Keyword Density Checker
Analyze the frequency and density of keywords in your content. The tool breaks your text into single words, 2-word phrases (bigrams), and 3-word phrases (trigrams), filters out common stopwords, and ranks what remains by frequency and density percentage. You get an instant view of what your content is actually about — and whether you might be over-optimizing for any single keyword.
How to Use It
Step 1: Paste your article, blog post, or page copy into the input. Step 2: Toggle between 1-word, 2-word, and 3-word views to see how different phrase lengths appear. Step 3: Look for your primary keyword in the top rankings — if it's not there, you may need to reinforce it. Step 4: Watch for the over-optimization warning. Any keyword above 4% density triggers it, which often correlates with keyword stuffing penalties from search engines.
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Deep Dive: The Complete Keyword Density Guide
Unigrams vs bigrams vs trigrams, the ideal density range for modern SEO, the 4% warning, stopword filtering, the writing-first workflow, and when density won't help you rank.
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See also: the People Also Ask Generator to plan a content brief before measuring density on the resulting draft; and the Related Keywords Extractor to surface the related keywords you should also cover, beyond the primary term.
Use Cases
The most common use of a density check is a post-mortem on a page that is not ranking — the writer wants to see whether the target term and its variations are showing up often enough to look topical, or so often that it looks stuffed. A density between roughly 0.5 and 2 percent for the primary term is the band most SEO practitioners aim for on a focused article, with the broader topical vocabulary spread across two and three-word phrases.
The tool is also useful for the inverse problem: a page that is ranking but for the wrong query. When the densest two and three-word phrase on a page is not what the page is supposed to be about, the topical center has drifted and the page is competing for the wrong query. Re-anchoring the introduction, the H2s, and the alt text on the intended term usually moves the density distribution back where it needs to be. Writers working on freelance briefs and content audits use the n-gram view to verify that the deliverable matches the keyword the client specified, before the draft goes back for review.
Frequently Asked Questions
What is keyword density?+
Keyword density is the percentage of times a keyword appears in your content relative to the total word count. For example, if a 1,000-word article uses 'pizza' 20 times, the density is 2%.
What's the ideal keyword density?+
There's no magic number. Most SEO professionals target 1-3% for primary keywords to keep content natural. Above 4% looks like keyword stuffing, which modern search engines penalize. Focus on natural, helpful writing over hitting a specific density.
Why does the tool exclude common words?+
The tool filters out stopwords (the, and, of, to, a, is, etc.) because they appear in every text and aren't meaningful SEO keywords. Focusing on content words gives you a clearer picture of what your article is actually about.
What are 2-word and 3-word phrases?+
These are called bigrams and trigrams. Search engines often match longer phrases rather than single words, so checking density of 2-word and 3-word combinations helps you optimize for long-tail keywords.
What’s a healthy keyword density?+
Roughly 1–2% for your primary keyword — high enough to signal relevance, low enough to avoid keyword-stuffing penalties. Modern SEO is more about topical coverage and entity relationships than raw density, but density still serves as a quick proofreading check.
Does the tool ignore stop words?+
By default yes — articles ("the", "a"), conjunctions ("and", "but"), prepositions ("of", "in"), and common pronouns are excluded so they don’t dominate the top results. Toggle them on for full-frequency analysis.
Can it analyse multi-word phrases?+
Yes — bigrams (2-word phrases) and trigrams (3-word phrases) are shown alongside single-word density. Useful for catching unnatural repetition of brand names or product taglines.
How does this differ from a TF-IDF analysis?+
TF-IDF compares term frequency in your document against a corpus to find distinctively-important terms. This tool measures only intra-document density. For competitive content analysis, use both — density to check your draft, TF-IDF to compare against ranking pages.
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