The data-driven text program shows the author keywords relevant to their text while they are writing to fulfill user/reader expectations and to be rated as relevant by Google for corresponding search queries. This removes the need for the writer to carry out comprehensive SEO research. The data is taken from the previously created briefing, which, in turn, is based on the data of the Searchmetrics Research Cloud.
Real-time recommendations for keyword coverage
In the Content Editor the author sees an overview of all the core information in the text, such as the topics and the URL, should the content of an already existing website need to be updated. This text can be added to the text field and optimized for the selected topics. On the left side of the Content Editor keywords are listed that the text should contain in order to be competitive. The use of the keywords is updated in real-time during writing. The keyword recommendations are divided into three categories:
- Must-have keywords are often used in the topic-specific content of competitors. They are therefore of central importance to the topics that your text deals with. They should be included in the text to achieve a good search engine ranking performance.
- Recommended keywords are terms that many competitors use. These terms are associated with the topics covered in the text, but are not as central as the must-have words. However, in order to create holistic content that comprehensively covers the topics, they should be included.
- Additional keywords are less central to the covered topics and are not even strictly relevant. Nevertheless, they can increase the uniqueness of the content. This allows texts to contrast from those of their competitors. Search engines reward uniqueness, such as with a better ranking.
The content score
In the recommended keyword area of Searchmetrics Content Experience, the application shows in real time to what extent the recommendations have already been implemented. The numbers show how many of the keywords the text contains compared to how many keywords are still missing.
In the column on the right the Content Editor shows various scores that measure the editorial success of the text in real-time. As a central measure, the content score shows how comprehensively the content covers the topics overall. The value states to what extent the recommendations of the briefing were used. It is mainly based on the use of recommended keywords in the content, the text length and a proprietary evaluation by Searchmetrics. The higher the content score, the better the coverage. With the coverage the likelihood rises that the text will be rated and ranked as relevant by the search engine.
The word count score shows the difference between the word count in the text and the set target value in the briefing. If the briefing has been applied to an existing website, the score also shows the difference to the word count on the existing website. The target word count is based on an average value of the competitor content. It influences the recommended keyword frequency in the Content Editor.
The readability score is inspired by the “Flesch-Kincaid readability tests” and shows how easy or difficult a text is to understand. The value is based on the average word count per sentence and syllable count per word. It ranges between 0 and 12. The higher the score, the easier the text is to understand.