How to Improve Brand Mentions in AI: A Data-Backed Guide [2026]

You rank on Google. You’ve got backlinks. Your domain authority is solid. And yet, when someone asks ChatGPT for a recommendation in your category, your brand doesn’t exist.

That gap between Google rankings and AI visibility is real, and it’s widening. Ahrefs studied 75,000 brands and found that branded web mentions across the open web are a far stronger predictor of AI visibility than backlinks, domain rating, or the number of pages on your site.

This guide breaks down what actually moves the needle, based on recent research, and what we’ve seen work with Quattr customers.

Why Google Rankings Alone Don’t Guarantee AI Visibility

Traditional SEO builds your visibility on Google’s rules. But AI search engines operate on a different logic. They don’t crawl, index, and rank. They read, synthesize, and recommend. 

What influences those recommendations isn’t your backlink profile, it’s how widely and consistently your brand gets mentioned across the open web.

The Ahrefs study confirmed what many GEO practitioners suspected: the top signal for AI visibility isn’t domain strength or link equity. It’s branded web mentions, by a wide margin. Backlinks, domain rating, and content volume all trailed far behind.

Kevin Indig’s research at Growth Memo landed on a similar conclusion: brand search volume is one of the biggest predictors for ChatGPT visibility. 

And Patrick Stox at Ahrefs has started calling this “the era of off-page SEO.”

The pattern is straightforward: the conversation happening about your brand matters more than the links pointing to your website. If your AI visibility strategy is still centered entirely on your own site, you’re optimizing for a game that already moved.

At Quattr, we’ve seen this firsthand with our customers. The teams seeing the biggest gains in AI citations aren’t the ones publishing more blog posts, they’re the ones showing up across more surfaces.

How AI Models Decide Which Brands to Mention

Before jumping into tactics, it’s worth understanding the mechanism behind AI recommendations.

AI models don’t sort a list of pages by authority and relevance the way Google’s algorithm does. They pull from training data, retrieval-augmented generation (RAG) pipelines, and live web results to construct answers. 

Your brand makes it into those answers when the model has built enough confidence, from repeated, consistent, contextual signals to include you.

Rand Fishkin’s SparkToro research (January 2026) tested this directly. His team had 600 volunteers run identical prompts through Claude, ChatGPT, and Google AI. Every answer was different in wording, but brand presence across responses was more consistent than expected. You can track brand frequency with statistical rigor, but “ranking” in AI is essentially meaningless.

What actually moves the needle is crossing what some researchers call the “corroboration threshold.” That’s the point where enough independent, credible sources say similar things about your brand that the AI commits to including you, rather than hedging or omitting you entirely.

Here’s a simple way to think about it. If only your own website says you’re the best project management tool for remote teams, the AI treats that as a marketing claim. But if G2, two Reddit threads, a Capterra comparison, a YouTube review, and a Forbes roundup all make similar points — that’s corroboration. That’s what builds confidence in the model.

How To Improve Brand Mentions

Build Your Off-Site Brand Mention Footprint

This is the single highest-ROI activity for AI brand visibility right now. And most teams are still underinvesting in it.

Ryan Law put this bluntly in a recent Ahrefs podcast (November 2025): unlinked mentions, plain text about your brand on other websites, have very little impact on traditional SEO. But they have a much bigger impact on AI visibility. 

LLMs understand brand authority from the prevalence of words, the co-occurrence of terms, and the context in which those words are used.

Tim Soulo, CMO of Ahrefs, went further and called citations “the new backlinks” for the AI era.

Several commenters on Rand Fishkin’s original LinkedIn post about co-occurrence made the same observation: this sounds like the re-emergence of public relations. They’re not wrong. 

Getting your brand mentioned alongside relevant industry terms in news coverage, podcast transcripts, conference recaps, expert roundups, and guest posts is exactly the kind of signal that builds AI confidence.

The difference from old-school PR? The goal isn’t just awareness with human readers. It’s building an information footprint that AI models can read, interpret, and rely on when constructing answers.

This is something we think about a lot at Quattr. Our platform connects AI visibility signals with SEO and content execution specifically so teams can identify where they need to be mentioned, and then take action on it, instead of just staring at a monitoring dashboard.

Get On the Pages AI Already Cites

Not all brand mentions carry equal weight. A mention on a random blog isn’t the same as getting included on a page ChatGPT already pulls from regularly.

The approach we recommend to our customers at Quattr: use AI visibility tools to identify which domains and specific URLs are most frequently cited in AI responses for your category. Then focus your outreach specifically on those pages.

