Keyword Density Checker

Analyze text or article keyword usage frequency in real-time. Calculate density for single keywords, 2-word, and 3-word key phrases client-side.

Text Subject to Analyze:

Keyword Analysis Results:

Keyword	Count	Density
No text parsed yet.

Keyword	Count	Density
No text parsed yet.

Keyword	Count	Density
No text parsed yet.

Features

Why Use Keyword Density Checker?

Extract and count keyword frequency density client-side.

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Frequency Counter

Extracts and aggregates exact usage counts for all single words and multi-word phrases.

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Avoid Over-Optimization

Ensure your target keywords do not exceed recommended density percentages (typically 1-3%) to avoid keyword stuffing penalties.

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Phrase Detection

Scrapes overlapping bigram and trigram keyword sequences for advanced content analysis.

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100% Offline Processing

All keyword parsing operations are executed client-side. We never monitor or log your articles.

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Responsive Layouts

Examine text copy comfortably on mobile phones, tablets, or desktop systems.

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Detailed Reports

Showcases top keywords in categorized single, 2-word, and 3-word phrase tables.

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Frequently Asked Questions

Keyword density is the percentage of times a keyword or phrase appears on a web page compared to the total number of words on the page.

While there is no fixed rule, most SEO professionals recommend a density of 1% to 3% to keep content natural and avoid keyword stuffing penalties.

These are called "stop words". Our tool lists all words, but you can easily identify stop words by their high counts and filter them out during review.

You can easily copy and paste any text subject directly into our analyzer input field to parse it instantly.

Keyword stuffing is the practice of loading a webpage with keywords in an attempt to manipulate search rankings, which often results in Google penalty actions.

Modern search engines use advanced natural language processing (like BERT and MUM) rather than strict keyword density checks, but maintaining natural density is still standard practice.

In text parsing, bigrams are two-word combinations (e.g. 'search engine') and trigrams are three-word combinations (e.g. 'search engine optimization').