Achieve Better SEO Results with Advanced Schema Markups

JavaScript Object Notation (JSON) is a lightweight and open standard file format to store and transport data from a server to a web page. Though it is a Java Script subset, JSON is a language-independent data format and offers flexibility for many modern languages (Python for example) to generate and parse code and can also be used as an alternative for XML in AJAX systems. JSON is preferred by programmers across the world as it is self-describing and easily understandable for humans to assimilate the context of the code and for machines to parse and generate as well. A fine example of JSON flexibility is its use to implement Schema code in the JavaScript. Using the JSON-LD extension, programmers can embed the schema code in 'script' tags at the head of a document (moving out of HTML body) - independent of the data is described below. This makes the process of adding schema to website code streamlined as it can be easily templated and any additions, updates, alteration, and removal of code to match the schema and its properties can be done with ease.

Schemas are basically a set of 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. Some of the common schema types are:

• Person
• Event
• Health
• Action
• Organization
• Review, Aggregate Rating
• Product, Offer, Aggregate Offer
• Place, Local Business, Restaurant

To give search engine bots context of the content when indexing the web page, the schema is implemented in the code in the form of schema attributes which help the search engine bots identify the entities and their relationships. 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 SERPs, 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.

With the roll-out of BERT and the previous algorithms by Google, they made 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-A-T (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-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.

Schemas are basically a set of 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. Some of the common schema types are:   Person Event Health Action Organization Review, Aggregate Rating Product, Offer, Aggregate Offer Place, Local Business, Restaurant   To give search engine bots context of the content when indexing the web page, the schema is implemented in the code in the form of schema attributes which help the search engine bots identify the entities and their relationships. 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 SERPs, 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 basic schema tagging is a start, created a nested schema architecture to coherently define the hierarchy of the entities and its relationship with other properties gives the search engine bot a finer understanding of what your website and its content is all about, which has resulted in a 20%-30% increase in organic search traffic for a website.   Example of nested schema architecture for a financial institution:   Example of nested schema architecture for a financial institution:

Milestone’s Schema Manager takes businesses through the entire circumference of the Schema Management process – from identifying page URLS, schema validation and deployment, schema monitoring and maintenance and essential schema impact reporting for businesses. Here are the key highlights of Milestone’s Schema Manager:

• Auto discovery of Page URLs that need schemas tags. The tool can auto discover up to 1 million URLs or you can choose to upload the URLs as well
• Point and click schema tagging
• One-click validation and deployment of schemas
• Continuous health check of schemas deployed or existing schemas of the website with error and warnings notifications. Raises alerts for deprecated schemas and ensures that the schema vocabulary is up to date
• Powerful Recommendation Engine to assist clients when adding schema tags using auto suggest and predictive methods to create a decisive nested schema architecture
• Bulk application of schemas to similar pages even by the thousands
• Integration with any CMS across the globe, Google Tag Manager, Adobe Tag Manager, and E-commerce Integration as well
• Top-notch reporting to check performance and impact. Clients can check impact by page/data type, rich result growth, universal saturation, and segment reporting showcases schema impact, errors and warning

Milestone Schema Manager goes past basic schema tagging and has given businesses a stable threshold that is easy-to-use to not only be in sync with Google shift to semantic search but to help businesses understand customer intent and use a nested schema architecture for their content to be the relevant answer on search in the form of rich results – which will only prompt an action and boost their clicks, impressions, click-through rate (CTR) and their overall visibility and revenue.

Listed below is the nested schema architecture for a Menu, Item or Recipe and the Knowledge Graph Visualization of schemas:

There are many different types of schema markup or structured data markup. But for the most part, here are the most popular:

• Person
• Local business schema
• Product
• Event
• Organization
• Movie
• Videos
• Book
• Recipes
• Review

Since there are so many types of schema markup, it makes it easier for you to get rewarded in rich snippets in Google. From star ratings, embedded photos and videos, NAP information, article and blogs, event dates, times and location, the options are endless.