The number of websites competing for top ranking positions is expanding rapidly
and the ways to achieve those high search engine rankings have evolved.
Search engines now use linguistic data sets to assist in understanding "entity salience" on web pages. Simply stated: how often related terms are used on a page determines how important a specific subject is. Topical relevance in search results has become more important than the presence of individual keywords.
Today, true website optimization requires a focus on entire semantic term groups instead of individual search terms and rankings require a much more sophisticated process including a TF-IDF analysis.*
|* TF-IDF is an abbreviation for "Term Frequency - Inverse Document Frequency." It is used to measure the importance of a given keyword on a page and throughout the entire website.||By analyzing a larger set of pages TF-IDF determines how important a specific search term is. Because Google uses
TF-IDF in indexing, knowing what the TF-IDF is for a specific term on a high ranking website is very useful information.
By looking at search term usage stats of a large number of your website pages and your high ranking competitors, an analysis using TF-IDF shows: