Keyword Density Analyzer
Count word and phrase frequency across any body of text — without keyword-stuffing.
Analyses single words plus 2-word and 3-word phrases, surfaces top-frequency terms, and flags anything above the natural-writing 3% threshold that could look manipulative to Google.
Anything above 3% may look manipulative. Aim for natural distribution.
Keyword density as a concept has been misapplied for two decades — there is no published Google target percentage, and chasing an arbitrary number ("keep it at exactly 2%") produces exactly the kind of unnatural, repetitive prose that modern ranking systems are specifically designed to detect and discount. What this tool measures isn't a ranking lever to optimise toward; it's a diagnostic for catching the opposite problem: accidental over-repetition that happens naturally when a writer is self-conscious about "including the keyword enough" and ends up repeating it awkwardly.
Run a finished draft through this analyzer the way a copy editor would use a find-and-replace count: not to hit a target, but to catch what your own eye has gone blind to after multiple read-throughs. A single term appearing at 4-5%+ frequency in body copy is almost always a sign of over-optimisation, not a sign you've done SEO correctly.
Why there's no correct keyword density percentage
Google's ranking systems, particularly since the shift toward embedding-based and BERT/MUM-style language understanding, evaluate semantic relevance and topical coverage far more than literal term-frequency counting. A page can rank well for a phrase it never states verbatim, if it comprehensively covers the underlying topic and satisfies the query's intent, and conversely a page can rank poorly despite hitting a supposed density target if the surrounding content is thin or the repetition reads unnaturally to the algorithm's language models.
The 3% threshold this tool flags isn't a Google-published rule — it's a practical heuristic drawn from analysing thousands of naturally-written, well-ranking pages, where single-word repetition rarely exceeds roughly 2-3% without starting to read as forced. Use it as a warning light, not a target to hit exactly.
Single words vs phrases — what each tells you
Single-word frequency catches brand-name or generic-term overuse ("seo", "austin", your own company name repeated past the point of natural reference). Two- and three-word phrase frequency is more diagnostic for actual keyword-stuffing patterns, since real keyword-stuffing almost always happens at the phrase level — repeating "austin seo agency" six times in 400 words reads far more obviously manipulative than any single word repeated the same number of times, because natural writing varies phrase structure even when discussing the same core topic repeatedly.
- Single-word frequency above 3-4%: check for brand-name or filler-word overuse.
- Exact-match phrase repeated more than 3-4 times in under 500 words: near-certain over-optimisation.
- Zero mentions of the target phrase or close semantic variants anywhere: a genuine relevance gap, worth fixing.
- Natural variation (synonyms, related entities, question phrasing) matters more than hitting an exact-match count.
Using this alongside competitor comparison
One legitimate use of density analysis is comparative, not absolute: run your draft and a top-three-ranking competitor's page through the same analyzer and compare which related terms and entities they cover that you don't, rather than trying to match their exact-match percentage. This surfaces genuine topical gaps — related sub-topics, questions, or entities a comprehensive page on the subject would be expected to address — far more usefully than chasing a percentage match.
Step-by-step workflow
- 1Paste your finished draft
Analyse complete copy, not an outline — density read on incomplete text is misleading.
- 2Review single-word frequency first
Catch obvious brand-name or filler-word over-repetition.
- 3Check 2-word and 3-word phrase frequency
This is where real keyword-stuffing patterns actually show up.
- 4Flag anything above roughly 3%
Treat it as a prompt to rewrite for natural variation, not a hard violation.
- 5Compare against a top-ranking competitor
Look for related terms and entities they cover that your draft is missing.
- 6Rewrite for variation, not repetition
Use synonyms, related entities, and natural phrasing instead of repeating the exact-match phrase.
Frequently asked questions
- What keyword density percentage should I target for SEO?
- There's no official target — Google doesn't publish or use a fixed keyword-density threshold for ranking. Write naturally and comprehensively about the topic; treat density analysis as a check against over-repetition, not a target to hit.
- Can keyword stuffing get a page penalised?
- Extreme, obvious stuffing can trigger Google's spam-detection systems, which target manipulative, low-value repetition specifically. Moderate over-repetition is less likely to trigger a formal penalty but still reads poorly to human readers and rarely helps rankings.
- Should I include exact-match keywords or is close variation fine?
- Close semantic variation is generally fine and often preferable — modern search systems understand synonyms and related phrasing well. Exact-match repetition matters far less than comprehensive, natural topical coverage.
- Why does my page rank well despite a 0% density on the target keyword?
- Google's language-understanding systems can match a page to a query based on semantic relevance even without the literal keyword phrase present, if the page clearly and comprehensively addresses the underlying topic and intent.
- Is it bad to have my brand name at a high density?
- Brand-name repetition is judged differently from generic keyword repetition and is less likely to read as manipulative, but excessive repetition of any term, brand included, can still make copy feel unnatural to readers.
- How is this different from a TF-IDF or content-gap analysis tool?
- This tool measures raw frequency within a single piece of text. TF-IDF and content-gap tools compare term importance across a whole corpus or competitor set — genuinely useful complements, but a different, more advanced analysis than a density check.
- ·Sanity-checking optimised copy
- ·Finding accidental over-use of a brand term
- ·Comparing draft vs top-ranking competitor
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