When someone asks ChatGPT, Google AI Mode, Gemini, or Perplexity for the best tools, products, services, or brands in a category, the answer may include only a small number of recommendations. That creates a new visibility challenge for businesses: what makes AI mention your brand instead of a competitor?
The honest answer is that there is no single AI ranking factor. Different platforms use different retrieval systems, data sources, search indexes, and model behaviour. However, recent research reveals several consistent signals associated with stronger AI visibility. Brands that are widely discussed, easy to verify, visible for relevant topics, and supported by useful evidence are far more likely to appear in AI-generated answers.
This article breaks down the most important data-backed AI visibility factors, what they mean in practice, and how marketers can use them to improve brand mentions in AI search.
The key takeaway
AI platforms do not simply reward the website with the most backlinks or the largest content library.
The data suggests that AI visibility is more closely associated with a broader digital footprint. This includes brand mentions across the web, branded search demand, topical relevance, credible evidence, useful content, and strong visibility across the search ecosystem.
In other words, AI is more likely to mention brands that appear to be genuinely known, discussed, and trusted within a category.
What counts as an AI brand mention?
An AI brand mention happens when a platform includes your business, product, or service within a generated response.
For example, a user may ask:
- What are the best affordable SEO tools?
- Which running shoe brands are best for beginners?
- What are the best project management platforms for small teams?
- Which accounting firms are recommended in Miami?
The AI response may name several brands, explain their strengths, compare them, or recommend one brand for a specific use case.
This is different from a traditional organic ranking.
Traditional SEO measures where a page ranks for a keyword. AI visibility measures whether your brand is included in the answer itself, whether your site is cited, how prominently you are mentioned, and whether competitors appear instead.
That is why AI visibility should be measured at the prompt level, not only through keyword rankings.
1. Brand mentions across the web are one of the strongest AI visibility signals
The strongest available evidence points to off-site brand mentions as a major predictor of AI visibility.
An Ahrefs study of 75,000 brands found that branded web mentions had the strongest correlation with appearing in Google AI Overviews. The correlation was 0.664, which was substantially higher than the correlation for backlinks at 0.218.
The same study found that brands in the highest quartile for web mentions earned a median of 169 AI Overview mentions. Brands in the next quartile earned only 14.
That is more than a tenfold difference.
This does not prove that every brand mention directly causes an AI mention. However, it strongly suggests that AI systems are more likely to recognise brands that appear repeatedly across articles, reviews, guides, forums, videos, publications, and industry conversations.
What this means for marketers
Your brand should appear in relevant conversations outside your own website.
A strong AI visibility strategy may include:
- Original research that journalists and bloggers can reference
- Digital PR campaigns
- Expert commentary in industry publications
- Guest contributions on relevant websites
- Inclusion in comparison articles and buying guides
- Product reviews from credible creators
- Community discussions where your brand is mentioned naturally
- Relevant YouTube videos, podcasts, and webinar appearances
The goal is not to create artificial mentions. It is to become a recognised entity within the conversations that matter to your industry.
This is where brand mention tracking becomes valuable. It helps you understand where your brand is being discussed, whether those discussions are positive or negative, and where competitors are gaining attention that you are missing.
2. Branded search demand and branded links matter more than raw backlink volume
The Ahrefs research found that branded anchors and branded search volume were also strongly associated with AI visibility.
A branded anchor is a hyperlink where the visible anchor text includes the brand name. For example, a link using the words “Seonoob keyword research tool” is a branded anchor.
The study found the following correlation levels with Google AI Overview visibility:
| Signal | Correlation with AI Overview Brand Visibility |
|---|---|
| Branded web mentions | 0.664 |
| Branded anchors | 0.527 |
| Branded search volume | 0.392 |
| Domain Rating | 0.326 |
| Referring domains | 0.295 |
| Backlinks | 0.218 |
This is an important distinction.
Backlinks still matter for organic search performance and can help establish authority. However, the data suggests that AI systems may respond more strongly to whether people actively talk about, search for, and reference a brand by name.
What this means for marketers
Do not focus only on earning links.
Build demand for your actual brand.
That may include:
- Creating memorable positioning and messaging
- Publishing tools, templates, calculators, and research assets
- Building a recognisable product category
- Running educational campaigns around a problem your audience cares about
- Encouraging customers to mention your brand in genuine reviews
- Appearing in industry newsletters, podcasts, videos, and expert roundups
- Publishing content that gives people a reason to search for your business by name
A brand with fewer backlinks but stronger awareness may still be more likely to appear in AI answers than a technically strong website that nobody discusses.
3. Traditional rankings still matter, but they are not the whole story
AI search has changed the role of traditional rankings. They still matter, but being number one for a single keyword does not guarantee an AI mention.
