What are LSI keywords?

Latent Semantic Indexing keywords are terms that naturally occur alongside a main keyword. For "heat pump" that is e.g. "COP value", "kWh", "energy rating", "installer". Content covering these terms reads as written by someone who knows the topic.

How many terms should I use in an article?

It depends on article length. For an article of around 1500 words, 20-30 semantically related terms is a reasonable target. Don't force them in — use them where they fit. The tool prioritizes the list so you can see which matter most.

Is this the same as keyword stuffing?

No, the opposite. Keyword stuffing is repeating the same word unnaturally. Semantic expansion is about using varied, related terms that make content more natural and informative.

Can I use this on existing content?

Yes, it is one of the most useful applications. Paste in the text and the tool points out which semantic terms are missing. You can then update the article where it reads naturally.

Does this work for Norwegian keywords?

Yes, the tool builds semantic fields for both Norwegian and English keywords, accounting for Norwegian compounds and domain terms used in the Nordic market.

Keywordsfreelancer

Semantic Magic Wand

What it does

Takes a keyword and suggests semantically related terms, synonyms, LSI keywords and related questions for better topical coverage.

Your content only uses the main keyword and lacks semantic depth

Google understands content semantically — not just based on exact keywords. If your article about "heat pump" only uses that one word, it lacks semantic context: related terms like "COP value", "air-to-water", "energy efficiency", "SCOP". Without this breadth the content reads thinner than competitors covering the entire semantic field.

Content repeating the main keyword without semantic variation
Missing related terms and concepts that belong to the topic
Thinner coverage than competitor content going broader on the same subject
No systematic method for finding semantically related terms

Expand each keyword into a complete semantic field

Semantic Magic Wand takes a keyword and builds out the semantic field around it: synonyms, LSI keywords, related concepts, common questions and entities. You get a word list that makes it easier to write content covering the topic broadly.

Synonyms: different ways of referring to the same concept
LSI keywords: terms that naturally belong with the main keyword
Related questions: "how to", "what is", "difference between" variants
Entities: people, organizations and concepts belonging to the topic

Features

Semantic field generator giving a broad set of related terms per keyword
Prioritization: which terms matter most for topical coverage
Content check: paste in existing text and the tool points out missing terms
Export to content brief: ready word list for writers

How it works

Enter a keyword or topic you want to expand semantically
The AI builds the semantic field with categorized terms
Use the word list to enrich existing content or plan new content

Use cases

Content writers wanting to create semantically rich articles
SEO specialists optimizing existing content for better topical coverage
Content strategists creating content briefs with semantic requirements

Why use Semantic Magic Wand?

Google's algorithm has moved from exact keyword match to semantic understanding. This means content that only repeats the main keyword stands weaker than content covering the entire semantic field. Semantic Magic Wand gives you the vocabulary belonging to the topic — so the text signals real familiarity instead of superficial optimization.

Semantic breadth is one of the easier ways to improve existing content. Instead of writing new articles you can go through the existing ones and fill in the terms that are missing. It changes neither structure nor length noticeably, but makes the coverage clearly more thorough.

For content teams, semantic word lists are practical in themselves. When writers get a list of terms that should be covered, the texts become more concrete and less general. The word list works as a simple quality check before publishing — a check that the topic is actually covered, not just mentioned.

FAQ

What are LSI keywords?: Latent Semantic Indexing keywords are terms that naturally occur alongside a main keyword. For "heat pump" that is e.g. "COP value", "kWh", "energy rating", "installer". Content covering these terms reads as written by someone who knows the topic.
How many terms should I use in an article?: It depends on article length. For an article of around 1500 words, 20-30 semantically related terms is a reasonable target. Don't force them in — use them where they fit. The tool prioritizes the list so you can see which matter most.
Is this the same as keyword stuffing?: No, the opposite. Keyword stuffing is repeating the same word unnaturally. Semantic expansion is about using varied, related terms that make content more natural and informative.
Can I use this on existing content?: Yes, it is one of the most useful applications. Paste in the text and the tool points out which semantic terms are missing. You can then update the article where it reads naturally.
Does this work for Norwegian keywords?: Yes, the tool builds semantic fields for both Norwegian and English keywords, accounting for Norwegian compounds and domain terms used in the Nordic market.

Try Semantic Magic Wand free