What is the recommended keyword density for SEO?

Most SEO guidelines recommend maintaining primary keyword density between 1% and 2.5% to avoid keyword stuffing penalties.

What are 2-word and 3-word n-grams?

N-grams are consecutive word combinations representing long-tail phrases that search engines use to understand your content's context.

Word & Character Counter

Analyze word count, characters, reading time, and keyword density in real-time.

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Keyword Density & Repetitions

Check frequency of 1, 2, and 3-word phrases to avoid keyword stuffing.

Ignore common words

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Keyword Density and On-Page SEO Optimization Guide

Calculate term frequency and repetition percentages across your blog posts and web copy. Balance semantic relevance with editorial readability to rank on Google without over-optimization penalties.

How is Keyword Density Calculated?

Keyword density expresses how frequently a specific term or search phrase appears relative to the total number of words in an article:

Density (%) = (Keyword Occurrence Count ÷ Total Article Words) × 100

For example, if your primary keyword appears 15 times in a 1,000-word article, your keyword density is exactly 1.5% (15 ÷ 1,000 × 100 = 1.5%), falling squarely in the safe zone.

Recommended Keyword Density Ranges

Under 0.8%

Under-Optimized

Search engine spiders may struggle to distinguish your primary subject from competing background topics.

1.0% to 2.5%

Optimal Sweet Spot

Natural semantic density. Search algorithms clearly categorize your content without detecting manipulation.

Over 3.5%

Keyword Stuffing Risk

Triggers algorithmic penalties for unnatural phrasing and repetitive copy, harming organic rankings.

Analyzing 1-Word, 2-Word, and 3-Word Phrases (N-Grams)

Modern users search via natural multi-word phrases. Our analyzer identifies:

1-Word Terms (Unigrams): Core broad topical concepts.
2-Word Phrases (Bigrams): Targeted compound phrases like "salary calculator" or "image converter".
3-Word Phrases (Trigrams): High-intent long-tail phrases such as "how to calculate hours" or "transparent png signature".

Frequently Asked Questions

Why filter stop words during analysis?: Stop words (such as "the", "and", "in", "of") account for over 40% of standard English text. Filtering them highlights meaningful commercial and informational keywords.
How should I incorporate semantic LSI synonyms?: Rather than repeating the exact same head phrase 30 times, use related contextual synonyms. Google's natural language AI understands contextual topic relationships.
Is my unpublished copy safe from scraping?: Yes. All lexical analysis runs strictly inside your local browser instance with zero server-side storage or tracking.