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The SEO world is shifting at an unexpected rate, and much of that change is driven by large language models (LLMs) like GPT-4. These AI advancements undoubtedly open up a plethora of opportunities for businesses and content creators, but they also pose new challenges.
Zero-click searches dominate results, reducing organic traffic as users find answers directly through AI Overviews and rich results. The rise of AI-generated content has raised the bar for quality, with search engines penalizing generic or thin AI-driven material. Add in hyper-personalized search results tailored to individual users, and SEO professionals are left navigating a complex digital playing field.
So, it doesn’t come as a surprise that over 57% of professionals report an increase in competition in the SEO space due to AI involvement. However, don’t let that discourage you. With the right strategies, you can achieve success in SEO, even with LLMs in the picture.
Maybe a few years ago, when ChatGPT was first introduced by OpenAI, you could ignore LLMs. However, the growth of AI language models is exponential, and we’re now in a time where SEOs must acknowledge their influence and incorporate them into their strategies.
In fact, those who have embraced LLMs are beginning to see the hazards of not doing so. In an SEOFOMO survey, 39% of SEOs said they felt threatened by AI Overviews, while 34% said that the adoption of LLMs to search instead of Google was a threat to their SEO consulting efforts. These findings indicate that it’s about time SEOs start focusing on LLM SEO to be prepared for the future of search.
Large Language Models (LLMs) represent a groundbreaking leap in how we approach SEO. These advanced AI systems, including trailblazers like GPT-4, ChatGPT, and Google’s Multitask Unified Model (MUM), are transforming search by processing language in ways that closely mimic human understanding.
It’s no longer like a traditional algorithm that would match your query with a page containing the same words. Instead, LLMs take your keyword and attempt to generate an answer through natural language processing. They look at everything from context to intent to deliver precise, personalized results.
Take Meta’s LLaMA as an example. It doesn’t merely work with a database of keywords; it has the ability to understand queries and context at an unprecedented level. The LLM breaks down the input text into smaller units called “tokens.” It then establishes a relationship between these tokens to understand their context. Finally, it generates a response, token by token, to cater to every aspect of the query.
This approach is far more advanced and superior to the one where an algorithm would look for your string or words on a web page and show it to you regardless of the context. It’s more like having a conversation with a human, where you ask a question and get a direct answer.
The SEO shift that we’ve explained above means that using the same old keyword optimization methods won’t work anymore and clinging to them can even harm your rankings. Google actively penalizes practices like keyword stuffing and over-optimization, as they detract from user experience and signal low-quality content. It’s time to move on to context-driven optimization. So, it’s keyword stuffing vs. intent-centric content, and the latter wins when it comes to LLM SEO.
But what does this mean for SEO strategies? Here are some actionable tactics that will help you adapt to this change.
“Make pages for users, not for search engines.” — Google, 2002
Our good advice then remains the same over two decades later. To succeed in Google Search, focus on people-first content.https://t.co/NaRQqb1SQx pic.twitter.com/bibv53icz9
— Google SearchLiaison (@searchliaison) July 6, 2023
Since LLMs have been around for some time, professional SEOs have figured out some best practices for optimizing for them. Below, we simplify the concept behind these tactics and then go on to explain how to put them into practice.
If you’ve had some experience using LLMs for search, you’ll notice how they don’t always bring up the top results from the usual keyword-based search. This means that some of the content ranking for long-tail queries might not rank as well when LLMs apply.
The difference lies in the way content was written traditionally and how it has been created now. LLMs don’t go for keyword-stuffed articles. Instead, they tend to show well-researched content that meets user intent. Their advanced understanding of language allows them to identify meaningful and nuanced information, rewarding pages that answer user queries in detail.
The way you structure and present your content also matters. LLMs analyze how content is organized to determine its topical relevance. Clearly defined sections, logical headers, tables, tags, and structured lists help LLMs “understand” your content more effectively.
Also, these models look for well-connected content. The more association there is between the content sections, the more likely it is that your page benefits from LLM-driven SERPs. For example, subtopics and potential follow-up questions help build this relationship to give your content the depth that LLMs use to judge its topical authority.
Some tools, such as the Semrush SEO Content Template, can create this content connectedness right off the bat. It gives your content the theoretical groundwork for an LLM-boosted search result. Rather than focusing on just isolated keywords, it encourages a focus on topic clusters, natural language patterns, and intent-driven organization. This way, it ensures that your content speaks to the user’s needs in the same way an LLM interprets and matches intent.
A successful example of this tool’s effectiveness comes from Why SEO Serious, an international SEO agency. They used the SEO Content Template tool to create outlines for their client’s (a local bakery) website. Combined with insights and assistance from other Semrush tools, the agency was able to rank its client in the top 10 search results for multiple keywords. The content based on the intent-driven outline is also likely to appear in AI Overviews (not yet live for client keywords as of now).
Keyword rankings
Traditional search engine algorithms relied on static keyword matching. In contrast, LLMs process user behavior, search history, and contextual factors to personalize results for every user. For example, Perplexity.ai, a conversational search engine that uses an LLM, has a ”contextual memory.” In simple words, if you ask follow-up questions, it will remember the context of your initial query and answer accordingly.
Perplexity AI’s Related Queries for “best laptop for students”
For SEOs, this means creating content to meet the individual search expectations of their target audience. Again, it’s a matter of focusing on intent and understanding the language patterns and topic clusters used by searchers. Your content needs to satisfy the contextual flow of a user’s search journey rather than solely answering their first question.
Since user preferences are always changing, an automated content optimization tool like the Semrush On Page SEO Checker can help you track how personalization affects rankings and highlight areas where you can adjust content to align it with search behaviors. These adjustments may be SERP features, new content ideas, semantic ideas, or strategic tweaks.
Semantic simply means ”relating to meaning in language or logic.” That’s what you need to keep in mind when conducting LLM SEO. LLMs analyze the relationships between words and topics for a more intuitive understanding of user intent. They consider context, synonyms, and even implied meanings to connect queries with the most relevant content.
This means when you search for ”best laptops for students,” you won’t just see web pages that have this keyword. The LLM will show content that provides suggestions based on a student’s laptop selection criteria, such as a reasonable cost, long battery life, and so on.
Since LLMs have taken SEO from single (or few) keywords to entire topics and clusters, you must follow suit. Your content needs to cover a topic’s breadth, which means covering all related subtopics and providing a comprehensive view.
For example, the Semrush Keyword Strategy Builder gives a pillar page suggestion based on your keyword list. It then breaks down the subtopics you should cover to provide thorough information on that topic. This way, you create a well-connected content hub that goes beyond single-topic coverage. These hubs not only improve user navigation but also help LLMs understand the hierarchy and associations within your content, making it easier for them to deliver your pages in response to complex queries.
The rise of zero-click searches, where users find answers directly on the SERP without clicking a link, means that people are no longer scrolling down to the actual organic results. LLMs interpret user intent with remarkable accuracy, helping search engines provide content-rich, contextually relevant responses right at the top of the page.
It doesn’t help that nearly 60% of searches result in zero clicks and of 1,000 searches, only 360 go to non-Google properties (organic or ad-paying). So, you’re working with about one-third of searches.
With such limited visibility, there’s a dire need to optimize your content accordingly. Content must now serve dual purposes: answering questions comprehensively while also aligning with the concise and structured format preferred for zero-click results. It should also be direct and concise because that’s what LLMs (and the searchers) want.
Answers should be direct and succinct, ideally between 40 to 60 words. The more directly your content addresses the query, the higher the likelihood of being pulled into a featured snippet.
Also, your content needs to address long-tail queries. Zero-click results often cater to specific questions such as, “What is the capital of France?” or “How to restart my S24 Ultra?” So, your content needs to be written for these keywords for it to appear in LLM-impacted zero-click results like AI Overviews.
Voice search is becoming common worldwide, with 25% of all internet users using voice assistants like Siri and Alexa on a weekly basis. When people use their voice to search the web, they’re no longer restrained by typing keywords and can use natural language. So, it’s no longer ”white shoes cleaning tips,” but ”how to clean white shoes at home.”
As evident, the search patterns have gotten more conversational. The queries are also longer and represent intent much better than typed keywords. Since LLMs understand the full scope of a voice query, they not only provide an accurate answer but also ensure its contextual relevance by accounting for factors like previous interactions.
In SEO, this mandates the need to answer questions people ask using voice search. For a business, these are queries people have about their products or services, such as how they work, who they are for, what their benefits are, and how they compare to competitors.
The focus needs to be on long-tail questions with natural language and conversational tone. These questions are likely to be picked up by voice assistants and featured as answers, especially when they’re asked in the form of a complete sentence.
You can optimize your content for these assistants and general voice search by using a tool like On Page SEO Checker. Since it identifies keywords that trigger SERP rich results (which are typically voice search answers), you can incorporate these phrases in your content to make it more voice-search-centric.
Based on the concepts we’ve covered earlier, let’s now look at actual tactics that will help you implement LLM SEO.
Before you go on to make changes to your SEO strategy, it’s important to audit it. The Semrush Site Audit gives you a snapshot of your domain’s technical health.
