Unlinked mentions still matter. Learn how to track them, evaluate their SEO and PR value, and use insights to strengthen brand visibility and authority.
How often are your brand, products, or people mentioned online without including a link to your site? Odds are, the answer to that question is “more often than you think.”
What you do about those mentions can have a sizable impact on your SEO and search engine visibility. However, it can be difficult and time-consuming to sift through them all, decide which warrant action, and reach out for a link.
In this article, we’ll distill that process down for you. We’ll explore how unlinked mentions impact your SEO, how to prioritize your outreach, what tools can help you streamline the process, how all of this affects LLM visibility, and more.
What are unlinked mentions?
Unlinked mentions are references to a brand, product, person, or website in online content that do not include a backlink. They signal awareness but, because there’s no backlink to your site, don’t pass SEO authority. These unlinked mentions can appear literally anywhere: from industry publications and news articles to social media posts, forums, and competitor analysis pieces.
Unlinked Mentions
Marketers often track unlinked mentions in order to reach out to site owners and ask for links on the mentions. When more of your mentions include a backlink, you’re getting:
Increased authority: When reputable sites mention your brand, they’re essentially vouching for your industry expertise and relevance.
Increased referral traffic: Linked brand mentions can drive highly qualified traffic to your website from audiences already interested in your space.
Improved entity recognition: Search engines use various signals, including backlinks, to understand what your brand represents and how it relates to topics in your industry.
But is all of this still relevant in the age of AI with the meteoric rise of large language model (LLM) search tools?
In short, yes.
However, the increase in AI-powered search and zero-click results has changed how brand authority manifests in search. Linked mentions are not the only way branded terms can significantly and quantifiably move the needle for you.
The AI Visibility Index found that citations and mentions by LLMs are determined by the content you post and the extents to which people talk about your brand—no link volumes or domain authority scores mentioned here. Zapier is a leading example of this; its rich resource content makes it number one in the B2B SaaS space in terms of citations, but only #44 for number of AI mentions.
Zapier Citeds Ources Vs Brand Mentions Scaled
And when it comes to LLMs, Kevin Indig independently confirmed a strong correlation between a brand’s popularity (i.e., how often it’s mentioned and searched by name on the web) and how often it appears in AI searches:
Growthmemo Factors Correlating Brand Search Volume Scaled
A Semrush study on the impact of AI search on SEO showed that nearly 9 out of 10 webpages cited by ChatGPT appear outside the top 20 results in standard organic search for the same queries. The classic SEO signals passed along by link equity simply don’t apply to AI’s understanding of content.
These differences are critical to how you approach your content optimization and visibility strategy.
Dig deeper: Brand mentions and how to make the most of them
Why unlinked mentions are critical for advanced SEOs
Advanced SEOs prioritize unlinked mention outreach because it has quite a few advantages over cold link building outreach.
Those advantages are:
Unlinked mentions are low-hanging fruit: Sites that already mention your brand clearly see value in your content, products, or expertise. This existing awareness makes them more receptive to adding a link to the mention when approached thoughtfully.
They contribute to a brand-driven SEO strategy: Converting unlinked mentions to backlinks strengthens E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals by connecting contextual references back to your site. This helps search engines understand your brand’s authority on specific topics.
They help you build relationships: These mentions might come from journalists, industry experts, or publications you’ll want ongoing relationships with. Converting an unlinked mention by reaching out to the publisher can be the start of valuable long-term partnerships.
They provide more opportunities for conversions: Getting backlinks isn’t just about increasing your position in the search results. Instead, you’re also potentially driving relevant referral traffic to your site, right into your conversion funnels.
They’re a scalable competitive advantage: While competitors can copy your content strategy or target the same keywords, they can’t easily replicate the specific mentions your brand has earned over time.
The key is approaching unlinked mentions as part of a broader digital PR and authority-building strategy rather than just another link-building tactic.
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How to prioritize unlinked mentions for outreach
Not all unlinked mentions are worth pursuing for backlinks. But then, how do you know if you should try to get a backlink from an unlinked mention?
Mention Outreach
Some mentions are more important than others and can be prioritized on your list. To figure out which ones to prioritize, consider each of these key factors:
Authority and relevance of the site
Placement and context of the mention
Conversion and traffic potential
Content freshness and evergreen potential
Author relationship potential
Page traffic and visibility
Now, let’s take a closer look at each of these, with some hypothetical examples.
Authority and relevance of the site
Consider the authority and topical relevance of the site where you’re mentioned. Depending on your preferred SEO tool, look up the metric that measures the domain’s relative authority. This could be Authority Score in Semrush, Domain Authority in Moz, Domain Rating in Ahrefs, and so on.
If a website scores high in domain authority metrics, it should probably be toward the top of your list of unlinked mentions to target for backlink outreach.
Example: A website with a domain authority of 81 would be a priority, whereas a domain authority of 35 might be lower on your list of sites to contact.
Another factor to consider is the topical relevance of the site. How relevant is the site to yours?
Example: Your SaaS product that helps nonprofits collect and manage donations is mentioned in an article about how to successfully manage donations on nonprofithub.org, a website devoted to helpful advice for nonprofits. While the site’s authority score isn’t as high as some others, that mention is incredibly relevant for your site and should be high on your outreach list.
Placement and context of the mention
The location on the page and context of your mention within the content both significantly impact the importance of an unlinked mention.
Editorial mentions within the main article content tend to carry more weight than passing references in sidebars, author bios, or comment sections. This is especially true if the article you’re mentioned in is contextually relevant to your business.
Also, pay attention to how your brand is discussed. Mentions that reference specific features, products, reports, or expertise tend to send traffic to your site that’s much more likely to convert than casual name-drops.
Example: Your donor management platform is mentioned in a sentence like “Tools like Donorbox, Kindful, and [YourBrand] have revolutionized how nonprofits manage donors and donations” within a comprehensive guide about donor management. This contextual editorial mention comparing you to established players is a link you should definitely prioritize on your list.
On the flip side, say the same website you were mentioned on in the example linked to you in a landing page sidebar in a list of sponsors for a conference. This type of mention, while definitely not worthless, doesn’t carry the same weight as the editorial mention and is therefore lower priority.
Even lower priority still would be a link from the conference event venue, since it’s not at all contextually relevant to your business.
