Keyword Density Analyzer

Analyze keyword frequency, density, and TF-IDF scores in your content

N-gram:

What Is Keyword Density?

Keyword density is the percentage of times a keyword appears on a page compared to the total number of words. It's calculated as: (keyword count / total words) x 100. While there's no ideal density, most SEO experts recommend keeping primary keywords between 1-3% to avoid keyword stuffing.

What Is TF-IDF?

TF-IDF (Term Frequency - Inverse Document Frequency) measures how important a word is relative to the entire content. Unlike simple density, TF-IDF accounts for how common a word is — common words get lower scores, while distinctive terms score higher. This helps identify the keywords that truly define your content's topic.

N-Grams Explained

Single Words (1-gram)

Individual keywords. Best for identifying your primary topic focus and checking if you're using your target keywords enough.

2-Word Phrases (2-gram)

Two-word combinations like "search engine" or "keyword density". Useful for finding long-tail keyword opportunities.

3-Word Phrases (3-gram)

Three-word phrases like "search engine optimization". Helps identify specific topic clusters and niche keyword phrases.

Best Practices

  • ✓ Keep primary keyword density between 1-3% for natural readability
  • ✓ Use 2-gram and 3-gram analysis to find natural phrase patterns in your content
  • ✓ Enable "Remove stop words" to focus on meaningful content keywords
  • ✓ Compare your content's keyword profile with top-ranking competitors
  • ✓ Focus on TF-IDF scores over raw density — they better reflect keyword importance
  • ✓ Don't over-optimize — write for humans first, then check keyword balance

Frequently Asked Questions

What keyword density should I aim for?

There's no magic number. Google has said there's no ideal keyword density. Focus on writing naturally. If your primary keyword appears at 1-3%, you're usually in a good range. Over 5% may signal keyword stuffing.

What are stop words?

Common words like "the", "is", "at", "on" that search engines typically ignore. Removing them from analysis helps you focus on meaningful content keywords rather than grammatical filler.

How does TF-IDF differ from keyword density?

Keyword density is a simple percentage (count/total). TF-IDF weighs both frequency AND uniqueness — a word that appears often but is common across all content scores lower than a distinctive term. This makes TF-IDF better at identifying your content's true topical focus.