Keyword Density Checker

Keyword density is how often a word or phrase appears in a text, as a percentage of the total word count. The formula is the number of times the keyword appears, divided by the total words, times 100. A 1,000-word article that uses "running shoes" 10 times has a density of 1 percent for that phrase. This tool computes density for every 1- to 5-word phrase in your content. It filters out stopwords and normalizes apostrophes first.

No. Google has said many times that keyword density is not a ranking factor. It stopped mattering more than a decade ago, when search engines moved from counting terms to understanding meaning. So why does this tool exist? Because density is still a useful check. Extreme values, far too high or far too low, often point to real on-page problems: thin content, keyword stuffing, or topic drift. We show the density numbers, but we pair them with what matters today. That means real monthly search volume for every phrase, and a coverage-gap analysis against the top-ranking pages on Google.

There is no correct number. The old advice of "1 to 2 percent" dates from early-2000s SEO and has no basis in modern Google. A better guideline: write naturally, cover your topic in full, and worry about density only when a phrase appears so often it feels forced. Above about 3 to 4 percent for any one keyword is usually a sign of stuffing. This tool flags over-emphasized phrases so you can spot them at a glance.

When you turn on Compare with top Google results, we fetch the top 5 organic results for your focus keyword from a paid third-party SERP API. We then fetch each result's page through our proxy. We pull every 1-, 2-, and 3-word phrase from those competitor pages and compare them with yours. The output is three panels. Missing topics lists phrases your competitors cover and you do not. Over-emphasized lists phrases you use more than they do. AI Overview phrases lists phrases from Google's AI Overview for that query, if there is one. All three are sorted by monthly search volume, so the gaps that drive traffic come first.

• Check a live URL: we fetch your published page through our proxy pool, read the HTML, and analyze the body text. Best for auditing what is live.
• Paste content: paste raw text, markdown, or HTML. Useful for a draft before publishing, or for content behind a paywall or login.
• Live editor: a rich-text editor that scores your content as you type. Everything runs in your browser, with no server call per keystroke. Best while you are writing and tuning a piece.

If a phrase is over-emphasized (red badge), replace some uses with synonyms, pronouns, or related variations. If a phrase shows in the Missing topics panel, find natural places in your existing structure to add it: subheadings, the intro and outro, or body paragraphs. Do not repeat the same phrase over and over. Modern search engines reward varied wording that covers the topic.

Words like the, a, and, of, to, is, and in hold sentences together but carry no topic meaning. They appear at about the same rate in every English text, whatever the subject. Counting them would fill the density table with noise. We filter about 150 common English stopwords from single-word counts by default. Turn them back on if you want the raw frequencies. For phrases of two or more words we drop any phrase that contains a stopword, so "the best" and "for you" are both filtered.

Partly. The tokenizer and density math work for any language that separates words with spaces, which covers most Latin-script languages, Cyrillic, Greek, and many others. The stopword list is English only, so a non-English analysis will show many filler words in the single-word table. The SERP comparison still works, because it compares phrase frequencies whether or not a word is a stopword. For languages written without spaces, such as Chinese and Japanese, the tokenizer treats whole sentences as one token, which limits its usefulness.