Keyword Density
Analyzer

Analyze keyword frequency and density in your content. Optimize SEO, identify patterns, and improve content strategy with detailed keyword insights.

Input Source:

Manual Text

Type or paste content

Load from URL

Extract from webpage

Analyze Keywords
Optimize Content

Instantly analyze keyword frequency and density in your content. Our powerful analyzer helps you optimize SEO, identify content patterns, and improve your content strategy with detailed keyword insights.

Whether you're optimizing blog posts, analyzing competitor content, or improving SEO rankings, our keyword density analyzer delivers accurate, real-time results with multi-word phrase detection.

How Keyword Density Analyzer Works

Simple Steps:

  1. 1Choose input mode - manual text or load from URL
  2. 2Paste your content or enter a webpage URL
  3. 3Adjust analysis settings (word length, filters)
  4. 4View instant results with keyword statistics
  5. 5Analyze single keywords and multi-word phrases

Pro Tips:

  • Use "Load from URL" to analyze competitor content and learn from their keyword strategies
  • Adjust minimum word length to focus on substantial keywords (3-5 characters recommended)
  • Enable "Exclude Common Words" to filter out stop words and focus on meaningful terms
  • Monitor two-word and three-word phrases - they're often more valuable than single keywords
  • Copy the full report to track keyword changes across multiple content revisions

Common Use Cases

SEO Content Optimization

Optimize blog posts and articles for target keywords while avoiding over-optimization penalties

Example:
Analyze "digital marketing" density in 2000-word article

Competitor Analysis

Analyze competitor content to understand their keyword strategies and identify gaps

Example:
Load competitor URL to see their keyword usage patterns

Content Strategy Planning

Identify keyword opportunities and natural phrase patterns in your content

Example:
Find underused long-tail keywords in existing content

Academic Writing

Analyze term frequency in research papers and ensure balanced keyword distribution

Example:
Check "machine learning" usage in thesis paper

Product Descriptions

Optimize e-commerce product descriptions for search visibility

Example:
Analyze keyword density in 500 product listings

Blog Post Analysis

Review published content to identify keyword patterns and improvement opportunities

Example:
Analyze 20+ blog posts to find common phrases

Frequently Asked Questions

🔧Technical Details & Keyword Analysis Math

1Keyword Density Calculation

The fundamental metric for measuring keyword usage in content. Density indicates how frequently a keyword appears relative to total word count.

Mathematical Formula

Keyword Density= (Keyword Count ÷ Total Words) × 100

Expressed as percentage

Phrase Density= (Phrase Count ÷ Total Words) × 100

Same formula for multi-word phrases

TF (Term Frequency)= Keyword Count / Total Words

Raw frequency without percentage

Worked Example

Total Words500
Keyword "SEO" Count15
Calculation: (15 ÷ 500) × 100 = 3.0%
Density3.0%

Status: ✓ Optimized

Falls within ideal 1.5-3.5% range

Why Density Matters for SEO:
📊
Relevance Signal:

Search engines use density to understand topic focus

⚖️
Balance Required:

Too low = poor targeting, too high = spam penalty

🎯
Natural Distribution:

Keywords should appear throughout content naturally

📈
Ranking Factor:

Part of broader on-page SEO optimization

2SEO Optimization Status & Thresholds

Keywords are categorized based on industry-standard density thresholds to help identify optimal usage for SEO.

Optimized

Keywords: 1.5% - 3.5%

Phrases: 0.8% - 2.5%

Ideal range for SEO without over-optimization. Provides clear relevance signal while maintaining natural readability.

Overused

Keywords: > 3.5%

Phrases: > 2.5%

May trigger keyword stuffing penalties from search engines. Reduce usage and use synonyms/variations.

Underused

Keywords: < 1.5%

Phrases: < 0.8%

Opportunity to increase keyword presence naturally. May benefit from additional strategic placement.

SEO Best Practices Based on Thresholds:
1
Primary Keywords (1-3 per page):

Aim for 2-3% density. These are your main target keywords that define the page topic.

2
Secondary Keywords (3-5 per page):

Aim for 1-2% density. Supporting terms that provide context and relevance.

3
Long-tail Phrases:

0.5-1.5% density is sufficient. These phrases naturally appear less frequently but are highly valuable.

4
Semantic Variations:

Use synonyms and related terms instead of repeating exact keywords. Search engines understand semantic relationships.

3N-Gram Analysis & Phrase Detection

Analyzes consecutive word sequences (n-grams) to identify multi-word keywords, long-tail phrases, and natural language patterns critical for modern SEO.

Two-Word Phrases (Bigrams)

Detection Algorithm:

Scans consecutive word pairs: word[i] + word[i+1]

for i in 0..length-1:
  phrase = words[i] + " " + words[i+1]

Examples: "keyword density", "content optimization", "search engine"

Optimal Density: 0.8% - 2.5%

More restrictive than single keywords due to lower natural occurrence

Three-Word Phrases (Trigrams)

Detection Algorithm:

Scans consecutive word triplets: word[i] + word[i+1] + word[i+2]

for i in 0..length-2:
  phrase = words[i] + " " +
          words[i+1] + " " +
          words[i+2]

Examples: "search engine optimization", "keyword density analyzer", "content marketing strategy"

Optimal Density: 0.8% - 2.5%

Highly specific phrases with strong intent signals

Why Multi-Word Phrases Matter for SEO:
🎯Higher Intent

Multi-word searches indicate specific user intent. "buy running shoes" is more actionable than just "shoes".

📉Lower Competition

Long-tail phrases face less competition. Easier to rank for "keyword density analyzer tool" than "analyzer".

🗣️Voice Search

Voice queries use natural phrases. "how to check keyword density" matches 3-5 word patterns.

