Semantic SEO: The Advanced Skill Most SEOs Pretend to Understand
Semantic SEO may appear intricate, but it essentially revolves around executing SEO without shortcuts. It’s not a distinct form of SEO; no wildly different actions are required. Instead, it represents a mental framework that enhances:
- The processes followed to achieve goals
- The SEO objectives aimed for
- The approach to SEO strategy
This is a straightforward, no-hype guide on implementing Semantic SEO on your site.
We’ll explore what “semantic” means, how it applies to search engines and LLMs, and how we, along with these experts, execute Semantic SEO to deliver tangible results for clients.
What Does “Semantic” Mean?
The term semantic relates to “meaning.”
According to Oxford Languages, semantic is defined as “relating to meaning in language or logic.”
For instance, the word “dog” holds significance for us, while “asdf” does not—it’s just a random string of characters.
To machines, all words are random strings of characters. The field of semantics focuses on training them to interpret word meanings based on human usage.
Search engines don’t understand English; they understand code. Semantic SEO involves translating your meaning into their language.
Amanda King, Marketing & SEO Consultant at FLOQ
The more frequently a particular character sequence appears, the higher its likelihood of having meaning.
When two separate strings are often used together, they are likely related.
Notice the language being used—“more likely,” “higher the chance”—it’s all about probabilities and calculations since machines cannot truly understand like humans do.
Repetition and patterns in human word usage allow machines to infer meaning.
This forms the foundation of semantic search.
So, What Is Semantic SEO About?
Semantic SEO focuses on appearing in search engines and LLMs that display content or generate responses based on meaning rather than word strings.
They typically match topics in a user’s query with documents covering that topic well.
This differs from old-school search engines that match content based on exact words (like how Google Scholar works today).
The perspective shared by all senior SEOs we interviewed views it as an intersection between:
- Brand: Ensuring machines accurately understand and represent your brand.
- Content: Linking your brand to core topics you want to be recognized for.
- Technical: Guaranteeing your brand, content, and website are machine-friendly.
It zeroes in on how machines interpret your brand and content so they reference you accurately in more responses.
The Goals of Semantic SEO
Rankings and traffic have traditionally been primary goals of conventional SEO projects. However, these focus solely on whether a brand appears in search results.
The manner of appearance doesn’t matter because content is expected to be featured verbatim from the brand’s website. While Google uses varied formatting to emphasize relevant parts for users, it refrains from rewriting your material entirely.
For example, this search result displays the article’s opening sentence exactly:
Screenshot of a Google search listing result for Ahrefs’ multilingual SEO post.
Conversely, the goals of Semantic SEO are much more focused on how a brand is presented.
- Is the sentiment surrounding the brand mention favorable?
- Is the brand accurately portrayed and represented?
- Does it appear as an authoritative, reliable source for appropriate subjects?
- Is the brand’s thought leadership acknowledged and referenced?
These queries now hold importance but were traditionally overlooked.
This shift occurs due to how contemporary search engines and LLMs deliver answers. Thanks to AI functionalities, they can now rephrase a brand’s content into confident, authoritative prose. They may (and often do) assert inaccuracies confidently, unlike traditional search results.
Moreover, they tend not to quote your brand’s content verbatim.
Instead, they summarize your content based on their understanding and interpretation (much of which stems from others’ commentary on your brand or subject).
Thus, to perform SEO effectively today, one must grasp how search engines have evolved over time and what factors currently affect your brand’s visibility.
How Semantics Apply to Search (And Why Google’s Not Truly a Semantic Search Engine)
Search engines (and now LLMs) retrieve and present information to users through various methods.
- Lexical search matches word strings, similar to searching for an exact song lyric. It also considers words like “bat” and “bar” as alike due to identical starting character sequences.
- Semantic search predicts patterns and infers word meanings and their connections. Most LLMs utilize this method, explaining why they adeptly associate “hypoallergenic dogs” with “low shedding dogs” despite minimal lexical resemblance.
- Hybrid search merges both approaches, which most search engines use today, including Google and Baidu. This combination leverages the strengths of both types of searches by operating on a lexical foundation supplemented with some semantics.
The application of semantic techniques for information retrieval influences how your content and brand surface.
For instance, Baidu has developed both a lexical and a semantic index, allowing it to catalog content in both manners. Google has long used vectorization and heavily depends on semantic techniques during the reranking phase, just before deciding which results to display to a searcher.
Conversely, LLMs are predominantly semantic and seldom use lexical or hybrid approaches.