Conversion and traffic potential
Backlinks aren’t just for search engines. They’re for humans, too! You want to drive relevant traffic to your website through your backlinks.
Think about whether the linking site’s audience aligns with your target customers and if traffic from this source might convert. A highly relevant, engaged audience outweighs raw authority metrics for unlinked mention priority.
Consider the site’s typical content, commenting activity, and whether their audience would realistically be interested in your content and product or service.
Example: A mention on a popular small business podcast’s website with an engaged community of nonprofit execs actively seeking business tools would be an absolutely fantastic backlink to have. Even if the domain authority is moderate, the audience alignment makes conversions from that traffic more likely.
On the flip side, say you have a mention on a high-authority tech news site that covers enterprise software, but your product targets small businesses. The authority is appealing, but audience mismatch reduces any traffic’s conversion potential. So you could drop this unlinked mention to the middle of your list.
Content freshness and evergreen potential
Recent mentions are often easier to convert because the content is still fresh in the author’s mind, and they may be more responsive to outreach. However, don’t ignore older mentions in evergreen content that continue getting traffic.
Check the publication date and try to determine whether the content is still being updated or referenced. Evergreen guides, resource lists, and comprehensive tutorials often get periodically updated, making them valuable long-term targets.
Example: A mention in a “[current year] Guide to Donation Management Tools” published three months ago is ideal. It’s recent enough for easy outreach but evergreen enough to provide ongoing value if converted, whereas an article with last year in the title isn’t as worthwhile targeting for outreach.
Author relationship potential
Research the author to determine if they regularly cover your industry and could become a valuable long-term contact. Authors who frequently write about your space are worth building relationships with, even if the current mention isn’t perfect.
Look at their recent articles, social media presence, and whether they’ve covered similar companies or topics. Building a relationship with one industry journalist could lead to multiple mentions over time.
Example: The author has written 15 articles about SaaS tools in the past year and actively engages with industry leaders on LinkedIn. Even if this specific mention is brief, the relationship potential makes it worth prioritizing.
Page traffic and visibility
A backlink on a high-traffic page that ranks well on Google search engine results pages (SERPs) or gets cited often by LLMs like ChatGPT and Claude is significantly more valuable than one buried on a low-visibility page. Check if the page mentioning you receives regular organic traffic and has visibility for relevant keywords or prompts.
Use tools like Semrush or Similarweb (or even some simple keyword searches and LLM prompts) to see if the page appears in Google results for industry-relevant terms. Pages that rank on the first page of Google or get cited in LLM responses for competitive keywords and topics will drive more referral traffic and pass more authority.
Example: Your donor management tool is mentioned in an article titled “Best Donor Management Software for Remote Teams” that consistently ranks around the third position in the SERPs for “donor management software” (a keyword with 2,400+ monthly searches) and frequently gets cited when users ask ChatGPT or Claude about donor management tools. This page likely receives many monthly visitors from both traditional search and AI-driven discovery, making a link extremely valuable.
On the other hand, say your brand is mentioned in a deep blog post about the author’s personal nonprofit management setup, and the page has never ranked for any meaningful keywords, receives minimal traffic, and rarely appears in AI responses to productivity-related questions. While still worth pursuing if easy, landing a hyperlink here should be a lower priority than high-visibility mentions that perform well across both traditional search and AI platforms.
The best tools for unlinked mentions
When it comes to finding and tracking unlinked mentions at scale, Semrush offers two different tools that can guide your initiative in different ways: Brand Monitoring and Brand Performance.
Brand Monitoring is a powerful tool that can find and monitor unlinked brand mentions across the web, whereas Brand Performance measures and analyzes your brand’s mentions in AI-generated responses.
Let’s take a look at the specific capabilities of each tool to see how they can help you with the different stages of your unlinked mention outreach strategy.
Brand Monitoring Brand Performance
Primary focus Discovering and tracking brand mentions across the web Tracking AI platform visibility and competitive positioning on LLMs
Data sources News sites, blogs, forums, social media platforms AI platforms like Google AI Mode, SearchGPT, ChatGPT, Perplexity, and Gemini
Key strength Finding unlinked mentions across the entire web with real-time alerts Strategic analysis of brand perception in AI-generated responses
Mention detection Automatically identifies mentions with/without backlinks Analyzes brand mentions within AI conversations and responses
Competitor analysis Track competitor mentions and share of voice across the web Track share of voice and sentiment among top competitors in AI-generated responses
Important insights Sentiment analysis, estimated reach, domain authority, author information Sentiment tracking, topic associations, strategic recommendations, competitive positioning
Actionable outputs List of unlinked mentions ready for outreach Strategic recommendations for getting more mentions
Brand Monitoring: Mention discovery and tracking
Brand Monitoring excels at finding mentions across the entire web, and it has powerful filtering and alert capabilities to keep you updated in real time.
Semrush Brand Monitoring Scaled
This tool can be your primary discovery engine for unlinked mention opportunities: All you have to do is filter by mentions without backlinks:
Semrush Brand Monitoring Unlinked Mention Opportunities Scaled
Plus, not only can you monitor your own mentions, you can also check out what mentions your competitors are getting. Track your share of voice, monitor a brand, monitor people, or track any keywords of your choice.
Core features:
Multi-source coverage: Monitors news sites, blogs, forums, and social media platforms like Facebook, Instagram, TikTok, and YouTube
Advanced filters: Set up complex queries using “with all of these,” “with any of these,” and exclusion operators to find precisely the mentions you want
Real-time alerts: Get immediately notified when new mentions appear, negative sentiment is detected, or unusual spikes in coverage occur
Backlink detection: Automatically identifies whether each mention includes a link back to your site, making unlinked mentions easy to spot
Rich mention data: Each mention includes sentiment analysis, estimated reach, domain authority, and author information
Brand Monitoring is awesome for unlinked mention strategies when you need to:
Cast a wide net to find all brand mentions across multiple channels
Track how competitors are mentioned and identify content gaps
Track mentions around product launches, PR campaigns, or industry events
Set up automated alerts to catch new unlinked mentions as they appear
Monitor brand perception and prioritize positive mentions for outreach
The filters are an essential and valuable part of Brand Monitoring. Here are a few examples of how you can use them:
Backlinks filter: Use the backlinks filter to show only mentions without links to your site. This is an easy, quick way to find unlinked brand mentions.
