If you’ve been doing SEO for a while, you’ve probably heard the term “LSI keywords” thrown around. You might even have used tools that promise to generate them. But here’s the truth: LSI keywords are a myth. They have nothing to do with how Google understands language today.
What actually matters is semantic keywords - the words, phrases, and concepts that give context to your content and help search engines grasp its true meaning.
In this comprehensive guide, you’ll learn:
What semantic keywords really are (and why LSI is outdated)
How Google uses topic models, entities, and context vectors
A step‑by‑step process to find semantic keywords
How to use them to create content that ranks and satisfies user intent
Let’s dive in.
1. What Are Semantic Keywords?
Semantic keywords are words and phrases that are conceptually related to your main topic. They aren’t just synonyms; they’re the supporting vocabulary that helps define the context, intent, and depth of your content.
For example, if your main topic is “coffee maker,” semantic keywords might include:
brewing methods (drip, pour‑over, espresso)
grind size
water temperature
cleaning descaling
reviews and best brands
When you use these terms naturally, you’re not just targeting a single keyword, you’re building a topic model that tells Google, “This page is a comprehensive resource about coffee makers.”
Why they matter:
They improve relevance and topical authority.
They help you rank for a wider array of long‑tail queries.
They align with how modern search engines (like Google’s BERT and MUM) understand language.
2. The LSI Myth: Why You Should Forget It
Walk into any SEO forum and you’ll see people asking for “LSI keywords.” The term sounds scientific, so many assume it’s the secret sauce. It’s not.
What is LSI?
Latent Semantic Indexing (LSI) is a mathematical technique developed at Bell Labs in 1990. It was designed to find relationships between terms in small, static document collections—think a library of 10,000 research papers. It was never meant for the ever‑changing, massive web.
Why it’s irrelevant for SEO:
Google doesn’t use LSI. It uses far more advanced systems like BERT (Bidirectional Encoder Representations from Transformers) and MUM (Multitask Unified Model).
The “LSI keyword tools” you see online are simply scraping related searches or co‑occurring terms from top results. They aren’t performing LSI, they’re just giving you semantic suggestions under a misleading name.
As the late Bill Slawski (an SEO patent expert) put it: “If anyone says to use LSI when doing keyword research, you should really question their knowledge – they are misinforming people.”
The bottom line: Stop using the term “LSI keywords.” Replace it with semantic keywords, contextual vocabulary, or topic‑related terms.
3. How Google Understands Semantics: The Real Science
To effectively use semantic keywords, you need to understand how Google actually interprets content. Here are the key concepts backed by Google patents and official documentation.
A. Topic Models
A topic model is a way for Google to group words that often appear together in documents about a specific subject. For example, in articles about “semantic SEO,” you’ll frequently see terms like “BERT,” “entities,” “user intent,” and “topic clusters.” By analyzing millions of pages, Google learns these patterns and uses them to evaluate your content’s relevance.
B. Phrase‑Based Indexing (PBI)
This is a Google patent from 2005 (still relevant) that describes indexing phrases instead of just single words. Google identifies important phrases in a document and uses them to understand the page’s main concepts. That’s why using meaningful multi‑word phrases is more effective than sprinkling isolated keywords.
C. Context Vectors
A word’s meaning is determined by the words around it. For instance, “apple” next to “pie” and “orchard” means fruit; “apple” next to “iPhone” and “MacBook” means the company. By analyzing the co‑occurrence of words, Google creates “context vectors” that disambiguate meaning.
D. BERT & MUM
BERT (2019) and MUM (2021) are neural network‑based models that understand language in a more human‑like way. They consider the full context of a query and can even interpret intent across languages and formats (text, images, video). For semantic keyword research, this means you need to think beyond exact‑match keywords, focus on answering questions, covering subtopics, and addressing user needs comprehensively.
4. Step‑by‑Step Semantic Keyword Research Process
Now that you understand the “why,” let’s get into the “how.” Follow these steps to build a semantic keyword list that will form the backbone of your content.
