Archives 2023

Are you making schema markups one by one and wish there was an easier way? Are you fed up with using plugins that create the same schema on every page? Do you want each page to have its own unique schema but don't know how to automate the process? Do you want to learn how to apply structured data on scale?

If you're interested in learning ontology and structured data for semantic SEO, as well as how to create dynamic schema markups, I'm currently building a course on these topics. Join my waiting list to be the first to know when it becomes available!

If you have a large website with thousands of pages, and you want to add dynamic markups to all of them, you're in the right place! we're going to explore the world of dynamic schema markups. We'll take a look at how they can be tailored for each page of your website, without the hassle of manual input. And how to uniquely customize them for each webpage dynamically, bypassing the time-consuming manual process. Say goodbye to generic schema and say hello to a streamlined, efficient process that not only saves you time but also enhances your website's SEO potential. Let's dive in and uncover the secrets of applying dynamic structured data on a grand scale!

The problem is that you want to apply unique structured data to your entire website, but you have a large amount of web pages.

The solution is to add schema to any number of pages with just one piece of dynamic code.

This guide will show you how to create dynamic schema markups and automate the process on scale.

• Install the Required Tools
• Suggested Tools
• Identify the Schema Types That You Want to Implement and Their Required Properties
• Create a Schema Template
• Identify Dynamic Content
• Transform Values into Variables
• Get the CSS Selectors for the Target Elements
• Create the Variables in GTM
• Deploy Your JSON-LD Code Using Google Tag Manager
• Test Your Implementation
• Submit Your Changes

Let’s start

Local Business Schema Optimization Guide

A local business schema is a type of schema markup that provides structured data about a particular physical business or branch of an organization.

By implementing local business schema markup on a website, businesses can provide search engines with clear and consistent information about their business.

This can help search engines display accurate and relevant information and increase the business's visibility to potential customers in the local area.

LocalBusiness schema provides several benefits, including improved search engine visibility, increased click-through rates, consistent information, better customer experience, and a competitive advantage over larger, national brands.

By implementing a high quality and semantic local business schema, businesses can improve their online presence, attract more customers in their local area, and make informed decisions about whether to visit or contact the business.

Here is how to Improve your local business schema for better performance:

• Educate yourself about local business properties
• Avoid repeating the same local business schema on the same page
• Avoid repeating the same schema on every page
• Pick the right local business schema type
• If you can't find the right type for your local business, use additional type
• Link your local business schema with your Google Business Profile
• Utilize reviews and aggregate rating markup
• Use DefinedTerm to declare your keywords
• Use the hasOfferCatalog relation to add an OfferCatalog to your local business
• Use the knowsAbout property
• Use the address and areaServed fields correctly
• Use the brand property to showcase your brand
• Regularly monitor and update your schema
• Consider including a founder field
• Connect all your entities in one schema
• Remove the pre-existing schemas on the page
• Check your local business schema with rich result testing tools

Google has recently introduced new guidelines regarding shipping details and merchant return policies to enhance merchant listings experience. These guidelines have been added to the product structured data help section.

This update is significant for businesses selling products. By including merchant return policy and shipping details in their structured data, along with the product price, reviews, and other rich result properties, businesses can enhance their visibility and attract more attention within Google Search. This, in turn, may impact their click-through rates positively from Google Search.

If you have exceptional shipping details and return policies, it is advisable to emphasize them through the Google Merchant Center and structured data to ensure their visibility within Google Search.

OfferShippingDetails and MerchantReturnPolicy are key requirements for the Rich Result experience in the Merchant listings of the Product schema. Your schema must include these properties, in addition to other specifications such as offer and price, to ensure compliance with the Rich Result guidelines.

Google Tag Manager can be used as a convenient method for adding offer shipping details and merchant return policy to an existing product schema using JavaScript.

If you have a WordPress website with an existing Product schema that lacks the necessary requirements for a merchant listing experience, and you're unsure how to add them, this article is tailored to help you.

I would like to express my gratitude to my friend Marcelo for bringing this issue to my attention. It is an important matter since numerous WordPress users face the same problem. Marcelo, a professional SEO consultant from Uruguay who has found a paid yet straightforward solution to this problem. I personally recommend him if you are in need of assistance.

In this article, I will guide you step by step on how to optimize the merchant listing experience to successfully pass the rich result test with no errors or warnings.

What is a knowledge graph?

A knowledge graph is a collection of interconnected data that is used to represent real-world entities and the relationships between them. The data is typically represented as a set of nodes (representing entities) and edges (representing relationships) in a graph structure hence the name "knowledge graph".

Knowledge graphs can be used to build semantic data models, and can also be utilized to enhance your website’s semantic model quality. One way to do it is by integrating it with external knowledge sources such as Wikipedia, Wikidata, and product ontology, This allows for the data to be linked with high authority resources and to be aligned with a common understanding of the concepts and relationships, which can improve the consistency and accuracy of your content.

In this article, we will explore the benefits of using ontologies and knowledge graphs, and how to implement them on a website in different industries ,while we are going to discuss the followings:

• What is ontology?
• How a knowledge graph works?
• What are popular knowledge graphs?
• Knowledge Graph Use-Cases: Is there examples of domain-specific industries?
  • Automotive Industry
  • Real Estates Industry
  • e-Commerce Industry
• Conclusion

SEO Guide to Building a Semantic Model Quality

In natural language processing, semantic model quality is used to evaluate and understand the performance of language models, machine translation systems, and other text-generating systems.

It is important because it helps to ensure that the model is able to convey text that aligns with the intended meaning.

Semantic quality is used in a wide range of applications such as text summarization and simplification, fact-checking, information retrieval, translation, chatbots, and question answering.

High-quality semantic models are coherent, consistent, and relevant to the current context. While poor-quality models are confusing, inconsistent, or irrelevant.

By evaluating the quality of a semantic model, SEO professionals can identify and address any issues that may be affecting the model's performance on search engines. This can help to improve the overall accuracy and effectiveness of the content for users and search engines.

So how you can measure this quality? The followings are the main quality dimensions that should be considered when evaluating a semantic data model:

• Accuracy
• Completeness
• Consistency
• Conciseness
• Timeliness
• Relevancy
• Understandability
• Trustworthiness
• How to increase semantic quality?