This article provides readers with a detailed understanding of what structured data is, and why structured data markup is valuable to Google, Bing, Yahoo and Yandex. Following are three guidelines for deploying accurate structured data markup.
Two general key points regarding structured data markup revolve around...
- making sure the website meets all SEO best practice requirements covered in our previous article, and
- maintaining an awareness and avoidance of potential errors and violations.
Structured data is content that is marked-up using "Structured data markup".
Structured data markup is a standardized way of annotating content so that search engines, such as Google, can understand it, and is a great way of communicating metadata to search engines.
Search engines use structured data to index that content better, extract pertinent information from it and presenting it more prominently in search results, as well as surface it in new experiences and interfaces, such as in voice, maps, etc.
Major search engines such as Google, Yahoo and Bing, support the schema.org vocabulary for representing data in astructured fashion. This vocabulary defines a standard set of type names and property names, for example, http://schema.org/Person can be used to represent information about a person. Such information may include their name(s), address(es), deathPlace and birthDate. Data in the schema.org vocabulary may be embedded in an HTML page using any of: microdata, RDFa, and JSON-LD.
Marking up content on your website can lead to the generation of rich snippets in search engine results, thereby having the potential to enhance search results' CTR.
It can also help the search engines' algorithms better index and understand the content of your website.
#1: Structured Data
Is Part of
Google's SERP Patent.
On June 2, 2011, Google, Microsoft and Yahoo announced jointly to support schema.org for creating and supporting a common vocabulary for structured data markup on web pages
It is useful to know that many of Google's patents use structured data to fill-in various pieces of information to display within their SERP templates. Logic tells us that it makes a lot of sense to spoon-feed all bots with properly coded structured data. These patents provide some level of transparency into exactly what Google is thinking, planning and doing. Other search engines are on a similar trajectory.
Schema.org Microdata is one of several hundred vocabularies to consider using when extracting “entities” from a web page. Optimizing entities has become more important than optimizing for keywords because search engines wish to provide users with better answers to queries, and they can do this by internally verifying data that link to trusted documents; therefore, entities that provide specific meaning on web pages can better answer user queries than simple keywords. Therefore, we suggest the following:
» Map entities to external trusted vocabularies like Schema.org and many other relevant vocabularies such as those listed at Linked Open Vocabularies (LOV).
» Mark up all contents and entities; there are 675 classes and 965 properties as of May 2015 ( Source: Web Data Commons )
» Create a process to describe the various relationships between entities, classes and properties.
» Map the relationship between other statements about those “things.”
» Consider related topics, themes, ideas and concepts to help search engines understand and position your brand, website, products and services prominently in SERPs.
» Consider citations and references from relevant vocabularies and trusted Google sources.
Semantic technology is a trusted, long-term asset for your business that affords more benefits for your brand than traditional SEO strategies including link building.
Structured Data Markup.
The quality of structured data markup means everything to Google, Bing, Yahoo and Yandex. It is better to not have any structured data markup than to have incorrect markup.
This slide deck from University of Mannheim offers some interesting statistics on how poorly structured data is currently being performed by business owners, web developers and SEOs.
The list of structured markup violations seen on websites today is extensive:
|Usage of wrong namespaces||http./schema.org|
|Usage of undefined types||http://schema.org/Breadcrumb|
|Usage of undefined properties||http://schema.org/postID|
|Confusion of datatype properties and object properties||_:n1 s:address “Jump Street 21”|
|Property domain and range violations||§ :n1 a s:Product § :n1 s:price “for free”|
Semantic strategy and properly coded/mapped structured data markup is unlike any other web development project and requires a semantic strategist and individuals familiar with building ontologies.
Take your time and do it right.
#3: Use JSON-LD
to Map & Link
JSON is a useful data serialization and messaging format, and used in many service APIs, such as Facebook, flickr, twitter, etc, while JSON-LD is a JSON-based format to serialize Linked Data.
Linked Data is a way to create a network of standards-based machine interpretable data across different documents
and Web sites. It allows an application to start at one piece of Linked Data, and follow embedded links to other pieces of Linked Data that are hosted on different sites across the Web.
Linked Data is the foundation of how many search engines have used to build their own versions of the Knowledge Graph.
» a universal identifier mechanism for JSON objects via the use of IRIs,
» a way to disambiguate keys shared among different JSON documents by mapping them to IRIs via a context,
» a mechanism in which a value in a JSON object may refer to a JSON object on a different site on the Web
» the ability to annotate strings with their language,
» a way to associate datatypes with values such as dates and times, and a facility to express one or more directed graphs, such as a social network, in a single document.
JSON-LD's syntax has been designed to not disturb already deployed systems running on JSON, but provide a smooth upgrade path from JSON. It is useful for self-describing messages by:
» giving objects their own types (via using @types)
» associating properties with IRIs
» re-using terms that were defines in a referenced context
» specifying property types in a context.
An example of how JSON-LD is used to model this mock-up web page, is shown below:
"about": "Nike Running Shoes",
"keywords": ["Nike Running shoes", "NIKE RUNNING SHOES BEST SELLERS", "RUNNING SHOES VIDEOS", "RUNNING SHOES PRODUCTS", "TOP COUPONS, PROMO CODES, AND DEALS FOR NIKE RUNNING SHOES"],
"name":"Nike Zoom Wildhorse 2 Trail-Running Shoes - Men's",
"keywords": "NIKE RUNNING SHOES BEST SELLERS",
"thumbnailUrl": "https://www.domain.com/images/nike-zoom-wildhorse-2-trailrunning-shoes-mens.jpg" ,
Implementing structured data on web content represents an important shift in our ever evolving SEO strategy; these new tactics provide a method for dealing with the science of managing information and big data. While implementation can be somewhat confusing for business owners, web developers and even SEOs, these obstacles can be overcome with training for proper structured markup implementation.
Every website will eventually require this new meta data - structured data markup - in order for your website or web page/s to communicate with search engines more effectively than traditional, conventional SEO tactics.
These new strategic tasks are ideally performed by experienced semantic strategists with extensive search engine knowledge and technical experience.
Remember, it is better not to have any structured data markup than to have incorrect markup for the content on your site. Incorrect structured data markup is absolutely the worst thing you can do to a website; search engines will react adversely.
Stay tuned for more exciting and informative content from us!
With our 2-step strategy of applying both Semantic Markup and Structured Data to your website, you will experience between 5% to 10% monthly growth in traffic and sales.
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