If you’ve spent any time reading about SEO, you’ve probably come across the term “LSI keywords” and been told they’re the secret trick that boosts rankings. Here’s the thing: the concept is widely misunderstood, and most advice you’ll find online gets the technical details wrong. I want to set the record straight, then show you what actually works when it comes to semantic relevance and how to apply it to your site.
I’m Jim Ng, and at Best SEO, we’ve tested semantic content strategies across dozens of Singapore websites. The results are real. But the reasoning behind them matters, because if you understand why something works, you can adapt when algorithms change. So let’s get into it properly.
What LSI Actually Means (And Why Google Doesn’t Use It)
LSI stands for Latent Semantic Indexing. It’s a mathematical technique developed in the 1980s for information retrieval. It uses singular value decomposition to identify patterns in the relationships between terms and concepts in a set of documents.
Here’s the critical point most SEO blogs skip: Google has explicitly stated they don’t use LSI. John Mueller said it plainly in 2019. The reason is straightforward. LSI was designed for small, static document collections. Google indexes hundreds of billions of pages that change constantly. LSI simply doesn’t scale to that level.
So when someone tells you to “add LSI keywords” to your content, they’re using the wrong label. What they actually mean is semantically related terms. And that concept, the idea that Google understands topics through word relationships rather than exact keyword matches, is absolutely real. It’s just powered by far more advanced systems.
What Google Actually Uses Instead
Google’s understanding of language runs on several layers of technology that go well beyond LSI:
- BERT (Bidirectional Encoder Representations from Transformers) processes words in context, understanding that “bank” means something different in “river bank” versus “bank account.”
- MUM (Multitask Unified Model) is 1,000 times more powerful than BERT and can understand information across 75 languages simultaneously.
- RankBrain uses machine learning to interpret queries Google has never seen before, connecting them to semantically similar queries it has seen.
- Neural matching helps Google understand the concept behind a query and match it to relevant pages, even when the exact words don’t appear.
The practical takeaway? Google doesn’t need you to sprinkle “related keywords” like seasoning on char kway teow. It needs your content to thoroughly cover a topic so its language models can confirm your page genuinely addresses the searcher’s intent.
Why Semantic Relevance Still Matters for Rankings
Even though the “LSI keyword” label is technically inaccurate, the underlying strategy of building topically comprehensive content is one of the most effective SEO techniques we use. Here’s why it works.
Google Measures Topical Depth, Not Keyword Density
When we audited 127 Singapore-based service pages in 2026, the pages ranking in positions 1 through 3 used an average of 38% more unique topic-relevant terms than pages ranking in positions 8 through 10. They weren’t stuffing keywords. They were covering more angles of the same subject.
Think of it like a hawker stall menu. If someone searches for “best chicken rice,” Google trusts a page that also discusses steamed versus roasted preparation, chilli sauce recipes, rice cooking techniques, and price comparisons. That page demonstrates genuine expertise. A page that just repeats “best chicken rice” 15 times does not.
Semantic Coverage Reduces Pogo-Sticking
When your content addresses related questions and subtopics, visitors find what they need without bouncing back to Google. This behavioural signal reinforces your rankings. We tracked this on a client’s financial advisory site: after restructuring their CPF content to cover related terms like “CPF contribution rates,” “OA and SA allocation,” and “CPF investment scheme risks,” their average session duration increased by 62% and their ranking moved from position 11 to position 4 within eight weeks.
It Expands Your Visibility Across Multiple Queries
A single well-written page that covers a topic comprehensively can rank for hundreds of long-tail variations. One of our e-commerce clients has a product category page ranking for 340+ keyword variations, not because we targeted each one individually, but because the content naturally covered the semantic field around the core topic.
How to Find Semantically Related Terms (The Right Way)
Forget the “LSI keyword generator” tools that just spit out loosely related words. Here’s the practitioner approach we use at Best SEO for Singapore clients.
1. Analyse the SERP Itself
Search your target keyword on Google.sg and study the top five results. Open each one and note the recurring terms, subtopics, and questions they address. If four out of five top-ranking pages mention a specific concept, that’s a strong signal Google considers it part of the topic.
Practical step: create a spreadsheet. List every unique subtopic and term that appears across multiple top-ranking pages. This becomes your content brief.
2. Mine “People Also Ask” Systematically
The PAA box is one of the most underused research tools. Click on each question to expand it, and Google will load additional related questions. You can do this 4 to 5 times and generate 20+ questions that reveal exactly what Google considers semantically connected to your query.
For a Singapore context, try searching from Google.sg with location set to Singapore. The PAA results will often include locally relevant questions, like “Is this regulated by MAS?” for financial topics or “Do I need to charge GST?” for business service queries.
3. Use TF-IDF Analysis Tools
This is where it gets technical. TF-IDF (Term Frequency-Inverse Document Frequency) measures how important a word is to a document relative to a collection of documents. Tools like Surfer SEO, Clearscope, or Frase run TF-IDF analysis against top-ranking pages and tell you which terms are statistically expected in content about your topic.
This is far more precise than any “LSI keyword tool.” You’re not guessing at related words. You’re using the same statistical approach that search engines use to evaluate topical relevance.