Authority filter: With the authority filter, you don’t have to spend time looking up the authority of every domain. It’s included in the results! You might start by focusing on unlinked mentions on high-authority sites.
Sentiment filter: In general, you’ll want to prioritize positive and neutral mentions for outreach, without going for negative mentions at all.
Date range: Recent and evergreen mentions will be easier to target through outreach. To start, try focusing on recent mentions (like in the last 30-90 days).
Source type: Want to look at PR mentions first? Or maybe discussion forums? Use the source type filter to filter by news, blogs, or discussions based on your goals.
Brand Performance: AI platform market position analysis
Brand Performance is part of Semrush’s AI SEO Toolkit. Instead of traditional brand mentions across the web, it analyzes your brand’s visibility across the major AI platforms. It focuses on showing your competitive positioning amongst your competitors and provides actionable recommendations to gain more visibility in LLMs.
Semrush Brand Monitoring Search Scaled
This tool analyzes millions of AI conversations to reveal how your audience perceives your brand compared to competitors. Track your brand’s visibility, sentiment, and association with key topics across platforms like Google AI Mode, SearchGPT, ChatGPT, Perplexity, and Gemini.
Core features:
Multi-platform visibility tracking: Monitor how different AI systems interpret and respond to queries about your brand
Share of voice analysis: See how your brand is mentioned compared to competitors across AI platforms
Sentiment and attribute tracking: Understand the tone and attributes used to describe your brand in AI responses
Topic association mapping: Discover emerging topics and user interests connected to your brand
Competitive positioning insights: Analyze competitor strengths and weaknesses in AI-generated responses
Strategic recommendations: Get specific, actionable recommendations for refining your brand’s positioning, messaging, and product offerings
Brand Performance is awesome for unlinked mention strategies when you need to:
Identify unmet customer needs and market gaps that competitors may be overlooking
See whether your mention-linking efforts are improving your overall market position in AI platforms
Focus your mention-building efforts on topics that will have the biggest impact on AI visibility
Monitor long-term trends in your AI platform performance and competitive position
Can Brand Monitoring and Brand Performance be used together?
You can absolutely use the Brand Monitoring and Brand Performance tools together to create an incredibly powerful, brand-building workflow consisting of the two types of mention tracking.
Here’s an example workflow with both tools:
Monitor and discover: First, set up both tools to get baseline reports on traditional web mentions and mentions in AI-generated responses. How does your share of voice compare to your competitors for both mention types?
Unlinked mention outreach: Next, use Brand Monitoring to find and prioritize your unlinked mentions. Begin reaching out to those that provide the most link benefits.
Measure: Over time, use Brand Performance to monitor your mentions in AI-generated responses. Watch to see if unlinked mention outreach (combined with other GEO strategies) is helping to increase your brand’s AI visibility and improve your share of voice.
Optimize: Use Brand Performance insights to refine your Brand Monitoring queries and targeting, focusing on the types of mentions that improve both traditional SEO and AI visibility.
Level up: Use AI-powered workflows for unlinked mentions
Artificial intelligence can dramatically improve both the efficiency and effectiveness of unlinked mention outreach strategies, as long as you’re keeping a human touch involved.
Here are a few practical ways to put AI tools to work in your unlinked mention strategy:
Entity recognition at scale: Use AI-powered tools with named entity recognition (NER) to scan large content datasets for variations of your brand name, product names, and key personnel. This catches mentions that simple keyword searches might miss, including misspellings or informal references.
Sentiment classification: Apply AI sentiment analysis (like Semrush’s) to automatically categorize mentions as positive, negative, or neutral. This allows you to prioritize outreach to positive mentions while flagging negative mentions for your mitigation strategy.
Brandmonitoring Overall Sentiment Scaled
Outreach personalization: Tools like the AI Backlink Builder can analyze the publication’s writing style, recent content themes, and author background to generate personalized outreach emails that match the site’s tone and demonstrate genuine familiarity with their work.
Predictive conversion scoring: Train AI models on your historical data to predict which unlinked mentions are most likely to convert based on factors like site authority, author responsiveness, mention context, and relationship history.
Automated clustering and campaign planning: Group similar mentions by topic, publication type, or geographic region (like the mention filters you see in Semrush) to enable batch outreach campaigns rather than individual emails. AI can identify patterns that make certain mention types more likely to convert.
Remember, the key here is combining AI efficiency with human relationship building. Let technology handle the heavy lifting while you handle messaging and human connections.
Moving beyond traditional link building
By identifying, prioritizing, and converting unlinked brand mentions to valuable backlinks while building genuine relationships with the authors, you create a sustainable link building campaign practice that compounds over time. Beyond link building, brands that use unlinked mention outreach establish themselves as authoritative voices that naturally attract high-quality mentions and links.
Focus on providing genuine value across your outreach efforts, and you’ll find that unlinked mention outreach builds lasting industry relationships that benefit your SEO strategy for years to come.
Unlinked mention outreach is one valuable method of link building, but what are the others? Is link building still an SEO tactic you should prioritize? What makes a “good” backlink, anyway?
Wednesday, November 26, 2025
Unlinked mentions: Measure brand impact beyond links
YouTube dominates AI search with 200x citation advantage: Data
AI platforms overwhelmingly cite YouTube, while rivals like TikTok, Vimeo and Twitch barely register in search results, new data shows.
YouTube is cited 200x more than any other video platform in AI search results, according to new data from enterprise SEO platform BrightEdge. YouTube was:
- Cited 200 times more than any other video platform by ChatGPT, Perplexity, and Google’s AI products.
- Present across all platforms and essentially the only video source that matters.
- A top information authority, rivaling Mayo Clinic and Investopedia.
By the numbers. YouTube had a 200x advantage over its nearest rival (Vimeo at 0.1%). Even platforms like Perplexity and ChatGPT, which have no incentive to favor Google properties, overwhelmingly cite YouTube.
- 20% average YouTube citation share across AI platforms.
- 29.5% of Google AI Overviews cite YouTube – making it the top domain overall, ahead of Mayo Clinic (12.5%).
- 100% week-over-week growth for ChatGPT (though off a small base).
