Structured data is a standardised way of providing information about a webpage. It can help search engines such as Google to become more informed about the content on a specific website. Once Google understands your page data more clearly and concisely, it can be presented in a more appealing way in Google Search.
It is important for businesses to pay attention to structured data as it helps to create rich results, making it easier for customers and clients to find out more about their services.
What is structured data?
For those asking ‘what is structured data’, structured data can be described as information or data that is organised or structured. This data is organised and formatted in a specific way to make it easily readable and understandable by both humans and machines. This is typically achieved through the use of a well-defined schema or data model, which provides a structure for the data.
It is common to find structured data presented in tables, rows, and columns, with each field containing a specific type of data relating to its category and value. It is akin to a spreadsheet that has specific headings for each column. This format makes it possible for search engine algorithms to pick up and understand the data posted by a site. Structured data enables both tools and individuals to quickly scan, organize, and analyse vast amounts of data for information.
What is an example of a structured data?
Data can usually be categorised as structured and unstructured. Where structured data is organised in a way that makes it easily searchable and readable by data analysis tools, unstructured data includes content such as videos, emails and images. This type of data has no internal identifier to aid with the recognition process conducted by search functions. It is important to note that these 2 types of data actually complement each other. For example, structured data can help unstructured data by permitting insights into your unstructured datasets.
One of the main examples of structured data is names and contact information. Names and contact information are considered structured data because they are specific pieces of information that can be consistently identified and organised across different webpages. For example, the name of a person or organization, or their contact information, can be tagged in such a way that search engines understand exactly what that data represents.
This is particularly useful for businesses or organisations that want their contact information to be easily found and understood by search engines. By using structured data markup, a business can tag their name, address, phone number, and other relevant information, making it easier for search engines to display this information in a useful and consistent manner.
In addition, structured data can also improve the visibility of a website on search engine results pages (SERPs), potentially increasing click-through rates and driving traffic. For example, a search for a specific business might display a rich result with the business’s name, location, hours of operation, and contact information, all of which is facilitated through the use of structured data. So, while names and contact information are just one type of structured data, they play a crucial role in helping search engines understand and display relevant information about a webpage.
How does Google use structured data?
In order to understand how Google uses structured data, it is important to understand more about marking up structured data. Marking up structured data refers to creating the structured data code. HTML is regarded as a markup language allowing for the content on a web page to be organised so that a user will see the code. This aids the browser when displaying a specific web page, while the code remains invisible to the site visitor. The HTML also has information content called meta data that is created for the benefit of search engines.
As structured data is a form of meta data, it operates in a similar fashion to HTML by communicating content or data in an organised way so that search engines can pick up on it and display the content in an appealing way. Again, this is not seen by the site visitors and is made to be seen by search engines such as Google. Whether it is images or content, search engines can use structured data to precisely display the content in the search results. For example, with a product image, structured data allows search engines to identify the fact that it is a product image without having to rely on algorithms to collect this information. This is because the image will be labelled as a product image using certain words as identifiers.
While it may seem insignificant or unimportant to implement structured data, it actually holds a lot of value. Although Google is becoming smarter at picking up on certain things without needing to rely on a lot of assistance, structured data helps to cultivate rich results in a seamless way. Although Google does a good job in determining the nature of such content, using structured data can help this search engine to get an in-depth insight into the specific type of content you are producing with the correct markup. This will aid in the short term by picking up on things that algorithms cannot but will also mean that the site will be well-structured with your content being clearly defined for the user.
When businesses are grappling with a whole host of competitors, using structured data can give them and edge and help cut the costs for special services that could achieve the same result. This is because rich snippets are known to drastically improve the click-rate on these websites.
Is structured data good for SEO?
While structured data is not directly correlated to ranking higher on Google, it can help to create rich results. Rich results are visually-enhanced search results with information pulled from relevant structured data. The most common type of rich results are rich snippets. These can often boost clickthrough rates and increase organic traffic to your pages.
When it comes to search engine optimisation (SEO), structured data aids seo by helping businesses to greatly boost a website’s visibility and reach. It enables search engines to get a better understanding of the content of pages, enhancing the likelihood of ranking higher in search results. Google will use structured data to better comprehend the content on a page in order to display rich results.
Structured data can also support semantic search. This shifts attention to the meaning behind search queries instead of traditional keyword matching. This ensures that Google is able to bring back better results, even when users search for something obscure.
What are three types of structured data?
Structured data is a type of information that is well organised, making it easy to search for data analysis tools. It is typically quantitative, meaning that it has data that can be easily measured. Quantitative data can include names, addresses and dates, which is information that can be recognised and searched easily by computers. It is common for quantitative data to be put into tables which allows structured data perfect for performing analysis and combining with other data sets for storage in a relational database.
Structured data also has predefined types, allowing for storage in tables with relationships between rows and columns. A well-known example of how this is used is Excel, which is used by many businesses to track figures or informational that is critical for propelling productivity. Some examples of predefined types are customer names, email addresses, product directories, phone numbers, dates, times, transaction information and inventory control.
Semi-structured data is another type of structured data that combines elements of both structured and unstructured data. This type retains some of the same quantitative properties as structured data, but also incorporates qualitative properties which entail descriptive or categorical features. Semi-structured data can include the body of an email, JSON or CSV documents as well as NoSQL databases. It is likely that these types of structured data will be used in diverse fields such as customer relationship management, enterprise resource planning systems, online forms, web server logs, medical devices and point-of-sale software.
How do you verify structured data?
Verifying structured data entails checking its compliance with the defined schema, guaranteeing consistency and completeness, verifying uniqueness of specific fields and confirming its accuracy and relevance. This process involves validating data types, formats, grappling with missing values, checking for duplicate values In unique fields and cross-referencing with reliable sources.
The specific methods can vary based on the data type and context, and could involve SQL queries for relational databases or data validation libraries for programming languages like Python or R.
It is a good idea to compare the performance of your pages that don’t have structured data to those which do to see what types of results you are getting. The main way to initiate this process is to carry out a run prior to implementing structured data and then test your web page after it is enforced. Although this can be complicated as page views can vary on a single page for different reasons, it is still worth carrying out.
In order to conduct this, you should look at some of the pages on your site that do not use structured data and ones that have a backlog of data in Search Console. The pages you select should be those that won’t be impacted by the time of year, meaning pages that won’t vary much but are those that will still get a wide readership to generate meaningful data. Then, you can add structured data to your pages before confirming that your markup is valid and that Google has located your structured data using the URL inspection tool. This will generate results in a performance report which can be filtered according to the URL, giving you valuable insights.
What tool can you use to test for errors in structured data?
There are many tools to check for mistakes in structured data. For example, JSONLint is a well-known tool used to check and reformat JSON. JSON is a format often used to exchange data.
If you have XML documents, you can use an XML Validator. This tool makes sure your XML documents follow an XSD schema. If you’re using CSV files, CSVLint is a useful tool. It checks if your file can be read.
For SQL, SQLFiddle is a good platform. It lets you test and share SQL queries. If you have YAML files, you can use YAML Lint to check them.
Finally, Google’s Structured Data Testing Tool is a complete tool for checking schema markup or other types of structured data. It is important to select a tool that matches the specific format of your structured data. Using a tool made for your data format will give you the best results.
Discover why structured data is important with Aqueous Digital
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