Some practical ways to do this:

• Target existing “best of” and comparison listicles on high-authority domains that already appear in AI answers. Getting included on one of those pages is often worth more than publishing five new blog posts on your own site.
• Contribute expert quotes to industry publications. When journalists cite your team by name and title alongside a specific claim, that creates exactly the kind of entity-level signal AI models look for.
• Publish original data or research that others want to reference. If your study gets cited by three different publications, you’ve created three off-site mentions from a single asset. That compounds quickly.
• Pursue co-marketing content with brands that already have strong AI visibility. AI models notice co-occurrence, being mentioned alongside established names strengthens your own signal.

The strategic question isn’t “how do I create more content?” It’s “how do I get mentioned on the pages AI already trusts?”

Show Up Where LLMs Over-Index: Reddit, YouTube, and Review Platforms

Some platforms carry outsized influence in AI-generated answers. And the data is specific enough to act on.

SE Ranking’s research found that domains with active profiles on review platforms like G2, Capterra, and Trustpilot have 3x higher chances of being cited by ChatGPT compared to those without. Domains with meaningful Reddit and Quora activity performed even better.

YouTube mentions showed the strongest single correlation with AI brand visibility in the Ahrefs 75K-brand study (December 2025), outperforming every other factor across ChatGPT, AI Mode, and AI Overviews.

What this means in practice:

• Reddit and Quora: Don’t treat these as link-building channels. Participate genuinely, answer real questions, share specific experiences with your product, contribute useful frameworks. Both the platforms’ moderation and AI models filter out promotional noise fast.
• YouTube: Get your brand mentioned in video reviews, comparisons, and tutorials. AI models read transcripts. A mention in a well-watched video carries a signal very similar to a mention in a written article.
• Review platforms: A well-maintained G2 or Capterra profile with real customer reviews gives AI a third-party validation signal. Especially important for SaaS and B2B brands.
• Wikipedia: Harder to control, but if your brand qualifies based on notability criteria, having a Wikipedia page dramatically strengthens entity recognition in LLMs.

The point isn’t to be everywhere. It’s to show up, specifically, on the platforms AI over-indexes for your category.

Structure Your Own Content for AI Parseability

Off-site mentions drive most of your AI visibility. But your own content still plays a supporting role, especially for grounded responses where AI retrieves and cites live web pages.

The question is: can AI actually extract useful, citable information from your pages?

Growth Memo’s analysis of 1.2 million ChatGPT citations (February 2026) found that the majority of citations come from the first third of an article’s text. If your strongest claims are buried after a long introduction, the AI might never reach them.

Here’s what structuring for AI parseability looks like:

• Lead with your best claim. Don’t open with context-setting or question-restating. State your position or key finding in the first paragraph, that’s what gets cited.
• Use a clear heading hierarchy. H2s and H3s help AI models segment your content into retrievable chunks. When a model answers “what are the best practices for X,” it pulls from a specific section, not your entire guide.
• Add schema markup. FAQPage, HowTo, Organization, Product, structured data gives AI models explicit context about what your page covers and how your brand relates to the topic.
• Write definitively. Kevin Indig’s citation analysis found that AI favors journalistic, definitive phrasing over hedged language. “Tool X solves this problem for this audience” gets cited. “You might want to consider exploring tool X” does not.

This is core to how we approach content optimization at Quattr. Our platform scores content for AI readability and structure, then shows you exactly which pages need updates to become more citable, and lets you act on it without switching tools.

Keep Your Content Fresh (AI Rewards Recency)

Ahrefs analyzed 17 million citations (July 2025) across seven AI platforms and found that AI-cited content is meaningfully fresher than what appears in Google’s organic results. 

ChatGPT showed the strongest recency preference, consistently citing newer URLs over older equivalents. This doesn’t mean publishing new content constantly. It means maintaining what you have.

• Add new data points to existing articles. 
• Refresh case studies with recent results. 
• Update comparison pages when competitors ship new features. 
• And make sure your “last updated” timestamp reflects the actual recency of the content, AI crawlers read those signals.

Content freshness in the AI era is the most important part. The brands that treat their content library like a living product, not a set-and-forget archive, are the ones getting cited.

Quattr’s content freshness scoring helps flag exactly which pages are losing relevance and where a refresh would have the highest impact on both traditional rankings and AI citations.

Think Prompts, Not Just Keywords

AI engines don’t respond to short-tail keywords. They respond to full, conversational questions. If your content only targets “best CRM software,” you’re missing how people actually phrase requests in ChatGPT or Perplexity.

Find real prompts in three places:

• Google Search Console. Filter for long-tail queries with 8-12+ words. These often mirror how users prompt AI tools. GSC now captures AI Mode queries too, review them closely.
• Reddit and Quora threads. The way users phrase questions on these platforms is nearly identical to how they query AI models. Scan threads in your niche for natural-language phrasings.
• GEO platforms. With Quattr, you can track which prompts your brand already appears in across ChatGPT, Perplexity, Claude, and Google AI Overviews, and identify the gaps where competitors are getting cited instead.

