompted ChatGPT:
“What’s the best email marketing tool for ecommerce in 2025? My priority is deliverability.”
In the chat URL, copy the alphanumeric sequence after the /c/ directory. For me, it was 68d4e99e-4818-8332-adbd-efab286f4007.
Note: You need to be logged into ChatGPT to get this sequence
Right-click on the page and click “Inspect”.
Choose the “Network” tab, paste the alphanumeric sequence in the filter field, and reload the page.
In the “Find” section, search for “search_model_queries“. Then, click on the search results.
Each decomposed query represents a different competitive pathway.
Omnisend might surface through deliverability discussions, but miss general tool comparisons.
Mailchimp could dominate broad searches while competitors own specialized angles.
This explains why you appear in AI answers for searches you never optimized for. The semantic understanding creates visibility through unexpected entity relationships rather than keyword matching.
You can check this yourself. Run the extracted queries in separate chats and note which brands appear where.
But maybe don’t build a strategy around exploiting this technique.
The methodology depends on undocumented functionality that OpenAI could change without notice.
Important finding: Simple queries produce simple results. When I prompted “Best email marketing tool for ecommerce,” it triggered exactly one internal search with basically the same language. No decomposition.
3. Map Competitive Entity Relationships
Traditional SEO competitive analysis asks “Who ranks for our keywords?”
Entity analysis asks “When do AI systems group us together?”
I tested this with Omnisend to understand when they appear alongside different competitors.
I ran 15 variations of email marketing queries through Google AI Mode to see which brands consistently appear together.
Note: I tested logged out, using a VPN set to San Francisco, in private browsing mode to minimize personalization bias.
I began with simple terms like “best email marketing for ecommerce” and “abandoned cart recovery tools.” Then, I tried different angles like “email automation for Shopify stores.”
Here’s what I found:
Query Context
Omnisend Present
Most Co-Mentioned
Klaviyo Present
Ecommerce email
5/5 queries
Klaviyo, Mailchimp
4/5 queries
General email
5/5 queries
Mailchimp, Brevo
2/5 queries
Deliverability focus
2/5 queries
Brevo, Mailchimp
0/5 queries
Omnisend appeared in 12 of 15 total queries — stronger entity presence than I expected.
But mentions shifted dramatically by context.
In ecommerce discussions, Klaviyo dominated as the top tool.
In general email marketing, Mailchimp took over as the main reference point.
The mention order revealed something important. Klaviyo appeared first in 5 of 5 ecommerce queries, with more positive language around their positioning.
Omnisend routinely ranked second or third. This suggests they’re part of the discussion but not at the forefront.
Here’s what’s interesting:
Klaviyo completely disappeared from deliverability-focused queries while Omnisend maintained some presence.
This shows entity relationships are radically contextual.
Being the leader in ecommerce email doesn’t mean presence in deliverability conversations.
4. Optimize For Entities in Your Content
Entity recognition works best when it has context-rich passages. This helps AI systems extract and understand information more easily.
Take generic descriptions like “Our automation features help ecommerce businesses increase revenue through targeted campaigns.”
An AI system may struggle to identify which product you mean, its automation features, or how it compares to others.
Compare that to: “Omnisend’s SMS automation integrates with Shopify’s abandoned cart data to trigger personalized recovery messages within 2 hours of cart abandonment, without requiring manual workflow setup.”
This version establishes multiple entity relationships (Omnisend → SMS automation → Shopify integration → abandoned cart recovery) within a single extractable passage.
LLMs prefer to use their training data for answers. But when they pull info from the web, strong entity connections help a lot.
You’re reducing friction for both bots and human readers.
As a test, run key passages from your most important pages through Google’s Natural Language API to see what entities get recognized. This can also be video scripts.
Content with strong entity density tends to get cited more often than content requiring additional context.
5. Build Strategic Co-Citations
Entity authority builds through consistent mention alongside relevant entities in trusted sources. This moves the focus from link building to building relationships where natural comparisons happen.
