LSI (Latent Semantic Indexing) keywords are words and phrases that help search engines understand the context of a page, not just the keyword.
In SEO, related terms help prevent shallow content, encourage broader topic coverage, target a wider range of keywords, and demonstrate to both search engines and users that you have expertise in a particular subject.
Here is a fact that may surprise many SEO professionals: Google has not used LSI for a very long time.
Don’t worry! I also thought LSI keywords existed for quite a while! 😂
- LSI Keywords and Modern Search Algorithms
- What Does Google Use Today?
- The Modern Interpretation of LSI Keywords
- Why Does Google Value This?
- Polysemic Words
- Why Do People Still Search for "LSI Keywords"?
- How to Find Topical Keywords and Related Terms
- Topical Keywords and Topical Authority
- Final Thoughts
LSI Keywords and Modern Search Algorithms
The term LSI, or Latent Semantic Indexing, refers to a mathematical method developed in the 1980s to help computers understand that different words can have similar meanings and may function as synonyms.
Today, Google relies on far more advanced machine learning systems, including BERT, RankBrain, and MUM.
These systems do not simply look for synonyms or words that frequently appear together. Instead, they analyze context, user intent, and relationships between entities to determine whether content truly answers a user’s query.
What Does Google Use Today?
Google has long moved beyond understanding individual words and now focuses on understanding context.
I already mentioned the main models, but let’s briefly look at each of them.
RankBrain
RankBrain was Google’s first large scale integration of machine learning into its ranking systems. It was introduced in 2015.
Its primary purpose was to help Google interpret search queries that it had never seen before or did not fully understand.
RankBrain connected unfamiliar words and phrases with concepts the algorithm already understood, allowing Google to better determine user intent and deliver more relevant search results.
BERT
BERT represented a major breakthrough in natural language processing (NLP).
Introduced in 2019, BERT significantly changed how Google interpreted search queries.
The model enabled Google to analyze words within their surrounding context rather than as isolated terms. It considers the words that come before and after a specific term, allowing the search engine to better understand the true meaning of both queries and content.
MUM
MUM was the next major step forward.
Introduced in 2021, it is substantially more powerful than BERT.
The key characteristic of MUM is that it is a multimodal model. It can understand not only text but also images, videos, audio, and other types of information simultaneously.
As a result, Google can analyze information more deeply and develop a more complete understanding of both page content and user intent.
These types of models form the foundation of Google’s modern search systems and allow the search engine to understand context, entities, and meaning far more effectively than was possible during the era of simple keyword matching.
The Modern Interpretation of LSI Keywords
You might ask: if Google no longer uses LSI, why write an article about it at all?
The answer is simple. The term became deeply embedded in SEO culture. Many SEO professionals entered the industry decades after the original technology was created, yet the term remains widely used today.
The reality is that when marketers and SEO specialists talk about LSI keywords, they are usually not referring to true Latent Semantic Indexing.
Instead, they are talking about topical words, entities, and contextually related terms. In other words, words and phrases that naturally belong to the same subject area as the primary topic.
In the past, LSI keywords were often described as synonyms or closely related words. Today, the term is more commonly used to describe words that belong to the same topical ecosystem.
For example, if the primary keyword is “mountain bike”, related topical terms might include suspension, frame, drivetrain, braking system, tire tread, fork, wheel size, and many others.
The more relevant topical vocabulary you naturally include in your content, the more comprehensively you cover the subject.
These terms can be common industry phrases, rare technical terminology, highly specialized concepts understood only by experts, or even slang expressions frequently used by professionals and real users.
As a result, search engines gain a stronger understanding that the author genuinely knows the subject and speaks the language of the audience.
Why Does Google Value This?
Google relies heavily on its Knowledge Graph.
The Knowledge Graph is a massive database that connects entities and concepts through relationships.
When Google sees words such as “roasting,” “Arabica,” “Robusta,” “coffee machine,” and “grind size” appearing alongside the word “coffee,” it gains a much clearer understanding of the page’s context.
The same principle applies to ambiguous terms.
For example, if a page contains the word “Napoleon”, Google must determine whether the content refers to the historical figure, the cake, or another entity.
If words such as “emperor,” “France,” “army,” and “battle” appear nearby, the search engine can infer that the page is discussing Napoleon Bonaparte.
If words such as “cream,” “layers,” and “dessert” appear instead, Google can conclude that the content is about the cake.
In this way, topical vocabulary helps enrich content, clarify context, and strengthen the topical relevance of a page.
Polysemic Words
These words are also called polysemic words, meaning words that have multiple related meanings. For example: head (body part, leader, top part), run (move quickly, operate, manage), light (illumination, not heavy), and so on.
I wonder how many of these words you know?