💰Better Conversion

Specific phrases convert better. "free keyword density tool" indicates ready-to-use intent.

4Text Processing & Tokenization

Advanced Unicode-aware text processing that handles international characters, diacritics, and complex scripts.

Tokenization Process

Step 1: Unicode Extraction text.match(/[\p{'{L}\p{'}M}]+/gu)

Extracts words using Unicode property escapes. Supports 150+ languages including Chinese, Arabic, Hebrew, emoji.

Step 2: Case Normalization word.toLowerCase()

Optional case-sensitive mode preserves original casing. Default converts to lowercase for matching.

Step 3: Filtering
  • • Length filter (configurable minimum)
  • • Stop word removal (90+ common words)
  • • Duplicate detection and counting

Stop Words List

Common Words Excluded (90+ total):

the, be, to, of, and, a, in, that, have, i, it, for, not, on, with, he, as, you, do, at, this, but, his, by, from, they, we, say, her, she, or, an, will, my, one, all, would, there, their, what, so, up, out, if, about, who, get, which, go, me, when, make, can, like, time, no, just, him, know, take, people, into, year, your, good, some, could, them, see, other, than, then, now, look, only, come, its, over, think, also, back, after, use, two, how, our, work, first, well, way, even, new, want, because, any, these, give, day, most, us

Why exclude these? Stop words appear frequently in all content regardless of topic. They add noise to keyword analysis and don't provide SEO value.

International Language Support:
🇺🇸

English

Full support

🇪🇸

Spanish

Diacritics: áéíóú

🇫🇷

French

Accents: èêëç

🇩🇪

German

Umlauts: äöüß

🇨🇳

Chinese

汉字支持

🇯🇵

Japanese

ひらがな・カタカナ

🇸🇦

Arabic

RTL: العربية

🇷🇺

Russian

Cyrillic: русский

5Performance Optimization & Efficiency

Optimized for real-time analysis of large documents with efficient data structures and reactive updates.

Time Complexity

Single Keyword AnalysisO(n)

Linear scan through words array. Each word processed once.

Phrase Detection (2-word)O(n)

Single pass checking consecutive pairs. n-1 comparisons.

Phrase Detection (3-word)O(n)

Single pass checking consecutive triplets. n-2 comparisons.

Space Complexity

Hash Map StorageO(k)

Where k = unique keywords. Typical k ≪ n for natural text.

Position ArraysO(n)

Stores position for each occurrence. Worst case: all words identical.

Total MemoryO(n + k)

Efficient for typical content. 10,000 words ≈ 1-2MB memory.

Real-World Performance Benchmarks:
Document SizeWord CountProcessing TimeMemory Usage
Short Article500<10ms~100KB
Blog Post1,500<20ms~300KB
Long Article5,000<50ms~1MB
Full Document10,000<100ms~2MB
Book Chapter50,000<500ms~10MB

Note: Tested on modern desktop browser (Chrome/Firefox). Mobile devices may be 2-3x slower. Vue 3 reactivity ensures UI updates remain smooth even with large documents.

🔒Privacy & Server-Assisted Processing

Your text content stays completely private. All analysis happens locally in your browser. Our server only assists with URL fetching to bypass CORS restrictions.

Text Analysis Privacy

📍Local Processing: All analysis in your browser via JavaScript
📍No Text Transfer: Your text content never leaves your device
📍Zero Tracking: No analytics on your content
📍Offline Capable: Works without internet after initial load (manual text mode)
📍No Storage: Data clears when you close the page

🔗URL Loading Process

1️⃣You enter a URL
2️⃣Only the URL is sent to our server
3️⃣Server fetches content (bypasses CORS)
4️⃣Content returned to your browser
5️⃣All analysis happens locally in browser
6️⃣Nothing stored on our servers
How It Works:

Manual Text Mode: All processing is 100% client-side with zero server communication. Your text stays on your device and is analyzed using Vue 3's reactive system with pure JavaScript.

URL Loading Mode: Uses our server as a proxy to bypass browser CORS restrictions. When you load from a URL, only the URL itself is transmitted to our server. Our server fetches the webpage content and immediately returns it to your browser. We do not store, log, or process the content - it's simply passed through to your browser where all analysis happens locally.

The Technology Stack:

  • Vue 3 Composition API: Reactive state management for instant updates
  • JavaScript Map Objects: Efficient O(1) keyword lookups
  • Unicode Regex (\\p{'{L}\\p{'}M}): International character support
  • Server Proxy (URL mode only): Nuxt API endpoint to fetch external URLs
  • Browser Storage: Only temporary in-memory storage, nothing persisted
  • No External Dependencies: Pure JavaScript for analysis, no third-party libraries
What Gets Sent to Our Server:
NOT Sent
  • • Your text content
  • • Keyword analysis results
  • • Any form of content data
  • • Personal information
  • • Analytics on what you analyze
Only Sent (URL mode)
  • • The URL you want to fetch
  • • Standard HTTP request headers
  • • Nothing else

Server acts only as a CORS proxy, immediately returning fetched content without any processing or storage.

Verify Privacy Yourself:

Open your browser's Network tab (Press F12 → Network tab) while using the analyzer. In manual text mode, you'll see zero HTTP requests related to your content. In URL mode, you'll see only one request to /api/fetch-url?url=... containing only the URL parameter - your analyzed text never appears in any request.

How to verify:
  1. Open Developer Tools (F12 or right-click → Inspect)
  2. Click the "Network" tab
  3. Clear any existing requests (trash icon)
  4. Manual text: Paste content - see zero requests sending your text
  5. URL mode: Load a URL - see only one GET request with URL parameter
  6. Check request payload - your text content is never transmitted

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