For Omnisend, this means being present in authentic discussions. It’s about genuine comparisons, not forced mentions, that strengthen specific relationships.
A Reddit thread comparing “Klaviyo vs Omnisend for Shopify stores” carries a different entity weight than appearing in generic “email marketing tools” content.
The specific context (Shopify integration) strengthens both brands’ association with ecommerce email marketing.
The most valuable co-citations happen in:
Reddit discussions comparing tools for specific use cases
YouTube reviews demonstrating multiple platforms
Industry roundups grouping tools by specialization
Podcast discussions of marketing technology stacks
This Reddit thread shows strategic co-citation in action. The original post creates dense entity relationships (Klaviyo → Omnisend → pricing → Shopify store). While the comment adds even more context (pricing concerns → business scaling → “pretty good” user experience).
The discussion goes way beyond optimized content. It’s genuine decision-making that strengthens both brands’ entity associations with ecommerce email marketing.
This approach emphasizes genuine participation. Your category is discussed and evaluated by actual users who make real decisions. This is better than having artificial mentions in content made mainly for search engines.
Moving Forward with Entity SEO
If you’ve built a strong brand across various channels, you’ve laid the foundation.
Quality SEO is still crucial.
Genuine mentions in industry talks, real customer chats, and multi-channel distribution matter too.
Begin with your key product line. Organize it well, track its appearances in AI responses, and then expand to other entities.
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AI answers are taking over search. More people are turning to Google AI Overviews, ChatGPT, and Perplexity for recommendations.
And if your brand isn’t showing up in those AI answers? You’re missing out on a huge (and growing) slice of your market.
That’s why Semrush built the AI SEO Toolkit. It’s a major unlock for marketers trying to understand how AI is impacting their
business.
Today, I’m going to show you how to use it — step by step — with a real example.
TL;DR: Measure Your AI Search Visibility
Here’s what you need to know about Semrush’s AI SEO Toolkit:
What it does:
Tracks how your brand appears across ChatGPT, Google AI Overviews, Google AI Mode, and Perplexity — showing which prompts include you and where you’re missing
Provides prompt tracking, content audits, and competitor comparisons
What it costs:
$99/month per domain (no trial)
Step 0: Start With a Brand
Before we analyze anything, let’s pick a brand to make this walkthrough concrete.
I went to Exploding Topics, browsed the ecommerce category, and picked Petlibro — a trending startup that sells smart pet feeders and water fountains.
I have zero affiliation with Petlibro. This isn’t sponsored. I just wanted a brand that’s growing fast and has enough search demand to make this example interesting.
Step 1: Get Your Search Baseline
Before we look at AI, we want to know how Petlibro is doing in traditional search. It’s super valuable context that will help us understand how they’re performing in LLMs.
Enter the brand’s domain name and look at the last 18 months. Looking at petlibro.com, they’ve been growing a TON.
They get most of their traffic from the U.S., rank for more than 25,000 keywords, and have a domain Authority Score of 43 with backlinks from 2.8K referring domains.
And they rank well in traditional SERPs for a bunch of highly relevant category and product keywords.
So they’re a real brand that’s already doing a good job with SEO. And good search engine optimization often correlates with good AI optimization.
If your brand has so far neglected SEO, now is the ideal time to tackle that with a solid AI SEO strategy (which this audit will help you form).
Step 2: Check Your AI Visibility
Now for the fun part.
Back in the Semrush dashboard, look for AI SEO in the sidebar.
Enter petlibro.com, and a few minutes later, your Brand Performance dashboard will be ready for review.
On the right side, you can see the Share of Voice versus Sentiment Score.
The most interesting thing I noticed right away is that Petlibro has relatively low Share of Voice (6%) in regular ChatGPT, without Search.
That’s because ChatGPT 5 without search enabled has a training data cutoff of September 30, 2024.
And as we saw in traditional search, Petlibro has been growing a LOT in the last year.
