As a result, users and search engines are increasingly focused on accessing high-quality, reliable information. This shift has led many organizations to revise their content strategies to maintain accuracy, relevance, and trust in this evolving environment.

To develop a successful content strategy in this new search experience, marketers must address several critical questions on an ongoing basis:

• How can you maintain an up-to-date content inventory?
• What content gaps exist, and where are opportunities for new high-quality content to be added?
• Which existing content pieces require improvement or disambiguation?
• How has your content impacted your website’s performance as search evolves?

While your website content is a rich data source, it’s often unstructured. This makes it difficult to analyze and answer these questions at scale. Many marketers manually review and revise content to inform their strategy, which is time-consuming and inefficient.

So what if you could automatically structure your content to make high-level analysis fast and easy? Good news, a content knowledge graph can be leveraged to do precisely that. This approach is particularly valuable for large websites or organizations managing multiple sites, where understanding the full scope of covered topics can be challenging.

This article will explore how leveraging your content knowledge graph can support and enhance your content strategy.

By harnessing the power of your content knowledge graph, you can make well-informed decisions that drive your content strategy forward in today’s competitive digital landscape.

Understanding Content Knowledge Graphs

At Schema App, we define a content knowledge graph as a graph that represents entities (things), their attributes, and the relationships between them on a publicly-facing website.

Like a general knowledge graph, it uses a standardized vocabulary or ontology (such as Schema.org) to create a structured, reusable data layer. This structure enables machines to discover new insights through inferencing, helping to explore and understand the connections between various entities in your content.

At Schema App, we build content knowledge graphs by mapping the content on your website to specific types and properties in the Schema.org vocabulary. This results in a precise and organized framework that accurately reflects your content’s meaning and relationships.

While Schema.org provides an excellent foundation for knowledge graph creation, its available types and properties can be limiting. That’s why Schema App created the Omni Linked Entity Recognition (Omni LER) feature, which automatically identifies entities in your content that have been described in external authoritative databases such as Wikipedia, Wikidata, and Google’s Knowledge Graph. This process is known as entity linking, and it offers two significant benefits:

1. Improved SEO: Embedding these entities in the Schema Markup on your pages helps to disambiguate them, which enhances search engine optimization for queries related to those entities.
2. Content Inventory: Identified entities also function as an inventory of what’s discussed in your content, offering valuable insights for content strategy planning.

By leveraging both the Schema.org vocabulary and Omni LER, the content knowledge graph provided by Schema App gives you a comprehensive understanding of your content architecture. This enables you to make data-driven decisions to optimize your content strategy for search.

Content Knowledge Graph Use Cases

Now that you’ve been introduced to content knowledge graphs, let’s explore some practical applications and effective ways to leverage this powerful resource to enhance your content strategy.

Improve Content Inventory Organization

When you develop a content knowledge graph with Schema App, you can implement a multi-dimensional categorization method for your content.

Schema App’s Highlighter builds your content knowledge graph by consistently tagging and classifying your website content at scale. This is particularly beneficial for organizations with large websites, a wide variety of assets, and different content stakeholders.

Your content knowledge graph establishes meaningful connections between different content pieces based on entities, types, and properties – not just keywords. For example, a blog post would likely show up in your content knowledge graph as an instance of a BlogPosting with properties like author, datePublished, and dateModified. If Omni LER is also used, additional metadata about the identified entities mentioned within the article body will be added. This enables you to do more detailed content analysis, which we will cover later in the article.

Content Coverage and Gap Identification

By constructing your content knowledge graph with both the Schema.org vocabulary and Omni LER, you can query all of your content with greater precision. Schema.org provides detailed types and properties, and Omni LER adds unique entities for varied levels of granularity in your data layer. When combined, you can leverage your content knowledge graph to help you determine what new content to add or which existing content to improve to better meet your audience’s needs.

This holistic view of the Schema.org types and entities covered by your website allows you to:

• Identify areas of content saturation
• Discover underrepresented topics
• Align your content with current business goals and market trends

Use Case 1: Aligning Content With Business Goals

For instance, one of Schema App’s customers aimed to be recognized for their product’s ease of use. To align their content with this business goal, we employed the following strategy:

1. First, we identified Schema.org types and properties that indicate user support and ease of use. These included:

• HowTo
• BreadcrumbList
• FAQPage
• VideoObject

These content types can represent ease of use by making processes feel manageable and easy to follow, empowering users to self-serve, or simplifying site navigation.

2. We then queried their content knowledge graph to pinpoint where these types and properties already exist on their site and where existing content could be further enhanced to align content with their goals.