Why Do People Still Search for “LSI Keywords”?
Although Google moved away from the traditional concept of LSI many years ago, the term never disappeared from the SEO industry.
Perhaps we simply became too attached to it.
Today, when an SEO professional talks about LSI keywords, they are usually not referring to genuine Latent Semantic Indexing.
Most often, they mean topical words, entities, contextual terms, and professional vocabulary that help cover a subject more thoroughly and demonstrate expertise.
How to Find Topical Keywords and Related Terms
Finding topical keywords starts with something more important than any tool: your own expertise, logic, and understanding of the niche. However, there are also several methods and tools that can help you discover relevant terms and entities more efficiently.
Analyze Search Results
The simplest approach is to study Google’s search results. The search engine itself provides clues about which topics, terms, and entities it considers important for a particular query.
Google Autocomplete
Start typing a query into Google’s search bar, but do not press Enter. Google will automatically suggest additional phrases and search variations.
Here is a useful trick: after entering your primary keyword, add different letters of the alphabet one by one. Each letter will trigger a new set of autocomplete suggestions, helping you discover a large number of related queries and topical terms.
People Also Ask
This is one of the most valuable sources of topical ideas.
The People Also Ask section contains real user questions that reveal important subtopics and topics that should ideally be covered within your content.
Related Searches
At the bottom of Google’s search results page, you will find the Related Searches section.
These queries often contain additional entities, concepts, and content ideas that can significantly enrich your article.
Competitor Analysis
Study three to five websites that already rank well for your target keyword.
Pay attention to their H2 and H3 headings, terminology, industry jargon, and uncommon phrases.
You should also carefully review their FAQ sections and article outlines. Important topical entities are often hidden within those sections.
Knowledge Graph
Explore what Google already knows about your topic.
For example, if you search for “mountain bike,” Google may display a Knowledge Panel alongside the search results.
Examine it closely. These panels often contain related entities, characteristics, brands, categories, and other important topical elements.
Artificial Intelligence
AI can also be an excellent tool for discovering topical vocabulary.
The key is asking the right question.
For example, when searching for words from the topic for the query “Keyword Research”, you could use a prompt like this:
List topical terms related to main keyword: “Keyword Research” without using the phrase ‘keyword research’ itself.
The response may include terms such as search volume, SERP, long-tail keywords, search intent, rankings, competition, and many other concepts associated with the topic.
Use the Right SEO Tools
Specialized SEO tools can dramatically speed up the process of finding topical keywords.
KeywordStat can identify related topical terms in just a few clicks, making content preparation much more efficient.
Reverse Engineering
Approach the problem like an expert.
Look at successful pages ranking in search results and identify which entities, concepts, and terms appear most frequently.
Build a Topic Association Map
Start with your primary topic and create an association map around it.
For example, if your topic is recipes, related concepts might include protein, vitamins, nutrition, health, calories, ingredients, cooking methods, and meal preparation.
Then continue expanding each branch by adding additional related concepts and terms.
This method allows you to quickly build a comprehensive list of topical keywords while gaining a better understanding of your future article structure.
Topical Keywords and Topical Authority
How are these two concepts connected?
The answer is quite simple. Google wants signals that your page genuinely belongs to a specific topic and that you have real expertise in that niche, rather than simply creating content around a particular keyword.
If you truly understand your subject, you will naturally be familiar with a large number of industry terms, concepts, entities, and professional expressions related to that field.
The more relevant topical vocabulary you naturally incorporate into your content, the easier it becomes for search engines to understand how deeply you cover the subject.
This does not mean you should force keywords into every paragraph. Instead, topical terms should appear naturally as a result of discussing the subject in depth.
When search engines consistently see relevant entities, concepts, and terminology appearing throughout your content, they gain additional confidence that your page is genuinely about the topic and not simply targeting a keyword.
Final Thoughts
By now, you have probably realized that most marketers and SEO professionals use the term LSI Keywords somewhat inaccurately.
We have simply become accustomed to the terminology, even though the original technology is no longer used in modern search engines.
That said, there is nothing wrong with continuing to use the term as long as you understand what it actually means.
Today, when people talk about LSI keywords, they are usually not referring to Latent Semantic Indexing. Instead, they are talking about topical keywords, entities, professional terminology, contextual vocabulary, and semantically related concepts.
If that is how you understand the term, then there is no problem using it.
You can confidently incorporate these topical terms into your SEO strategy to enrich your content, demonstrate expertise, and help search engines better understand the subject matter of your website.
Ultimately, the goal is not to add more keywords. The goal is to cover a topic as thoroughly as possible and communicate in the language of your audience.
That is all from me. Thank you for reading this article. Be sure to explore the other resources in this blog and take advantage of our keyword research and keyword analysis tools.
