EAT & thematic brand positioning as a critical success factor in SEO
Posted: Thu Jan 30, 2025 9:08 am
Thematic positioning in subject areas relevant to your company is the basis for users and Google to perceive you as an authority or expert in these subject areas and to trust you. Keyword: EAT
Table of contents [ Hide ]
1 EAT as a concept for brand identification and quality assurance
2 EAT as gatekeeper and important ranking influence
3 The influence of EAT on Google ranking
4 entities and EAT
5 Factors Influencing EAT
6 Thematic positioning of the brand/domain
7 How do you position yourself in a topic area?
EAT as a concept for brand identification and quality assurance
EAT is Google's own concept to identify publishers and authors who are a brand. Google wants to use it to improve the quality of search results and thus the user experience with the SERPs.
Google itself distinguishes between relevance and quality. Relevance always has a bearing on the search query and relates to the respective document. (More on the topic of relevance in the article Relevance, pertinence and usefulness on Google ). Quality can relate to the quality of the content of the document or the publisher or author. Brand concepts can be used especially for the latter in order to consider the EAT concept.
brand characteristics
A trademark has the following essential characteristics:
popularity
Trust
thematic authority
thematic expertise and competence
Three of these characteristics can also be found in EAT. Pure popularity is not a useful characteristic for determining quality, as it is detached from the topic. Applied to Google, the search volume for a brand is therefore not necessarily decisive for EAT.
EAT as a gatekeeper and important ranking influence
It has been clear to every SEO since the core updates of recent years that EAT has an important influence on rankings . John Müller spoke of a relatively new ranking influence at Commerce Week 2021. However, EAT has been prominently mentioned in the Quality Rater Guidelines since 2014 .
The latest prominent mention of EAT was in 2019 in russia phone number data the wake of core updates and Google's official information on them (see What webmasters should know about Google's core updates )
It's important to understand that search raters have no control over how pages rank. Rater data is not used directly in our ranking algorithms. Rather, we use them as a restaurant might get feedback cards from diners. The feedback helps us know if our systems seem to be working.
If you understand how raters learn to assess good content , that might help you improve your own content. In turn, you might perhaps do better in Search.
In particular, raters are trained to understand if content has what we call strong EAT. That stands for Expertise, Authoritativeness and Trustworthiness. Reading the guidelines may help you assess how your content is doing from an EAT perspective and improvements to consider.
It is very likely that the manual evaluations of the search evaluators or quality raters since 2014 have been used as manually verified machine learning algorithms as learning material for the creation of models for the algorithmic determination of EAT. These models are based on recognized on- and off-page patterns that are significant for EAT.
Machine learning systems need time to build models, especially if they are supervised. This means that they learn with manually verified training data.
Table of contents [ Hide ]
1 EAT as a concept for brand identification and quality assurance
2 EAT as gatekeeper and important ranking influence
3 The influence of EAT on Google ranking
4 entities and EAT
5 Factors Influencing EAT
6 Thematic positioning of the brand/domain
7 How do you position yourself in a topic area?
EAT as a concept for brand identification and quality assurance
EAT is Google's own concept to identify publishers and authors who are a brand. Google wants to use it to improve the quality of search results and thus the user experience with the SERPs.
Google itself distinguishes between relevance and quality. Relevance always has a bearing on the search query and relates to the respective document. (More on the topic of relevance in the article Relevance, pertinence and usefulness on Google ). Quality can relate to the quality of the content of the document or the publisher or author. Brand concepts can be used especially for the latter in order to consider the EAT concept.
brand characteristics
A trademark has the following essential characteristics:
popularity
Trust
thematic authority
thematic expertise and competence
Three of these characteristics can also be found in EAT. Pure popularity is not a useful characteristic for determining quality, as it is detached from the topic. Applied to Google, the search volume for a brand is therefore not necessarily decisive for EAT.
EAT as a gatekeeper and important ranking influence
It has been clear to every SEO since the core updates of recent years that EAT has an important influence on rankings . John Müller spoke of a relatively new ranking influence at Commerce Week 2021. However, EAT has been prominently mentioned in the Quality Rater Guidelines since 2014 .
The latest prominent mention of EAT was in 2019 in russia phone number data the wake of core updates and Google's official information on them (see What webmasters should know about Google's core updates )
It's important to understand that search raters have no control over how pages rank. Rater data is not used directly in our ranking algorithms. Rather, we use them as a restaurant might get feedback cards from diners. The feedback helps us know if our systems seem to be working.
If you understand how raters learn to assess good content , that might help you improve your own content. In turn, you might perhaps do better in Search.
In particular, raters are trained to understand if content has what we call strong EAT. That stands for Expertise, Authoritativeness and Trustworthiness. Reading the guidelines may help you assess how your content is doing from an EAT perspective and improvements to consider.
It is very likely that the manual evaluations of the search evaluators or quality raters since 2014 have been used as manually verified machine learning algorithms as learning material for the creation of models for the algorithmic determination of EAT. These models are based on recognized on- and off-page patterns that are significant for EAT.
Machine learning systems need time to build models, especially if they are supervised. This means that they learn with manually verified training data.