How to Get Recommended and mentioned by AI: A Practical Guide for B2B Marketers

LLMs like ChatGPT and Claude are already influencing buying decisions, we received a highly qualified lead direct from ChatGPT ourselves recently. When B2B buyers ask for recommendations, these tools give highly specific and relevant suggestions, and if your company isn’t one of them, you’re invisible.

The challenge with optimizing for AI recommendations is that it isn’t exactly SEO and it isn’t exactly PR, but it’s influenced by both. Until recently, we’ve had little more than anecdotal evidence on what works.

TL;DR – What the Research Says About AI Citations

Three major studies (Adi Srikanth, Ahrefs, Diggity Marketing) found that AI models like Google’s AI Overviews cite sources based on relevance, clarity, authority, and recognizability, not just domain size or backlinks.
Key patterns emerged:

  • Topical depth and intent alignment outweigh raw domain authority (Srikanth)
  • Brand authority signals like branded mentions, branded anchors, branded search volume are the strongest statistical indicators of inclusion (Ahrefs)
  • Organic top rankings matter. 91.4% of citations come from URLs in the top five results, but structure, clarity, and E-E-A-T also heavily influence selection (Diggity Marketing)

In short: be specific, be easy to quote, be visible, and be recognized.

Want to get into more detail? Let’s start by outlining what we know about being cited or recommended by AI.

How AI Optimization Works

Much of the current recommendations for AI optimization is what I would call “informed speculation.” Recommendations are based on theorizing how LLMs work, incorporating a few traditional SEO best practices.

Three notable studies analyzed AI Overviews and LLM recommendations to reverse engineer what situations trigger an AI Overview and what factors influence which brands are cited within them. The first study by Adi Srikanth focused on authority, search intent, and content. More recently, Ahrefs published a study that identified brand authority signals, and finally, Diggity Marketing published a case study with findings on how to structure and write content.

Let’s dive into each study one by one.

AI Overviews value authority, search intent, and content

Adi Srikanth’s study tracked 1,000 informational search queries across 10 industries, monitoring whether an AI Overview was triggered and which domains were cited. He then analyzed the cited domains for frequency in appearing in AIOs, domain authority (via Moz), overall organic search performance (via Semrush), and the use of structured data.

What he found was:

With AI Overviews, authority does not guarantee inclusion

High-authority domains were cited frequently, but authority alone was not predictive of inclusion. Some lower-authority domains still appeared prominently.

Relevance and context are strong signals to AI

Domains that deeply covered a specific topic or had highly relevant content performed better than more generalist sites—even if they had lower authority.

Niche domains can compete in AI Overviews

In certain verticals, smaller or niche players outperformed industry giants, suggesting Google’s AI systems prioritize content relevance and topical depth over just size or authority.

Structured content increases citation likelihood

Pages with clear, scannable formatting (like FAQs, how-tos, summaries) were more likely to be cited, supporting the idea that content structure aids AI comprehension.

Search intent alignment is critical for AI mentions

Content that aligned more precisely with the user’s search intent, particularly informational or educational, was featured more often than purely commercial or sales-oriented content.

Essentially, what he found was that tropical depth and specificity trump domain authority and that clear, structured, and intent-aligned content is where to focus your efforts. Additionally, where possible, using schema and smart formatting can help AI interpret your content and increase the likelihood of being cited as well.

More recently, Ahrefs released a study analyzing over 75,000 brands across 100,000 AI-generated responses and discovered strong correlations between citations and brand authority signals.

AI heavily relies on brand authority signals

As mentioned earlier, the key takeaway from the Ahref study is that brand signals had the strongest relevance for appearance in AI overviews. Specifically:

  • Branded web mentions
  • Branded anchors
  • Branded search volume

These weren’t just loosely associated; they were the most statistically significant indicators across the study.

We’ve seen the same trends reflected in our client work, particularly when comparing AI citation performance before and after brand or content investments.

With that context in mind, here are the three areas to focus on if you want to increase your chances of showing up in AI-generated buying recommendations or citations.

AI Overviews favor top rankings and clear, relevant content

Diggity Marketing’s study analyzed 10,000 keywords and 40,000 citations in Google’s AI Overviews and found that the algorithm leans heavily on existing organic rankings when selecting sources.

In fact, 91.4% of cited URLs ranked in the top five results for the query, making organic visibility the single strongest predictor of inclusion. Similar to the previous studies, they found that authority still played a role, with high Domain Rating sites appearing more often, but smaller sites could compete when their content precisely matched the search intent and was easy for AI to parse.

