Structured Data Checker: Schema Markup Validator Tool

Introduction

Toolibex Structured Data Checker is ideal for website owners and SEO specialists who want to learn if their schema markup is correct and what part of it may need improvement. Bloggers, online shops, and business owners who want to ensure that their markup does not have any errors that may affect their business should also take a closer look at the tool. It will help you extract the most relevant information from web pages and make it searchable.

About the Toolibex Structured Data Checker

Toolibex Structured Data Checker is suitable for analyzing the information contained in structured data markup of the selected web page or the markup provided by the user, depending on the tool’s settings. This tool helps determine the page’s schema markup errors, check if the structured data is valid, and fix the issues detected. Schema markup is typically written in JSON-LD, though Microdata and RDFa can also be used.

A structured data checker can therefore be helpful to developers, companies with an online store, content managers, digital marketers, and SEO specialists. They can use it to check various types of page elements: Articles, products, organizations, and local businesses.

It is also essential to differentiate between validation of schema markup and eligibility for rich snippets. Schema validation tool checks if the markup is correct. Google Rich Results Test, in its turn, focuses on elements eligible for enhancement. Another thing to note is that correct schema markup does not guarantee that a website will appear in rich snippets. The two are interrelated but comprise separate concepts.

Why Schema Markup Matters for SEO

Schema markup helps search engines better comprehend the data on a website.

For instance, for an article, it makes the headline, author, date of publishing, and image address recognizable. As for a product, its name, price, availability, and other details become searchable. Correct and comprehensive use of schema markup can enable a site to appear in search results in a rich media snippet. Below are the primary advantages of using correct schema markup:

• Enhanced content – the search engine can comprehend data on the page better
• Eligibility for rich snippets – correct use of markup can validate the page for enhanced search results
• Better presentation of metadata – a more organized view of the page’s metadata
• Simpler maintenance – facilitates the detection of missing metadata, incorrect values, malformed data
• Higher site quality – the website’s structured data can be rechecked after its redesign or updates

Though it might seem that schema markup can improve any website’s rating, it is not entirely accurate. Properly formatted and correct schema markup does not influence the position in SERP directly but rather facilitates the search engine’s recognition of the page content. Therefore, for a website to rank high in search results, it should provide users with high-quality content, be accessible, include keywords, and follow SEO guidelines.

How Does the Structured Data Checker Work?

Validation of structured data markup entails several steps.

First of all, it is required to select the page that needs to be validated or prepare the markup that the tool is capable of processing. Then, using the Structured Data Checker, one can see the page’s or provided markup’s structured data. It is vitally important to pay attention to any errors, warnings, suggestions that may arise.

Errors indicate what exactly was wrong with the markup. They show invalid syntax or values. Warnings, in their turn, reflect some issues that should be taken care of. They usually concern the properties that are helpful but not necessary.

The meaning of every error and warning depends on the validation tool and the page’s markup type. Therefore, it is important to follow every instruction. After the necessary corrections to the markup have been made, it should be validated once more. If one wants to see if the website qualifies for a rich result in Google Search, it is advisable to use the Google Search Console validation tool. Besides, it is critical to ensure that the selected page is actually published and is indexed correctly.

Structured Data Checker and Result Analysis

After structured data has been processed, a series of recommendations and corrections to the markup may appear. The following suggestions would assist in understanding the result of validation.

Valid Structured Data

In terms of the schema, valid structured data means that the markup was validated successfully by a certain tool. However, it does not guarantee that the page will appear in the search results in a rich snippet because it should also conform to the specific requirements of the search engine.

Errors

When there are errors in the structured data, this indicates that certain issues prevent successful validation. There might be numerous reasons for those issues. The most common ones are incorrect JSON syntax, the use of invalid JSON-LD or Microdata, or the absence of some required properties. Errors can be seen in JSON-LD as highlighted lines of code. These lines indicate that there is something wrong with them. For instance, there might be an extra comma that spoils the entire JSON script. In cases like this, the issue can be solved by simply eliminating the extra comma.

Warnings and Recommended Properties

Typically, warnings are not obligatory. They indicate that a specific property is recommended but not necessary. It is advisable to include them in the markup to ensure that search engines recognize the page correctly.

