Keyword Density Checker: SEO Analysis

What Is Keyword Density Checker?

Paste any block of text and the Keyword Density Checker ranks each word by frequency and shows what percentage of the total it represents. I usually pull this up before publishing a blog post to catch a word I've leaned on too hard without noticing.

Key Features

The tool tokenizes input by extracting lowercase letter sequences, then counts every word that meets the minimum length threshold. Each word's density is calculated as (count / totalWords) * 100 and shown to two decimal places. Results update live on every keystroke, so editing the textarea immediately reshuffles the table.

A toggle switch enables filtering of 80+ common English stop words (a, an, the, in, of, is, are, was, were, have, do, and similar). A numeric input controls the shortest word included in analysis (default 3, max 10), which filters most single and two-letter words. Another input limits how many keywords appear in the results table (default 20, max 100).

A four-panel stats row shows total word count, unique word count after filtering, character count of the raw input, and the density percentage of the top keyword. Density values are color-coded: green for 1 to 2 percent, yellow for 2 to 3 percent, red for 3 percent and above. Values below 1 percent show in muted text.

For exporting, the Export CSV button downloads a keyword-density.csv file with three columns (Keyword, Count, Density). The Copy Keywords button copies all keyword strings as a comma-separated list to the clipboard, ready to paste into a meta keywords field or a research tool.

How to Use Keyword Density Checker

Open the Coming Soon: Keyword Density Checker and paste your article into the textarea. There's no submit button: the stats row and results table update with every keystroke.

Below the textarea, three controls tune the analysis. Min Word Length can be raised to 4 to drop short words like "for" and "on" that aren't on the stop list. Filter Stop Words is enabled by default; turning it off reveals every word, useful for analyzing reading level or phrasing patterns. Show Top changes how many rows the results table renders.

Try this 250-word product description for a hypothetical hiking boot:

TrailMaster Pro hiking boots are engineered for serious trail runners and hikers who demand performance on technical terrain. The TrailMaster Pro features a Vibram outsole for superior grip on wet rock and loose gravel. TrailMaster Pro boots include a waterproof Gore-Tex membrane that keeps feet dry in stream crossings and rain. The midsole uses proprietary foam cushioning that returns energy with every step on the trail. TrailMaster Pro lacing provides a secure lockdown fit for technical trail running and steep ascents. Professional hikers and trail runners consistently rate TrailMaster Pro as the most durable trail boot available.

The stats row will show roughly 103 total words, 42 unique words after stop-word filtering, and 571 characters. The results table ranks keywords by count descending, and "trailmaster," "trail," and "pro" all land in the red zone:

Red flags above 3 percent signal potential over-optimization. Rewrite sections to vary phrasing and pull primary keywords back into the 1 to 2.5 percent range (green). When you're satisfied, click Copy Keywords for a comma-separated list, or Export CSV to download the full data including all keywords beyond the visible table.

Practical Examples

Example 1: SEO Content Audit

You write a 1,200-word blog post and want to verify keyword distribution before publishing. Paste the article body. The results table shows your primary keyword ("cloud computing") at 2.3% (green, good), a secondary keyword ("data storage") at 1.1% (green), and a phrase fragment ("the cloud") appearing at 4.2% (red, review needed). Rewrite two paragraphs to vary the phrasing and bring the flagged term into an acceptable range.

Example 2: Competitor Content Analysis

Copy the text content of a competitor's ranking page and paste it into the checker. The top 10 keywords reveal which terms they emphasize. Export the CSV and compare it against your own content's keyword distribution to identify gaps or over-optimized terms.

Sample output: a competitor's 800-word article shows "machine learning" at 2.8% (green, near the upper limit), "neural network" at 1.4% (green), and "AI model" at 0.9% (muted, below 1%).

Example 3: Product Description Consistency Check

A product catalog has 50 descriptions. Paste each one and check whether the primary product name appears in the optimal 1 to 2 percent range. Descriptions where the product name appears only once in 200 words (0.5%, muted) need the keyword added naturally. Descriptions where it appears 8 times in 150 words (5.3%, red) need revision to remove repetition.

