Optimizing LLMs for B2B SEO: An overview

Mohit Chouhan January 06, 2025
Optimizing LLMs for B2B SEO: An overview

We’re still in (very) early days for LLM (large language model) search, but fast-increasing user adoption is helping us draw insights on effective tactics for brands to deploy to appear in results on platforms like Perplexity, ChatGPT search, Gemini, and more.

This article looks at those tactics from a B2B lens, broken down by the following SEO initiatives:

Note that many of these tactics – but not all – should be familiar to SEOs who have experience with traditional search engines. 

Content strategy

The first step toward creating effective content for LLMs is to understand the nature of user queries. 

LLMs, more than traditional search engines, are host to conversational queries, like “How can I protect my business from ransomware attacks?” (where a similar Google query might be “ransomware attack protection for businesses”).

To adapt your content strategy, study the nature of the queries and create content that directly answers them. This includes conversational headings like “The best software to protect businesses from ransomware attacks.” 

In B2B, where the purchase journey is longer, it’s not as simple as optimizing for product-related queries; it’s essential to incorporate educational content to ease users into the awareness and engagement stages.

When it comes to the content itself, many of the principles of traditional SEO apply – particularly the need to go both broad and deep to establish authority and relevance. 

Incorporate supporting content like guides, case studies, and user testimonials. 

Make sure you’re working with pillar pages linking to in-depth blogs like “How CRM helps sales teams close deals faster.”

Remember that context matters a ton for LLMs for each piece of content (no matter the format). 

Optimize for nuanced, contextual responses by addressing multiple facets of a topic in the same piece. 

For example, a rich blog post for a fintech company could be titled “What is embedded finance? Benefits and challenges for SaaS platforms,” with subsections for: 

  • Benefits for startups.
  • Use cases in real-world scenarios.
  • Integration challenges and how to overcome them.

Semantic SEO

“Semantic SEO” is a relatively recent SEO initiative that means approaching content with respect to the full topic, not just keyword elements. 

In LLM SEO, the first item of semantic SEO is entity-based optimization, which includes:

For example, a cloud solutions provider can use schema markup to:

  • Mark up product pages with “Product” schema for solutions like “Cloud Data Storage Services.”
  • Build authority by linking to their business profile on Wikipedia, LinkedIn, and/or Crunchbase.

Because semantic SEO widens its focus from keywords, it’s essential to optimize for diverse phrases and synonyms instead of fixating solely on exact-match keywords. 

(You can use tools like Google Natural Language Processing or OpenAI embeddings to understand the relationship between tools.)

Let’s use a marketing automation platform as an example. 

Along with optimizing for a primary keyword, like “lead generation software,” include synonyms and variants like “Automated lead management tools” and “B2B marketing platforms.”

Dig deeper: ChatGPT search vs. Google: A deep dive analysis of 62 queries

Technical SEO

At this point, technical SEO for LLMs isn’t (by my understanding) all that different than technical SEO for traditional search engines. 

To increase your chances of showing up in LLM searches, tackle the following:

Data accessibility

  • Confirm content is crawlable and indexable by search engines and available for API integrations.
  • Optimize page speed and mobile performance for enhanced usability.

Structured data

  • Leverage structured data to signal intent and relevance clearly.
  • Implement detailed schema, such as “FAQPage,” “HowTo,” and “Product,” to improve how LLMs process your content.

User intent matching

Advanced SEO in both traditional search and LLMs incorporates an understanding of user intent into content. 

For B2B, this content should be strategically distributed across all stages of the buyer journey: awareness, education, technical understanding of solutions, and ultimately purchase intent.

For “instant” queries, provide actionable and direct responses, formatting answers in bullet points or concise paragraphs for LLM readiness while providing links to deeper resources. 

For example, a business offering AI-powered analytics can create content like: “What is predictive analytics in B2B?” and provide direct answers such as:

  • “Predictive analytics uses historical data to forecast future trends. For B2B, this helps identify potential leads and optimize sales strategies.”

Dig deeper: How to optimize for search intent: 19 practical tips

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Authority and trust

This is perhaps the area where we see almost no difference (yet) between LLMs and traditional search engines: establishing E-E-A-T principles is critical.

To do this (if you aren’t already), make sure your owned media:

  • Prioritizes experience, expertise, authoritativeness, and trustworthiness in all content.
  • Includes author bios, credentials, and citations to reinforce trustworthiness.
  • Cites reliable sources like Gartner, Forrester, or proprietary data studies.
  • Builds backlinks from authoritative domains to strengthen your site’s credibility.
  • Gains mentions in trusted publications to improve how LLMs perceive your brand.

For example, a logistics software company could secure backlinks from:

  • Industry publications like Logistics Management.
  • Mentions in business-oriented media like TechCrunch or Forbes.

Dig deeper: Decoding Google’s E-E-A-T: A comprehensive guide to quality assessment signals

AI feature optimization

This initiative is where SEO practices diverge most widely from traditional search engines. 

The way users interact with LLMs differs from how they interact with the Google search bar. 

For LLM-specific content enhancements:

  • Focus on content that answers “People Also Ask” and conversational follow-up queries.
  • Experiment with creating and optimizing content designed for direct API consumption.

For example, a tech consulting firm could create a resource hub for topics like “common cloud migration questions” with detailed Q&A formats that AI can surface easily.

If user behavior continues to feature more structured, question-based queries, make sure your content is designed to answer those directly. 

For example, a company specializing in ERP software can design content to appear for queries like:

  • “What are the best ERP solutions for mid-sized companies?”
  • “What is the ROI of implementing ERP software?”

Some LLMs (and we expect more to move in this direction) are multimedia-focused. 

For those, rich media integration – using videos, infographics, and charts to enhance engagement and improve content retrievability – will help spur inclusion in search results.

For example, a cybersecurity firm can enhance blogs with:

  • Infographics summarizing “5 types of cyberattacks businesses should watch for in 2025.”
  • Embedded videos explaining “How our threat detection tool works in real-time.”

Dig deeper: How to evolve your organic approach for the rise of answer engines

Continuous testing and adaptation

At this relatively early stage of LLM SEO maturity (and our understanding of it), continuous testing, measurement, and adaptation are among the most critical initiatives. 

At our agency, we focus on two fronts:

As you gather more information about what’s working, you can find common themes to deploy across your accounts. 

Dig deeper: How to cultivate SEO growth through continuous improvement

Optimizing for LLM-driven search in B2B

Because LLMs are in their infancy and because user behavior is changing so rapidly across the search landscape, find and regularly reference trusted sources to stay on top of trends and developments. 

In 12 months, this article might look woefully outdated, so it’s best to keep your finger on the pulse to adapt quickly.

Dig deeper: Decoding LLMs: How to be visible in generative AI search results



source https://searchengineland.com/optimizing-llms-b2b-seo-450180

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