Keyword Density Checker — Analyse Your Content Before Publishing
Updated: May 2026
Keyword density tells you what percentage of your total word count a specific term represents. Get it right and your content signals relevance to search engines naturally. Get it wrong and you risk both poor rankings and a poor reading experience.
Free · No upload · Instant
What is keyword density and how is it calculated?
Keyword density is the number of times a target word appears in a text divided by the total word count, expressed as a percentage. If the word "content" appears 15 times in a 1,000-word article, its keyword density is 1.5%.
The formula is straightforward: (keyword count ÷ total word count) × 100. What matters is choosing the right denominator. Should you count stop words in the total? Most SEO professionals count all words, which produces a lower density figure and is the more conservative — and more accurate — approach.
The Flowfiles word frequency counter shows density for every word in your text, so you can check your primary keyword, your secondary keywords and any terms you want to avoid all in a single analysis.
What is the ideal keyword density for SEO in 2026?
There is no universally correct answer, but industry consensus has stabilised around a practical range. The reference numbers below are based on analysis of top-ranking pages across multiple competitive niches:
| Density range | Interpretation | Recommendation |
|---|---|---|
| Below 0.5% | Under-optimized | Add the term more naturally in headings and body text |
| 0.5% – 1.5% | Natural, well-calibrated | Ideal for most long-form content |
| 1.5% – 3% | Moderately optimized | Acceptable if the usage reads naturally |
| Above 3% | Potentially over-optimized | Review for keyword stuffing — revise if it reads awkwardly |
| Above 5% | Keyword stuffing risk | Rewrite; this level is detectable and penalizable |
Density thresholds vary by topic. A very technical specification document may legitimately use a product name at 4% because there is no natural synonym. Context always matters more than the number alone.
Primary keyword vs. secondary keywords
Modern SEO content strategy distinguishes between primary keywords (the main search intent you are targeting) and secondary keywords (related terms, synonyms, and supporting concepts). Your word frequency analysis should reflect this hierarchy.
- Primary keyword: aim for 1–2% density. It should appear in the title, at least one H2, the first 100 words, and naturally throughout the body.
- Secondary keywords: 0.3–1% each. Their combined presence signals topical depth to search engines.
- LSI terms (latent semantic indexing): these are conceptually related words that don't need deliberate targeting — they emerge naturally when you write with expertise.
A frequency analysis of a well-written, expert article will show a cluster of semantically related words in the top 20. If your results show your primary keyword flanked by unrelated high-frequency terms, the content may lack coherent focus.
How to check keyword density with Flowfiles
The tool calculates density for every word in your text automatically. Here is the workflow for a content audit:
- Copy the full text of your page — body copy, headings, and any visible on-page text — and paste it into the counter.
- Enable stop word filtering to see only content words in the results.
- Set minimum word length to 3 to eliminate stray tokens.
- Click Analyze. The density column shows the percentage for every term.
- Use the search box to look up your target keyword directly without scrolling through the full table.
- If the density is outside your target range, adjust the content and re-run the analysis.
The tool also counts total words, unique words, and sentence count. A high unique-word-to-total-word ratio indicates lexical richness — a positive signal for content quality.
Keyword stuffing: what it looks like and why it fails
Keyword stuffing is the practice of inserting a target keyword far more often than natural writing would require, in an attempt to signal relevance to search engines. It was effective with early search algorithms. Modern search engines have been explicitly trained to detect and discount it.
Common patterns that trigger over-optimization signals:
- Repeating the exact keyword phrase in consecutive sentences without variation.
- Using the keyword in every heading, even when it disrupts the heading's natural purpose.
- Adding keyword-dense text in a footer or hidden section that doesn't serve readers.
- Using the exact keyword match when a pronoun or synonym would read more naturally.
Beyond rankings, keyword stuffing damages the user experience. A reader who notices artificial repetition loses trust in the content's authority — and trust is increasingly what search engines measure through engagement signals.
Keyword density for multi-word phrases
The Flowfiles counter currently analyzes single tokens (individual words), which is the standard approach for frequency analysis. For multi-word phrases (sometimes called n-grams), such as "keyword density checker" as a three-word unit, you can use the search feature to locate individual component words and estimate phrase frequency manually.
For most practical content auditing purposes, single-word density analysis is sufficient: if "keyword", "density" and "checker" all appear at healthy frequencies in the right range, the phrase is almost certainly present at an appropriate level. Search engines also understand semantic relationships between terms, so individual word presence is a valid proxy for phrase relevance.
Beyond density: what the full frequency table tells you
A keyword density check is most useful when you read the full frequency table, not just look up one word. The top 20 content words after stop word filtering should form a coherent topic cluster — words that a knowledgeable reader would expect to find together in a well-researched piece on your subject.
If you find high-frequency words that have nothing to do with your topic, it usually means you included unnecessary boilerplate, a repeated disclaimer, or a template section that dilutes the content signal. Removing or reducing that content often improves both the reading experience and the density distribution of the words that actually matter.