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Co-occurrence & Related Terms Tool
The Co-occurrence & Related Terms tool finds the words that show up most often near a target term inside a body of text, which is one of the fastest ways to see the vocabulary a topic actually travels with. Search engines lean heavily on co-occurrence to judge whether a page covers a subject in depth, so the terms that cluster around your focus keyword in top-ranking copy are a practical map of what your own page is expected to mention.
It is free and entirely browser-based: paste a competitor’s article or your own draft, set a target word and a window size, and the tool counts the real content words inside each window around every occurrence. Nothing you paste is uploaded, so it is safe for unpublished drafts and confidential client work.
🔒 Private: everything runs in your browser. Nothing you paste is uploaded.
How to use the co-occurrence & related terms tool
Paste a corpus, type a target term, and pick how many words on each side count as “near”. The table updates on every keystroke and ranks each related term by how many windows around the target it appears in.
Choose a window size that matches the relationship you want
The window is how many words on each side of the target count as nearby. A tight window of two or three words surfaces the phrases and modifiers that sit right against the term, which is useful for spotting collocations and likely long-tail variants. A wider window of six to ten words captures the broader topical field, the supporting concepts that a thorough page tends to mention in the same breath. Start narrow to find phrasing, widen to find subtopics, and compare the two lists to separate tight word pairs from loose thematic neighbours.
Keep the stopword filter on so the signal is topical, not grammatical
Without filtering, the words most often near any term are function words like the, and, of, and to, because every sentence is full of them. The built-in stopword list removes that grammatical noise and leaves the content words that actually describe the topic. Each related term is also counted once per window around the target, so a single sentence cannot inflate a word’s score, and the target word is excluded from its own results. Untick the filter only when you specifically want to study raw phrasing, including the connective words.
Read the results as a content gap, not a keyword quota
Run the same target across two or three top-ranking pages and the terms that recur are the shared vocabulary of that topic. Anything those pages mention near your keyword that your own draft does not is a genuine coverage gap worth addressing, in context, where it reads naturally. The goal is comprehension, not stuffing: a high co-occurrence count signals a concept the topic expects, not a phrase to repeat a fixed number of times. Use the ranked list to brief writers and to sanity-check that a draft covers the same conceptual ground as the competition.
Co-occurrence & related terms frequently asked questions
Q1What is term co-occurrence in SEO?
Co-occurrence is how often two words appear near each other in text. In SEO it is used as a proxy for topical relevance: when the same supporting terms consistently surround a keyword across ranking pages, search engines treat that vocabulary as part of covering the topic well. This tool measures that pattern directly by counting the content words inside a window around each occurrence of your target term.
Q2How is the window size used in the calculation?
The window is the number of words counted on each side of every occurrence of the target. With a window of four, the tool looks at the four words before and four words after each hit, counting each distinct content word once for that window. A narrow window finds tight phrasing and collocations, while a wider window captures the broader set of concepts a page mentions alongside the term.
Q3Why are stopwords removed by default?
Function words such as the, and, of, and to appear near almost every term simply because they fill ordinary sentences, so they would dominate the results without adding topical meaning. The default stopword filter drops them and leaves the content words that describe the subject. You can untick the filter when you want to study raw phrasing, including the connective words, rather than the underlying topic.
Q4Does this tool fetch URLs or send my text anywhere?
No. The tool analyses only the text you paste into the box and never fetches a URL or contacts a server. All tokenising, windowing, and counting run in your browser with JavaScript, and nothing you paste is uploaded, logged, or stored. That makes it safe for unpublished drafts, client material, and any text you would rather not share.
Q5How many words should I paste for reliable results?
Co-occurrence is a frequency signal, so a few hundred words give a rough picture and a full article or several combined pages give a stable one. The more times your target appears, the more meaningful the ranking becomes, because each occurrence contributes one window of evidence. If a term shows up only once or twice, treat the related list as suggestive rather than conclusive.
