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How it works
Keyword density is the percentage of times a target keyword appears in a body of text relative to total word count. While keyword stuffing (artificially inflating density) is penalised by Google, too-low density on a competitive topic can signal weak relevance. The Keyword Density Checker analyses your page content for keyword frequency, density percentage, and distribution across the page — helping you calibrate natural keyword usage.
How density is calculated: Keyword density = (keyword occurrences ÷ total words) × 100. A 1,000-word page mentioning "SEO tools" 5 times has a 0.5% density for that phrase. Google's guidelines don't specify a target density — the concept of an "optimal" 2–3% density is a widely repeated myth. What matters is that keywords appear naturally in semantically relevant positions.
What the tool analyses: - **Term frequency**: exact match count for your keyword across the full text - **Density percentage**: keyword count ÷ total word count × 100 - **TF-IDF signal**: how unusual the keyword's frequency is relative to typical English prose — high TF-IDF suggests good topical specificity - **Position analysis**: does the keyword appear in the first 100 words (weighted heavily by Google), in headers, and near the end? - **Related terms**: words that co-occur with your keyword in the text — Google's semantic indexing values topical co-occurrence over raw density
Practical guidelines: - A primary keyword appearing 3–8 times per 1,000 words reads naturally and is sufficient - Secondary keywords and synonyms (LSI terms) should appear 1–3 times per 1,000 words - The keyword must appear in: the title tag, the first paragraph (within 100 words), at least one H2 heading, and the meta description
How to use: 1. Paste your page content into the text area. 2. Enter your target keyword or phrase. 3. Density, frequency, and position analysis appear instantly.
Privacy: all analysis runs in the browser. Your content is never transmitted.
Frequently Asked Questions
- There is no ideal keyword density number. The concept of a 'target' density (2–3% is a common myth) was debunked after Google's Panda and Hummingbird updates. Google's algorithm evaluates topical relevance through semantic understanding, not keyword frequency. Practically: ensure your primary keyword appears in the title tag, first paragraph, at least one H2, and the meta description. In body text, use the keyword naturally — if it reads awkwardly from repetition, it's too frequent.
- TF-IDF (Term Frequency-Inverse Document Frequency) measures how important a term is to a document relative to how commonly that term appears across all documents. A high TF-IDF for a term means the term is used frequently in your document but rarely across the web — indicating strong topical specificity. TF-IDF is a more sophisticated signal than raw density and is one component of Google's relevance scoring. Tools like Surfer SEO use TF-IDF comparisons against top-ranking pages to identify which terms to add or increase.
- Yes. Keyword stuffing — artificially inflating keyword frequency to manipulate rankings — is a violation of Google's Webmaster Guidelines and triggers algorithmic penalties (Panda) or manual actions. Signs of keyword stuffing: repeating the same phrase every 2–3 sentences, listing keywords in the footer, hiding keywords in white text on white background, or using keywords in a way that makes no grammatical sense. Natural writing at Grade 8 reading level with the keyword in key structural positions is the correct approach.
- Yes. Latent Semantic Indexing (LSI) keywords — semantically related terms that naturally co-occur with your primary keyword — help Google confirm topical relevance. A page about 'json formatter' should also contain terms like 'pretty print', 'indent', 'parse', 'validate', 'minify'. Their presence signals comprehensive topic coverage. Check that your top 5 semantically related terms each appear at least 1–2 times per 1,000 words — not stuffed, but present.