In SEO term, cosine similarity measures how much a given keyword available in the document is similar to the overall context of the landing page. In SEO, the more similar a keyword is with respect to the landing page, the better it is for ranking in SERP.

We first take the given keyword against the target landing page URL and compute the cosine value in % based on our AI code.


After that, we compare it with our competitor’s mean value and check for comparison whether the data obtained is less or greater than the competitor’s. If our value is greater than the mean value of the competitor’s then no action needed. Else we run our code again to suggest how much occurrence we need to add again to the landing page for improving the score.

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Insert landing page & Keyword

Add competitor &
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Cosine Similarity measure a particular keyword or key phase present in a particular landing page or not. This is a one of the important module in webtool. Easily measure a particular keyword or key phase present in a particular landing page or not. If the cosine score not satisfy the criteria of ideal score or low rather than competitors score then should add the focus keyword in the content or optimize the content with the focus keyword. But all the measurement will be done based on word count. word count of a landing page is one of the big thing. Based on word count of a landing page cosine score is depend. Content & word count play a big role in this module. If content will fix according to the suggestion then the cosine score will automatically increase. That will help google boot to quickly fetch the keyword from a particular webpage.