Schema Type and its Properties

Schema type is a markup tag used to identify the type of item on the page. It is important to choose the correct schema type for each page. There are several schema types, each of which has a set of properties. Schema properties define the characteristics of items of a specific type. So, for instance, the Article schema type entails the presence of such properties as headline, description, author, and others. At the same time, different schema types have different sets of properties. The list of required and recommended properties is provided by Schema.org.

Eligibility for Rich Results

Google Search Console tool helps validate structured data against specific Google rich results features.

While general schema validation tools facilitate the search engine’s recognition of a website, they do not ensure that it will validate against Google’s specific features. Even when a structured data page validates successfully, that does not guarantee that Google will show it in a rich result snippet. The selection of a rich result is made by Google algorithms based on several factors.

Examples of Schema Markup Validation

Example 1: Article

An example of using schema markup can be a blog about indoor plants. In this case, the blog post can be identified as an Article. The example of JSON-LD code for an Article would be:

{"@context":"https://schema.org","@type":"Article","headline":"Indoor Gardening Tips for Beginners"}

Example 2: Ecommerce

Another example of using structured data markup can be an online store. In this case, a product page should include Product schema. The example of JSON-LD code for a product would be:

{"@context":"https://schema.org","@type":"Product","image":"[URL]","name":"Indoor Gardening Tips for Beginners","offers":{"@type":"Offer","availability":"[availability]","price":[price],"priceCurrency":"USD"}}

As the example shows, in the case of a product, it is necessary to indicate its name, price, currency, and availability. Moreover, the image of the product should also be identified. The most common mistake is that the indicated price differs from the one shown on the website.

Example 3: Organization

This example concerns a business website. In this case, it is vital to indicate the type of business. Organization schema has several subtypes, each of which has to be identified as well. So, for instance, there are such subtypes as LocalBusiness, FoodEstablishment, Gym, and others. The example of JSON-LD code for an organization would be:

{"@context":"https://schema.org","@type":"Organization","name":"Indoor Gardening Tips for Beginners","url":__PROTECTED_FOREIGN_QUOTE_1__,"email":__PROTECTED_FOREIGN_QUOTE_2__}

Example 4: Organization (another one)

{"@context":"https://schema.org","@type":"Organization","name":"Indoor Gardening Tips for Beginners","url":__PROTECTED_FOREIGN_QUOTE_1__,"telephone":__PROTECTED_FOREIGN_QUOTE_2__,"openingHours":[openingHours]}

Schema Markup Validation Tips

• Select the correct schema type. Make sure that the chosen schema type is correct. It should correspond to the content on the page.
• Keep structured data consistent with the content on the page. Ensure that all the data indicated in the structured markup can be found on the page. Avoid using data that users will not be able to see.
• Use JSON-LD. JSON-LD is used in the majority of cases. It is important to write correct JSON-LD code since any syntax error will lead to validation failure. Besides, JSON-LD is usually simpler than Microdata and RDFa.
• Fix the syntax issues. Invalid JSON or incorrect code will prevent further validation. Make sure that the JSON syntax is correct and that there are no extra spaces or characters.
• Differentiate between errors and warnings. Errors indicate that something is wrong and should be corrected. Warnings, in their turn, suggest that something can be improved. Each tool has its own list of warnings.
• Consult documentation. Different tools have different sets of indications. To find out the list of properties that should be included in the schema markup, it is advisable to consult the documentation provided by Schema.org and/or Google Search Central.
• Check the website regularly. After making any changes to the website, it is essential to verify that the structured markup is still valid. Besides, it should also be checked when a new page is created or an existing one is updated or redesigned. Another scenario when a structured data scan is required is when a website has been changed, e.g., the SEO plugin has been replaced, or the theme has been updated.
• Avoid false advertising. Structured data markup should not be utilized to provide false information to search engines. Rather, it should transparently represent the contents of the page.
• Check the validity of the page. Schema markup should be valid; otherwise, it will not be processed. However, validation of structured data markup should not be the sole criterion for deciding if the page is correct. Instead, it is advisable to consult the recommendations provided by Google Search Console about the necessary properties. The tool can also help validate the page against Google rich results features.
• Consult separate tools for separate purposes. Schema validation tool and Google Search Console should not be used interchangeably. Each of them serves a different purpose, so they should be perceived as separate parts of the process.