The development of Google into a semantic search engine and the increasing influence of E-A-T on rankings go hand in hand.
There is a common thread of innovation and updates that Google has been following for the past 12-plus years. Here’s a timeline of key events:
The organization of data and information around entities makes it possible for Google to rank entities of the entity type Person such as authors and organizations (publishers and companies) with regard to topics according to E-A-T.
Authors, companies and publishers as entities
Content is published by people such as authors and organizations such as companies, associations and government agencies. These organizations and people are named entities.
Google increasingly arranges or organizes content around entities. Google can draw conclusions about the credibility and relevance of the document or content via the respective entity.
In the case of online content, there are usually at least two parties involved. The author/producer who created the content and the publisher or domain on which the content is published.
The author is not always a direct employee or owner of the domain. For example, in the case of a guest article, the publisher and author are not the same.
In my view of SEO, the entity classes such as organizations, products and people play a special role, as these can be evaluated via the characteristics of a brand such as authority and trust or E-A-T.
Digital representations of entities
Entities that belong to certain entity classes, such as persons or organizations, can have digital representations such as the official website (domain), social media profiles, images and Wikipedia entries. While images tend to be the visual image of the entity, especially for people or landmarks, a person’s corporate website or social media profile is the content image.
These digital representations are the central landmarks closely linked to the entity.
Google can identify this linkage primarily through external linking of the website or profiles with link texts containing the exact entity name and/or the unique click behavior in search queries with navigational or brand or person-related search intent on the URL.
It’s all about relevance, trust and authority
The credibility of author and publisher has become increasingly important for Google. The search engine came under considerable pressure because of its fake news problem. A high degree of accuracy and relevance is a top priority for Google and its users.
Through numerous core updates and the E-A-T ratings introduced in version 5.0 of the Quality Rater Guidelines as part of the PQ rating in 2015, it is clear how important the factors of relevance, trust and authority are for Google in this regard.
The Quality Rater Guidelines list the following important criteria for evaluating a website:
- The Purpose of the Page
- Expertise, Authoritativeness, Trustworthiness: This is an important quality characteristic. Use your research on the additional factors below to inform your rating.
- Main Content Quality and Amount: The rating should be based on the landing page of the task URL.
- Website Information/information about who is responsible for the MC: Find information about the website as well as the creator of the MC.
- Website Reputation/reputation about who is responsible for the MC: Links to help with reputation research will be provided.
Here, the points E-A-T, transparency with regard to the operator of the website and his reputation play a role in the domain-wide evaluation.
Expertise, authoritativeness and trustworthiness are currently described as follows in the Quality Rater Guidelines:
- The expertise of the creator of the MC.
- The authoritativeness of the creator of the MC, the MC itself, and the website.
- The trustworthiness of the creator of the MC, the MC itself, and the website.
From entity to digital authority and brand
If we look at the characteristics of a brand, expertise, authority and trust play a central role.
In addition to the aforementioned characteristics, popularity is also an important characteristic of a brand, although this is not necessarily the main focus for authority or expertise.
Therefore, it can be said that a brand also combines all the characteristics of authority plus a high level of awareness or popularity.
Google attaches great importance to brands and authorities when ranking websites.
As early as 2009, Google rolled out the Vince Update, which gave large brands a significant ranking advantage.
Not surprising, given this statement:
“The internet is fast becoming a ‘cesspool’ where false information thrives. Brands are the solution, not the problem. Brands are how you sort out the cesspool. Brand affinity is clearly hard-wired. It is so fundamental to human existence that it’s not going away. It must have a genetic component.”
Former Google CEO Eric Schmidt
Brands combine characteristics such as popularity, authority and reputation (i.e., trust). I see trust and authority as one of the most important criteria, in addition to document relevance in relation to the search intent, as to whether Google allows content to appear on Page 1 of search results.
Google cannot afford to place content from untrustworthy sources in the user’s field of vision, especially for YMYL topics.
As a result, many affiliate projects that haven’t bothered to build a brand have fallen flat on their face. Popularity alone only plays a limited role.
Amazon and eBay are very popular brands, but they lack authority in certain thematic areas. That’s why more specialized stores usually rank better than the big e-commerce portals.
Organize an index around entities
A semantic database is organized out of entities, their relations and attributes. Unlike a classic database, information is captured around entities and relationships can be created between entities via edges.
As already mentioned, entities can be provided with labels or information for clear identification and for better classification in the ontological or thematic context.
Entities are increasingly becoming the central organizational element in the Google index. Insofar as search queries have an entity reference, Google can quickly access all stored information about the relevant entities and relationships to other entities via the Knowledge Graph.
Search queries without reference to entities recorded in the Knowledge Graph are handled as usual according to classic information retrieval rules. However, Google can now use NLP to identify entities not in the Knowledge Graph, provided that the search term contains an existing grammatical structure of subject, predicate and object (triples).
Screenshot from the Google NLP-API
I think that in the future, there will be an increasing exchange between the classic Google search index and the Knowledge Graph via an interface. The more entities are recorded in the Knowledge Graph, the greater the influence on the SERPs.
However, Google still faces the major challenge of reconciling completeness and accuracy.