Key takeaways from the study:

  • Rank in the top five for your target queries to maximize inclusion odds.
  • Match search intent exactly with concise, direct answers.
  • Use structured formatting such as lists, tables, and headings to aid AI extraction.
  • Show E-E-A-T signals with expert bios, sourcing, and trust indicators.
  • Expect diversity, as most AI Overviews cite 3–5 different sources.

1. Deepen topical coverage with structured, intent-aligned content

The single most impactful thing you can do is improve your content.

LLMs rely on public information to decide who to recommend. If your site doesn’t clearly describe the specific problems you solve for the specific people you serve, you won’t be mentioned. General content won’t cut it.

LLMs excel at matching specificity. With traditional search, someone searching “secure file sharing for automotive engineering teams with complex permissions requirements and modest budgets” would struggle to find a useful result. Because of its specificity, the provider would need to create a specific page discussing that particular use case.

LLMs can develop a comprehensive understanding of your solution and make a recommendation based on nuances. This, of course, requires content on your website speaking to the nuances and specific use cases.

A client offering document automation for life sciences firms wasn’t being mentioned by AI when users asked for “document management platforms for FDA-regulated businesses.” We created a targeted page explaining their compliance-ready workflows, specifically for the life sciences industry. After publication, they began appearing in recommendation-style answers within 60 days.

To do this well, you need a solid understanding of your ICP. Interview your customers. Run win-loss interviews. Use keyword research tools like Ahrefs, Semrush, or AlsoAsked to study how real people describe their problems. Use SparkToro to better understand the language your audience uses and where they get information.

Focus your content strategy on use-case-specific pages and long-tail prompts.

For example, instead of targeting “expense software,” aim for queries like “expense tracking software for remote nonprofit teams managing grants.” Include subheadings that match the types of natural queries people use in AI tools, such as “Does this tool support grant reporting?” or “Can it automate multi-currency reimbursements?”

Focus on:

  • Specific verticals
  • Specific company sizes
  • Specific use cases
  • Specific integrations or features
  • Specific regions or industries

You don’t need dozens of pages. You need a handful of clear, confident explanations that reflect how your ideal customers would describe their problem.

2. Prioritize traditional SEO and create digestible and conversational content

As the Diggty case study shows, Google’s AI overwhelmingly relies on sites that are already winning in organic search. 91.4% of the URLs cited ranked in the top five for the query. That means your AIO strategy is, in large part, an SEO strategy.

There is more to AIO than traditional SEO; AI pulls from sources it can easily understand, trust, and quote. That means writing in a clear, conversational style, structuring information so it’s easy to lift directly into an answer, and demonstrating that expertise, authority, and trustworthiness.

Here’s how to put those findings into practice:

Double down on SEO for AI visibility

Even though the landscape of SEO is changing, it’s still vitally important for online findability. Now is not the time to take your foot off the gas; if anything, you need to invest more into your SEO strategy and efforts.

Answer AI Questions Directly

The study found that content that precisely addressed the search intent was far more likely to be included. Avoid burying the answer lead with it in the first paragraph and then expanding.

We recommend including a “Key Takeaways” or “TLDR” section at the top of an article or page that helps both humans and robots get the key insights without having to consume long-form content.

Structure content for AI

Use bullet points, numbered lists, tables, and descriptive headings. These make it easier for Google’s AI to pull clean, scannable snippets.

Additional examples include summaries, FAQs, pros and cons lists, and comparison tables. These help both humans and machines understand what you’re offering and why it matters in a specific context.

Demonstrate expertise, experience, authority, and trustworthiness

Search engines and AI aim to provide their users with trustworthy, accurate, and expert information. When either platform fails to do so, users lose trust in the platforms themselves and are less likely to use them in the future.

The three studies referenced earlier all validate that evidence of expertise, experience, authority, and trustworthiness (E-E-A-T) increases the likelihood of being included in both traditional search and AI.

You can demonstrate E-E-A-T by:

  • Including expert bios
  • Citing reputable sources (notice that’s what AI does at the end of every query?)
  • Linking to active social profiles
  • Demonstrating transparency on where you got your information
  • Discussing your own experiences
  • Creating content around a topic demonstrating knowledge and authority

Target a piece of the overview

Since most AIOs cite 3–5 sources, you can win by being the most relevant source for a specific angle, even if you’re not dominating the whole SERP.

