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Keyword Density Checker

Analyze keyword frequency and density in body text.

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About the Keyword Density Checker

The Keyword Density Checker analyzes body copy to show how often each meaningful term appears and whether any keyword has crossed into over-optimization territory. Paste a blog post or page draft into the textarea and the tool tokenizes it live, strips a built-in list of roughly sixty common English stopwords (the, and, for, with, your, and the rest), ignores one-character fragments, and builds a ranked table of the top twenty terms with counts and density percentages. Density is computed against the total word count, so the number reflects how the page reads to a crawler rather than just the filtered list. Stat tiles summarize total words, unique terms, and the current top keyword, and any term at or above 3% density gets a red badge, matching the warning printed below the table that such levels can read as keyword stuffing to search engines. That is the practical use case: catch accidental repetition before publishing, verify that your primary keyword appears often enough to be topically obvious, and spot stuffed copy from freelance drafts before they go live. Because the analysis runs instantly in the browser, you can iterate on wording and watch the density numbers move in real time without exporting anything.

Keyword Density Checker examples

Input
Body text: "Sustainable coffee starts with sustainable sourcing. Our coffee guide covers coffee brewing at home, coffee roasting basics, and sustainable coffee brands you can trust. Brewing coffee sustainably is easier than you think. Coffee lovers ask us about grinding coffee beans and choosing fair trade coffee every week."
Output
Total words: 47 · Unique terms: 24 · Top keyword: coffee

coffee — 9 × 19.15% (red)
sustainable — 3 × 6.38% (red)
brewing — 2 × 4.26% (red)
starts, sourcing, guide, covers, home, roasting, basics, brands, trust, sustainably, easier, think, lovers, ask, grinding, beans, choosing, fair, trade, every, week — 1 × 2.13% each
Note: Stopwords like with, at, and, you, can, is are excluded from the ranked terms but remain in the total word count denominator. All three terms at or above 3% carry the red badge.
Input
Body text: "Email marketing tips for small business owners. Email automation saves time, and email segmentation boosts open rates."
Output
Total words: 17 · Unique terms: 13 · Top keyword: email

email — 3 × 17.65% (red)
automation, boosts, business, marketing, open, owners, rates, saves, segmentation, small, time, tips — 1 × 5.88% each
Note: The header reads "Top 13 of 13" since every unique term fits in the table, ranked by count and then alphabetically. The single dominant term flags immediately at 17.65% density.
Input
Body text: "to the a an of in on at is are was"
Output
Total words: 10 · Unique terms: 0 · Top keyword: —

Table shows the empty state: "Paste body text above to compute keyword density."
Note: When every token is a stopword, no meaningful terms remain. The stats still report the total word count, but the table renders its empty state.

How to use the Keyword Density Checker

  1. 1

    Paste the full body text of your article into the Body text textarea — the word count updates live in the hint above it.

  2. 2

    Read the Total words, Unique terms, and Top keyword stat tiles for a quick overview of the copy.

  3. 3

    Scan the keyword table: terms are ranked by count with density percentages, and anything at 3% or more gets a red badge.

  4. 4

    Watch for one term dominating the table — a single term far above the others usually signals repetition or stuffing.

  5. 5

    Edit your copy, paste the revised version, and compare; the analysis runs instantly so you can iterate until the top keyword sits in a healthy range.

Common use cases

  • Pre-publish content audits — scan drafts for accidental over-repetition of the target keyword before going live.
  • Freelance writer reviews — quickly vet submitted articles for keyword stuffing without manual counting.
  • Competitor analysis — paste a ranking competitor's body copy and compare term emphasis against your own draft.
  • Content refreshes — re-analyze aging posts to spot drifted keyword focus after multiple rounds of edits.
  • Product description QC — check e-commerce copy for stuffed terms that could trip spam filters.
  • Briefing writers — show new contributors which terms the page must include and at what rough frequency.

Technical SEO best practices

  • Treat the 3% red badge as a warning zone, not a hard penalty line — but if your primary term sits far above it, rewrite for humans.
  • Remember that density is a diagnostic, not a ranking lever; Google uses semantic analysis, so rank topics by coverage, not repetition.
  • Run the checker on rendered body text only — it analyzes copy, not meta tags, alt text, or headings outside the pasted content.
  • Compare densities across your own top pages and your competitors' pages to calibrate a realistic term budget for your niche.
  • Keep the primary keyword naturally in the title, first 100 words, and at least one heading — the table tells you if the body overdoes the rest.
  • Re-run after every major edit; term drift during revision is one of the most common silent SEO regressions.

Tips

  • Run the checker on your best-performing page to learn what a healthy density profile looks like for your niche.
  • Paste competitor copy and compare top terms — the gap between the two lists becomes your content brief.
  • Remember the tool strips stopwords only for analysis, never from your published page.
  • Check density after the editor's final pass, since heavy edits shift term frequency more than first drafts do.

Frequently asked questions

Each term's count is divided by the total word count of the pasted text, then multiplied by 100. Stopwords and one-character fragments are excluded from the counted terms but remain in the denominator, so the percentage reflects how often a keyword appears in the copy as a whole — the same way an over-optimization check would look at it.

There is no single magic number — Google's guidance points to natural, readable writing rather than a target ratio. Practically, most healthy pages keep the primary term between about 0.5% and 2%, which means the top rows of this table usually land well under the 3% red-flag line. If your term is above 3%, rewrite for variety; if it is far below, consider adding one or two natural mentions.

The checker filters a built-in list of English stopwords — the, and, for, with, your, and roughly sixty more — plus any token shorter than two characters. These words carry no topical signal and would otherwise crowd out meaningful terms. They are still counted in the total word count for density math; they simply do not appear as keywords in the ranked table.

Not by itself — Google has no published density threshold, and the 3% flag here is a heuristic warning, not a rule. What hurts is keyword stuffing: repetition so unnatural it damages readability, which ranking systems detect through user engagement and content quality signals. Treat the red badges as an early warning to polish copy, not as evidence of an incoming penalty.

The top twenty terms by frequency are shown, out of the total unique terms reported in the header. Ranking signals come from your most repeated terms, so the long tail of single-occurrence words rarely matters for analysis. If a target keyword is missing from the table entirely, that itself is the insight: the copy is not mentioning it enough to register.

No — it tokenizes single words only. A phrase like "sustainable coffee" is analyzed as the two separate terms "sustainable" and "coffee". For phrase-level tracking, watch both component terms in the table: when both rank high, the phrase is likely well represented. The word-level view is still the fastest way to spot stuffing and repetition.

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