The tool Diffbot Natural Language API Demo shows very nicely how text analysis via Natural Language Processing can be used to collect information about an entity and can be transformed into a Knowledge Graph.
In an entity-based Index, you have the following components:
- Nodes (Entities)
- Entity ID
- Entity Name
- Edges (Relationship between entities)
- Digital Representations (could be also own nodes/entities)
- Resources (documents, videos, audios, images, etc.)
- Entity Types or Classes
- Topic Classes and their keyword clusters
The organizational structure around single entities might look like this:
Possible index structure for the entities Taylor Swift and Joe Alwyn
The Structure around an entity is influenced by the entity types and attributes mined over the digital representations and documents, videos and other resources Google can crawl and analyze.
So Google can connect topics and their keyword clusters with entities.
The E-A-T evaluation is also based on these resources depending on the signals I mentioned in my article 14 ways Google may evaluate E-A-T.
Non-validated entities next to Knowledge Graph
I think Google has more entities on the screen than just the ones officially recorded in the Knowledge Graph. Since the Knowledge Vault and Natural Language Processing can be used to analyze entities in search queries and content of any kind, there will be a second unvalidated database next to the Knowledge Graph. This database could contain all entities recognized as entities, assigned to a domain and an entity type, but that is not socially relevant enough for a knowledge panel.
For performance reasons, something like this would make sense, as such a repository would allow not to start from scratch again and again. I think all entities are stored there, where the information regarding correctness cannot (yet) be validated.
Thus, Google would also have the possibility to apply the explained signals to other entities besides those recorded in the Knowledge Graph to perform E-A-T evaluations.
Overview: Data Mining for the Google Knowledge Graph
Google can recognize semantic relationships between keywords, topics, entities
Since the launch of Hummingbird, Google has sought to identify, extract, and related entities.
The relationships between entities, people and topics are important to Google because this is the way they can algorithmically determine contextual relationships, the quality or strength of the relationship, and about it, authority and expertise.
Google can recognize via co-occurrences of entities and keywords with which topics entities are in context. The more frequently these co-occurrences occur, the greater the probability that a semantic relationship exists. These co-occurrences can be determined via structured and unstructured information from website content and search terms.
If the entity “Empire State Building” is often named together with the entity type “skyscraper,” there is a relationship. Thus, Google can determine the relationship between entities and entity types, topics and keywords. Google can determine the degree of relationship by the average proximity in the texts and/or the frequency of co-occurrences.
For example, Zalando is closely related to other entities such as fashion brands (e.g., Tom Tailor, Nike, Tommy Hilfiger and Marco Polo) and product groups (shoes, dresses, bikinis).
These relationships can vary in strength. Google can use the strength of these relationships to assess expertise and, above all, authority and incorporate them into the E-A-T concept.
Recognize authority and entity relevance via the domain
As already explained, the website is a digital representation of an entity. Google Keyword Planner can be used to display keywords related to a domain.
The keywords are output in a list sorted by relevance, as shown here in the example of the domain footlocker.com.
The keyword combinations in which footlocker appears together with products and topics are interesting. They show in which context users search for the brand Footlocker.
Keyword List based on Footlocker.com
If you then remove all keywords with Footlocker from the list via the filter, you get a list of generic keywords that are still sorted according to a (semantic) relevance in relation to the domain.
Keyword List based on Footlocker.com without Footlocker
Exciting? I leave it to everyone to speculate further.
In my experience, domains for these keywords and topics have it easier to rank in Google search.
What this all means for SEOs and content marketers
Brand and authority are playing an increasingly important role in search engine optimization. This ensures that SEO techniques can no longer influence search results alone. It is just as much about marketing and PR.
In addition to the well-known SEO fundamentals of ensuring crawlability, indexing control, internal linking optimization and website hygiene, it is primarily the triad of relevance, trust and authority that needs to be considered.
For findability on Google, but also in general, SEOs and online marketers should focus not only on content, link building, crawling and indexing control but also on the effects on ranking through brand building. This requires collaboration with the people responsible for branding and PR. This way, possible synergies can already be taken into account during the campaign conception.
Relate your brand to topics/products for which you want to be found
Do this in all marketing and PR activities, with a view to Google ranking. Be it marketing campaigns, marketing collaborations such as Home2go or Footlocker have been done to promote certain search query patterns.
One should try to generate cooccurrences and links from topic-related editorial environments via PR campaigns or content marketing campaigns.
In general, owning content via owned media and signals via co-occurrences or brand and domain mentions in certain topic environments can increase the authority of a brand and thus the ranking for keywords located in these environments.
The more clearly Google can identify the positioning of the company, author and publisher, the easier it will be to rank the thematically relevant content linked to this entity.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
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About The Author
Olaf Kopp is an online marketing professional with over 15 years of experience in Google Ads, SEO and content marketing. He is the co-founder, chief business development officer and head of SEO at the German online marketing agency Aufgesang GmbH. Olaf Kopp is an author, podcaster and internationally recognized industry expert for semantic SEO, E-A-T, content marketing strategies, customer journey management and digital brand building. He is co-organizer of the PPC-Event SEAcamp and host of the podcasts OM Cafe and Content-Kompass (German language).