- 32.8% recent dip in AI Overviews citations, but YouTube still dominates.
By platform. Here’s a breakdown of YouTube’s performance across engines:
- Google AI Overviews: 29.5% citation share, #1 domain, average rank position 6.3.
- Google AI Mode: 16.6% share, #1 domain, average position 9.7.
- Perplexity: 9.7% share, #5 domain, 4.8% weekly growth.
- ChatGPT: 0.2% share, growing fast, average position 5.2.
Where YouTube showed up.
- Tutorials (finance, software, medical “how-to” content).
- Pricing, deal hunting, product demos, reviews.
- Less likely: career advice, strategy, abstract concepts, or pure informational queries.
Why it matters. If your brand isn’t creating video content, you may be invisible in AI search. YouTube isn’t just winning – it’s the only video platform that AI platforms appear to trust.
About the data. BrightEdge analyzed YouTube citation patterns across Google AI Overviews, Google AI Mode, ChatGPT, and Perplexity from May 2024 to September 2025 using its AI Catalyst platform. The study tracked citation rates, platform competition, query types, and week-over-week changes
Organizing content for AI search: A 3-level framework
Google's FastSearch and RankEmbed reveal why clarity drives AI visibility. Here's how to strengthen the signals that count.
Traditional search engines rely on countless ranking signals to deliver the most relevant answers to users.
In the age of AI, signals appear to be simpler – at least for now.
Court documents from Google’s antitrust case reveal that AI Overviews rely on lighter signals and fewer documents in the index.
However, content clarity and topical connections are more important than ever.
To be visible in the era of AI search requires content that is:
- Well-structured, so that relationships between topics are clear.
- Expertly written, so that the meaning and depth are obvious.
- Machine-readable, so entities and relationships are easy to interpret.
In other words, the same framework that has guided SEO for years – architecture, expert content, and optimization – is just as important today.
This article shows how each can reinforce the signals that matter most in AI search.
FastSearch and RankEmbed: A quick overview
In U.S. v. Google LLC, the court describes how Google’s FastSearch is used in grounding Google’s generative AI answers.
In short, the technology retrieves only a subset of search results and relies on lighter ranking signals.
From the court documents:
- “To ground its Gemini models, Google uses a proprietary technology called FastSearch. … FastSearch is based on RankEmbed signals – a set of search ranking signals – and generates abbreviated, ranked web results that a model can use to produce a grounded response. …FastSearch delivers results more quickly than Search because it retrieves fewer documents, but the resulting quality is lower than Search’s fully ranked web results.”
This could explain why some AI Overviews have surfaced low-quality content – a point that Ryan Jones made on LinkedIn:
The court describes RankEmbed as one of Google’s “top-level” deep-learning signals, capable of “finding and exploiting patterns in vast data sets.”
RankEmbed is designed to capture meaning by recognizing semantic relationships between queries and documents.
Dig deeper: The ABCs of Google ranking signals: What top search engineers revealed
Unlike other signals that measure popularity or count backlinks, RankEmbed focuses on how closely a piece of content aligns with the meaning of what the user asked.
And RankEmbed is a key part of FastSearch.
This could explain why FastSearch, which grounds AI Overviews, sometimes surfaces results that look different from traditional search rankings.
It prioritizes semantic clarity over other authority-type signals.
If RankEmbed is central to FastSearch, then the things that matter to AI visibility are those that strengthen semantic connections.
And those are the strategies I’m going to talk about next.
1. The foundation: A solid content architecture
How you organize the content on a site creates relationships, and those relationships make it easier for both search engines and AI systems to interpret relevance.
And at the same time, a clear information architecture allows website visitors to engage more deeply with a website, as it provides complete answers to questions along their search journey.
This is not a new concept. SEO siloing is something we’ve been doing at my agency for 25 years.
However, in the age of AI, it helps signal that a site is semantically clear and contextually relevant.
So what’s it all about? Let’s look quickly at this strategy in action.
Analyzing the business
The first step seems simple, but it’s surprising how much clarity it can offer when organizing a website’s information.
This step consists of analyzing the products, services, and types of information a brand provides.
We take this information as a starting point for more research.
That research includes looking at what topics the site is currently gaining visibility for in search results and what queries are triggering that.
Then, we look at missed opportunities. If the website were a book, what story would it tell? What chapters would naturally fit under that story? And what chapters are missing?
At the end of this research, you have:
- A roadmap for the structure.
- An understanding of how the content that’s already published fits in.
- A plan for the topics that need to be created.
Implementing the structure
A “silo” is the name for the structure. We call it a silo because it keeps topical themes tightly connected without being intermingled with other topics that dilute its relevance.
When topics are intermingled, it is confusing to users and engines. But when you begin to organize them, it creates clarity.
The structure can be formed in two distinct ways: either through the physical directory (URL structure) or virtual connections (internal linking).
Let’s look closer at those two tactics now.
Physical silos structure URLs that create a hierarchy of topical relevance.
If a company’s main focus is CRM software, the overarching theme would be “CRM Technology.”
Under that, categories could be based on the major functions or use cases customers care about, such as:
That’s three silos. Then, each category gets its own landing page, and is supported by subpages/subcategories that cover specific features or solutions.
For example, the sales automation silo might include:
- Main landing page:
companycrm.com/crm/sales-automation - Subcategories:
companycrm.com/crm/sales-automation/lead-scoringcompanycrm.com/crm/sales-automation/email-trackingcompanycrm.com/crm/sales-automation/opportunity-management
For this fictional site, this structure would signal to search engines/LLMs that the site is a good source on CRM software.
Virtual silos, on the other hand, connect related pages through internal links, even if they’re not in the same directory.
This is a good fit when the physical directory cannot be altered in any way.
It’s also an effective hybrid approach that forms relationships between content when the content lives outside of the physical directory, such as in a blog.
For instance, on a CRM website, a blog post about improving customer retention could link directly to the main customer support tools landing page, even though the blog lives in a separate /blog/ directory.
These contextual links build virtual silos.
Even if the blog isn’t physically nested under /crm/, the internal linking ties it back to the main theme and strengthens topical authority.
It also allows website visitors more opportunities to follow links and engage more deeply with the site as they continue on their customer journey.