Will Search Engines Like Google Become Purely Semantic?
According to Olaf Behrendt (Senior Data Scientist at Yep) and Brandon Li (Machine Learning Engineer at Ahrefs), it’s improbable that Google or other search engines will become entirely semantic and supplant lexical search entirely for several reasons:
- Fully semantic results remain unreliable and untrustworthy.
- Exact match (lexical) search continues to dominate how people use Google.
- It’s prohibitively costly and resource-intensive.
Future advancements, particularly with features like Google’s AI mode becoming more prevalent, could alter this scenario. However, until then, keyword-level optimization will persist as a crucial foundation for appearing in traditional search outcomes.
Entity SEO (and other Semantic SEO methodologies) must augment your fundamental keyword approach to boost visibility in LLMs or AI-driven segments of search results, such as AI Overviews.
How Experts Actually “Do” Semantic SEO
While understanding all this theory is beneficial, you might wonder how to apply it. Remember, practicing Semantic SEO doesn’t necessitate anything different from regular SEO.
It represents a sophisticated mindset centered on optimizing for significance. It’s about being concerned with how your brand and content appear, not merely whether they do.
This is why Semantic SEO was highlighted as one of the premier advanced SEO skills in a recent survey among 100+ SEO professionals. Let’s examine how experts incorporate semantic thinking into common SEO practices.
1. Define Your Brand and Build a Universal Brand Guide
Creating a universal brand guide ensures your brand remains consistent across all platforms where it appears. This guide also helps everyone in your organization refer to the brand uniformly in all forms of communication.
A significant focus of Semantic SEO is ensuring that a brand is clearly defined and communicated since machines cannot deduce meaning solely from the brand name:
- Apple — might be associated with the fruit
- Nike — could be linked to the Greek goddess of victory
- Adidas — holds no semantic significance beyond its brand identity
Specifically, this involves the technical aspects of branding and formalizing your brand guide so that machines can accurately interpret who you are and what you represent.
More importantly, formalizing your brand allows you to instruct others on the appropriate way to reference you. Consider media kits, public logo files, and the correct or incorrect ways to abbreviate your brand name.
Sidenote: Formalizing here does not imply converting your brand into code. Instead, it refers to devising a well-considered plan or system for how your brand should be portrayed and documenting it in clear brand guidelines for both internal (company) and external (media) use.
For example, check out Ahrefs’ media kit, which simplifies the process for others to reference our brand consistently.
2. Add Keywords (and Meaning) to “Alphabet Soup” URLs
Have you ever managed a project where URLs were automatically generated by a CMS, resulting in something like site.com/kj72376g8js?
We refer to these as “alphabet soup” URLs since they consist of random characters that are nonsensical to both machines and humans.
Transforming these into user-friendly and search-engine-friendly URLs enhances SEO, though it can indeed be a challenging task. However, Semantic SEO can simplify this process!
For instance, you can utilize various tools that provide semantic insights about each page on the site, such as:
- Top ranking keywords
- Page titles and descriptions
- H1 headings
- Body content, and more.
To streamline things, we prefer using Ahrefs’ Top Pages report if the site has been operational for some time.
With a single view, you can link URLs to their highest-performing keyword and refine your strategy for modifying and redirecting URLs.
Additionally, for large websites, you gain built-in prioritization since you can sort pages based on:
- The traffic they currently receive: allowing you to enhance the performance of top pages or identify weaker ones needing attention.
- The number of keywords they rank for: enabling you to improve on-page optimization for pages with the highest potential for a quick traffic increase.
- The volume of the top keyword: helping you assess untapped potential due to inadequate optimization and prioritize pages with the most monthly searches.
3. Map Out a User and Search-Friendly Information Architecture
Many SEO professionals consider information architecture synonymous with “URL structure,” but it actually encompasses much more:
- Navigation + menus
- Internal linking
- Taxonomies (such as categories and tags)
- Labels for pages and categories
- Filters and faceted navigation systems
Traditionally, mapping out these elements is part of the UX design process. Where many designers falter is failing to align these components with the keywords that users search for.
Advanced SEO practitioners collaborate with design teams to ensure these elements are not only optimized for keywords but also semantically optimized.
