Keyword Density Checker

Analyze keyword frequency and density in your content. Identify over-optimized keywords and surface the most prominent terms in any text.

Your Content
Paste content and click Analyze.

Frequently Asked Questions

Keyword density is the percentage of times a specific word or phrase appears in your content relative to the total word count. Formula: (keyword count / total words) × 100. Most SEO experts recommend keeping it between 1–3% for your primary keyword.
Keyword stuffing is the practice of excessively repeating keywords to manipulate search rankings. Google's algorithms penalize it. A density above 3–5% for the same keyword is generally considered a risk factor. Aim for natural, reader-first writing.
Stop words (the, and, is, a, for…) appear in almost every piece of text and carry no SEO value. Excluding them lets you focus on the meaningful keywords in your content. You can uncheck the option to see the full frequency list including stop words.
The tool generates bigrams — every consecutive pair of words in the text — then counts and ranks them by frequency. This surfaces important two-word keyword phrases (e.g., "machine learning", "email marketing") that a single-word analysis would miss.
There is no strict rule, but most SEO practitioners recommend a keyword density of 1–2% for your primary keyword. What matters more than a specific percentage is natural, contextually appropriate usage. Google's algorithms are sophisticated enough to understand topic relevance without keyword repetition, so writing for humans first and using keywords where they fit naturally is the best approach.
Keyword stuffing is the practice of forcing a keyword into content at an unnaturally high frequency to manipulate search rankings. Google's Panda algorithm and its successors penalize stuffing with ranking demotions or manual actions. Density above 3–5% for the same keyword is generally a warning sign. The penalty ranges from lower rankings to complete removal from the index.
LSI (Latent Semantic Indexing) keywords are terms that are conceptually related to your primary keyword — synonyms, related phrases, and co-occurring terms that appear in content on the same topic. For example, an article about "coffee" would naturally contain LSI terms like "espresso", "caffeine", "brewing", and "roast". Including these terms helps Google better understand your content's topic and can improve rankings for a wider range of related queries.
TF-IDF (Term Frequency–Inverse Document Frequency) measures how important a word is in a document relative to a collection of documents. Unlike keyword density (which only counts occurrences in your page), TF-IDF compares your term usage against the entire web corpus. A high TF-IDF score for a term means it appears frequently in your document but rarely across other documents, signalling strong relevance. Advanced SEO tools use TF-IDF to identify content gaps.
Modern Google uses neural matching and large language model-based systems to understand meaning, not just keywords. It evaluates overall topical depth, entity relationships, and how comprehensively a page covers a subject. This means covering related subtopics, answering follow-up questions, and demonstrating expertise is more effective than optimizing for keyword frequency alone.
A primary keyword is the main term you want a page to rank for — it should appear in the title tag, H1, URL, and naturally throughout the content. Secondary keywords are related terms and variations that support the primary topic (e.g., "best running shoes" as primary, with secondaries like "trail running footwear" or "running shoe reviews"). Targeting both increases the range of queries a single page can rank for.

About This Keyword Density Checker

This free keyword density checker analyses the text of any webpage or pasted content and shows how frequently each word and phrase appears, expressed as a percentage of total words. Enter a URL or paste text to see a ranked frequency table.

Keyword density is not a direct ranking factor, but monitoring it helps identify unintentional keyword stuffing and ensures that important terms appear naturally throughout the content.

When to use this tool

  • Checking that a target keyword appears a reasonable number of times
  • Identifying accidental keyword repetition or stuffing
  • Comparing keyword distribution against competing pages
  • Auditing AI-generated content for over-used terms

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