Seer Interactive found that first-page Google rankings had a strong correlation of roughly 0.65 with brand mentions in AI-generated answers. Bing visibility also showed a meaningful relationship.
However, newer research from Ahrefs shows that only about 38% of URLs cited in Google AI Overviews also ranked within the top 10 organic positions for the same query.
That means AI Overviews often use sources outside the direct top ten results.
This happens because Google may use a process called query fan-out. Instead of relying only on the original user query, the system can break a question into multiple related searches and retrieve supporting information from a wider range of pages.
For example, a user may ask:
What is the best SEO platform for a small agency?
The system may also explore related questions such as:
- What SEO tools have agency reporting features?
- What affordable rank trackers are available?
- Which SEO platforms include keyword research?
- What tools support AI visibility tracking?
- What are the best SEO tools for small marketing teams?
Your page may not rank first for the original query but could still contribute useful information to one of the related subtopics.
What this means for marketers
Do not create one generic page and expect it to win every AI answer.
Instead, build topical coverage around the real questions buyers ask before they choose a solution.
For a SaaS company, that may include:
- Product comparison pages
- Use-case pages
- Industry-specific pages
- Pricing and affordability guides
- Feature explainers
- Educational how-to content
- Buyer guides
- Alternatives pages
- Research reports
- Frequently asked questions based on real customer concerns
Use your keyword research process to identify the topics, questions, modifiers, and commercial comparisons that exist around your product category.
Then create content that gives a genuinely useful answer to those questions.
4. Evidence, statistics, and credible citations can increase visibility
One of the strongest controlled studies in this area comes from the Generative Engine Optimization research paper published at KDD.
The researchers developed a benchmark of 10,000 queries across 25 domains and tested different ways of improving source visibility within generative answers.
Their findings showed that adding relevant citations, quotations, and statistics could improve visibility by 30% to 40% on some evaluation measures.
In a real-world test using Perplexity, quotation additions improved one visibility measure by 22%, while statistics additions improved subjective impression by 37%.
The important point is not that every page should be overloaded with statistics.
The lesson is that AI systems appear more likely to use content that is verifiable, specific, and rich with useful evidence.
What this means for marketers
Create pages that provide evidence instead of broad claims.
Weak content often says:
Our platform helps businesses improve SEO results.
Stronger content says:
Our platform helps marketing teams monitor brand mentions, prioritise keyword opportunities, and track visibility across AI-generated answers using prompt-level reporting.
The strongest version adds proof:
In a study of 75,000 brands, branded web mentions had a stronger relationship with AI Overview visibility than backlinks, suggesting that off-site brand awareness may play a meaningful role in AI discovery.
Useful evidence may include:
- Original survey data
- Internal product data
- Benchmark studies
- Customer research
- Expert interviews
- Industry reports
- Government data
- Academic research
- Product comparison tables
- Clear methodology notes
- Transparent source citations
This is especially important for research-based content, product comparisons, finance, health, legal topics, and any category where users need to trust the information they receive.
5. Topical relevance and complete answers matter more than surface-level optimisation
AI platforms are designed to answer a question, not simply match a keyword.
A recent controlled study involving 252,000 tests across six language models found that topical relevance was one of the strongest factors affecting whether a source was cited first. The study also found that explicit pricing, recent timestamps, completeness, and trust signals could improve citation likelihood in certain contexts.
This supports a simple principle: content should directly answer the question behind the prompt.
A page about “best project management tools” should not only mention project management software. It should explain:
- Who each tool is best for
- Key differences between options
- Pricing considerations
- Main features
- Common limitations
- Use cases
- Alternatives
- Decision criteria
AI systems are more likely to use content that helps them construct a complete answer.
What this means for marketers
Write content that reduces uncertainty for the user.
Ask these questions when creating a page:
- Does this page directly answer the main question?
- Does it explain the decision criteria?
- Does it include useful facts rather than vague claims?
- Does it compare relevant options fairly?
- Does it acknowledge limitations where appropriate?
- Does it contain current information?
- Does it provide a perspective that is difficult to copy from generic AI-generated content?
The best AI visibility content is rarely the most keyword-heavy content.
It is usually the content that is most useful when someone needs to make a decision.
6. YouTube and multi-format brand discussions can strengthen visibility
Ahrefs found that YouTube-related brand mentions had the strongest correlation with AI visibility across ChatGPT, Google AI Mode, and AI Overviews.
This does not mean every business needs to publish videos constantly.
It means that when a brand is actively discussed in videos, titles, descriptions, reviews, and educational content, that broader visibility may contribute to its recognisability across AI systems.
At the same time, Seer Interactive found that simply adding more content formats did not automatically improve brand visibility. The difference is important.
Creating a random video for every blog post is unlikely to help.
Creating useful videos that answer real buyer questions, demonstrate products, review tools, explain categories, or generate discussion may help because the brand is becoming more visible in meaningful contexts.