Tips and Best Practices

• The density color scale is a guide, not a rule: Green (1 to 2 percent) and yellow (2 to 3 percent) are healthy ranges for primary keywords in most content types. Red is a signal to review, not an automatic penalty indicator.
• Filter stop words to reveal true keyword density: With stop words filtered on, the total word count includes only meaningful words, which raises apparent density percentages. For SEO purposes, that's the number you want.
• Adjust minimum word length for your content type: Technical content uses short acronyms (API, CSS, SQL) that are meaningful but only 3 characters. Keep the minimum at 3 to include them. For general prose, 4 or 5 filters more noise.
• Use the "Show Top" control for large articles: For a 3,000-word article with hundreds of unique words, set Show Top to 30 or 50 to see the full picture beyond the default 20.
• The copy keywords feature produces a flat list: The copied output is word1, word2, word3, ... sorted by frequency. Paste it directly into a meta keywords tag or a spreadsheet.

Common Issues and Troubleshooting

Results table shows no keywords: The text is either empty or all words are filtered out by the stop words list and minimum length setting. Disable stop word filtering or reduce the minimum word length to 1 to see all tokens.

Total word count is lower than expected: The tool extracts words by matching lowercase letter sequences ([a-z]+) after replacing all non-letter characters with spaces. Numbers, hyphens, apostrophes, and punctuation are removed. "e-commerce" counts as two words: "e" (filtered at minimum length 3) and "commerce."

Density percentages look higher than expected: Density is calculated relative to the filtered word count, not the raw total. If stop words are filtered, the denominator decreases, which raises density percentages for the remaining words. Disable the stop word filter to calculate density relative to all words.

CSV file contains more rows than the "Show Top" display: The CSV export includes all keywords, not just the ones shown in the table. The "Show Top" setting only limits the visual table; the export always contains the full dataset.

Privacy and Security

Keyword Density Checker processes all text entirely in your browser using JavaScript. Your content is never sent to any server and never stored outside your local session. The tool uses React's useMemo hook for reactive computation, so analysis runs locally whenever the text or settings change. That makes it safe for unpublished drafts, client content under NDA, or any text you'd rather not expose externally.

Frequently Asked Questions

What density percentage is considered optimal for SEO? The tool uses green (1 to 2 percent), yellow (2 to 3 percent), and red (3 percent and above) as color thresholds. Most SEO practitioners target 1 to 2.5 percent for primary keywords in body content. Density alone is not a ranking factor: context, topic relevance, and semantic variation matter more than hitting a specific number.

Does the tool analyze keyword phrases (bigrams, trigrams)? No. The tool analyzes individual word tokens only. It does not detect multi-word keyword phrases like "machine learning" or "content marketing." Use the word frequency data as a signal for individual term prominence, then assess phrase density manually.

Can I analyze text in languages other than English? The stop word list is English-only. For non-English text, disable the stop word filter. The word tokenization (extract lowercase letter sequences, minimum length) works for any Latin-alphabet language. Languages using non-Latin scripts (Chinese, Japanese, Arabic) will not tokenize correctly because the regex only matches [a-z] characters.

How does the tool count words with hyphens or apostrophes? Hyphens and apostrophes are treated as word separators. "state-of-the-art" becomes four tokens: "state," "of" (filtered as stop word), "the" (filtered), and "art." "don't" becomes "don" and "t," and "t" is filtered by minimum word length 3. That's a known limitation for compound words and contractions.

What is the maximum text length the tool can handle? There is no explicit character limit. The tool has been tested with articles up to several thousand words. Very large documents (50,000+ words) may cause noticeable processing delay since analysis runs synchronously on every keystroke. For large documents, paste the full text at once rather than typing it in.

Can I export keyword data for use in other tools? Yes. The CSV export (keyword-density.csv) contains Keyword, Count, and Density (%) columns for all keywords in the analysis. The "Copy Keywords" button produces a comma-separated keyword list for pasting into Google Keyword Planner, Ahrefs, or similar tools.

Related Tools

• Coming Soon: SERP Preview: Preview how your title and meta description appear in Google search results alongside your keyword-optimized content.
• Coming Soon: Meta Tag Generator: Generate the title and meta description tags for your keyword-optimized content with character count guidance.
• Coming Soon: Page SEO Analyzer: Run a full SEO analysis on a live page URL to audit keyword usage in headings, body text, and meta tags together.

Try Keyword Density Checker now: Coming Soon: Glyph Widgets Keyword Density Checker