The significance of siloing on LLMs
AI models are more likely to retrieve content that shows clear topic coverage and surface sites that demonstrate semantic consistency across related pages.
However, a bunch of content on a topic spread across the site is not going to build that authority on its own. It has to match intent and be linked properly.
The siloing strategy may seem quite simple on the surface. However, there are still many technical considerations.
Then there’s the matter of disruption. Siloing a large website is no easy feat. This is where partnering with an expert can be critical.
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2. Authority layer: True expertise
We are living in a world where AI content is starting to dominate the search results.
Some speculate that it won’t be long before expertly written, human-generated content will come at a premium.
And if that’s the case, it won’t be hard to stand out among the generic, machine-generated content if you put in the effort.
When creating content for your silos, each page needs to answer a query expertly, completely, and with additional resources to other areas of the site.
Think about how you can elevate your content, not just make it more efficient. In the age of AI, this will once again become a real challenge for many.
But we still have guideposts for doing this. So, let’s look at the baseline content strategies that will help a brand remain an expert.
Approach writing professionally
Hire people who are professional writers, even if they’re working with you to refine AI content.
They should inherently have a grasp of how to write well, and will navigate things like:
- Logical consistencies: Make sure to resolve any contradictions or conflicts in your content by thoroughly researching the topic and reviewing contradictory statements.
- Persuasive writing: You can always strengthen your arguments and ensure they are well-supported by using solid research and relevant examples.
- Accuracy: Be sure to verify the accuracy of your information through multiple reliable sources before publishing. Fact-checking is essential to avoid spreading misinformation.
- Ethical standards: Familiarize yourself with and adhere to ethical standards, including not plagiarizing and following search engine guidelines. Ethics around AI is a developing topic that SEO/GEO professionals should familiarize themselves with.
Dig deeper: Mastering content quality: The ultimate guide
Create helpful content, per Google
By now, most are familiar with Google’s guidance on helpful content, which includes useful self-assessment questions, such as:
- Does the content provide original information, reporting, research, or analysis?
- Does the content provide a substantial, complete, or comprehensive description of the topic?
- Does the content provide insightful analysis or interesting information that is beyond the obvious?
- If the content draws on other sources, does it avoid simply copying or rewriting those sources and instead provide substantial additional value and originality?
- Does the content provide substantial value when compared to other pages in search results?
Marketing leaders should treat these as foundational guidelines during any editorial review of content produced by an SEO/GEO program.
Uphold Google’s E-E-A-T framework
E-E-A-T is a holistic, quality framework for content.
But E-E-A-T must be earned over time through consistently delivering value and building genuine trust with your audience.
And it matters most for “Your Money or Your Life” (YMYL) topics.
You can earn E-E-A-T by things like:
- Offering original insights or analysis: Your content should provide unique, valuable perspectives outside of what everyone else is saying.
- Demonstrating firsthand experience or expertise: Authentic credentials and real-world knowledge matter. Incorporate anecdotes and professional guidance freely.
- Aligning with user intent: Focus on solving real people’s problems, not just chasing keywords and mass-producing content.
- Avoiding superficial templates or generic output: Authentic, thoughtfully crafted content always wins over a formulaic output (like content often coming from machines).
The bottom line is simple. Write for people first, and build trust over time.
Ultimately, it all comes down to one thing: creating good results for searchers.
Significance of quality content on LLMs
We know that being a subject matter expert is vital to ranking high in search. And we know that good SEO is needed for good GEO – at least that’s what Google’s Danny Sullivan says.
At his keynote at WordCamp U.S. in August 2025, Sullivan reiterated that:
- “SEO means you understand how people search for content and then you understand how to have your content there.”
He added:
- “Good SEO is really having good content for people.”
Remember that while not a direct correlation all the time, studies show there’s often overlap between high-ranking search results and AI Overview inclusions, even though the underlying systems use different signals.
In other words, there’s a good chance that if you are trusted in search, you will be trusted for inclusion in Google’s generative AI answers.
Some may argue that bad content written by machines is already visible in AI Overviews, so what’s the use of putting in the effort?
Well, first, because of ethics. We should uphold ethics in our marketing.
This has been my personal belief for decades, dating back to when black hats were gaming the system every day and winning.
Secondly, things can turn on a dime. Algorithms can change and content can be wiped from the face of the search results. Let’s not forget the March 2024 updates.
And in that moment, if you’ve done everything right, you have just been catapulted to the top, a spot that will not easily be taken back.
3. Signal layer: Structured data/schema
Structured data or schema is the layer that can help translate your content into signals that machines can better interpret.
This can make it easier for AI systems to connect the dots.
That said, some research suggests that it may not play a role in direct AI Overview visibility.
Even so, Google advises using structured data to ensure content performs well in Google’s AI experiences, and so it’s one of those practices that require experimentation.
Here’s what Google says:
- “Structured data is useful for sharing information about your content in a machine-readable way that our systems consider and makes pages eligible for certain search features and rich results. If you’re using structured data, be sure to follow our guidelines, such as making sure that all the content in your markup is also visible on your web page and that you validate the structured data markup.”
Many in the industry are already implementing or planning to implement schema/structured data as part of their GEO strategies.
The SEOFOMO State of AI Search Optimization Survey, 2025 Edition, shows that structured data/schema was most frequently mentioned as a way to optimize for AI search.
The challenge will be to implement the schema methodically.
For instance, don’t just use schema on your homepage or a few products; add it everywhere it makes sense.
However, don’t misuse, abuse, or overdo it.
Structured data should accurately represent the page’s main content, so choosing the most relevant type of structured data for the content is key.
(Remember that Google states structured data issues can trigger a manual action.)
And above all, test and validate.
Significance of structured data on LLMs
AI Overviews rely on understanding entities like people, places, products, organizations and concepts.
Structured data helps define those entities and makes it easier for search engines like Google (and its AI-powered technology) to trust the information.
Schema.org has been around for almost 15 years, so while it’s not a new tactic, it’s useful for clarifying content, even if its impact on AI visibility is still being tested.
Either way, structured data is resurging as a way to reduce ambiguity in the era of AI search.
Build clarity for lasting visibility
What does it really take to stand out in AI-powered search? The answer is clarity.
Clear structure, expertise, and signals help both your audience and search technologies connect the dots.
