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Analyzing a Blog Post for Keyword Density
Paste a 500-word blog post about "JavaScript performance" into the checker. The tool analyzes all words and phrases and returns a density table. Example results:
Keyword Count Density
─────────────────────────────────────────
javascript 12 2.4%
performance 10 2.0%
code 8 1.6%
function 7 1.4%
javascript performance 5 1.0%
optimize 4 0.8%
browser 4 0.8%
memory 3 0.6%The primary keyword "javascript" appears at 2.4% — within the recommended 1–3% range. "javascript performance" as a phrase appears at 1.0%, which is healthy for a two-word target phrase.
Detecting Keyword Stuffing
A product description with over-optimized keyword usage might show:
Keyword Count Density
──────────────────────────────────────
running shoes 18 6.0%
shoes 22 7.3%
running 20 6.7%
buy running shoes 9 3.0%Densities above 4–5% for a primary keyword are a red flag for keyword stuffing. Search engines may penalize this content. The fix is to replace some keyword repetitions with synonyms and related terms like "athletic footwear", "trainers", or "jogging gear".
Checking a 1,000-Word Article
For a 1,000-word article targeting "email marketing", the checker shows:
Keyword Count Density
────────────────────────────────────────────
email 28 2.8%
marketing 22 2.2%
email marketing 15 1.5%
subscribers 11 1.1%
campaign 9 0.9%
open rate 7 0.7%
click-through rate 5 0.5%
email marketing campaign 4 0.4%This distribution looks natural. The primary keyword "email marketing" at 1.5% is well within the optimal range, and related terms like "subscribers", "campaign", and "open rate" show the content covers the topic comprehensively.
Comparing Your Content to a Competitor
Paste the top-ranking competitor's article for your target keyword "python web scraping" and analyze it:
Competitor article keyword analysis:
Keyword Count Density
────────────────────────────────────────
python 18 1.8%
scraping 16 1.6%
web scraping 12 1.2%
requests 10 1.0%
beautifulsoup 9 0.9%
html 8 0.8%
data 14 1.4%
parse 7 0.7%Now analyze your own article and compare. If your article mentions "beautifulsoup" only twice (0.2%) while the competitor uses it 9 times (0.9%), that's a gap to address. Adding more coverage of BeautifulSoup could help your content better match what ranks well.
Analyzing a Product Page
For an e-commerce product page targeting "wireless noise cancelling headphones":
Keyword Count Density
──────────────────────────────────────────────────────
headphones 8 2.7%
wireless 6 2.0%
noise cancelling 5 1.7%
wireless noise cancelling 3 1.0%
wireless noise cancelling headphones 2 0.7%
battery life 4 1.3%
bluetooth 5 1.7%For a 300-word product description, these counts are appropriate. The long-tail phrase "wireless noise cancelling headphones" appears twice — enough to signal relevance without feeling forced.
Checking Stop Word Filtering
With stop word filtering enabled, common words like "the", "and", "is", "of" are excluded from results. Without filtering, the same text shows:
Without stop word filter:
Keyword Count Density
────────────────────────────
the 45 9.0%
and 32 6.4%
is 18 3.6%
of 22 4.4%
to 28 5.6%
With stop word filter (same text):
Keyword Count Density
────────────────────────────
javascript 12 2.4%
function 8 1.6%
code 7 1.4%Stop word filtering is essential for meaningful SEO analysis. Enable it to focus on the keywords that actually matter for search rankings.
Identifying Keyword Cannibalization
Run the checker on two different pages from your site that both target "react hooks tutorial". If both pages show similar keyword density profiles for the same terms, they may be competing against each other in search results:
Page 1 — "Introduction to React Hooks":
react hooks → 1.8% density
Page 2 — "React Hooks Complete Guide":
react hooks → 2.1% densityBoth pages are optimized for the same keyword. Consider merging them into one comprehensive page, or differentiating them by targeting more specific variations like "react hooks for beginners" vs "advanced react hooks patterns".
Optimizing a Thin Content Page
A 200-word page targeting "SQL JOIN types" shows very low keyword density:
Keyword Count Density
────────────────────────────────
sql 2 1.0%
join 3 1.5%
sql join 1 0.5%
inner join 1 0.5%
outer join 0 0.0%
left join 1 0.5%The page barely covers the topic. Recommendations based on this analysis:
- Expand the content to at least 800 words
- Add dedicated sections for INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN
- Include code examples for each join type
- Target a density of 1.5–2% for "SQL JOIN" and 0.5–1% for each specific join type
Phrase Density vs Single Keyword Density
Understanding the difference between single keyword and phrase density is important for modern SEO. For a page about "machine learning algorithms":
Single keywords:
machine → 2.5%
learning → 2.3%
algorithms → 1.8%
Two-word phrases:
machine learning → 1.9%
learning algorithms → 1.2%
machine learning algorithms → 0.8%The phrase "machine learning" at 1.9% is more meaningful than the individual word "machine" at 2.5%, because it shows the words appear together in context rather than scattered throughout the text. Modern search engines understand phrase context, so phrase density is often a better indicator of content relevance than single keyword density.