Semrush Site Audit
It covers aspects like site performance, international SEO, crawlability, internal linking, and so on. You should pay close attention to issues like slow loading times, broken links, missing meta tags, duplicate content, and crawlability since these can become hurdles in your LLM SEO efforts.
Semrush Site Audit
Semrush also provides recommendations to fix these issues. Prioritize the ones that are directly related to your site’s visibility in LLMs. For example, poor crawlability means that search engines will have difficulties in indexing your content, which could lead to lower rankings. Similarly, the absence of structured data (check in the Markup tab in Semrush), which LLMs use to understand the content, could be hampering your reach.
As we’ve explained earlier, the keywords you target for LLM SEO should be conversational and long-tail. So, focus on these terms in your keyword research.
The Semrush Keyword Magic Tool is quite helpful here. Simply search for your seed keyword, and the tool will suggest a list of related terms and their relevant metrics. You can either select long-tail keywords manually or use a filter.
Keyword Magic Tool
In the Advanced Filters tab, go to Word Count and select 3 to 5 (or higher if suitable) to get long-tail keywords. These longer and more specific phrases are likely to better target LLM queries.
Advanced filters in Semrush
Since the Keyword Magic Tool also shows you the intent for every keyword, you can better align your content with what the user wants to see. Similarly, you may filter keywords by intent, especially if you’re only focusing on creating content for a certain customer segment.
After you’ve selected a keyword, click on it to get more information in the Keyword Overview tool. Here, you’ll find long-tail variations of the term that you can use in your content to give it more context. Plus, the Keyword Overview tool shows question-based queries, which are likely to match LLM searches.
Keyword Overview tool
Enter the keyword/s you’ve chosen in the SEO Content Template tool. Taking insights and data from the current SERPs, the tool will create an in-depth outline that includes supporting sections to cover the topic from most, if not all, angles. The semantic relatedness of the suggested subtopics will make your content more appealing to LLMs.
When writing content within this outline, incorporate the long-tail keywords and question-based queries from both the Keyword Magic Tool and Keyword Overview tool. However, don’t just add them for the sake of it. Answer them in detail based on the intent behind them.
SEO Content Template
The SEO Content Template tool will also show you keyword variations that you can include to build semantic relationships between different sections. Besides comprehensiveness, make sure your content also has a good structure that an LLM can parse through easily. Use headers, sub-headers, bullet points, and numbered lists to break down your content. If relevant, you can also add a table or infographic to visually present data.
After you’ve published the content, wait for it to get indexed by search engines. Then, start monitoring its performance using the Semrush Position Tracking tool. You can set up a project for multiple keywords, depending on how much LLM-optimized content you’ve written so far.
Semrush Position Tracking
Track the performance of your content on a weekly or monthly basis, depending on how frequently you publish new LLM-focused content. Notice which keywords have had a positive impact on visibility gain and how much.
In the Pages tab, you can further see which pages have had a positive position shift. Monitor these changes to determine how your LLM SEO content is performing.
Semrush is one of the first tools to show you position data for AI Overviews. Keep a close eye on how many of your domain’s pages appear in these SERP results. Since these are generative search engine results, your content’s visibility here reflects its potential for appearing in other LLMs’ results.
Semrush Position Tracking
Don’t limit yourself to positive results only. Monitor which pages aren’t performing well and analyze why. The Semrush On Page SEO Checker can suggest improvements to your content to help it rank better. Make the suggested changes and then analyze the results again. If you notice improvements, replicate these tactics on other underperforming pages.
On Page SEO Checker
Since you’re dealing with an AI algorithmic system, it makes sense to use AI to optimize for it, too. For starters, AI tools can help with initial content research. The Semrush Topic Research tool is a good example. It finds topics related to your keyword on the general web or a specific domain. Plus, it provides optimized headings and questions for your content, too.
Next, you can use another tool to create an outline. The SEO Content Template is one such tool. Going further, you may even use AI content generation tools to write the content. However, don’t do this blindly; always review and edit the generated content. It’s better if you only use AI to write or complete sections rather than full articles.
AI tools also assist in keyword research by conducting detailed SERP analyses so that you can gauge relevant intent for every query. For example, you can create a keyword list using the Keyword Magic Tool and then use ChatGPT to develop content clusters. ChatGPT SEO strategies also include topical authority building, user behavior analysis, international SEO, and content repurposing.
You can also use ChatGPT for link-building, leveraging the tool for AI-assisted internal link suggestions and backlink outreach. Similarly, AI writing tools can generate FAQ sections for your content, which may increase its LLM visibility since voice searches usually contain full-length questions.
