SEO · Free tool
Keyword Density Analyser
Paste your draft. The tool counts terms, computes density and flags anything above 3% as potentially over-optimised.
Total words: 38 · Counted: 24
| # | Term | Count | Density | |
|---|---|---|---|---|
| 1 | your | 2 | 8.33% | over-optimised |
| 2 | keyword | 2 | 8.33% | over-optimised |
| 3 | density | 2 | 8.33% | over-optimised |
| 4 | paste | 1 | 4.17% | over-optimised |
| 5 | draft | 1 | 4.17% | over-optimised |
| 6 | here | 1 | 4.17% | over-optimised |
| 7 | analyser | 1 | 4.17% | over-optimised |
| 8 | compute | 1 | 4.17% | over-optimised |
| 9 | top | 1 | 4.17% | over-optimised |
| 10 | terms | 1 | 4.17% | over-optimised |
| 11 | percentages | 1 | 4.17% | over-optimised |
| 12 | flag | 1 | 4.17% | over-optimised |
| 13 | any | 1 | 4.17% | over-optimised |
| 14 | above | 1 | 4.17% | over-optimised |
| 15 | potentially | 1 | 4.17% | over-optimised |
Density as a warning, not a target
There's no "ideal" keyword density — Google ditched density-based ranking models well over a decade ago. The genuine use case here is over-optimisation detection: if your primary keyword appears above 3% of total words, the page reads as keyword-stuffed to both users and Google's spam systems. Aim for natural 0.5–2.5%.
What to do instead of chasing density
Cover the topic comprehensively with synonyms, related entities and natural variants. Use the heading structure extractor to confirm your H2/H3 hierarchy mirrors the topic naturally. Read about why density is a myth in the keyword density myth, 2026 edition.
Quick checklist
- Primary keyword: 0.5–2.5% density, naturally distributed.
- Secondary keywords (related terms): present, but not forced.
- Synonyms and entity variants: rich and varied.
- If any term is above 3%, rewrite to vary the language.
FAQ
What is the ideal keyword density?
There is no ideal number - Google has been clear since 2010 that density-based ranking is myth. A natural occurrence rate (usually 0.5-2.5% for the primary term) is symptomatic of well-written content, not a ranking lever.
When is keyword density a useful signal?
As an over-optimisation warning. If your primary keyword appears more than 3% of total words, the page reads as keyword-stuffed to both users and Google spam systems. The tool flags this threshold automatically.
What is TF-IDF and why does it matter more?
Term Frequency x Inverse Document Frequency compares your term usage to the overall corpus. Modern search uses TF-IDF-like models (and far more sophisticated transformers). Cover topic, synonyms and related entities instead of obsessing over one term.