Keyword Density Analyser
Analyse word and phrase frequency in any text.
Overview
The Keyword Density Analyser counts the frequency of each word and multi-word phrase in pasted text and ranks them by occurrence and percentage. It excludes common stop words by default (the, and, of, a, to) and lets you see one-word, two-word, and three-word phrase distributions side by side.
Useful for SEO writers and content editors learning how to calculate keyword density or how to find over-used phrases in a blog post. Reach for it auditing a draft for topical relevance, checking competitor content for target phrases, or making sure you have not accidentally written the same word twenty times in a 500-word article.
How it works
The analyser tokenises the input on whitespace and punctuation, lowercases each token, optionally removes stop words, and counts: unigrams (single words), bigrams (two-word sequences), and trigrams (three-word sequences). Density is reported as a percentage of total non-stop words.
Modern SEO discourages chasing a specific density target — search engines moved past that signal a decade ago — but density is still a useful sanity check for repetition and topical focus. A natural article rarely sees any single phrase above 2-3% of the total.
Examples
- A 500-word article shows
responsive designappearing 8 times (1.6%), the top bigram. - The same article shows
theas the most common unigram before stop-word filtering, thendesignafter. - An over-optimised post shows the target keyword at 6% density — a sign of keyword stuffing.
- A weak post shows the target keyword appears once in the entire body — likely not topically focused enough.
FAQ
What is a good keyword density?
There is no magic number. Aim for natural writing. If your target keyword appears in the title, the first paragraph, and a couple of subheadings, the density will fall where it should — usually 0.5-2%.
Should I filter stop words?
Yes, for meaningful analysis. With stop words included, the top words are always the, and, of and you learn nothing about topic.
Does Google use density as a ranking signal?
Not directly. Google evaluates topical relevance through semantic models. Density is useful for spotting your own repetition habits, not for chasing rankings.
What about LSI keywords?
Latent Semantic Indexing is more myth than reality, but the underlying advice is sound: vary your vocabulary with related terms rather than repeating a single phrase.