From information needs to SEO keyword strategy

Before words comes the need, which is only later translated into language. This is why Like Reply builds semantic indexing on keywords based on the latent and explicit information needs of users that have been identified and understood.


Keywords are just the tip of the iceberg of the SEO semantic strategy. It starts with users and their information needs: keywords are the concise expression of these needs. In fact, the need for information indicates the user's search intent, the reason why people perform specific searches on the internet. Although the need for information is the cornerstone of any communication objective, the awareness of having to go to the source of users' needs is the result of two major algorithm updates in 2013 and 2014: Hummingbird and Rankbrain, which allow Google to better understand the motivation behind user searches and provide more precise answers, including through the use of machine learning systems, to determine the most relevant results. 

Why information needs are analysed? 

  • To create new content that meets these needs 
  • To identify new relevant keywords to index 
  • To strengthen the ranking of keywords that are already indexed 
  • To increase website trust in relation to a topic 


Information needs can be explicit or latent, which complicates their analysis and understanding.

To identify and fully understand them, Like Reply adopts an analysis that covers the website, the business, its objectives, users and competitors. This also includes SERP analysis and the use of specific tools and software.


The main steps of the semantic SEO strategy


GSC gives access to first party data, related to the organic searches which make the website appear in SERP. This data allows to optimise the content in order to better respond to the needs of users. The limitation is the fact that needs not identified cannot be tracked in this way.


It is important to study each element of the Search Engine Results Page (paid ads and organic results) to understand user searches. Particular attention should be paid to the autocomplete and People Also Ask features. Unlike the GSC, these actions allow to identify suggested content that is not yet mapped on the website.


The Like Reply team analyses spot access tools such as chatbots and internal search engines to obtain direct information about the needs of users – after all, it is they who are expressing them directly. They look at chatbot logs and internal search analytics to determine which queries can generate semantic optimisations. Only once the information needs have been mapped and understood can they move on to structuring an effective keyword strategy to map the site based on the conversion funnel.


By using Google Analytics or another digital analytics tool, low traffic and/or high bounce content requiring optimisation can be identified, indications that the content does not fully meet the needs of users.


The study of heatmaps and recordings allows to understand the user experience of the website pages and user behaviour. Non-fluid browsing may be caused by problems with content that needs to be optimised.


Search trends and their analysis help to identify the frequency and seasonal patterns of web searches for a given keyword or long-tail keyword.