What this means for marketers
Use video as a distribution and education channel, not as a checkbox.
For example, Seonoob could build video content around:
- How to track your brand in AI search
- How to find keyword opportunities for a new website
- How to build an AI visibility reporting workflow
- How to measure competitor share of voice in AI answers
- How to turn keyword research into a content plan
- How to monitor brand mentions without manually searching the web
These videos can support product discovery, reinforce topical authority, and create additional surfaces where your brand is discussed.
7. Technical SEO remains essential for AI visibility
AI visibility does not replace SEO fundamentals.
Google has confirmed that pages need to be indexed and eligible to appear in Google Search before they can be shown as supporting links in AI Overviews or AI Mode.
Google also recommends maintaining crawlability, internal links, useful text content, relevant images and video, strong page experience, and accurate structured data.
This means the basics still matter:
- Important pages should be indexable
- Content should not be blocked by robots.txt or technical errors
- Internal links should make key pages easy to discover
- Important information should be available as text
- Pages should load reliably and work well on mobile devices
- Structured data should match visible content
- Duplicate and thin pages should be reduced
- Product, business, and pricing information should remain accurate
Google also makes it clear that there is no special markup, special AI file, or shortcut that guarantees visibility in AI search.
You do not need to create content solely for every possible AI query variation. You do not need to rely on artificial mentions. You do not need to use keyword stuffing.
The better long-term strategy is to create useful content that people and search systems can understand, access, and trust.
What does not appear to work well
The available research suggests several tactics should not be treated as shortcuts to AI visibility.
Publishing large volumes of low-value content
Ahrefs found almost no relationship between the total number of pages on a site and AI visibility.
More pages do not automatically create more AI mentions.
Chasing backlinks without building brand awareness
Backlinks still have value, but the relationship between raw backlink volume and AI visibility was weaker than the relationship with brand mentions, branded links, and branded search demand.
Keyword stuffing
The GEO study found that keyword stuffing performed worse than the baseline in its real-world Perplexity testing.
Creating artificial brand mentions
Google warns against pursuing inauthentic mentions simply to manipulate AI search visibility.
Treating one AI platform as identical to another
ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, and other systems can produce different answers for the same prompt.
That is why prompt-level tracking and competitor analysis are essential.
A practical AI visibility framework for brands
A practical strategy can be broken into five steps.
Step 1: Measure your current AI visibility
Start with a focused list of prompts that reflect how customers discover your category.
Include prompts across different stages of the buying journey:
- Educational prompts
- Problem-solving prompts
- Best-of prompts
- Comparison prompts
- Alternatives prompts
- Local prompts
- Industry-specific prompts
- Pricing prompts
- Feature prompts
Track whether your brand is mentioned, cited, recommended, or excluded.
A consistent LLM rank tracking workflow helps you monitor these changes over time instead of relying on one-off manual searches.
Step 2: Identify the competitors winning the conversation
For every important prompt, identify:
- Which brands are mentioned most often
- Which websites are cited
- Which topics competitors own
- Which sources appear repeatedly
- What evidence competitors provide
- Whether their pages are more specific, more current, or easier to understand
This gives you a practical content and brand-building roadmap.
Step 3: Build evidence-first content
Prioritise pages that include original value.
Examples include:
- Industry benchmark reports
- Data studies
- Product comparison research
- Customer survey findings
- Expert commentary
- Detailed implementation guides
- Use-case libraries
- Templates and checklists
- Case studies
- Transparent pricing and feature pages
Generic summaries are easy for AI systems to recreate. Original evidence is harder to replace.
Step 4: Earn genuine discussion beyond your website
Create reasons for other people to talk about your brand.
Focus on useful ideas, tools, data, and expertise that others can cite.
This may involve digital PR, partnerships, creator outreach, expert interviews, guest contributions, webinars, product reviews, and community participation.
Step 5: Track changes and refine your strategy
AI answers can change frequently based on model updates, fresh sources, search behaviour, prompt wording, and competitor activity.
Monitor your priority prompts regularly.
When visibility improves, identify what changed. When visibility declines, investigate which competitors or sources replaced you.
This is where a structured workflow using LLM rank tracking, keyword research, and brand mention monitoring can help you turn AI visibility into an ongoing growth channel rather than a guessing game.
Final thoughts
The brands that win in AI search will not necessarily be the brands with the most pages, the most keywords, or the most backlinks.
They are more likely to be the brands that are genuinely visible across the web, closely associated with relevant topics, supported by useful evidence, and easy for AI systems to verify.
AI visibility is not separate from brand building. It is brand building measured through a new interface.
Build useful content. Publish original research. Earn genuine mentions. Maintain strong SEO foundations. Track the prompts that influence your buyers.
Over time, those signals give AI systems more reasons to recognise, cite, and recommend your brand.