Fortunately, they’re performing much better in SearchGPT, Google AI Mode, and Perplexity. All three of which use live search to generate their answers. For example, Petlibro’s Share of Voice in Google AI Mode is 27.8%:
Pro tip: Keep this in mind when analyzing your own brand too. These tools might not have your newest content in their training data. This can affect your apparent visibility, so be sure to check your visibility when search is enabled (as search-powered experiences are becoming more common).
This tab gives you a broad overview of your brand’s visibility. The next step will help you get more granular.
Step 3. Gauge Visibility at the Prompt Level
You can get prompt-level details by heading to the Visibility Overview tab.
Note: Things are evolving fast in the AI SEO space. This tool is brand new at the time of writing, so there isn’t much in the way of historical data right now. But tracking your visibility here over time will help you understand how well optimized your site is for an increasingly AI-based search landscape.
Scroll down and you’ll be able to quickly understand:
Your top-performing topics
Opportunities to improve your brand’s visibility
Popular sources for prompts relevant to your industry
Where your competitors are being cited that you’re not
Where you are being cited as a source
Click on any of the topics (or select Prompts) to see exact prompts and the AI response that you appear as part of.
To get more data on the prompts your rivals are appearing for that you’re not, head to the Narrative Drivers tab. First, you’ll see your brand’s Share of Voice by platform.
This gives you an overview of where your rivals are winning on each AI platform. But we want to scroll down to Share of Voice and switch to the Average Position view.
You can then toggle each competitor individually to get a better idea of how you perform against key rivals over time.
This view essentially gives you a snapshot of your brand’s visibility for key prompts.
To understand which prompts you are and are not appearing for compared to your rivals, you want to scroll down to the Breakdown by Question section.
You’ll see your position, which is where you show up in the answer snippet compared to your competitors.
You can see which ones your rivals appear for that you don’t by using the filters:
For example, Petlibro isn’t appearing for a few prompts that multiple competitors are mentioned in:
Identify the most relevant queries you want to start appearing for, and do this for each AI tool (using the toggle at the top left).
Note these down somewhere, as these will help frame your AI optimization strategy. Think of this part like the keyword research stage in a traditional SEO campaign.
Step 4. Review Your Brand’s Trust Factors
Next, you want to understand where your brand is doing a good job of appearing trustworthy to both your users and the LLMs themselves.
To do this, head back to the Brand Performance tab and scroll down to Key Business Drivers.
This essentially shows where your brand is strong compared to your competitors in various areas that help convey trust to users.
It might look overwhelming at first.
But basically:
The numbers illustrate how often key business drivers (i.e., trust factors) appear in answers where your brand is also mentioned. The bigger the number, the better.
(Look for the trophy icon to see where you’re currently ahead of your competitors.)
For example:
Searchers may value smart home integration when selecting a smart pet feeder.
When AI tools mention PetSafe, they also sometimes mention the fact it has these features.
This makes the brand more likely to appear in AI search responses when a user is looking for smart pet feeders with features like smart home integrations.
If Petlibro offers this, the brand needs to do a better job of conveying that in their content, or they’re going to struggle to appear in AI responses for relevant prompts.
Meanwhile, PetSafe is being mentioned for this kind of user prompt:
Go through this tab and identify trust factors you want to appear for.
If you spot areas competitors are strong but you’re not being picked up, make sure you:
Include trust factors and unique selling points on your website homepage
Add mentions of relevant features to product pages
Write helpful FAQ questions on product pages and blog posts that cater to these trust factors
Step 5. Audit Brand Sentiment in AI Tools
The next step involves diving deeper into how AI tools (and by proxy your users) perceive your brand.
To do this, we’ll head to the Perception report and scroll to the Key Sentiment Drivers section.
This will show you Brand Strength Factors and Areas for Improvement.
This is a great snapshot to see where you’re already doing well. And where you might need to focus new efforts on improving your brand’s perception in AI responses.
Brand strength factors are essentially areas where the AI tools talk positively about your brand.
