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Keyword Density Checker

Analyse keyword density in any text to optimise your content for SEO. Free, private.

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What Is Keyword Density?

Keyword density is the percentage of times a specific keyword or phrase appears in a piece of text relative to the total word count. The formula is simple: (keyword occurrences ÷ total words) × 100. If your article is 1,000 words long and your target keyword appears 15 times, the density is 1.5%.

Keyword density was one of the earliest SEO metrics because early search engines relied heavily on word frequency to determine what a page was about. While Google's algorithms have evolved far beyond simple counting, monitoring keyword density is still a useful signal to avoid two opposite problems: under-using your target topic (making the page seem off-topic) or over-using it (triggering a keyword stuffing filter).

How to Interpret Keyword Density

DensityInterpretationAction
< 0.5%Keyword barely presentConsider adding more natural mentions
0.5–1%Light usageFine for secondary keywords
1–2%Healthy rangeGood for primary keywords
2–4%DenseReview context — may read unnaturally
> 4%Over-optimisedRisk of keyword stuffing penalty

How to Calculate Keyword Density

To calculate keyword density manually: count the number of times the keyword appears in the content, divide by the total word count, and multiply by 100. For example, if "SEO tools" appears 8 times in a 600-word article: 8 ÷ 600 × 100 = 1.33%. This tool does the calculation instantly — paste your content, enter the keyword in the specific phrase field, and the result appears immediately.

What Is a Good Keyword Density for SEO?

There is no universally correct number, but most SEO professionals target 1–2% for the primary keyword. This means roughly 10–20 mentions per 1,000 words — enough to signal the topic clearly without sounding repetitive. For secondary keywords and related terms, 0.5–1% is fine. The more important measure is whether the sentence reads naturally. If removing a keyword mention would not hurt the sentence, that mention is probably unnecessary.

Keyword Density vs Keyword Relevance

Google's current algorithms evaluate topical depth, not raw keyword frequency. A page that covers all the subtopics around a subject — using synonyms, related terms and semantically connected phrases — will outrank a page that mechanically repeats the exact keyword. Use this checker to spot over-use and under-use, but focus your writing on answering the user's question comprehensively. Related terms and LSI (latent semantic indexing) phrases matter as much as the primary keyword.

Single Words vs Phrases (n-grams)

The frequency table shows individual word counts. For phrase-level analysis — your actual focus keyphrase — use the specific keyword field. Enter the exact phrase (e.g. "keyword density checker") and the tool counts how many times that exact sequence appears and calculates its density. Phrase density is especially useful for checking multi-word keyphrases that appear naturally in the text but might be diluted by slight wording variations.

How to Fix Over-Optimised Content

If your density is above 3–4%, you have too many exact-match repetitions. Fix this by: replacing some occurrences with synonyms or pronoun references, restructuring sentences so the keyword is implied rather than stated, moving some keyword mentions to subheadings (where they carry weight but do not count toward body text density), and adding supporting content that uses related terms naturally.

'Should I filter out stop words?', 'a' => 'Yes for meaningful analysis. Stop words (the, a, and, in, of…) dominate word counts and obscure which meaningful keywords actually appear most. Filtering them focuses the table on words that carry semantic value.'], ['q' => 'What is the difference between keyword density and keyword frequency?', 'a' => 'Keyword frequency is the raw count — how many times a word appears. Keyword density is frequency expressed as a percentage of total words. Density is more useful for comparison because it is normalised for article length: 20 mentions in a 500-word post (4%) is very different from 20 mentions in a 2,000-word article (1%).'], ]" />