Step 1: Start with a Seed Keyword
Identify your core topic. For this guide, the seed keyword is “semantic keywords.”
Step 2: Analyze the Top 10 SERP Results
Go to Google and search for your seed keyword. Open the top 10 ranking pages in separate tabs. You’re looking for:
Common subtopics and headings
Frequently used phrases and terms
Questions answered (“People also ask” boxes)
Pro tip: Use a tool like Ahrefs’ Site Explorer or Semrush’s Organic Research to see which keywords these pages already rank for. That gives you a list of terms Google considers relevant.
Step 3: Extract Co‑occurring Terms
List all the meaningful nouns, verbs, and phrases that appear across these top pages. Ignore stop words. Look for:
Synonyms (e.g., “semantic SEO,” “topic modeling”)
Supporting concepts (e.g., “BERT,” “user intent,” “entities”)
Related questions (e.g., “what are semantic keywords,” “how to find semantic keywords”)
You can do this manually or with NLP tools like MarketMuse, Frase, or even WordCounter.
Step 4: Expand Using Google’s Own Suggestions
People also ask (PAA): Click on several PAA boxes to reveal more questions. These are direct indicators of what users want to know.
Related searches: Scroll to the bottom of the SERP and note the “Searches related to…” terms.
Autocomplete: Type your seed keyword into Google and note the suggestions.
Step 5: Cluster into Topics
Group your extracted terms into logical clusters. For “semantic keywords,” clusters might be:
Technology: BERT, MUM, phrase‑based indexing, context vectors
Research methods: SERP analysis, co‑occurrence, NLP tools
Application: content optimization, topical authority, entity SEO
Myths: LSI, keyword density
These clusters will become the sections of your outline.
Step 6: Identify Gaps
Compare your list of topics with the top‑ranking pages. Is there anything they don’t cover that you could add? For example, a detailed step‑by‑step tutorial with screenshots, a downloadable template, or a section on measuring success could set your article apart.
5. Tools for Semantic Keyword Research
You don’t need to do everything manually. Here are the best tools to accelerate your semantic research.
| Tool | Best For |
|---|---|
| Ahrefs / Semrush | Analyzing top pages’ keyword rankings, finding question keywords |
| Surfer SEO | Content briefs based on semantic analysis of top 20 SERP results |
| Clearscope / MarketMuse | NLP‑powered topic recommendations, content scoring |
| Frase | Answering “People also ask” questions, content briefs |
| Google Search Console | Identifying terms your site already ranks for—great for expanding semantic relevance |
| KeywordTool.io / AnswerThePublic | Generating questions and long‑tail variations |
6. How to Use Semantic Keywords in Your Content
Having a list of semantic keywords is only half the battle. You need to integrate them naturally.
A. Structure Your Content with Subtopics
Use your topic clusters to create a logical outline. Each cluster can become a section (like we did in this guide). Within each section, use related terms naturally, don’t force them.
B. Write for People First, Search Engines Second
Semantic keywords are not a checklist to be ticked off. Write comprehensive, helpful content. If you genuinely cover a topic in depth, you’ll naturally include the relevant semantic vocabulary.
C. Use Headers to Signal Topics
Include semantic keywords in H2 and H3 tags where they fit. For example:
H2: “How Google Understands Semantics: The Real Science”
H3: “Phrase‑Based Indexing (PBI)”
D. Answer Questions Clearly
If your semantic research turned up questions (e.g., “what is phrase‑based indexing”), answer them directly in a dedicated section or FAQ. This not only satisfies user intent but also increases your chances of appearing in featured snippets.
E. Optimize for Entity Salience
Modern SEO emphasizes entities (people, places, things) rather than just keywords. Use schema markup (see next section) and mention key entities with their standard names and attributes.
7. Advanced Tactics: Entity SEO & Schema Markup
To truly leverage semantic keywords, you need to think about entities.
