WDF = Within Document Frequency

IDF = Inverse Document Frequency

WDF*IDF

In search engine optimization, the term WDF*IDF has also become popular (which is similar to TF-IDF). Here the relevance of a document is put in relation to the competition. IDF refers to the inverse document frequency. The IDF value is calculated by dividing the total number of all indexed documents, i.e. documents known to the search engine, by the number of all those documents that contain the corresponding search term. This results in the (logarithmically compressed) IDF value being higher the fewer documents there are in total for the respective search term. Conversely, the IDF value drops towards 1 if the search term is already used on a very large number of pages.

The WDF*IDF formula results in a relevant document being weighted higher the less frequently its combination of topics has been covered so far, as it then adds new and potentially useful information to the already existing content. Correspondingly, documents that are also relevant to the search term, and thus have a high WDF value, but essentially only repeat what has already been written in other documents, receive a lower IDF value and thus an overall lower WDF*IDF weighting. With a value close to 1, the IDF factor in the WDF*IDF equation then hardly matters as a ranking factor. (Source: Wikipedia)

The WDF*IDF analysis helps with

1. the keyword research

2. the optimization of a text to be published

If you start a WDF*IDF analysis in the Content Editor without reference to an existing text, the contents of the first 10 Google results are analyzed with regard to the frequency of the search terms appearing in the texts.

These findings can then be used to create your own text, because: "For every search term, there are more or less important secondary terms that describe the topic in question and meaningfully complement the search term." (Source: SEOlyze)

For the search term "mineral water" on google.de, the WDF*IDF analysis delivered the following result:

Click on "Details" for more information:

Note: With the word filter, you can exclude terms that are not relevant before starting the WDFIDF analysis, e.g.:

These words are subsequently not included in the database.

As soon as a now text is in the editor, a recommendation appears regarding the frequency of the used terms.

This recommendation is continuously compared and updated with the stored analysis results while writing! If you click on "Update analysis", the analysis results - based on the Google Top 10 - will be updated.

Again, the details provide more detailed information:

The orange line (your text) should now run above the average WDF*IDF value (light blue), but not exceed the maximum WDF*IDF value!

Here is the example of a quite successful optimization for the keyword "online casinos":

For more information, visit: https://www.seolyze.com/HowTo/, or watch our expert webinar.