Keyword Density Analyzer Online Free
Analyze single words, two-word phrases, and three-word n-grams across your articles, essays, and landing page copy. Detect search engine keyword stuffing risks, audit topical entity coverage, and export comprehensive frequency reports without uploading your drafts.
Keyword Density Analyzer In-Browser Workspace
Input data or select files to begin. 100% private, client-side execution with zero server transmission.
How to Use Keyword Density Analyzer
- Step 1: Paste your draft article, blog post, or webpage copy into the text input area.
- Step 2: Select your desired phrase length: choose 1-Word keywords, 2-Word keyphrases, or 3-Word long-tail n-grams.
- Step 3: Toggle "Filter Common Stop Words" to automatically ignore filler words ("the", "is", "at", "which").
- Step 4: Inspect the density percentage breakdown and watch for warning flags highlighting keywords that exceed 3.0%.
- Step 5: Click "Copy CSV" or "Download CSV" to export your keyword frequency audit into Excel or Google Sheets.
About Keyword Density Analyzer
Modern search engine algorithms like Google Helpful Content and RankBrain analyze natural topical entity distributions rather than crude keyword repetitions. Early SEO tactics often repeated phrases excessively—a practice known as "keyword stuffing" that now triggers algorithmic penalties. Modern SEO guidelines recommend keeping primary target keywords between 1.0% and 2.5% of total word count while distributing natural contextual synonyms and semantically related terms. Our Keyword Density Analyzer tokenizes text into n-grams of degree 1, 2, and 3, filters grammatical conjunctions and prepositions, and calculates exact mathematical densities: (Occurrences ÷ Total Words) × 100. The entire statistical evaluation executes locally in your browser memory.
Frequently Asked Questions
What is an ideal keyword density for SEO?
An ideal keyword density for primary search phrases is generally between 1.0% and 2.5%. Anything exceeding 3.0% runs a high risk of triggering search engine keyword stuffing filters.
What are 2-word and 3-word n-grams?
N-grams are contiguous sequences of words. A 2-word n-gram is a bigram (e.g. "free online converter") and a 3-word n-gram is a trigram (e.g. "client-side web tools"). Analyzing n-grams uncovers multi-word search phrase patterns.
Why are stop words filtered by default?
Stop words like "the", "and", "is", and "of" naturally appear most frequently in human speech. Filtering them highlights the substantive topical keywords in your text.
Can I export the analysis to a spreadsheet?
Yes. Click "Download CSV" to save a structured spreadsheet containing every detected keyword, its occurrence count, and exact density percentage.
Is my text private and secure?
Yes, 100%. All text tokenization and frequency computations execute client-side in your browser. Your draft copy is never uploaded or saved to remote servers.