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Keyword Density Checker

Paste content to see top keywords and phrases with counts and density percentages, helping you avoid over- or under-optimization. In-browser.

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How to use Keyword Density Checker

Paste any article, blog post, or web-page content to see exactly how often each word and phrase appears — as a raw count and as a density percentage of the total word count. Keyword density analysis helps you spot over-optimisation (keyword stuffing that triggers Google penalties), under-optimisation (topics you're not mentioning enough), and missed long-tail opportunities visible only in 2- and 3-word n-gram breakdowns. Toggle a stopword filter to skip filler words and focus on meaningful terms.

  1. Paste your full article, landing page copy, or any text block into the input area.
  2. Toggle "Ignore stopwords" on (default) to filter out common words like "the", "and", "is" — this surfaces your actual topic keywords.
  3. Click "Analyze" to compute 1-word, 2-word, and 3-word phrase frequencies.
  4. Switch between the "1-word", "2-word", and "3-word" tabs to explore unigrams, bigrams, and trigrams.
  5. Review density percentages: anything above 3–5% for a single keyword may indicate over-optimisation; below 0.5% may mean the topic is underrepresented.
  6. Copy the table data for use in a spreadsheet or SEO reporting tool.

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What keyword density means for SEO

Keyword density is the ratio of how often a target keyword or phrase appears in your content to the total word count, expressed as a percentage. A density of 1% means the word appears once per 100 words. In the early 2000s, SEOs aimed for 2–8% density as a ranking signal; Google's Penguin and Panda updates (2011–2012) penalised pages where unnatural repetition degraded readability. Today, Google's NLP systems (BERT, MUM) evaluate semantic relevance rather than raw repetition — a page that naturally uses synonyms, co-occurring terms, and related entities outperforms one that mechanically repeats a target phrase. Keyword density analysis is now useful as a diagnostic (too low = topic underrepresented; too high = potential stuffing) rather than a target to optimise for directly.

Density rangeInterpretationRecommended action
< 0.5%Keyword underrepresentedConsider adding more natural references to the topic
0.5–2%Natural, well-integratedNo action needed — healthy range
2–5%Noticeable repetitionReview whether the repetition reads naturally
> 5%Potential keyword stuffingRevise content to reduce unnatural repetition

N-gram analysis for long-tail keyword research

While single-keyword density gives a surface view, bigram (2-word) and trigram (3-word) phrase analysis reveals which long-tail combinations appear in your content — and whether they align with your target search queries. For example, a page about photography might have high frequency for "camera" (unigram) but the bigram report might show "camera settings" and "portrait photography" are also prominent, helping you understand the semantic scope of your content. Comparing your trigrams against Google Search Console query data shows whether your content naturally uses the same 3-word phrases users search for. If searchers look for "best running shoes for flat feet" but your content only contains "running shoes", adding the full phrase context improves topical relevance.

Glossary

Keyword density
The percentage of times a keyword appears in a text relative to the total word count (occurrences ÷ total words × 100).
Stopwords
Common words (the, and, is, of, etc.) that carry little meaning and are typically excluded from keyword frequency analysis.
N-gram
A contiguous sequence of N words in text — unigrams (1 word), bigrams (2 words), trigrams (3 words).
Keyword stuffing
The practice of overloading a page with a keyword to manipulate rankings — a quality violation that can trigger Google penalties.
TF-IDF
Term Frequency–Inverse Document Frequency — a statistical measure of how important a word is to a document relative to a corpus; more nuanced than raw density.

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Why use Keyword Density Checker?

  • Preview how posts and metadata appear on each platform
  • Validate character counts against platform limits
  • Generate production-ready meta tags with one click
  • Identify username availability across all major networks

Common use cases

  • Preview how a blog post looks when shared on Facebook
  • Check Twitter card tags before a product launch
  • Find an available username across all social networks
  • Generate Open Graph tags for a landing page
  • Create a social media post mockup for a client pitch

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