What Are Entities?
An entity is a unique, well‑defined thing, a person, organization, concept, or object. Google builds a Knowledge Graph of entities and their relationships.
How to Use Entities in Your Content
Identify the main entities related to your topic (e.g., for this article: “Bill Slawski,” “BERT,” “topic model,” “phrase‑based indexing”).
Use unambiguous names (e.g., “BERT (language model)” rather than just “BERT”).
Link to authoritative sources (e.g., Google’s AI blog) to reinforce the entity relationships.
Schema Markup
Add structured data to help Google understand your content’s entity relationships. For an article, you can use:
Article schema with about and mentions properties
FAQPage schema for Q&A sections
HowTo schema if applicable
Tools like Merlin or Schema.org can help you generate the markup.
8. Measuring the Impact of Semantic Optimization
Semantic optimization isn’t a one‑and‑done task. Track these metrics to gauge success:
Keyword rankings: Monitor not only your main keyword but also the secondary semantic terms you targeted. You should see a wider spread of rankings.
Organic traffic: Increased topic coverage often leads to more long‑tail traffic.
Dwell time & engagement: A well‑structured, comprehensive article keeps users on the page longer—a positive engagement signal.
SERP features: Track if you’re winning “People also ask” boxes or featured snippets for your semantic keywords.
Use Google Search Console to see which queries are bringing impressions and clicks. Over time, you’ll notice your pages ranking for more diverse, semantically related terms.
9. Common Mistakes to Avoid
Even with the best intentions, SEOs fall into these traps:
Keyword stuffing semantic terms: If you force in every related phrase, your content becomes unreadable. Use only what fits naturally.
Ignoring user intent: Semantic keywords should align with what the user wants. If you’re targeting a commercial keyword, a page focused on informational semantic terms may not convert.
Forgetting about content quality: No amount of semantic optimization can save thin or poorly written content.
Using “LSI keyword” tools blindly: Many of these tools simply give you related terms from a static database, not tailored to the current SERP. Always verify with actual SERP analysis.
Not updating: Semantic associations change. A guide from 2019 may be outdated. Regularly refresh your content to reflect new technologies and terms.
10. Conclusion: Build Topical Authority, Not Keyword Density
The shift from isolated keywords to semantic topics is one of the most important changes in SEO over the last decade. By understanding and applying the principles in this guide, debunking LSI, using real research methods, leveraging modern tools, and focusing on entities, you’ll create content that satisfies both users and search engines.
Remember, the goal isn’t to rank for a single keyword; it’s to become the go‑to resource for a whole topic. That’s how you build lasting organic visibility.
Ready to put this into practice? Start by analyzing your top 10 SERP results for your main keyword today. Extract those co‑occurring terms, build a better outline, and create content that truly serves your audience.
Frequently Asked Questions
Q: Are semantic keywords the same as LSI keywords?
A: No. LSI is an outdated mathematical model that Google does not use. “Semantic keywords” refers to the conceptually related terms that help establish context and topical authority.
Q: How many semantic keywords should I use?
A: There’s no magic number. Focus on covering the topic comprehensively. If you include every relevant subtopic and use natural language, you’ll automatically include the right semantic terms.
Q: Do I need expensive tools to find semantic keywords?
A: Not necessarily. You can do manual SERP analysis, extract terms from “People also ask,” and use free tools like Google Search Console. However, paid tools can save time and provide deeper insights.
Q: Can I use semantic keywords in meta tags?
A: Yes, including semantic relevance in title tags and meta descriptions can improve click‑through rates, but the main impact comes from on‑page content.
Q: How often should I update my semantic keyword research?
A: At least once a year, or whenever Google releases a major algorithm update. Topics evolve, and new terms can become relevant.
This guide was last updated in March 2026 to reflect the latest SEO practices and Google’s algorithm advancements.
If you need further refinements, additional sections, or a downloadable template to accompany the article, let me know and I’ll provide them.
