Utinzo

Keyword Extractor

Extract the most important keywords and phrases from any text. Great for SEO research, content analysis, and meta keyword generation.

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How to use this calculator

  1. 1

    Paste any text — an article, blog post, competitor page, or document.

  2. 2

    Select how many keywords to extract and whether you want single words, phrases, or both.

  3. 3

    Choose how you plan to use the keywords to get relevant tips.

  4. 4

    Copy the comma-separated list directly into your meta keywords, ad campaign, or content plan.

  5. 5

    Use the phrase section to discover 2–3 word long-tail keywords for SEO targeting.

Frequently asked questions

What counts as a keyword here?

Anything that is repeated. A single word must be at least three letters long, must not be on the built-in English stop-word list (words such as the, with, your, from) and must appear at least twice. A phrase of two or three words must also appear at least twice. Ranking is by raw count, so a term used once never appears, however important it is. Numbers on their own are skipped, although a number can sit inside a phrase.

Why do I get fewer keywords than I asked for?

The menu sets a ceiling of 10, 20 or 30, not a target. Short texts rarely repeat enough words, so a 75-word email-marketing paragraph returns 16 entries even with 30 selected, and "A short note about cats and dogs." produces none, in which case the tool says no word or phrase appears twice. Paste at least a few hundred words for a usable list.

How do the three keyword types differ?

"Single words only" lists repeated words by frequency. "Phrases" lists the repeated three-word phrases first and the repeated two-word phrases after them, so a three-word phrase seen twice outranks a two-word phrase seen ten times. "Single words + phrases" takes up to 5 three-word phrases, up to 10 two-word phrases and all repeated words, then sorts the lot by count, which means a phrase and its own words (for example "email marketing", "email" and "marketing") can all appear in the list.

How are phrases detected?

Two-word phrases are pairs of neighbouring words in which neither word is a stop word and both are at least three characters. Three-word phrases need a non-stop-word at each end, but the middle word can be anything, so "cost of living" qualifies. Punctuation is ignored when pairing, which means a phrase can span the end of one sentence and the start of the next. Hyphenated terms such as state-of-the-art are counted as one word in the single-word list but are split at the hyphens in the phrase list.

Does the "How will you use these?" menu change which keywords are found?

No. The extraction is identical for every option. The menu changes only the explanatory note under the list, and the "social" option also adds a line of hashtags built from the first 15 entries by deleting spaces, such as #emailmarketing. The SEO note reminds you to check that important terms appear in the title, H1 and opening paragraph. It also points out that Google ignores the meta keywords tag, so there is no need to fill it in.

Does it group "panel" and "panels", or find related terms?

No. There is no stemming, lemmatising or synonym matching: "panel" and "panels" are two separate entries, and text with the same topic described in different words splits its counts between them. The tool also gives no keyword density figure, search volume or competition data. It reports only how often words and phrases occur in the text you paste.

What sort of words slip through the stop-word filter?

The list is short and generic, so frequent but empty words such as "good", "make" or "one" are not removed and can reach the list if repeated. Use the ranking to spot topic terms and ignore filler entries by eye. Because the list is English, other languages get no filtering at all, although accented letters are kept inside words.

Can I use it to see which keywords a competitor’s page emphasises?

Partly. Pasting a rival article shows the terms and phrases it repeats, which is a quick way to see its vocabulary. It cannot tell you where those terms sit on the page (title, headings or body), whether they are what the page ranks for, or how much traffic they bring, because it only counts repeats in the pasted text.

About keyword extractor

Finding the repeated terms in a piece of text

Which entries each mode returns

The extractor ranks by how many times a word or phrase appears. What differs between the three keyword types is which candidates enter the list and how they are ordered. The table summarises the rules, taken from the way the tool builds each list.

Keyword type options
TypeCandidatesOrder
Single words onlyWords of 3+ letters seen at least twice, stop words removedHighest count first
Phrases (2–3 words)Two- and three-word phrases seen at least twiceAll three-word phrases first, then two-word phrases, each by count
Single words + phrasesUp to 5 three-word phrases, up to 10 two-word phrases and all repeated wordsMerged and sorted by count

Worked example: an email-marketing paragraph

Run on a 75-word paragraph about email marketing with 10 keywords and the combined type, the tool reports 43 unique content words and ranks "email" first at four uses. Next come "email marketing" (3), "marketing" (3), "subscribers" (3), "small businesses" (2), "clean list" (2), "subject lines" (2), then "small", "businesses" and "clean" (2 each). The top-five phrase block lists email marketing, small businesses, clean list and subject lines, and no three-word phrase repeats in this text.

Worked example: single words and hashtags

With the single-words type on the same paragraph, the list becomes email (4), marketing (3), subscribers (3), small, businesses, clean, list, subject, lines and open (all 2). Selecting phrases only and the social option gives four entries, which the tool turns into the hashtags #emailmarketing #smallbusinesses #cleanlist #subjectlines. Only four entries are shown even though ten were requested, because nothing else repeats.

Reading the list sensibly

Frequency shows what a text talks about most, not what it ranks for. A word repeated for grammatical reasons, a brand name in every paragraph or a navigation label pasted by accident can top the list, so strip menus and footers before extracting. Check the entries against your target keyword: if it is missing or buried far below filler words, the page may not be as focused as you think.

Limits to keep in mind

The extractor sees a flat string. It knows nothing about headings, links, bold text or position, and it counts "Marketing" and "marketing" as the same word but "marketer" as a different one. Hyphenated terms count whole in the single-word list. Phrases can join the last word of one sentence to the first of the next. For anything that depends on search demand or competition you need a keyword research source, not a frequency count.

Keyword Extractor – Utinzo

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