Maximize Search Visibility with Advanced Nested Schema Markup

Schema markup, also known as structured data markup, is a type of code that you can add to your website's HTML code. It helps search engines understand the content and context of your content and the relationship between web pages better, allowing them to provide more informative and relevant search results. As a result, it also helps your website appear in more rich results like Featured Snippets, FAQs and People Also Ask.

Schema markup uses a standardized vocabulary of tags (or properties) that define different types of information, such as articles, events, products, reviews, organizations, and more. By implementing schema markup, you can provide explicit metadata about your content, which search engines can use to enhance the display of search results with rich snippets, knowledge panels, and other enhanced features.

The roll-out of BERT and previous algorithms by Google provided a clear indication that rather than index keywords, they were moving towards indexing entities, in short, entity optimization - as entities are language agnostic, and hold universal significance. Schemas are essential for a website’s SEO as they play an important role in entity recognition, as they give search engine bots a clear context of the website content, thereby enabling the content to be indexed as a rich result on SERPs.

In addition, with quality content a key factor for websites to rank on search, Google rolled out the E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) framework for SEO and it has since become the guidelines for experts around the world to ensure their pages rank on search and schemas play a vital role in showing that the website meets E-E-A-T and the Quality Rater’s Guidelines. In the words of Google, schema mark-up offers clues of the relationship of entities of the website and as it helps search engine bots understand the context of the content. In short, schemas help Google’s EAT scoring process easier as they help the search engine reduce ambiguities between entities, create connections between them and provide additional information about an entity that Google might not have picked up when indexing a page.

Establishing that schemas do give search engines clear context of the website content which help them retrieve the content as a relevant answer for a query online, and that it helps a website meet E-A-T and the Quality Rater’s Guidelines, schemas have in fact proved to boost the revenue of a business. How? You have to now consider Google as your homepage of your business, irrespective of whether you have a dedicated website or just a GMB profile. By giving the search engine surety of your website content – it's entities and relationships – you’re allowing the search engine to display your content as rich results on SERPs.

This in turn paves way for higher clicks, impressions and click-through rate as the relevant information displayed on SERPs and its attractive nature prompts users to take an action. Thereby, not only improving your visibility online but increasing the chances of a conversion and your business’s revenue.

There are many ways in which schema markup helps with SEO. Some of the key SEO benefits of schema markup include:

1.      Improved search results: Schema markup helps search engines better understand your content and display it more prominently in search results. This can lead to higher visibility, increased click-through rates, and improved organic traffic.

2.      Structured data types: Schema markup supports various types of structured data, including CreativeWorks (articles, books, movies), Events, Local Businesses, Organizations, Products, Recipes, Reviews, and more. Each type has its own set of properties to describe specific attributes. This helps search engines understand your industry, focus and content better, helping you rank for more relevant terms.

3.      Rich snippets: Schema markup can enable rich snippets, which are additional visual elements or information that appear alongside regular search results. For example, a recipe rich snippet may display the recipe's rating, cooking time, and calorie count.

4.      Knowledge graph: Schema markup can contribute to the creation of knowledge graphs and knowledge, which are information boxes that appear on the right side of search results. These panels provide concise information about a particular entity, such as a person, organization, or landmark. For a business, as search engines like Google understands your brand as an entity, Google Knowledge Graph can start appearing for searches of your brand. As Google understands more of your content, the knowledge graph becomes richer with more information about your business, increasing your brand visibility and trustworthiness.

5.      Brand visibility: As a result, your brand and content can appear across various elements in the search results page, growing your brand visibility, recall and trust.

In summary, schema markup is a way to provide structured data about your web content, helping search engines understand and present your information in a more organized and visually appealing manner. It can enhance your website's visibility, click-through rates, and overall, SEO performance.

Schema.org has over 850 types of schema markup and this vocabulary is constantly growing. Each schema type is designed to represent different types of content and entities. Here are some of the most common types of schema markup:

• Organization Schema: Used to describe an organization or business entity. It includes properties like name, logo, contact information, social media profiles, and opening hours. There are also schema types available for a wide range of industries. In addition to organization, you can markup your website with the most relevant industry type that your business belongs to.

• LocalBusiness Schema: A specific subtype of the Organization schema, used to mark up local businesses like restaurants, shops, or hotels. It includes properties such as address, phone number, opening hours, and customer reviews.

• Product Schema: Used to mark-up products available for purchase. It includes properties like name, description, image, price, availability, and review ratings.

• Review Schema: Used to mark-up reviews of various items, including products, services, businesses, and movies. It includes properties such as reviewer, rating, review text, and datePublished.

• Article Schema: Used to mark-up news articles, blog posts, and other written content. It includes properties such as headline, description, datePublished, and author.

• Person Schema: Used to describe an individual person. It includes properties like name, image, job title, birth date, and social media profiles.

• FAQ Schema: Used to mark-up frequently asked questions and their corresponding answers. It helps search engines display the FAQ content directly in search results.

• Video Schema: Used to mark-up video content, such as movies, TV episodes, or online videos. It includes properties like name, description, thumbnail URL, duration, and upload date.

• Event Schema: Used to describe events such as concerts, conferences, or sports events. It includes properties such as name, startDate, endDate, location, and performer.

• Recipe Schema: Used to mark-up cooking or baking recipes. It includes properties such as name, ingredients, instructions, cook time, and nutrition information.

These are just a few examples of the types of schema markup available. The schema.org website provides a comprehensive list of schema types and their respective properties, allowing you to choose the most appropriate markup for your content or entity.

The recommended format for implementing schema markup is JSON-LD (JavaScript Object Notation for Linked Data). JSON-LD is a lightweight and easily readable data format that allows you to embed schema markup within the HTML of your web pages.

