Token count
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Word frequency in a listing block so you can see which tokens dominate.
Page updated 2026-09-14.
Token count
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The sample copy 'stainless bottle leakproof bottle hiking bottle BPA-free stainless lid' tokenizes into 10 words, with 'bottle' appearing 3 times, 'stainless' 2 times, and 'leakproof', 'hiking', 'bpa', 'free', and 'lid' each appearing once.
'Bottle' at 3 of 10 tokens (30% of the counted words) is the dominant term in this sample -- exactly what you'd want for the primary product keyword to be the most frequent, confirming the listing copy is actually centered on its main search term rather than diluted across too many competing phrases.
Notice 'BPA-free' splits into two separate tokens ('bpa' and 'free') rather than being counted as one compound term -- a reminder that simple word-based tokenization treats hyphenated or compound product terms as their individual parts, which can undercount how often a specific compound phrase like 'BPA-free' actually appears together.
Counts tokens of 3+ letters. Not a ranking or indexing report. Short words (under 3 letters, like 'a', 'of', 'to') are excluded from the count entirely, since they're rarely meaningful search terms and would otherwise dominate a frequency count without adding insight.
This is a raw frequency count of your own pasted copy -- it says nothing about how Amazon's A9/A10 search algorithm actually weighs or indexes these terms, which depends on many factors (backend search terms, category, conversion rate, sales velocity) well beyond front-end copy word frequency.
Keyword stuffing (repeating a term far beyond natural, readable usage) can hurt conversion even if it might seem to help density -- use this as a check that your primary keyword appears naturally and prominently, not as a target to maximize at any cost.
Once keyword usage in the visible copy looks right, character length is the other constraint to check -- see the Amazon Listing Title & Bullet Counter.
For podcast or blog content instead of a product listing, the Podcast Transcript SEO Keyword Density Checker applies similar logic to a different content type.
This tool tokenizes on word boundaries, splitting hyphenated terms into their individual words -- 'BPA-free' becomes 'bpa' and 'free' as separate tokens, each counted on its own rather than as one combined phrase.
Counts tokens of 3+ letters. Not a ranking or indexing report. Words under 3 letters (like 'a', 'of', 'to', 'in') are filtered out because they're common connector words that would otherwise dominate a frequency count without being meaningful search terms.
No. This only counts how often words appear in the copy you paste -- it doesn't reflect Amazon's actual search ranking algorithm, which weighs many other factors like backend search terms, sales history, and conversion rate.
Yes, in practice -- keyword stuffing that makes copy read unnaturally can hurt conversion even if it doesn't directly hurt this tool's density count. Use natural, readable repetition of your primary term rather than maximizing frequency for its own sake.
No. This only analyzes the visible listing copy you paste in (title, bullets, description). Amazon's separate backend search terms field is a distinct part of listing optimization not covered by this front-end copy analysis.
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