Keyword Density Analyzer
Measure keyword frequency and density in any text — spot keyword stuffing before search engines do.
| Keyword | Count | Density | Status |
|---|
How terms are counted
- N-grams — 1-, 2- and 3-word phrases counted separately; a trigram like content-marketing-strategy reports as one unit.
- Stop-word handling — per-language filterable list so density is not inflated by filler words.
- Placement flags — top terms show hits across title tag, H1-H3, meta description, image alt and opening paragraph.
- Honest baseline — natural prose sits at 0.5–2.5% for a primary term; above 4% flags as stuffing risk rather than encouraging more.
Density plus placement, not just percentages
See which terms dominate, where they appear (title, headings, first 100 words) and whether long-tail variants beat single-word stuffing.
Density, not just counts
Every keyword gets a share-of-text percentage computed against the meaningful tokens — 10 mentions in a 200-word article is clearly different from 10 in 2,000 words.
Keyword-stuffing alerts
Terms repeated past about 3% of the text with at least three mentions get a warning badge — the classic pattern that reads as spam to both users and search engines.
Chinese text included
Chinese has no spaces between words, so the analyzer extracts character bigrams — the standard no-dictionary technique — instead of pretending English word splitting works.
Frequently asked questions
What is a good keyword density?⌄
Search engines publish no official number. In practice, natural copy usually sits between 1% and 3% per keyword; this tool flags terms past about 3% with at least three mentions as worth trimming — a sign to edit, not a guaranteed penalty.
How does it handle Chinese text?⌄
Chinese has no word boundaries, so the tool analyzes adjacent character pairs (bigrams) and filters out pairs containing common function characters like 的了在. That is the standard no-dictionary approach — no segmentation model required.
Is my text uploaded anywhere?⌄
No. Everything runs in your browser; the text never leaves your device. Paste freely, including drafts and client copy.
Is there an ideal keyword density?⌄
No magic number exists — modern ranking cares about topic coverage and placement. Use density to spot accidental repetition, not to hit a quota.
Related tools
What is a keyword density analyzer?
Keyword density is the share of visible text devoted to one term — a rough signal search engines once leaned on and still use to spot stuffing. This tool counts every word and phrase in your draft, shows each term's occurrences and percentage, and flags the ones crossing into risky territory.
How the counting works
Latin words are lowercased and tokenised with apostrophes kept inside words; pure numbers and single letters are discarded. Chinese, Japanese and Korean text has no spaces, so the tool slides a two-character window and filters grammatical particles — the standard dictionary-free technique. Density divides by content tokens after stop-words are removed, so a sea of the and is never mistakes filler for focus.
Reading the flags
A term is marked high only when it appears at least 3 times and reaches 3 percent — short blurbs where one word mathematically must dominate stay green. Results sort by density, then count, then alphabetically, capped at the top 50 so the table stays scannable.
When you would use it
It earns its keep in three spots:
- Audit a blog draft before publishing to catch accidental repetition
- Compare two rewrites of a product description to see which reads more naturally
- Show a client why their tenth exact-match keyword has to go
Honest limits
Chinese bigrams can pair characters that are not real words, and the score knows nothing about search intent or synonyms — it measures repetition, not relevance. Treat red flags as editing prompts, not verdicts.
Privacy
Privacy is straightforward here: analysis runs entirely on your device as you type, with a short debounce, and your drafts are never uploaded anywhere.
Last updated · 2026-09-01
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