Our methodology involves using the EAV model (entity-attribute-value):
What is it | Example in action |
---|---|
Entity | Represents the object or item you’re optimizing. Products, categories, users |
Attribute | This is a characteristic or feature of the entity Colors, sizes, materials |
Value | This is the specific information tied to the attribute Red, medium, cotton |
This approach is particularly beneficial for sites that need to organize collections of listings like:
- E-commerce stores (organizing product listings)
- Marketplaces (organizing marketplace items)
- Real estate (organizing property listings)
- Job boards (organizing job listings)
- Directories (organizing business listings)
The listings serve as the entities you’re optimizing for.
The collections of listings are generally where you’ll need to consider applicable features and attributes. The exact values you use will stem from keyword research. These typically include adjectives or descriptive modifiers found in keywords.
Most SEOs create collection pages based on these features. However, the best ones extend this practice to taxonomies (categories and tags), filters, and navigation elements. Even microcopy like page and product titles can benefit from including these attributes clearly.
For large sites with numerous listings, you can automate much of the tagging and labeling for your listings and their images with tools like Filestack. Many of its intelligence features are inherently semantic, as they interpret the meaning (and even emotions) behind images and text.
This is the key to sustained growth despite multiple algorithm updates. Here’s an example from one of our B2B e-commerce clients for whom we developed a semantically-optimized information architecture over four years ago.
4. Add Information Gain to Your Content
Incorporating information gain into content aligns with a Semantic SEO strategy, focusing on meaning, relevance, and contributing to a broader knowledge graph.
Content writing forms the backbone of most SEO efforts. However, traditional approaches (enforced by content optimization tools) typically involve:
- Examining what currently ranks
- Reverse engineering its on-page optimization
- Copying the blueprint and ensuring at least 10% is “truly original”
This often boils down to cramming keywords and entities into your content.
There are several issues with this method. Firstly, it’s the primary reason most SEO content ends up as just another indistinguishable drop in the sea of sameness.
Secondly, it’s essentially a slightly more nuanced version of keyword stuffing.
More advanced writers aim to do more than remix existing content. They strive to contribute something new to the conversation, ensuring their content truly stands out and benefits their audience.
This is why at Ahrefs, we adopted the approach of highlighting interesting and relevant topics in our AI Content Helper instead of providing a list of terms to squeeze into your content.
5. Close Page-Level Topic Gaps with Content Improvements
One of our favorite applications of Semantic SEO is closing page-level topic gaps when updating content.
Content updates are standard practice in SEO to maintain freshness. When you also address topic gaps, it becomes a semantic task because it involves covering meaningfully related concepts rather than merely sprinkling in missing keywords.
However, saying “add more topics” to content is one thing; knowing exactly what topics to add and precisely where and how to do it is another.
The simplest method is to explore Ahrefs’ AI Content Grader.
6. Create Clear, Structured Data with Schema and Semantic HTML
Structured data serves as a powerful data source for search engineers.
They can draw from various sources across the web, but you should meticulously optimize two on your website: schema markup and semantic HTML.
This perspective was echoed by Brandon, one of Ahrefs’ data scientists with extensive expertise in knowledge graph architecture. He highlighted structured data as a valuable dataset if it remains clean, well-organized, and used appropriately.
7. Use Links and Mentions to Improve Brand Sentiment and Reputation
Link building continues to be a crucial pillar in SEO. However, traditional SEO thinking has primarily focused on acquiring links.
As search engines become more semantic, merely obtaining a link or mention is no longer adequate.
Modern SEO practitioners increasingly consider the context surrounding these links, particularly regarding brand sentiment. Semantic search engines can now assess not only the meaning behind content but also the sentiment—positive, negative, or neutral—towards a brand.
8. Optimize All Entities Associated with Your Local Business
Local SEO often gets overlooked when delving into more complex topics like Semantic SEO and entity optimization. Nevertheless, significant opportunities exist here, especially when you move beyond traditional keywords and start optimizing the broader semantic context of your business.
The key is to go beyond just services and locations, which are typically the basics of local SEO, and thoroughly explore the details.
In essence, this is Semantic SEO because you’re assisting search engines in building a richer, more accurate understanding of what your business does by mapping out the complete set of related concepts, services, technologies, materials, and features.
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Final Thoughts
Ultimately, Semantic SEO simply means doing SEO properly.
Granted, there’s a technical aspect to it, but that’s true for all of SEO. It’s about how machines interpret who you are, what you’re about, and how your content fits into the bigger picture.
At the risk of sounding reductionist, if you’re engaging in “advanced SEO,” “LLMO,” “entity SEO,” “GEO,” or any other acronym people coin when optimizing for semantic information retrieval, it’s all Semantic SEO… which is regular SEO done correctly.