TF-IDF (short for "term frequency versus inverse document frequency") is used to measure the importance of a given keyword on a page. Unlike keyword density, it doesn't just look at the number of times the term is used on the page but analyzes a larger set of pages and determines how important this or that keyword is.
The product of these two metrics is the TF-IDF formula that indicates the relevance of a keyword to the document. This formula is widely used by search engines to determine the corpus of web-pages that are relevant to a search query. The larger is the TF-IDF value - the more relevant (important) is the keyword to the document.
TF-IDF feature in WebSite Auditor helps you reverse-engineer your competitors’ content and discover topically-relevant keywords to enrich your content and improve pages' relevance.
TF-IDF module is a spreadsheet-like module with the list of topically relevant keywords the app has extracted from competitors' pages upon running Page Audit. You can switch between the analyzed pages to see the competitive analysis and TF-IDF stats/recommendations for each.
The bottom tab reflects the usage of each keyword by competitors (select the ones to be displayed from the list on the right). Hovering over any keyword on the graph, you can see detailed stats.
Through the top toolbars, you can:
You may also switch between the single-word keywords and multi-word keywords.
From the data in the columns you can: