Keyword Density Checker
Paste your copy and see which words and phrases it actually leans on. Single word, two word and three word counts, density, and how far into the page each term first appears. Everything runs in your browser.
Your content
Paste some copy above and the counts appear here. Nothing is uploaded: the analysis runs entirely in your browser.
Short answer
Keyword density is the share of a page's total words made up by one word or phrase: occurrences divided by total word count, multiplied by 100. A term used 8 times in a 1,000 word page sits at 0.8 percent. There is no correct figure to aim for. Google has never published a target, and its spam policies describe keyword stuffing as unnatural repetition rather than a threshold. Naturally written copy lands between 0.5 and 2.5 percent for its main term, which describes how people write rather than a goal. Check the number to catch a phrase repeated where a pronoun belongs, and to see which sub-topics the page skipped.
What density measures, and the target that does not exist
The formula is arithmetic, not a ranking signal. Occurrences divided by total words, times 100. Every tool agrees on the calculation, and the disagreement is entirely about what the resulting number is worth.
In the early 2000s it was worth a great deal, because early search engines really did rank on term frequency. That era is what produced the 2 percent rule of thumb still repeated in SEO advice. Ranking systems moved to meaning years ago, and Google representatives have said plainly and repeatedly that there is no ideal density.
So the metric survives as a diagnostic. Three readings are still worth having:
- Repetition a reader would notice. A term at 5 or 6 percent usually means the copy repeats a phrase where a pronoun or a synonym belongs. That is a readability problem first and a spam signal second.
- Coverage gaps. The two and three word tabs show which sub-topics the page actually discusses. Terms you expected to see and do not are the useful finding, and they are invisible in a single percentage.
- Accidental focus. Pages often lean hardest on a phrase nobody searches for, usually product or internal vocabulary. The frequency table makes that obvious in a way rereading your own copy never does.
Context decides the number
A glossary entry defining canonical tags will show a high density for the phrase and is working exactly as intended. A landing page at the same figure is probably padded. The percentage cannot tell the two apart, which is why it is a prompt to reread rather than a verdict.
How to read your results
Six columns, and the two most useful are the ones other density tools tend to leave out: where a phrase first appears, and what the phrase tables look like next to each other.
| Column | What it tells you | What to do with it |
|---|---|---|
| Count | Raw occurrences of the word or phrase | The honest number. Compare it against the page length rather than against a benchmark |
| Density | Count as a percentage of total words | Useful for spotting outliers, not for hitting a target. Anything above roughly 4 percent is worth rereading |
| Share | The bar, scaled against the most frequent term | Shows how concentrated the page is. One bar towering over the rest usually means thin coverage |
| First at | How far into the copy the term first appears, as a percentage | A main term appearing at 40 percent means the opening never confirms what the page is about |
| Words / Unique words | Length, and how varied the vocabulary is | A low unique-to-total ratio on a long page is the clearest sign of padding |
| Target keyword box | Occurrences, density, and whether the phrase lands in the first 100 words | The first-100-words check is the one to act on. The percentage is context |
Common words are filtered by default so the table is not three screens of the, of and and. The toggle turns the filter off when you want raw frequency, which is the right mode for judging whether a passage reads repetitively.
What over-optimisation actually looks like
Google's spam policies define keyword stuffing by behaviour, not by ratio: loading a page with terms to manipulate rankings, in ways that read as unnatural to a person. Every example given is a pattern rather than a percentage.
| Pattern | How it shows up in the table | The fix |
|---|---|---|
| Exact-match repetition | One phrase far above everything else, often 5 percent or more | Replace most instances with pronouns or the phrasing you would use out loud |
| Location lists | Dozens of two word phrases sharing a stem, each appearing once or twice | One page per location with copy specific to it, or one page with genuinely local detail |
| Padding to hit a word count | High total words, low unique-word ratio, no phrase concentration anywhere | Cut. Length that adds no information is the most common thin-content failure |
| Keyword blocks in footers | Terms that appear once, late, and never in the body | Delete them. Footer keyword lists have been a documented spam signal for over a decade |
| Missing vocabulary | Expected phrases absent from the two and three word tabs | Cover the sub-topic properly. This is the gap worth fixing, and it is not a density problem |
The last row is the one that changes rankings. Stuffing is rare in copy written by a person; missing coverage is near-universal. If you only act on one line of your results, make it the phrase you expected to see and did not.
How to check keyword density
Six steps, and the fourth is the one that produces an edit list rather than a reassuring number.
- 01
Paste the page copy, not the whole HTML file
The number you want describes what a reader sees. Pasting raw HTML works because the tool strips tags, scripts and styles first, but navigation, footers and cookie banners still count as words if they come along. Copy the article body wherever you can.
- 02
Enter the term the page is meant to rank for
The target keyword field reports occurrences, density and whether the phrase appears inside the first 100 words. That last check matters more than the percentage: it is where a reader decides the page answers the query they typed.
- 03
Read the two and three word tabs before the single words
Single word counts are dominated by whatever the topic is called and tell you little. Two and three word phrases show the shape of the page: which sub-topics were covered, which were mentioned once, and which phrasing you repeated without noticing.
- 04
Look for terms that should be there and are not
The most useful finding is usually absence. If a page about audit pricing never says cost, hourly, or retainer, it is missing the vocabulary the query family uses. Coverage gaps move rankings; a percentage point of density does not.
- 05
Flag anything above roughly 4 percent and read it aloud
There is no threshold that triggers a penalty, so treat a high figure as a prompt rather than a verdict. Read the passage out loud. If the phrase repeats where a pronoun or a synonym would sound more natural, rewrite it for the reader and the number drops on its own.
- 06
Export the CSV and compare against the pages already ranking
Run the same check on the top three results for your query and put the exports side by side. The gap in phrase coverage between your page and theirs is a concrete edit list, which a single density figure never is.
Density is one input to on-page quality, and the placements matter more than the ratio. Once the copy reads well, check that the title and description carry the term too: the meta tags generator writes them with live character counts, and the meta tag checker reads back what a live page is currently serving.
A word count is not a strategy
Comparing your phrase table against the pages already ranking is worth more than any threshold. The SEO checklist for blog posts covers the placements that do carry weight, and the technical SEO audit guide covers what to check once the copy is settled.
What this tool measures
Single word counts
Every word ranked by frequency, with density and a share bar
Two and three word phrases
Counted within sentences, so no phrase spans a full stop
Target keyword check
Occurrences, density, and whether it lands in the first 100 words
First-mention position
How far into the copy each term first appears, as a percentage
Stopword filter
Function words hidden by default, one toggle to see raw counts
HTML accepted
Tags, scripts and styles stripped before anything is counted
Content stats
Words, unique words, sentences, characters and reading time
CSV export
Every phrase at the selected length, not just the visible rows
Nothing you paste leaves your browser
Frequently asked questions
What is keyword density?
Keyword density is the share of a page's total words made up by one word or phrase, written as a percentage. The formula is occurrences divided by total word count, multiplied by 100. A term used 8 times in a 1,000 word page has a density of 0.8 percent.
What is a good keyword density percentage?
There is no good figure, because search engines do not score pages against one. Google has never published a target and its representatives have repeatedly said there is no ideal density. Naturally written copy usually lands somewhere between 0.5 and 2.5 percent for its main term, but that is a description of how people write, not a target to hit.
How do you calculate keyword density?
Count how many times the term appears, divide by the total number of words on the page, and multiply by 100. For multi-word phrases the same formula is used by most tools, which slightly understates the share of text the phrase occupies. This checker uses the standard formula so the numbers are comparable with other tools.
Does keyword density still matter for SEO in 2026?
Not as a ranking factor to optimise. It matters as a diagnostic: it catches copy that repeats a phrase unnaturally, and it shows which sub-topics a page covers and which it skips. Modern ranking systems work on meaning rather than term frequency, so the useful reading is coverage and readability, not a percentage.
What counts as keyword stuffing?
Google's spam policies define it as loading a page with keywords to manipulate rankings, and the examples given are lists of cities with no added value, blocks of repeated words, and phrases inserted so awkwardly they read as unnatural. The test is whether the repetition serves the reader, not whether a percentage was crossed.
Can a high keyword density get a page penalised?
A high percentage on its own does not trigger anything. What gets acted on is the behaviour the percentage sometimes reveals: text written for a crawler rather than a person. A glossary page will show a high density for the term it defines and is entirely fine, which is why the number always needs reading in context.
Should I include stopwords in the count?
Not for topical analysis. Function words like the, of and and dominate every English text and bury the terms you are actually checking, so they are filtered by default here. Turn the filter off when you want raw frequency, for example when checking whether a piece of copy is repetitive to read.
Why check two and three word phrases instead of single words?
Because queries are phrases. Single word counts tell you what the page is nominally about, which you already knew. Phrase counts show which specific angles the page covers, and comparing them against a competitor's page produces an edit list rather than a percentage.
Does this tool check a live URL?
No. It analyses text you paste, which keeps everything in your browser with nothing uploaded. Raw HTML is accepted and the tags, scripts and styles are stripped before counting, so copying a page's source works. For live-page checks, the meta tag checker and the page indexability checker fetch the URL for you.
Where should the target keyword appear on a page?
In the title tag, the H1, the URL where it fits naturally, and somewhere in the first 100 words. Those placements confirm to a reader in the first few seconds that the page answers their query. After that, use the phrasing that reads best rather than repeating the exact string.
Do headings and alt text count toward keyword density?
In most tools, including this one, whatever text you paste is counted, so headings count and alt attributes do not unless you paste them in. Search engines read all of it but weight placement rather than tallying a single ratio, which is another reason the total percentage is a weak signal.
How is density different from TF-IDF?
Density measures frequency inside one document. TF-IDF weighs a term's frequency in the document against how common it is across a whole corpus, so it promotes terms that are distinctive rather than merely frequent. TF-IDF is the more informative measure, and both are inputs to editing rather than targets.
Is this keyword density checker free?
Yes, with no signup and no usage limit. The analysis runs entirely in your browser, so nothing you paste is sent to a server, and there is no length cap beyond what your browser can hold in a textarea.
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