Three ways to use schema Markup for SEO

 Search engine Optimization (SEO) is the art of presenting content on a web page in such a way that it is easy for a search engine to match it to the right queries.

Schema Markup can help an algorithm to interpret the information in your article correctly.

1. Classification and Branding

The first information a search engine, such as Google, wants to know is "What kind of page is this?" Second, it wants to know who is responsible for the content and can it trust the publisher and the author. 

Classification

Google wants to classify pages to determine if the content fits any specific type of structured data it wants to highlight in the search engine results page (SERP). Google calls such highlights rich results.

The most common type of page on a blog is an article. That type of page is a news article or an article that lays out some important information. Yet Google looks for other types of pages, such as step-by-step guides or frequently asked questions (FAQ) pages.

Branding (EEAT)

Search engines want to deliver only trustworthy content in their search results. In the. early days the links were the signal of trust across the World Wide Web. These days search engines look for more sophisticated signals to determine trust.

Belongs to a Website

You can use schema to state that this article belongs to a certain website. This may seem trivial, but articles are not only published as part of the website. They may be distributed as PDFs or as downloadable documents.

Published by a Business (or Entity)

You can also express that an article is published by a specific entity, such as a business or non-profit.

If you operate a niche website, the entity publishing may be the website itself or just a makeshift entity with the same name. However, if your website publishes content to market your legally registered business, then this is the entity you want to state as a publisher.

Written by an Author

Every piece of content is written by one or more authors. Search engines build a profile of authors they can identify and assign trust points to this author.

Especially if you hire an outside writer or a subject matter expert, you want to benefit from her or his good name.

2. Clarification of the subject matter

Humans are good at picking up on ambiguous subjects and figuring out which context the given text belongs to. Algorithms and search engines could use some help.

Google has built a knowledge graph to identify entities that one can relate to. Entities can be People, Organizations, Products, Events, or Concepts. 

What is the Article about?

Schema markup can specify the names of people, organizations, things, or concepts and link them to known entities with an identity in Google's knowledge graph.

By tying a name (as used in the text) to an entity with an ID Google can clearly understand what the article is about.

What entities does the article mention?

In the same way, as in the About section, you can clarify what entities you mean concerning the main subject(s)

Example for About and Mentions - Sections

For example, if you say: "The Macintosh has one core" we could speak about a computer with a one-core processor or about the fruit that has a core with seeds.

Using schema markup you can specify that the "apple" (https://en.wikipedia.org/wiki/Apple) refers to a fruit and the "core" is the endocarp (https://en.wikipedia.org/wiki/Fruit_anatomy#Endocarp) of the apple.

3. Clarification of Entities

As mentioned humans are good at picking up what is the meaning of a term from context. Computers can perform much better when they can infer from precise information.

What are entities?

The term entity is used in natural language processing to describe an object or concept with a name. A name may be one or more words. For example "Apple Inc." is an organization incorporated as a business. "Apple" may refer to that organization or a tasty fruit. "Marketing" is a field of study and a concept.

Disambiguating the Entities in the article

Search engines can interpret the text with methods from natural language processing to find the entities a text is referring to. The field of study is called "named entity recognition" in natural language processing. The state-of-the-art models can extract more than 90% of entities correctly. So they miss less than 10% of entities. Some of them may be not missed but incorrectly identified. 

With schema markup as described above, you the author or publisher can make sure that the right entities are classified as the subject of the text and also the right entities are linked in the mentions section.

Clarifying Values

Values are a special problem for natural language processing models. For example, the Google NLP API demo recognizes "$35" as a price entity and a number "35". 

However, I have produced content where the "$35" was a pay rate for labor. Now you may say a pay-rate is a price for a unit of labor, but what about the unit? Is it in an hour or a certain task? With schema markup, I was able to clarify to any machine what this $35 means in this context and this text.

Summary

There are three main ways to use schema markup for search engine optimization (SEO)

1. Classification and Branding

1. Type of page

2. Is part of publication

3. Publisher

4. Author

2. Clarify subject matter

1. About entities

2. Mention entities

3. Clarification of entities

1. Apple the fruit or Apple the tech brand?