Understanding Augmented Search Queries in SEO: 10-point definition and explanation

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In the world of natural referencing, Augmented Search Queries are an essential concept for improving the visibility of your website. website in search engine results such as Google.

In this article, we will explain in 10 key points what Augmented Search Queries are in SEO, why they are important and how they can help optimise your site for better performance in organic searches.

Augmented Search Queries

1. Definition of Augmented Search Queries

Augmented Search Queries are complex search queries. which integrate several elements such as entities, attributes and relationships between these entities in order to provide more precise and relevant search results.

These types of queries enable search engines to better understand the search intention behind the initial query, thus improving the effectiveness of the results offered to users.

2. Changes in user behaviour on search engines

Over the years, there has been a progressive changes in user behaviour when searching on search engines. Internet users began to ask more complex and specific questions, as well as using longer and more detailed search terms. In response, search engines had to adapt to provide results that matched the search intentions of these users.

3. Entities in Augmented Search Queries

In the context of Augmented Search Queries, a entity is a clearly defined concept or object that can be identified independently of its context and linguistic form. For example, "Apple" could be considered an entity because it represents a well-known brand, just like "Paris", which is both a city and the name of a sports team. Search engines therefore need to correctly identify and understand these entities in order to offer relevant results to queries containing these concepts.

4. Attributes and relationships between entities

In addition to entities, Augmented Search Queries also include attributes, which represent specific properties or characteristics of the entities in question. Example: "price" or "colour" for a product. Similarly, the relationships between different entities help search engines to understand how they are related to each other, for example a company and its products, or a celebrity and the film in which they star. Analysing these attributes and relationships helps to refine the results offered to users.

5. Typology of requests

Augmented Search Queries can be classified into several types:

  • Informative queries The user is looking for general information on a given subject (e.g. "history of the Eiffel Tower").
  • Transactional requests The intention of the search is to carry out an action, often a purchase (e.g. "buy cheap iPhone").
  • Navigation queries These are used to link directly to a specific website or web page (e.g. " Facebook login").
  • Local requests The user searches for information about a specific geographical location (e.g. "Italian restaurant in Paris").

6. The role of search engine algorithms

In order to respond effectively to Augmented Search Queries, the various search engines are developing and implementing sophisticated algorithms that analyse the semantic context and relationships between entities to deliver personalised results. These algorithms are constantly refined and updated to adapt to changes in user behaviour and new market requirements.

7. The importance of structured data

The use of structured data by websites can make it much easier for search engines to understand the entities and attributes contained in Augmented Search Queries. schemas.org and other microformats are tools that enable webmasters to highlight certain information on their site and to help search engine algorithms to correctly identify the entities and attributes present in their content.

8. Contextual and semantic natural referencing

To take advantage of Augmented Search Queries, webmasters and SEO experts now need to adapt their natural referencing strategies to incorporate more contextual and semantic elements. This includes setting up a clear, well-structured tree structure, using HTML and developing a network of relevant internal and external links.

9. The benefits of Augmented Search Queries for websites

Sites that manage to optimise their content correctly for Augmented Search Queries can obtain numerous advantages in terms of visibility and performance in search engine results.

  • Better understanding of search intent : When search engines clearly understand the intention behind a query, they are more likely to direct users to your site if it provides the information they are looking for.
  • More relevant search results : The entities and attributes present in Augmented Search Queries enable search engines to provide more precise results tailored to the user's needs, thereby increasing visitor satisfaction and loyalty.
  • Improved positioning : By providing relevant answers to complex types of query, your site has a better chance of ranking well in the search engine results and therefore attracting more organic traffic.

10. The challenges of optimising your site with Augmented Search Queries

Even if the potential benefits are numerous, taking into account and optimising your site for Augmented Search Queries represents a real challenge for the teams in charge of SEO. It is essential to develop a solid understanding of the semantics and entities/attributes involved for each sector of activity, as well as adopting the right methodologies and tools to put in place an effective strategy around these new opportunities offered by search engines.

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