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.