However, you shouldn’t just go with whatever AI tools suggest or create. There’s always room for error with these tools, so human oversight is a must. Again, you can use the On Page SEO Checker to find improvements and then implement them to optimize your AI-generated material, such as content drafts or keywords for ranking.
Go to the Idea Tasks tab and search for the URL you’ve optimized for LLM using AI tools. Then, see if Semrush has suggested an idea to improve it.
Semrush Idea Tasks
The potential and implications of LLM SEO may differ across industries. Some sectors are more prone to LLM searches, while others may not experience it as much. Here’s how stakeholders from every business can adjust their SEO strategies for generative results.
eCommerce businesses can use LLM SEO tactics that are most likely to impact their conversions. For example, nowadays, shoppers search with specific, conversational queries like, “What are the best vacuum cleaners for people with allergies?”
So, the product pages should be optimized for these search queries. Also, use descriptive product titles and FAQs tailored to buyer intent. It also helps to include high-quality pictures of your products since many LLM-based conversational search engines show images and videos, too.
You can also use LLM-driven insights to personalize shopping experiences for your customers. For example, Perplexity.ai shows Related searches for every query. These can be used to generate personalized suggestions for additional products that the user may be interested in, increasing the chances of cross-selling or upselling.
Related searches in Perplexity.ai
In our vacuum cleaner example, Perplexity.ai showed related searches like “HEPA vacuum for those on a budget” and “pros and cons of XYZ vacuum for allergy sufferers. You can use these insights to create a “Similar Products” section on your product pages. Plus, include feature lists and specifications for your items since LLMs are likely to pick this concise data rather than lengthy descriptions.
In healthcare, where searchers are looking for medical advice or solutions, trust and authority are non-negotiable. So, LLMs prioritize content from authoritative sources. This means healthcare websites must adhere to E-E-A-T principles. Providing credentials for authors, citing reputable sources, and keeping content up-to-date are critical steps to meet these standards.
It’s also important to create your content based on what users are searching for. LLMs may be remarkable at understanding medical jargon, but people search using layman’s terms. For example, someone might use “what is the best treatment for joint pain” instead of “what are the best osteoarthritis therapy options.” These are the keywords you should use in your articles rather than complex terminology.
You can find these keywords using the Keyword Magic Tool, just like Universal Health Services, a healthcare marketing agency, does. They also use the Topic Research tool to further find relevant keyword-centric topics that fit into a broader content cluster.
Source: semrush.com
Since the tool also provides relevant keywords and the most popular questions, the agency can develop its clients’ content to be super-comprehensive, which is just what LLMs want. They’ve been able to amplify their in-house campaigns and client success significantly with this approach.
Besides contextual content, LLMs are also more likely to show content that answers highly specific queries with user-friendly explanations. Think “How much magnesium should I take daily?” rather than general topics like “magnesium benefits.” Write your content in a way that answers these intent-specific questions, and then go into detail.
The tech and SaaS industries are highly competitive, which means that you’ll need more and continuous LLM SEO optimization. Doing this is even more important, considering LLMs are owned and operated by tech companies, so their results will often favor their parent company even if better options are available.
An interesting example of this comes from our own quick research. We looked for the best LLMs to search the web. Both Google Gemini and Perplexity.ai displayed themselves as the top results.
Gemini result
Businesses that make the same products or offer the same services as these top-ranked companies will need to have a strong LLM strategy to compete for visibility and traffic.
Perplexity.ai result
So, what’s the solution? Create in-depth and intent-driven content to answer your audience’s questions. Incorporate long-tail keywords in your content and focus on FAQ sections since LLMs tend to favor this type of content.
The return for all this optimization is worth the effort. FormulaBot, an AI-powered tool that generates Excel formulas appeared higher than Microsoft Excel’s own AI features in ChatGPT results.
Not only that, the tool’s appearance in LLM search results also resulted in customer interest and lead generation. So, tech and SaaS companies can actually improve conversions by optimizing their SEO strategies for LLMs.
While eCommerce sectors have to focus on description-specific keywords, the travel and hospitality industry needs to account for location-specific queries. Use conversational keywords in your content that pertain to certain tourist attractions in the area or popular places to stay.
For example, creating your content around ”what are the best hotels to stay in London with kids?” is a much more LLM-friendly approach than just ”best hotels in London.” Don’t just focus on the length but also the intent, which, in this case, is finding accommodations for families traveling with children.
Since you’re writing for LLMs, which have a knack for giving comprehensive answers to help improve user experience, consider including additional elements like travel guides, local tips, and recommendations within your content. You can collect these personalized recommendations from LLMs themselves.
