What is a safe keyword density?

There is no such figure. Density was never a fixed threshold, and modern search guidance treats natural coverage of a topic as more important than hitting a ratio. This tool reports what is there rather than inventing a target to chase.

How is density calculated here?

The count of a term divided by the total number of word tokens, times one hundred. The denominator includes function words, because a reader asking what share of the text a term occupies means the whole text, not a filtered subset.

Why are phrases filtered for content words?

So that combinations such as of the, which occur constantly and mean nothing, are never reported as keywords. A two-word phrase must contain at least one non-function word before it appears in the phrase table.

Is keyword density a Google ranking factor?

There is no published fixed density threshold, and repeated formulas for one are folklore rather than documentation. The safer reading is that a page which answers a query well and reads naturally will outperform one that was tuned to a ratio.

Should function words count in the denominator?

Yes, for this measurement. If the denominator excluded them, the percentage would describe a share of content words rather than a share of the text, which is not what a reader asking about density is looking for.

Keyword Density Analyzer

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Minimum occurrencesRows per table

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Density

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The Keyword Density Analyzer reports how much of your text each word and two-word phrase occupies, with the denominator stated and no suggested target, because no universal safe density exists.

What is Keyword Density Analyzer?

Density sounds like a rule you can follow and is really just a ratio. The Keyword Density Analyzer computes how much of a text each term takes up, shows the counts behind the percentage, and deliberately refuses to hand you a target figure.

The arithmetic is simple and is printed on the page. Density is the number of times a term appears divided by the total number of word tokens, multiplied by one hundred. The denominator includes function words, because when a reader asks what share of the text a term occupies they mean all of it, not a filtered subset. Each row also shows the per-thousand rate, which is the same information on a scale that does not shrink when the text gets shorter, and the raw count, which is what most people actually want.

Two tables are produced. The first counts single words, with function words hidden by default so the content words stand out. The second counts two-word phrases, and a phrase is only reported when at least one of its words is a content word, so combinations such as of the never masquerade as a keyword. Phrases often reveal what a single-word table cannot: a document about keyword density will show density high in the single-word table and also keyword density high in the phrase table, and the phrase is the more informative of the two.

The minimum-occurrence threshold and the number of rows are both adjustable. A short caption may need a threshold of two; a long article can raise it to four or five so only genuine patterns survive. Matching is case-insensitive, and ties are broken by first appearance so equal counts keep document order rather than shuffling as you type.

The tool does not propose an ideal percentage, and that is a deliberate editorial position rather than a missing feature. Density was treated as a ranking signal in the early days of search, and the folklore that a term should occupy a specific percentage of a page has been repeated ever since without evidence. Contemporary guidance is that writing naturally and covering a topic well matter more than hitting a ratio, and a tool that invented a target would be encouraging the opposite.

What density is genuinely good for is diagnosis. A term near the top of both tables may be the subject of the piece, or it may be evidence that a paragraph repeats itself. A phrase that appears far more often than its words suggest can point at a stock expression. Read the top few rows, look at the counts rather than the percentages, and use the context of the piece to decide whether the concentration is earned. Nothing you paste leaves the browser.

Two names are used for the same measurement, and both appear in the wild. Keyword frequency usually means the raw count of a term, while term frequency in information retrieval means a normalised rate, which is what the density column here computes. The tool reports the count, the share and the per-thousand rate together so the two senses are never confused, and you can read whichever one your question actually needs.

How to use Keyword Density Analyzer

Paste the text you want to analyse; both tables fill as you type.
Set the minimum occurrences and the number of rows you want to see.
Read the single-word table from the top, ignoring the percentages until you have seen the counts.
Check the two-word phrase table, which often reveals stock expressions the word list hides.
Decide in context whether the concentration is the subject of the piece or an accidental tic.

When to use Keyword Density Analyzer vs related tools

Use the density analyzer when you want to know how much room specific terms take up and how often phrases repeat. When the concern is a word returning too quickly rather than too often overall, the Overused Word Finder measures the distance between occurrences instead of the total.

If the density is a symptom of a narrow vocabulary rather than a single overused term, the Vocabulary Richness Scorer measures the breadth of word choice, and the Text Fingerprint Analyzer compares two drafts on the same measurable features.

Privacy & Security

This tool runs entirely in your browser — no data ever leaves your device. There is no server round-trip, no upload, no logging, and no account required. Your input is processed locally using client-side JavaScript and is never stored, transmitted, or accessible to anyone else. When you close the tab, everything disappears.