User intent is now a central factor in content and search engine optimization and is eclipsing individual keywords as a dominant ranking factor.
User intent can be informational, transactional or navigational. If a keyword is usually searched for with the intention of finding out more about it, then this search is informational. If the user wants to be lead to a certain site, such as with brand names, their search is navigational. If user’s intent is to buy something behind a search term, then the search is transactional.
Google recognizes user intent
Google strives towards displaying the most relevant information for the user in its search results. Search engines increasingly focus on finding out the intention of the user and improving the semantic search: Instead of the individual keyword, the search engine inspects the connection between all words of a search term. Google can now recognize the semantic meaning, the context and the user intent of a search query.
Good content satisfies user intent
This development moves good, holistic content, that satisfies the user intention, into the center of search engine optimization. High-quality content coordinated with the expectations of the users measurably influences ranking factors and allows a good ranking in Google results. This means that knowledge of user requirements is a basic condition for good content, which is considered relevant by Google. Companies and publishers must consider whether their content satisfies the requirement of their readers. They need to orient their content around keywords that correspond to the user intent that they want to serve. Technical optimization must be associated with relevant content, which is context and user-centered.
Data science and agile content development
It is out of this necessity that agile content development has developed: A technology-supported method of developing and continuously optimizing competitive content. Agile content development makes superior content possible, which more specifically meet the needs of consumers.
Data science therefore replaces the previous guesswork regarding what the user wants with actual knowledge. The procedure model is based on the deep learning technology of Searchmetrics: Based on millions of pieces of collected and analyzed data this determines the precise user intention behind search terms.
User intent in Searchmetrics Content Experience (SCE)
The Searchmetrics Content Experience (SCE) combines measured data with the creative process of writing. Here the software shows the way to effective storytelling that fulfills the expectations of your users.
The Topic Explorer, the instrument of SCE for topic research, displays semantically related topics and depicts them as search intentions, amongst other things. A further form of depiction is offered by the sales funnel. This divides the topics into the four phases that a potential buyer goes through during their purchase: Perception, evaluation, purchase and customer loyalty. SCE gives an indication of which questions the text must answer in order to serve the user intent and the search engine.