Amy Stettler, a marketing executive, explains that this is exactly how Perplexity.ai helps her improve audience engagement and personalization. The LLM’s results give her an insight into readers’ interests and language predictability, which enables her to produce marketing material and content that keeps the audience hooked.
For example, if you search for the best hotels in London for families with kids in an LLM, it may further show you related searches like ”family-friendly activities in London.” It’s likely that people who first search for hotels then go on to look for kid-friendly things to do in the area. If your content already includes some of these activities, an LLM is likely to show it as the result of the user’s query.
Like in healthcare, businesses in the finance sector have to establish a certain level of trust and authority to be considered credible by people and search engines (traditional and LLMs). Besides long-tail queries and intent-driven content, financial services also have to optimize with two other tactics.
AI-driven changes, especially generative search results, demand a proactive mindset. Traditional SEO tactics alone are no longer sufficient; staying competitive requires an ongoing commitment to learning and adjusting.
SEO professionals need to shift their focus from static optimization to dynamic and responsive strategies. This means not only planning for now but also for the future. Predictive SEO can help you stay ahead of LLMs by anticipating user behavior and creating content that AI search engines are likely to show in the future; for instance, you can identify rising trends with tools like Google Trends and develop evergreen resources for recurring queries to maintain relevance as LLMs highlight new priorities.
In addition to predictive SEO, ongoing monitoring and analysis of AI-driven changes is imperative. For example, use Semrush’s On Page SEO Checker regularly to see how your LLM-optimized content is doing. Similarly, in the Position Tracking tool, focus on AI Overviews, People Also Ask, and featured snippets to ensure visibility in these prime real estate spots.
As new LLM-driven features continue to emerge, be prepared to learn and adapt to them quickly. Besides keeping up with industry news, you can also follow Google Search Liaison Danny Sullivan on X, where he regularly shares updates and insights on the search engine’s developments.
LLMs are not just transforming SEO but redefining it. By prioritizing user intent, contextual understanding, semantic relevance, and personalized search results, they have shifted the focus from traditional keyword-based strategies to more dynamic, value-driven approaches. Businesses that adapt by creating high-quality, semantically rich content and optimizing for evolving SERP features will position themselves as leaders going forward.
As we’ve explored, tools like Semrush can simplify this transition, offering robust insights and automation to streamline keyword research, content optimization, and performance tracking. You can even combine it with other AI tools to further enhance your LLM SEO strategy.
The bottom line is that SEO is now tied to AI and LLMs. So, the sooner you start adapting to these new technologies, the better equipped you will be to stay ahead.
In SEO, a large language model (LLM) is an AI model like ChatGPT or Google Gemini that can process and generate natural language. These models themselves act as search engines, providing intent-based answers to searchers. They can also serve as automation tools for SEO tasks like content generation and optimization.
LLM optimization refers to fine-tuning large language models like ChatGPT to perform specific tasks better. In SEO, it could mean training LLMs to perform certain SEO tasks like SERP analysis. The goal is to make the AI more accurate and useful for whatever purpose you’re using it for. On the flip side, it may mean optimizing your content so that it appears in LLM-generated search results.
You can use LLMs to generate content briefs, write meta descriptions, or create blog drafts that align with keywords. They’re also great for summarizing competitor research, analyzing search intent, brainstorming headline ideas, and generating insights from data. You may pair them with tools like Semrush to integrate them into your workflow for automating tasks like creating content clusters or backlink outreach.
LLM-based optimization is more focused on understanding and generating human-like content, whereas traditional SEO is about manually optimizing elements like keywords, backlinks, and page structure. Unlike conventional SEO, where optimum keyword use would be fruitful, LLM optimization requires intent-based keyword use and direct, comprehensive content.
Here are some tips for structuring your content for LLMs:
For businesses that optimize their content for long-tail, local keywords, LLM-based searches can improve their local SEO rankings. These businesses can benefit by optimizing for more natural language searches and focusing on local content, like adding location-specific keywords or reviews. It makes local search results more dynamic and aligned with what users are actually asking.
LLMs can consider customer reviews when generating search results. Positive reviews and frequent mentions of relevant keywords can boost a business’s visibility in search results. While LLMs don’t directly “rank” reviews, they contribute to overall content understanding, meaning reviews can influence how content is perceived by AI search engines.
To optimize for LLM-based search engines, use conversational language in your content. As for keywords, think about how people actually search, i.e., using full questions or phrases instead of just single keywords. Also, organize content with clear headings, bullet points, and FAQ sections to help LLMs extract the most relevant information. You can also implement structured data to contextualize your content.
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