How Google ranks entities based on trust factors

For a long time now we knew that Trust and authority are the two major factors for ranking in Google and that other low quality techniques are just quick fixes that doesn’t last long and doesn’t pin you to the top results.

Trust factors are calculated not only by the SeedList but for entities also, the more authority the entity has the higher trust rank it gets for the information published. Therefor if we associate our content and marketing efforts around trust rank and authority we will be able to rank higher and for long period of times and across a broader spectrum. Either by associating ourselves with established high trust rank entities or by establishing high trust rank ourselves.

A patent Google filed back in 2006 and got in 2009 might shed some light on how an entity gains high trust factors and how it is calculated.

In Google Patent for ranking based on Trust factors it is clearly shown that there are several mechanisms at work when trying to compute trust factors for entities, labels and user behaviors.

Mechanism 1 & 2

Determining trust rank for an entity and trust factors between users and entity.

When an entity* (A person, a group, organization, website, business, institution, government agency or any other.) writes or publish online on specific label* (subjects, categorical identifier), Google makes an annotation* (marks the relationship between the entity and the subject and saves it in an annotation DB) then google calculates the trust factors between a user and the entity in relation to the label using different indicators such as “Trust Button”* (explained later on this document) and stores the record for

the trust relationship between user and entity. Then determine the trust rank for the entity in direct relation to the label*

How Google determine trust factors for an “Expert” or an entity.

To make a long story short, there are different levels of trust the user can give the entity and on many different subjects, that means that an entity can gain the respect of users on politics and not on sports.

One of the examples used by Google to determine the trust factors between a user and an entity is the use of a “Trust button” on the entity’s website, although Google does not provide an out loud explanation to what is actually a “trust button” you can understand it from a short description on how users interact with a “Trust button” and it is safe to assume that it is a link within the page that directly correlates to the query that was used by the user in the initial search or the label Google is trying to compute trust factors to. Which means User behavior is directly connected to trust factors.

Trust buttons or trust lists or vanity lists are some of the factors taken by Google to determine the relationship between the user and the entity in order to determine the trust rank the entity gets.

After Google had determined the trust factors for a specific label through an entity it re-ranks the search results based on the new trust rank.

Google are comparing the label trust rank and relevancy to the document itself and then to the labels associated with the document and then to the entity associated with the document and the label and then re ranks everything accordingly.

Trust rank is dynamic and can change all the time, Google describes in their patent that trust factors can decay if users does not use the “Trust Button” and other indicators over time, meaning that an entity keeps high trust factors the more users associate the entity as an authority on the label that entity publishes.

Trust rank increases when more trust lists are connecting the entity to a certain label, therefor an “Author” is extremely important for gaining trust.

In Conclusion, Trust factors are extremely important in today’s Google ranking and gaining this trust requires a well orchestrated marketing efforts through content marketing, unified message and consistency over long period of time. Trust is gained only in the long run and can sustain your brand high in rankings for a very long time.

You can see the Original Publishing on Linkedin