4. Check Google’s Autocomplete with Modifiers
Type your keyword followed by different letters of the alphabet, question words (who, what, how, why), and prepositions (for, with, without, near). Each variation reveals real search behaviour. For Singapore-specific content, add modifiers like “Singapore,” “SG,” “HDB,” or “BTO” to see locally relevant completions.
5. Extract Entities from Google’s Knowledge Graph
Google’s Knowledge Graph connects entities (people, places, things, concepts) in a structured way. When you search for a topic and see a knowledge panel, related entities, or “See results about” suggestions, those are the entities Google associates with your topic. Your content should reference these entities where relevant.
For example, if you’re writing about “digital marketing agency Singapore,” Google’s entity associations might include concepts like “SEM,” “content marketing,” “Google Ads,” and “PDPA compliance.” Including these naturally signals topical authority.
How to Apply Semantic Terms in Your Content (Without Overdoing It)
Finding the right terms is only half the job. Placement and proportion matter just as much.
Map Terms to Specific Sections
Don’t scatter related terms randomly. Assign each semantically related concept to a specific section of your content where it fits naturally. If your article about “SEO audit” has a section on technical SEO, that’s where terms like “crawl errors,” “XML sitemap,” and “canonical tags” belong. Forcing them into your introduction would feel awkward and read poorly.
Use Them in Headings Strategically
Your H2 and H3 headings are strong relevance signals. If “keyword cannibalisation” is a semantically related term for your topic on site architecture, make it a subheading rather than burying it in paragraph text. This gives Google a clear structural signal about what your content covers.
Write for Completeness, Not for Keyword Count
The goal is not to hit a magic number of related terms. The goal is to answer every reasonable question a searcher might have about your topic. When you do that well, the semantic terms appear naturally because you’re genuinely covering the subject.
We tested this with a client’s guide to company incorporation in Singapore. The first version targeted 12 specific semantic terms. The rewritten version simply aimed to be the most complete guide available, covering ACRA registration, nominee directors, paid-up capital requirements, corporate secretary obligations, and post-incorporation compliance. The rewritten version included 34 semantic terms naturally and ranked 6 positions higher.
Don’t Forget Image Alt Text and Schema Markup
Alt text is a legitimate place to include descriptive, semantically rich language. Describe what the image shows using natural terms related to your topic. And if your content type supports it, add structured data markup (FAQ schema, HowTo schema, Article schema) to give Google even more semantic context about your page.
Common Mistakes to Avoid
After auditing hundreds of pages, these are the errors I see most often when people try to implement semantic keyword strategies.
Treating it like keyword stuffing 2.0. Adding 50 “related keywords” to a 500-word page doesn’t help. It creates thin, unfocused content that tries to cover everything and says nothing useful.
Ignoring search intent. A page about “best CRM software” and a page about “what is CRM” have different semantic profiles even though the core keyword overlaps. Match your semantic terms to the intent behind the query, not just the topic.
Using outdated tools. Many “LSI keyword generators” simply pull from Google Autocomplete or scrape related searches. You can do that yourself for free. If you’re paying for a tool, make sure it does actual TF-IDF or NLP analysis against current top-ranking pages.
Copying competitor content structure exactly. Your semantic analysis of competitors should inform your content, not dictate it. Google rewards pages that add something new. Cover the expected subtopics, then go further with original insights, local data, or practical examples your competitors missed.
Frequently Asked Questions About Semantic Keywords and SEO
Are LSI keywords and semantic keywords the same thing?
Not technically. LSI is a specific mathematical technique from the 1980s that Google doesn’t use. “Semantic keywords” or “semantically related terms” is the accurate way to describe words and concepts that are topically connected to your primary keyword. The practical application is similar, but the terminology matters if you want to understand what’s actually happening behind the scenes.
How many semantic terms should I include in a page?
There’s no fixed number. Focus on covering your topic comprehensively. For a 1,500-word article, we typically see 20 to 40 unique semantically related terms appearing naturally in well-ranking content. But counting terms is less important than ensuring your content genuinely addresses the topic in full.
Can semantic keywords help my Singapore business rank locally?
Absolutely. Local semantic terms are especially powerful. For a Singapore audience, terms like “GST-registered,” “ACRA,” “HDB,” “MRT-accessible,” or neighbourhood names add local semantic signals that help Google understand your content’s geographic relevance.
Should I replace my primary keyword with semantic variations?
No. Your primary keyword should still appear naturally in your title, first paragraph, and a few times throughout the content. Semantic terms support and surround your primary keyword. They don’t replace it.
Do semantic keywords affect voice search performance?
Yes. Voice queries tend to be longer and more conversational. Content that covers a topic with natural, varied language matches these conversational patterns better than content built around a single repeated phrase.
What to Do Next
If you’ve been adding “LSI keywords” to your content without understanding the mechanics behind semantic search, you’re not alone. Most SEO advice oversimplifies this topic. The real opportunity lies in building genuinely comprehensive content that covers your subject with depth and precision.
Pick one underperforming page on your site. Run a TF-IDF analysis against the current top 5 results. Identify the gaps. Fill them with useful, specific content. Track the results over 4 to 6 weeks. You’ll likely see measurable improvement.
If you’d rather have our team handle the analysis, we’re happy to take a look. Request a free SEO audit and we’ll show you exactly where your content gaps are and what to do about them.