This is the kind of groundwork that search engines and AI systems depend on.
The bottom line is that you don’t need to chase every new GEO trick to succeed.
The fundamentals that have guided SEO for decades are still the path forward.
Focusing on a site’s information architecture, creating expert content, and using key optimization techniques like schema helps create connections that people, search engines, and AI systems can rely on.
Google sends 831x more visitors than AI systems: Report
AI bots outpace Microsoft Bing in traffic, but send almost no visitors, driving up publisher costs and fueling new content access battles.
Google sends publishers 831x more visitors than AI systems, according to TollBit’s State of the Bots Q2 2025 report. Even though AI referrals barely register next to Google’s, bots are hammering publisher sites — pushing costs higher, scraping more content, and often ignoring rules meant to limit them.
Scraping up, referrals down. AI is scraping the web, but it still isn’t sending meaningful visitors back.
- Google referrals dropped from 90%+ of all external traffic in Q2 2024 to 84.1% in Q2 2025.
- AI apps sent just 0.102% of referrals.
- For every visitor from an AI system, Google delivered 831.
- Click-through rates from AI interfaces were weak – 91% lower than top-10 organic search CTRs. It took about 135 AI scrapes to produce a single human referral.
- Publishers with OpenAI licensing deals saw 88% more scraping and significantly stronger referral rates than those without.
More bots up, less humans. AI bots are becoming a dominant force in web traffic, even as they deliver no value to publishers.
- Human visitors to TollBit-tracked sites fell 9.4% from Q1 to Q2 2025, while AI traffic rose.
- At the start of 2025, 1 in 200 visitors was an AI bot. By Q2, it was 1 in 50 – a 4x increase.
- AI bot traffic has now surpassed Bingbot, the world’s second-largest search crawler.
- Google’s AI Overviews expansion last October drove a 34.8% increase in Googlebot crawls, but the crawl-to-referral ratio worsened by 24.4%.
Content demand shifts. AI tools are shifting consumer behavior, answering questions directly instead of sending users to publishers.
- B2B/professional content saw the highest scraping levels relative to human traffic.
- The fastest AI request growth was for parenting (333%) and deals/shopping (111%) content.
- National news got 5x more real-time RAG scrapes than training crawlers.
- APAC sites were hit the hardest, receiving 3x more requests than U.S. sites, while European sites saw 27% fewer AI requests.
Bot wars escalate. Publishers are pushing back, but many AI bots are still breaking (or rewriting) the rules.
- Publisher blocking AI bots surged 336% YoY.
- TollBit’s Bot Paywall hits grew 360% between Q1 and Q2 2025.
- 13.26% of AI bot requests ignored robots.txt in Q2 2025, up from 3.3% versus Q4 2024.
- OpenAI’s 404 error rate jumped from 0.3% to 3.7%, often due to hallucinated URLs.
- Anthropic’s Claude error rate fell sharply after gaining live web access (from 55% in Q2 2024 to 4.8%).
Why we care. The open web appears to be in trouble. Human visitors are declining, while AI bots are multiplying, scraping more content, and sending back almost no traffic (which is why we’ve seen Cloudflare’s pay-per-crawl and RSL initiatives). If this continues, publishers will likely face higher costs and fewer returns (e.g., less clicks, customers, and revenue), which threatens the web’s business model.
Methodology. TollBit analyzed web traffic across its partner publisher network, tracking billions of requests to measure human visitors, AI bot activity, referral rates, and server responses from Q1–Q2
How to create product demos that convert and differentiate your brand
Great demos require empathy, practice, and competitive clarity. See how to turn presentations into powerful growth assets.
More than a sales tool, a product demo can be the moment your brand earns credibility and converts prospects.
A strong demo proves value in real time, turning curiosity into confidence.
Too often, though, demos fall flat – sounding like a scripted feature list instead of a compelling, conversational story.
This article shows how to create demos that resonate with real customer needs and differentiate your brand through empathy, consistency, and competitive insight.
Know your product, know the problem it solves
A demo isn’t about memorizing features. It’s about mastering the problem your product solves.
Without this deep understanding, you’re just delivering a monologue.
To build an effective, people-first demo that connects with real pain points, you need to become a subject matter expert on your product, inside and out.
- Get hands-on: Use the product yourself. Explore every feature and setting to understand its purpose and avoid technical glitches during a live demo.
- Talk to the team: Engage with product managers, engineers, and customer support. They have a great deal of practical knowledge that may not be in formal documentation and can provide crucial insights into how the product really works.
- Listen to customers: The most profound insights come from your users. Have direct conversations, read online reviews, and pay attention to feedback. This audience sentiment will reveal their needs, challenges, and how they actually use the product.
A demo’s success is determined by your mastery of the user’s problem.
When you show genuine empathy for their struggles, you transform the demo from a sales pitch into a trusted consultation.
Ask questions at the beginning stage of the demo if you haven’t met them before. This can help you tailor your demo to address specific issues the person is trying to solve.
Dig deeper: How to do audience research for SEO
The differentiator playbook: How to leverage competitive analysis
Every demo is a comparison in the buyer’s mind.
To stand out, you need to highlight your unique value proposition – and that starts with competitive analysis.
Done well, it’s more than research. It’s storytelling.
To conduct a targeted competitive analysis:
- Set clear goals: Define what you want to learn. Are you identifying unique selling points, uncovering pricing advantages, or spotting market gaps? Your goals should be measurable and aligned with your strategy.
- Identify your competitors: Look at both direct and indirect competitors. Direct competitors offer a similar product to the same audience, while indirect ones may solve the same problem with a different solution, like a water brand competing with a soda brand as a lunch-time beverage.
- Use the right tools: Use a blend of primary research (e.g., signing up for free trials) and secondary research (e.g., search engine analysis tools to see which keywords they’re targeting). Read online reviews to understand their strengths and weaknesses from a user’s perspective.
With this data, you can build a “differentiator-driven script.”
Your demo’s story should focus on a common pain point and show how your product uniquely solves it, especially where a competitor’s solution falls short.
Here’s a simple framework to organize your findings:
This is a great task for you to get help from your favorite generative AI tool.
I’ve built several competitive “battle cards” using Gemini’s deep research feature, which has been particularly helpful for this task.