Then shape your content around those full-sentence prompts. Frame H2s and H3s as questions. Write direct, complete answers within the first 2–3 sentences of each heading. Cover variations, as people ask the same question a dozen different ways.

The shift is simple: keywords are for Google, prompts are for AI engines.

Track AI Mentions and Measure What Matters

You can’t improve what you don’t track. And the measurement landscape for AI brand visibility has matured fast.

Platforms like Quattr, Ahrefs Brand Radar, and Peec AI now track how often, and in what context, your brand appears across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews. Some let you set up custom prompts so you can monitor the exact questions your buyers ask.

But here’s the nuance that trips teams up: don’t chase rank position in AI. It’s statistically unreliable. Focus instead on three things:

• Mention frequency: How often does your brand appear across a relevant set of prompts, compared to competitors? This is your AI share of voice.
• Sentiment: Are you being mentioned positively? A brand that shows up consistently but with negative framing has a visibility problem even if the numbers look good on the surface.
• Source diversity: Which pages and domains are feeding AI its information about your brand? If your AI visibility depends on a single outdated listicle, that’s fragile. You want a diverse set of sources corroborating your claims.

Track these regularly. AI responses shift fast. What sets Quattr apart here is the connection between monitoring and action. We don’t just show you where you appear, we tie AI visibility data to GSC, GA4, and first-party analytics so you can see which optimizations actually move the needle on traffic, engagement, and conversions.

This Isn’t a New Strategy; It’s Brand Building, Measured Differently

Here’s what makes this topic both exciting and frustrating: there’s no AI visibility silver bullet.

Every function in your marketing org already feeds into it. Your PR team earning media coverage? That builds branded web mentions. Your product team collecting G2 reviews? That builds third-party corroboration. 

Your content team publishing original research? That creates citable material. Your social team engaging on LinkedIn and Reddit? That generates exactly the kind of context AI models consume.

The brands winning in AI search right now aren’t running some secret GEO playbook. They’re the ones who built genuine authority across multiple surfaces, earned real mentions from diverse sources, and made their content easy for both humans and machines to parse.

That’s the same thing great marketing has always been. The difference is that now, for the first time, we can measure how machines perceive our brand, and use that data to close the gaps.

At Quattr, our whole approach is built on this principle: AI visibility isn’t a separate channel. It’s the measurable output of good marketing across every surface your audience (and the AI models serving that audience) can find you on. 

We built our platform to connect those signals, prioritize the highest-impact actions, and help teams execute — not just monitor.

The question for every marketing team in 2026 isn’t “should we invest in AI visibility?” You already are, whether you know it or not. The question is whether you’re doing it with intention.

To see Quattr in action, get in touch!

FAQs on How to Improve Brand Mentions in AI

1. Can I pay to get my brand mentioned in ChatGPT or Google’s AI Overviews?

Not directly. AI-generated answers are based on training data and retrieved sources, not paid placements. You can’t buy your way into a ChatGPT response the way you’d buy a Google Ad. The path to AI visibility runs through earning genuine brand mentions across authoritative sources, maintaining fresh and well-structured content, and building credible presence on the platforms LLMs draw from most.

2. How long does it take to see consistent AI brand mentions?

It depends on your starting point. Brands with existing web presence, active review profiles, and regular media coverage may see shifts within weeks of intentional optimization. Brands starting from scratch should expect a 3–6 month runway. AI models update their training data and retrieval sources on different schedules, so consistency matters more than speed.

3. Does blocking AI crawlers in robots.txt hurt my AI visibility?

Yes. If you’ve blocked bots like GPTBot, ChatGPT-User, or Google-Extended in your robots.txt, AI engines can’t access your content for retrieval-augmented generation. Even excellent content won’t appear in grounded AI responses if crawlers can’t reach it. Check your robots.txt before doing anything else.

4. Should I focus on ChatGPT, Google AI, or Perplexity first?

Each platform cites differently. Google AI Overviews correlate most strongly with traditional search rankings and brand signals. ChatGPT draws from a wider range of sources, including lower-ranking pages, making it a more accessible entry point for smaller brands. Perplexity leans heavily on recent web content. The best approach is to track your visibility across all three and prioritize based on where your audience is actually searching. Quattr tracks all of these in one dashboard.

5. Is traditional SEO still relevant for AI visibility?

Absolutely. There’s significant overlap between Google’s top organic results and AI citations. Strong SEO builds the domain authority, content quality, and web presence that AI models rely on when selecting sources. Think of SEO and GEO as complementary strategies — not competing ones. That’s why Quattr unifies both workflows in a single platform.