Token count
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Word Frequency Counter & Density Inspector
Top tokens of three or more letters with counts and percent density in the passage.
Page updated 2026-09-04.
Calculator
Calculated Results
Unique tokens
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Which words dominate a piece of text, and by how much
'stainless bottle leakproof bottle hiking bottle lid stainless hike' (9 tokens, 6 unique words) shows 'bottle' at 3 occurrences (33.3%), 'stainless' at 2 (22.2%), and 'hike', 'hiking', 'leakproof', and 'lid' each at 1 (11.1%).
Notice 'hike' and 'hiking' are counted as two entirely separate tokens rather than being combined as variants of the same root word -- this is a real limitation of simple word-frequency counting: it operates on exact text matches, not on linguistic stemming or lemmatization, so related word forms don't get consolidated into one count.
9 total tokens but only 6 unique words means a 66.7% uniqueness ratio -- a useful secondary signal alongside the top-word percentages, since text with very low word variety (many repeats of just a few words) reads differently than text with high variety even at similar top-word percentages.
What this measures, and its stated boundary
Lowercased alphanumeric tokens only. Not a ranking or SEO audit. Every word is lowercased before counting (so 'Bottle' and 'bottle' count as the same token) and only alphanumeric tokens are counted -- punctuation-only fragments or symbols aren't treated as words.
This is a pure frequency count of the text you provide -- it says nothing about how a search engine actually weighs or ranks these terms, which depends on many factors (page authority, backend metadata, competing content) well beyond how often a word appears in one block of text.
High density for a term isn't automatically good -- unnaturally repetitive use of a word well beyond what reads naturally is a pattern some content-quality systems flag negatively, so this tool is more useful for spotting whether your primary term appears with reasonable, natural frequency than for maximizing density as a goal.
Related text-analysis tools
For applying this same kind of frequency analysis specifically to an Amazon product listing, the Amazon Product Keyword Density Analyzer is purpose-built for that context.
For a simple word and character count without the frequency breakdown, the Word & Character Counter is the more basic companion tool.
Frequently Asked Questions (FAQ)
Why are 'hike' and 'hiking' counted as two separate words?
This tool counts exact text matches only, not linguistic word roots -- it doesn't perform stemming or lemmatization to recognize that 'hike' and 'hiking' share a root word, so each distinct spelling is tallied as its own separate token.
How is the 33.3% figure for 'bottle' calculated?
Percentage = occurrences of that word / total token count x 100 = 3 / 9 x 100 = 33.3%. It reflects that word's share of all counted tokens in the text, not its importance or search ranking value.
Does high word frequency mean better SEO performance?
Lowercased alphanumeric tokens only. Not a ranking or SEO audit. No. This is a raw frequency count, not a ranking signal. Search engines weigh many factors beyond simple word repetition, and unnaturally high repetition of a term can actually be flagged negatively by some content-quality systems rather than helping.
Does capitalization affect how words are counted?
No. Lowercased alphanumeric tokens only. Not a ranking or SEO audit. Every word is lowercased before counting, so 'Bottle' and 'bottle' are combined into the same token count rather than being treated as two different words.
What does the unique-token count (6 here) tell me beyond the top-word list?
It shows word variety independent of frequency -- 6 unique words out of 9 total tokens (66.7% uniqueness) indicates moderate repetition. Comparing this ratio across different texts can reveal whether one passage relies more heavily on repeating a small set of words than another.
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