During the demo, don’t talk about competitors’ weaknesses.
Focus on your product’s strengths, especially those that differ from other products the prospective customer may mention.
Dig deeper: How to analyze your SEO competitors to find opportunities
Get the newsletter search marketers rely on.
Consistency and practice: The foundation of a great presentation
A demo is a conversation, not a monologue, and practice is what elevates it from a memorized script to a fluid, conversational discussion.
Consistency, meanwhile, ensures that your brand’s tone, style, and messaging are unified across every touchpoint, from live demos to pre-recorded videos.
To perfect your demo:
- Ditch the script, embrace the dialogue: Scripts are a starting point, but your goal is to internalize the material so you can respond flexibly to real-time questions. Role-playing with a colleague is a great way to practice thinking on your feet and build confidence.
- Stick to the 3-point rule: Avoid overwhelming the audience with a “feature dump.” Instead, focus on demonstrating only the two or three core value propositions that directly address the prospect’s pain points.
- Build a single source of truth: A centralized repository for all brand assets, from slide templates to approved messaging, ensures every department, not just marketing, stays on-brand. This consistency can result in increased information retention for customers and sales.
- Use technology to scale: Tools like Marq or Prezent can automate brand compliance, allowing teams to create on-brand presentations instantly. This ensures your message remains cohesive even as the company grows.
Dig deeper: The complete guide to high-impact educational video content
Mastering the pivot: How to handle questions and concerns
An engaged prospect asks questions, which is a great sign.
It means they’re paying attention and considering your product’s value.
Handling these inquiries gracefully is a hallmark of expertise and professionalism.
- Respond verbally first: Instead of immediately jumping into the software, answer with a simple “yes” or a quick explanation. This addresses their curiosity without derailing your demo or losing control of the narrative.
- Park questions that don’t fit: If a question is too big or unrelated, acknowledge it and explain that you’ll “circle back to that at the end” or follow up afterward.
- Make a visible promise: Write the question on a notepad or shared screen to show the prospect you’ve heard them and won’t forget it.
- Create a high-value follow-up: Treat unanswered questions as opportunities to continue the conversation. Send a personalized email that directly addresses the concern, reinforcing your reliability and expertise.
The journey after a demo is just as crucial as the demo itself.
A speedy, proactive, and thoughtful follow-up keeps you top of mind and makes your potential client feel important.
Dig deeper: How to make engaging long-form YouTube videos
Winning demos start with the customer
A great product demo is a strategic asset grounded in empathy, insight, and consistency – not luck or charisma.
By knowing your product, understanding the competition, and delivering with a human-centered approach, you turn a demo into a growth engine.
The best demos always begin with the customer’s needs.
ChatGPT Shopping is here – and it’s changing ecommerce SEO rules
Ecommerce SEOs face a new channel: ChatGPT Shopping. See how structured data, product feeds, and reviews shape rankings inside ChatGPT.
AI-powered search is moving fast. The latest shift? ChatGPT Shopping.
Since April, OpenAI has been rolling out a shopping experience that surfaces product cards directly inside ChatGPT.
Instead of sending users to a long list of search results, the interface now provides curated recommendations with images, labels, and “buy” links.
For ecommerce SEOs, this is a new channel with very different rules.
Placement
isn’t driven by ads or bids, at least not yet. Instead, visibility
depends on the quality of product data, structured markup, and external
signals like reviews and mentions.
The implications are significant.
Results are condensed to just a handful of products, meaning if you’re not in the shortlist, you’re invisible.
As Kevin Indig observes:
- “The clicks that we get … are highly qualified because people will have all their questions answered through ChatGPT … then being sent out … close to a purchase decision.”
ChatGPT Shopping is already being tested across retail verticals, raising questions about traffic, conversion, and how optimization strategies will need to adapt.
Current impact on retail search
ChatGPT Shopping is no longer theoretical. It’s showing up in ecommerce analytics as a distinct referral channel. (In GA4, utm_source=chatgpt.com.)
While the traffic is still small compared to organic or paid search, the early patterns are consistent across verticals:
- Traffic volume is limited: For most retailers, ChatGPT contributes well under 1% of sessions. Even the highest performers in our data are nowhere near our other acquisition channels.
- Conversion rates are disproportionately high: Industry research backs this up. ChatGPT sessions convert at ~15.9% compared to ~1.8% for Google Organic, a Seer Interactive study found.
These benchmarks align with client data, which shows that traffic from ChatGPT converts 2–4 times higher than site averages.
While overall volumes remain small, the trajectory isn’t uniform across industries.
Vertical patterns worth watching
Early analytics and external studies point to three distinct vertical patterns:
- Electronics: High product demand and robust data feeds are leading to electronics brands showing up most consistently. Sessions are rising fastest in this category, and cards often mirror Google Shopping with specs, ratings, and review summaries.
- Food and grocery: Volumes are more modest, but users are steady. Engagement often reflects recurring purchase intent, and bottom-funnel queries like “best grass-fed beef box” or “healthy snack subscription” convert at strong rates when surfaced.
- Fashion and apparel: Traffic is lighter compared to other categories, but conversion rates consistently outperform site averages. When ChatGPT presents a shortlist of robes, dresses, or pajamas, shoppers clicking through are often ready to purchase.
ChatGPT isn’t a discovery engine at scale just yet. But when it does drive clicks, those sessions are among the most qualified in retail.
That’s because the user journey looks very different from a Google search.
Instead of scrolling through dozens of blue links, ChatGPT processes the query, breaks down the decision criteria, and then surfaces a shortlist of products.
What the current experience looks like
When a user enters a shopping-intent query such as “best smart home camera,” ChatGPT outlines factors like:
- Resolution.
- Night vision.
- Indoor vs. outdoor use before recommending specific models.
By the time a shopper clicks through, they’ve already worked through the decision-making criteria and are much closer to purchase.
This process highlights the real shift: the shopping experience inside ChatGPT looks and feels different from traditional search.
Instead of filters and menus, users refine results conversationally by saying things like “only in black” or “exclude Amazon.”
Follow-up questions trigger new, context-aware answers that help influence the purchase decision.
A key feature of ChatGPT is OpenAI’s memory capabilities.