In Petlibro’s case, these are factors like app connectivity, mechanical jams, and customer support.
Pro tip: Look for anything that’s not accurate here. You don’t want AI tools to be recommending your brand for things you don’t offer — this will just lead to disappointed customers.
The areas for improvement are areas where you might want to:
Create optimized content to make it clear to customers what you offer
Optimize your existing product pages to better reflect their strengths
Improve your products or services to better meet your customers’ needs
That final point is worth emphasizing. Semrush’s AI SEO tools don’t just give you content ideas.
You can use the insights you gain here and the prompts real users are inputting into AI tools to understand where you can improve and expand your products/services.
The future of marketing is truly collaborative across departments. And these kinds of insights can help align both your SEO/content teams and your product and marketing divisions.
This can lead to a better user experience on your site, a better product for your customers, and increased business growth.
Pro tip: At the bottom of most of these tabs, you’ll also find “AI Strategic Insights.” These are AI-powered suggestions you can use immediately to boost your AI visibility.
Step 6. Identify More Content Ideas
Step 6 is to find more ideas for creating new content and optimizing your existing pages.
First, head to the Questions tab and scroll down to the Query Topics section.
Answer these questions with new content or in your existing content.
For example, Petlibro could create a blog post titled “How to Stop Your Cat Shaking Food Out of Its Feeder.”
They could also update their product pages to highlight that their feeders support different portion sizes for morning and evening meals, and add an FAQ section answering common branded questions.
To understand what content you might want to create (and which prompts are actually worth optimizing for), enter the relevant ones into tools like ChatGPT. (Make sure you enable web search.)
The example below returns a lot of scientific papers, so it would likely be a tough one for Petlibro to appear for.
But there is a Reddit thread in there too. Which means a Reddit marketing strategy could be worth exploring to boost visibility for these kinds of prompts.
This next one is a more likely candidate, and we can see PetSafe (a competitor) gets cited as a source. (And Reddit appears again too.)
There is also a product carousel with links further down — none of which are from Petlibro.
So this would definitely be worth digging into to see why PetSafe (and the other products) are being recommended:
Do the product pages do a better job of conveying trust signals?
Are they more descriptive?
Do they have FAQ sections that answer the prompt’s question?
Bottom line:
You need to look closer than simply the prompts themselves to understand why other brands are being recommended ahead of yours.
But once again, if you scroll to the bottom, you’ll find AI-powered insights that can give you a head start.
Turn Your AI SEO Audit Insights Into Action
An AI SEO audit is a vital first step to make your brand AI ready. And Semrush’s AI SEO Toolkit gives you everything you need to get started.
But the audit is just the first step. Use these resources to turn what you learn from the tool into action for your brand:
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Google’s Performance Max (PMax) campaigns now support vertical 9:16 image ads, bringing the popular mobile-friendly format to the platform’s most automated campaign type.
What’s new. Google Ads specialist Thomas Eccel spotted the update, noting that vertical “Story Image Ads” – first seen in Demand Gen campaigns earlier this year – are now available in PMax.
Specs at a glance:
Minimum size: 600×1067 (recommended: 1080×1920)
Maximum file size: 5MB
Google hasn’t officially confirmed where these will serve, though in Demand Gen, they appear in YouTube Shorts Image placements.
Why we care. Vertical 9:16 images let PMax campaigns fit naturally into mobile-first environments like YouTube Shorts, where user attention is highest. Experts say this update goes beyond creative specs. As Phil Byrne, founder of Positive Sparks Marketing LTD, noted, it’s about “meeting users where they naturally consume content.”
With Shorts, Reels, and TikTok dominating mobile engagement, vertical formats are key to maintaining attention and relevance.
The bigger picture. Mike Ryan, head of ecommerce insights at Smarter Ecommerce, added that PMax is already monetizing YouTube Shorts through “GMC Image Shorts,” which display multiple product images for remarketing and personalization – a sign that Google is leaning deeper into short-form, shoppable media.
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