Structur data allows you to tell Googlebot what kind of information a website contains so it can better interpret it , and with certain types of data, enrich how search results appear and generate impressions for voice assistants. However, if appli incorrectly, it could penalize the page in a manual Google review .
In the documentation on the manual actions that Google takes to penalize a site , we find multiple examples of misuse or abuse of structur data. These errors are always made intentionally as a Black Hat SEO strategy, in order to appear in the SERPs with rich snippets . It is very rare to make one of these errors unintentionally, so even if we claim that we have done it unintentionally, we will still be penaliz during a manual review.
They can be of two types:The tasks on the language format
We should not be afraid of being penaliz for structur data , since, as we have already mention on other occasions, when us well, they improve positioning and visibility in searches , as well as appearances in voice searches. To take advantage of the benefits of structur data without being penaliz, we must always apply them correctly and without deception .
Next, we are going to see what types of errors we should avoid , whether we want Google to correctly interpret the data or if we do not want to be penaliz . Basically, we have these types of errors:
The assignments on the grammar specifi by the schema.org and Google vocabularies
Semantic errors.
These are the same mistakes that can be made with We provide perfect and precise databases that are supposed to be qualitative enough for contacting your target audience. Ultimately, we want your company to grow in such a way so that there is not even one error with the database. We even Refurbish shop our database on the Weekly Basis. High-performance database of list websites that is said to be the source, and you can use our databases which listed both high-resolution issuance or release date. any markup language .
Syntactic errors
Syntactic errors occur when a language is written and the grammar rules of that language are not follow . In the case of structur data, we have to follow two types of grammar rules : those of the format in which we are going to write it, for example JSON-LD, and the grammar rules of the language defin by the schema.org vocabulary.
Syntactic errors regarding the format
As we have already mention, these are errors made when writing the format of structur data , whether JSON-LD or microdata , so that the data type cannot be interpret .
Let’s look at an example where we generate a JSON-LD with several typical syntax errors . One of them is caus because we didn’t take into account that the “license” attribute can be empty when generating this code:
The other syntax errors correct in the example, in case you miss them, are the quoting of attributes and the removal of the last comma before the closing braces. Requir attributes are also missing, but these are not errors due to not following the syntax of the format, but rather errors due to not following the syntax of the vocabulary.
In order to avoid making mistakes when forming structur data, we must follow the JSON grammar, defin in RFC 7159 , the JSON-LD specification at the W3C and the microdata specification at the WhatWG .
When a markup language follows the grammatical rules of viral marketing strategy for business its format correctly, it is said to be well-form (in XML validation tools , such as a sitemap, it is common to find this expression).
Syntactic errors on schem and Google
These are committ by not following the grammatical rules of the schema.org or Google specification .
Assigning an incorrect or non-existent data type to an attribute value. For example, if the attribute author can only be of type Organization or Person. We cannot break the grammar rules by assigning it data of type Event .
Adding an attribute to a data type that does not have one, due to errors in following the specification. For example,
This is an error because the specification indicates that LocalBusiness is compos of an address attribute of type PostalAddress , to which the addressLocality attribute corresponds, and not LocalBusiness :
Examples of syntactical errors of this type are:
Syntactic errors due to not following the vocabulary specification can be subdivid into two types: those made by not following the general schema.org specification and those made by not following the Google specification . We have already explain how to interpret schema.org to create structur data and that in the Google specification. We will find additional restrictions to the schema.org specification, such as which attributes are requir .
Differentiate the type of syntactical error with validation tools
This is important, because for the vocabulary of a structur data type to be correct, its format must first be syntactically correct. So if we have just one syntactical error in the format. Google will not read anything from the structur data type , and if we don’t have them.
But we have several errors in the vocabulary, it may interpret something even if it points out the errors in r.
Semantic errors
These are those committ by giving the data a meaning other than what it has . A clear and exaggerat example would be to use the Book data type for a recipe . Syntactically we can do it and, in addition. The Book type and the Recipe type inherit the same attributes from CreativeWork that we could fill in. But the meaning we would be giving it would not be correct .
It is common to find cases where, although there is no error, the meaning could be improv. For example, assigning the Article data type to a Blog post instead of the deriv type BlogPosting . But this is not a reason for a penalty .
No automat tool will tell us if the document is semantically correct . This is why Google performs manual reviews and why structur data exists – if the machine. Were able to duce the meaning of the data and the relationships between them without making mistakes. There would be no ne to mark them up.
In Google’s structur data specification
We will find the semantic meaning of each type of data in greater detail than in schema.org. The search engine’s documentation also includes examples to avoid confusion that could lead to a penalty.
For example, it happens a lot lately with the FAQPage and How to data types . As rich snippets start to be generat in SERPs and voice searches, they have start to be abus.
Other errors
Adding structur data to information that is not on the anhui mobile phone number list page or is hidden from the user is a common type of error by the most daring Black Hat SEO. Which we could also consider a semantic error and is grounds for penalty. This usually occurs, for example.
This is the kind of mistake that Black Hat SEOs often make on purpose
Google has recently limit the number of structur data types to which. It can be appli and does not allow its use on comments manag by itself in the LocalBusiness and Organization types. Due to the abuse of this type of structur data.
