Keyword Density Checker
Paste text to see word and phrase frequency and density for one-, two- and three-word phrases, with stop-word filtering. Spot missing topics and keyword stuffing.
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Paste some text to see the keyword breakdown.
Density is a term’s count divided by the total word count. There is no ideal number — modern search engines do not reward a target percentage, and anything that reads as repetitive (roughly above 3–4% for a single keyword) looks like keyword stuffing. Use this to check that your main topic actually appears, to spot accidental over-use, and to find two- and three-word phrases worth turning into headings. Analysis is done in your browser.
Keyword density: a diagnostic, not a target
Keyword density is the number of times a term appears divided by the total word count, as a percentage. It is easy to compute and, for a long time, was treated as something to optimise. That era is over: search engines rank on topic modelling and query intent, not raw term frequency, so there is no magic percentage to aim for.
What the number is still good for is diagnosis. Run your draft through it and check three things. First, does your main topic actually appear with reasonable frequency, or did you dance around it? Second, is any single word spiking — a keyword much above 3–4% usually reads as repetitive and can look manipulative. Third, which two- and three-word phrases recur? Those are candidates for headings and internal-link anchor text.
Phrase analysis matters more than single words. Real searches are phrases, and seeing that "noise cancelling headphones" appears eight times, or that many sentences open with "how to", tells you what the page is really about. Single-word counts are noisy; bigrams and trigrams show structure.
Method notes: the text is lowercased and stripped of punctuation and apostrophes before counting, so "Don’t" and "dont" are one token. The stop-word filter removes high-frequency function words (the, a, of, to, and…) from single-word results so the topical vocabulary stands out; turn it off to see raw counts. Paste the article body only — navigation and footer text will skew the numbers.
The analysis runs entirely in your browser. Nothing you paste is uploaded or stored.
Key formulas (reference)
density(term) = count(term) ÷ totalWords × 100 bigram / trigram counts: slide an n-word window across the token list rule of thumb: investigate any single keyword above ~3–4%
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Frequently Asked Questions
What is keyword density?
It is how often a word or phrase appears in a text, expressed as a percentage of the total word count. If "espresso" appears 12 times in a 600-word article, its density is 2%. This tool reports it for single words and for two- and three-word phrases.
What is the ideal keyword density?
There is no target to hit. Search engines moved past raw term-frequency ranking many years ago and now model topics and intent. Writing naturally for a specific topic produces a sensible density on its own. Chasing a percentage leads to stuffed, low-quality copy.
When is density too high?
As a rough guide, a single keyword much above 3–4% usually reads as repetitive and can look manipulative. More useful than the number is reading the sentences aloud: if a phrase appears so often that it grates, thin it out with synonyms and pronouns.
What are the stop words being ignored?
Common function words — the, a, of, to, and, is, in, for, and similar — that appear frequently in any English text and carry little topical meaning. Filtering them out surfaces the words that actually describe your subject. Turn the option off to see the raw counts.
Why check two- and three-word phrases?
Single words are noisy; real search queries are usually phrases. Seeing that "cold brew coffee" appears often, or that "how to" starts many of your sentences, tells you more about what the page is about and which phrases could become headings.
Can I analyse a live URL?
No — this tool works on text you paste, because it runs entirely in your browser with no server to fetch pages. Copy the article body (not the navigation and footer) and paste it in for the cleanest reading.
Does it count words the same way as a word counter?
Close, but it lowercases everything and strips punctuation and apostrophes before counting, so "Don’t" and "dont" are the same token. The total it reports is the count before stop-word and length filtering.