With shopping, ChatGPT can reference past conversations and saved preferences to customize product offerings. These improvements already apply to free, Plus, and Pro users.
Clicking a card expands to a detail panel:
- A short AI explanation of why the product is recommended.
- Aggregated star ratings.
- Review counts.
- Purchase links from multiple retailers.
The takeaway is simple: Fewer results and more context mean that if your products don’t make the shortlist, they may as well not exist.
What’s next for ChatGPT Shopping
ChatGPT Shopping is still new but evolving quickly. Several shifts are already on the horizon:
- Sponsored placements: While results are organic today, many expect monetization to follow. Ads or eligibility costs (bids) may start playing a role soon.
- In-chat checkout: OpenAI has already launched Instant Checkout for Etsy, letting users buy without leaving ChatGPT. Earlier, Reuters reported a broader Shopify integration in development, with merchants expected to pay a commission.
Seeing how ChatGPT Shopping works in practice is one thing.
The bigger question is how SEOs are making sense of it, balancing the upside of highly qualified traffic with the frustrations of small numbers and fast-changing results.
Get the newsletter search marketers rely on.
How SEOs are framing it
Practitioners are stressing both the opportunity and the limits of ChatGPT Shopping.
While ChatGPT-driven traffic is more engaging than organic search, the volume still lags considerably, recent analysis from Siege Media shows.
The conversion quality may be undeniable, but the scale is not there yet.
At the same time, volatility is a recurring theme.
Since April 2025, ChatGPT Shopping results have undergone the most significant update since launch.
The format is evolving quickly.
Interface changes, new product labels, and shifts in how results are explained have already been implemented.
For SEOs, that means constant monitoring, as visibility can shift overnight.
Others are looking at the bigger picture.
In other words, this isn’t a side experiment.
ChatGPT shopping is here to stay and will be a structural shift in how product discovery happens.
Industry studies back up this sentiment.
A recent Semrush report found that:
- “The average LLM visitor is worth 4.4 times the average visit from traditional organic search.”
- “AI search visitors [will] surpass traditional search visitors in 2028.”
Even if ChatGPT Shopping referrals are a trickle today, the long-term direction is unmistakable.
For SEOs, the takeaway is straightforward: track it now and experiment with what improves visibility.
With so much still unsettled, the best way to understand ChatGPT Shopping is through practice.
Early experiments are already revealing what works, what breaks, and where the quirks lie.
Field notes: Early wins, misses, and quirks
ChatGPT Shopping still feels new.
The front-end is polished, but experiments by agencies, in-house teams, and SEOs show it’s unstable, inconsistent, and sometimes unpredictable.
Let’s see what really works and what doesn’t from the field.
What’s working consistently
- Complete product data matters: Brands with clean, fully populated product feeds are getting rewarded. Specifically, products with brand, model, variant, synced pricing and stock availability, and identifiers like GTIN/MPN are repeatedly surfacing for queries. An article from CleanDigital notes that product feed quality is one of the most immediate and valuable levers to pull.
- Schema and structured data help significantly: Sites using robust JSON-LD (Product, Offer, AggregateRating, FAQ) are more likely to be included, especially when schema is server-rendered instead of added late via JS. Wolfgang Digital’s guide confirms structured metadata is a major ranking signal in ChatGPT Shopping.
- Benefit-led content wins: Product pages that describe “who this is for” and “why it’s good” give the AI strong content to echo back (labels or short explanations).
- Public reviews and mentions increase trust. Product sentiment, review volume, and off-site mentions in blogs or forums help build labels like “durable,” “quiet,” and “budget-friendly.” ChatGPT pulls from third-party reviews, forums, publisher content, and merchant feeds.
Where things break down
- Variants are messy: Users asking for “black sneakers” may see navy; “king-size sheets” may pull “Cal King.” When variant info (size, color) is vague or inconsistent, mistakes happen.
- Price and stock lag behind: The displayed price sometimes misses promotions; stock is often out of date. Users click through and find “out of stock,” harming trust.
- Retailer order seems arbitrary: In purchasing options, listings appear driven by feed completeness or earliest indexed feed, not always best price or loyalty.
- Result volatility is real: The same query can return very different product sets even hours apart. For SEO tracking, this means rank reports are unstable and less useful.
Quirks and unexpected behavior
- Bing correlation: Products that do well in Bing Shopping are disproportionately likely to show up in ChatGPT. Bing feeds seem to be a key data source.
- Shopify edge: Shopify stores appear to enjoy advantages, such as streamlined catalog integration, easier feed management, and more consistently filled fields.
- Niche retailers rising: In tests, specialist merchants with strong product data and rich descriptions surface for competitive queries even over large generalist retailers.
What this means for practitioners
The patterns are still early, but the message is clear.
Products win when they deliver on four core pillars – what we can call the “FEED” method.
F: Full product data
Winners: Complete, consistent data across feeds and schema. Every GTIN, variant, and spec is accounted for.
Failures: Ambiguous variant labeling, stale feeds, or missing schema leave LLMs guessing and avoiding products altogether.
E: External validation
Winners: Reviews that are plentiful, fresh, and visible across multiple sites. Off-site mentions that reinforce credibility.
Failures: Thin brand presence outside the official site undermines trust and keeps products off the shortlist.
E: Engaging benefit-led copy
Winners: Copy that speaks in benefits and use-cases, not just specs. Framing around “who this is for” and “problems solved.”
Failures: Dry, specifications-only product pages that don’t tell a story fail to resonate with the AI or the buyer.
D: Dynamic monitoring
Winners: Teams who track appearance rates, monitor representation accuracy, and measure conversions post-click.
Failures: Relying on traditional rank tracking in a volatile system where today’s shortlist may be completely different from tomorrow’s list.
A new channel, a new playbook
For SEOs and ecommerce marketers, this is both frustrating and exciting.
Frustrating because traditional tracking tools don’t apply. Exciting because the playing field feels open.
Smaller brands with clean data and strong customer voices can break into conversations where they’d never outrank a big box retailer on Google.
The key is to treat ChatGPT Shopping like a new distribution channel. It’s not about tweaking meta titles.
It’s about feeding the AI a complete, consistent, and credible story across data, content, and customer proof.
Brands that adapt fastest will own the shortlist while others are still debating whether AI shopping is “real.”