The JSON-LD format offers several advantages for implementing schema markup:

• Separation of concerns: JSON-LD keeps the schema markup separate from the main HTML content, making it easier to maintain and update.

• Flexibility and readability: JSON-LD is human-readable and allows for more flexibility in organizing and representing the schema markup. It also supports nested structures and can accommodate complex data relationships.

• Compatibility: JSON-LD is widely supported by search engines, including Google, Bing, and Yahoo!, making it the recommended format for implementing schema markup.

Schemas are basically a set of content types, and each type has its set of properties. As defined by search engines Google, Yahoo, Bing, and Yandex, schema types are arranged in a hierarchal structure and till date, there are 818 Types, 1326 Properties, and 289 Enumeration values in the schema dictionary or vocabulary.

When schema is implemented in the code of a web page in the form of schema attributes, it helps search engine bots identify the entities within your content and their relationships to one another. Schema attributes are basically information in the website code that make up the schema property. While the attribute is simplistic, the combination of attributes is complex and help define the schema property and its relationship.

There are generally two types of attributes – Default attribute and Fixed Attributes. As the name suggests, a default attribute is what it is and cannot be changed while a fixed attribute is one which has a fixed value and cannot be changed. Examples: The schema attributes can be implemented in the website’s HTML code using either JSON-LD or RDFA syntaxes.

However, Over the last few years, JSON-LD has become the most preferred structured data. Why? JSON-LD is well-implemented. It can be embedded in "script" tags in the head of a document (moving out of HTML body), separated from the data it describes. This makes JSON-LD a format that can be templated, easily implemented and a great option for adding, deleting, or updating purposes. 

Other formats like Microdata or RDFa are neither that flexible nor easy to use options for adding, deleting, or updating purposes. RDFa are inline markups applied to HTML documents and define attributes that are added to the HTML. Above all, search engines love and prefer JSON-LD and thus JSON-LDs are more picked up. Here is what Google has to say – “Google recommends using JSON-LD for structured data whenever possible”. Period. 

Once the schema code is implemented in the HTML using a Schema Generator, the schema code has to be validated for any errors or warnings using a schema testing tool. If the schema code has errors in case you have included a deprecated schema property, it has an incorrect structuring of the file, or due to other reasons, there will be no point publishing the schema on your website. Instead, rectify the errors and warnings before publishing it on your website. 

To see how your content would look as a rich result on the search result page (SERP), run the JSON-LD block that contains the schema code on Google’s Rich Result Testing tool. 

Many businesses often assume that the job is done once the schemas are published on the website – error and warning free. However, this is not the case as the schemas implemented on the website need to monitored closely for errors or warnings that prop up – which can happen if there are any website content changes or Schema.Org changes or updates their vocabulary. Deprecated schema properties will be flagged as an error and for the content to be indexed and displayed on SERPs as a rich result, it should be error-free.

Having a system in place to monitor published schema and having impact reporting for your business to assess the difference schemas are making on your website in terms of rich result growth and SERP saturation is as important as taking the first step of publishing schemas on your website.

While implementing schema markup can bring various benefits, there are a few challenges that you may encounter during the process. Here are some common challenges with schema markup implementation:

• Technical knowledge: Implementing basic schema markup requires familiarity with HTML and the ability to modify website code. However, implementing basic schemas will not help search engines fully understand your content. The nesting of different schema types and use of advanced schema attributes requires a deep understanding of schema architecture.

• Identifying appropriate schema types: Choosing the correct schema types to represent your content or entity can sometimes be confusing. It's important to research and understand the available schema types to accurately represent the specific attributes and properties of your content. In addition, to effectively build relationships between the content elements or entities, nesting schemas correctly is important. At Milestone, we have done years of research and testing to solve this problem for our clients and to help them deploy and maintain error-free schema markup on their website at scale.

• Schema updates and changes: Schema.org periodically releases updates and new versions of schema markup. Similarly, search engines also change guidelines for schemas. For instance, a schema attribute that is optional today can become mandatory tomorrow resulting in errors in your schema implementation. 

• Compatibility across platforms: Different search engines and platforms may have varying levels of support for schema markup or interpret it differently. It's essential to ensure that your schema markup is compatible with the search engine(s) you're targeting to maximize its effectiveness. Milestone Schema Manager is platform agnostic and does not require engineering resources at your end to implement advanced, nested schema architecture on your website, irrespective of the platform you use.

• Code implementation: Integrating schema markup into existing website code can be complex, especially if your website has a large number of pages or a complex structure. Ensuring that the markup is added consistently and accurately across all relevant pages can be a time-consuming task. Manually implementing schemas on your website can be a time and resource drain. Milestone Schema Manager helps automate the process of implementing and maintaining error-free schemas on your website.

• Validation and errors: After implementing schema markup, it's crucial to validate it using tools like Google's Rich Results Testing Tool and Schema.org’s schema markup validator. Ensuring that the markup is error-free and properly interpreted by search engines can be a challenge, especially if there are complex or nested markup structures.

• Monitoring and maintenance: As your website evolves and content changes, it's important to regularly monitor and update your schema markup accordingly. Search engines ignore schemas with errors. As schema vocabulary evolves, updating your schema tags to maintain error-free schemas can be time consuming. Maintenance can be a challenge, particularly if you have a large website with frequent updates or if you're using a variety of schema types. This is where automation of schemas with Milestone Schema Manager can significantly reduce the cost and overhead of maintenance.

Despite these challenges, the SEO impact of schema markup implementation makes it worth the effort. With Milestone Schema Manager, you can eliminate most of the challenges of schema implementation and save on resources and maintenance overheads.