3. Expand branded authority through mentions and search volume

According to the Ahrefs study, the most cited brands weren’t necessarily those with the most backlinks or the highest domain authority. They were the ones with the strongest brand presence.

There are two areas of brand authority you need to focus on, brand mentions and branded search volume.

Build brand mentions to increase AI traffic

According to the Ahrefs study, the more relevant and authoritative sources that mention your brand, the more likely it is to be mentioned.

To increase your brand mentions, start with:

  • Mentions in editorial content (press, roundups, expert quotes)
  • Listings in industry directories or association sites
  • Consistent review activity on platforms like G2, Capterra, Trustpilot

Branded mentions on relevant third-party sites also play a key role. This includes blog mentions, podcast appearances, being quoted in roundups, and being listed in industry-specific directories. When your name keeps appearing in contextually relevant places, LLMs are more likely to associate your brand with specific solutions.

Reviews are especially important because they offload risk. When LLMs recommend vendors, they tend to pick names that are widely cited and safely validated by other users. A high volume of recent, descriptive reviews on platforms like G2 or Trustpilot increases confidence in your brand as a low-risk suggestion.

How to increase branded search volume

As the name suggests, branded search volume refers to the frequency with which users search for your brand name on search engines like Google and Bing.

There is no single way to increase the number of times that your brand is searched every month. Content marketing, brand campaigns, and partnerships can indirectly drive search demand for your brand by name. Generally speaking, any activity that increases brand awareness will result in more branded search volume.

We previously ran a Google ad campaign for a cafe franchise that focused on brand awareness, and one of the strong indicators of success was the steady growth in branded search volume.

You can keep an eye on branded search volume through tools like Google Search Console, SEMRush or Ahrefs to see if your efforts are working.

4. Use Schema markup to help AI understand your content

Schema.org markup helps search engines and AI systems better understand the structure and purpose of your content. While it won’t guarantee inclusion, using structured data can improve how your content is interpreted, particularly for service-based businesses, FAQs, reviews, and articles.

Start with the basics:

  • Add schema for your organization, including name, description, and contact info
  • Use FAQ and HowTo schema where appropriate
  • Tag review content and testimonials with Review schema

We worked with a client that had strong blog content about compliance software added structured data to highlight service pages and FAQs. After implementation, their content began surfacing more consistently in AI answers that quoted specific feature sets.

Beyond the basics like Organization, FAQ, and Review schema, consider Article schema for blog posts, Breadcrumb schema for site structure, and Product or Service schema for core offerings.

Tools like Google’s Rich Results Test, Merkle’s Schema Markup Generator, or Yoast (for WordPress) can help with implementation. HubSpot users can embed schema via script modules or HTML blocks.

Make sure your structured data is clean, consistent, and reflects actual page content. When paired with semantic HTML, strong subheadings, and clearly labeled content sections, schema can make it easier for AI models to extract and understand the core message.

Schema won’t make you rank on its own, but it’s a smart, low-lift technical investment that supports the other levers that do, content and brand authority.

The Takeaways

If you want to increase your presence in AI-generated vendor recommendations, you need to do more than just rank—you need to be easy for AI to understand, trust, and reference. Based on the combined findings of the three studies:

  • Deepen topical coverage with structured, intent-aligned content
    Write to the exact problems your ICP describes in their own words. Create clear, use-case-specific pages with subheadings that mirror natural queries AI tools might see. Use bullet points, summaries, and schema to make information easy to parse and cite.
  • Pair traditional SEO with conversational, citable writing
    Strong rankings are the biggest predictor of inclusion, but the content has to be presented in a conversational, concise way that surfaces the answer immediately. Lead with the key takeaway, then expand.
  • Build branded authority
    Earn branded mentions on credible, topic-relevant sites, in industry directories, and through reviews on trusted platforms. Increase branded search volume with awareness campaigns, partnerships, and thought leadership.
  • Demonstrate E-E-A-T everywhere
    Include expert bios, cite reputable sources, show your own experience, and be transparent about where your information comes from. AI tools echo the same trust signals that humans look for.
  • Use schema markup to reinforce structure
    Tag core elements like organization details, FAQs, and reviews. This helps AI models (and search engines) understand your content and map it to user intent more precisely.

By combining these approaches, you’re not just improving your AI visibility—you’re creating content and brand signals that strengthen SEO, increase buyer trust, and make it easier for both people and algorithms to recommend you.