3. Finally, we identified opportunities to add net new content in alignment with their goal. For instance, we recommended creating more HowTo content with clear steps and accompanying images and/or videos to support ease of use.

Through this process, our customer identified content gaps that, when addressed, aligned better with their business goals and enhanced the quality of their site’s content.

Just like how content knowledge graphs can identify gaps in your content, they can also reveal how much of your existing content overlaps with desired entities. This information is crucial for ensuring that your content strategy covers all necessary areas and effectively addresses your audience’s interests.

Use Case 2: Assessing and Revising Content Coverage

Consider another example from one of our healthcare customers:

Our customer did entity linking using our OmniLER feature. The feature automatically identified known entities in their content, which revealed an unexpected insight: they had numerous blog posts mentioning COVID-19, a topic they no longer wished to emphasize in their content strategy.

Armed with this information, the customer was able to:

• Quickly identify all content pieces mentioning COVID-19
• Assess the relevance and necessity of each mention
• Selectively remove or update content to align with their updated business goals

This targeted approach allowed the customer to refine their content strategy without needing a time-consuming manual review of their entire content inventory.

Disambiguating Entities to Ensure Brand Name Consistency

Your content knowledge graph can also ensure the disambiguation of your entities and brand voice consistency across your website. This capability is particularly valuable when dealing with ambiguous terms or acronyms that could lead to misinterpretation or unintended associations.

For instance, imagine a scenario where our brand, Schema App, faces a challenge when its name is shortened to just “Schema” in some content. The word “Schema” can refer to various concepts on the web, from psychology to structured data. If machines unintentionally link this shortened form to unrelated information, it could confuse and potentially damage our brand image.

To resolve this issue, we would leverage our content knowledge graph to:

• Locate all instances where our brand name is inconsistently represented
• Implement a standardized approach to always use our full brand name, “Schema App”
• Disambiguate our brand using Schema Markup and entity linking. This ensures our brand is accurately identified and associated with the correct definition in external authoritative knowledge bases
• Ensure that our brand is consistently and correctly represented across all content

This scenario illustrates how a content knowledge graph enables organizations like ours to:

• Gain a holistic view of entity usage across our content
• Identify areas where content should be more explicit based on entity interpretation and their links to external knowledge bases
• Make informed decisions about content revisions to maintain brand integrity
• Ensure consistent brand voice and messaging across all content

By leveraging a content knowledge graph, we can proactively address potential ambiguities, maintain brand consistency, and enhance our content’s overall quality and clarity. This approach not only improves user experience but also protects our brand from unintended associations or misrepresentations, ultimately enhancing our performance in search.

Schema App Helps Develop Your Content Knowledge Graph

As explored throughout this article, a content knowledge graph is a powerful tool for optimizing your content strategy, improving SEO performance, and preparing your organization for the future of AI-driven search.

At Schema App, we implement semantic Schema Markup and automate the entity linking on your website to develop your organization’s content knowledge graph.

If you’re a current Schema App customer interested in leveraging your content knowledge graph, we encourage you to reach out to your Customer Success Manager. They can take you through what’s currently available so that you can leverage your content knowledge graph to support and enhance your content strategy.

If you’re new to Schema App and interested in harnessing the power of a content knowledge graph for your organization, now is the perfect time to get started. Our team is ready to help you navigate the complexities of semantic SEO and knowledge graph development, ensuring your content strategy is primed for success in today’s digital landscape.

Don’t let your content strategy fall behind in the era of semantic search and AI. Contact our team today to begin developing your content knowledge graph and optimizing your content strategy for search.

The post How to Optimize Your Content Strategy Using Your Content Knowledge Graph appeared first on Schema App Solutions.

Many large enterprises leverage AEM to create rich online experiences due to its high level of customization. AEM’s component-based architecture offers a flexible and modular approach to building and customizing websites, which, while powerful, can also create a complex environment.

Organizations can customize their AEM setup extensively, whether running on-premise or in the cloud, and can use AEM headless to deliver experiences across platforms and channels at scale.

Why Implement Schema Markup on an AEM Site?

Implementing Schema Markup on an AEM site is crucial for enhancing a website’s performance.

Schema Markup helps search engines understand and contextualize your website’s content more effectively, leading to better-aligned search queries, improved search performance, and higher conversion rates. Implementing specific types of Schema Markup can also make your web page eligible for rich results, allowing your brand to further enhance its visibility on the search engine results page (SERP).

Additionally, Schema Markup supports AI initiatives by building your organization’s content knowledge graph, facilitating deep machine understanding of your content and brand.

How to Implement Schema Markup on Your AEM Site

While the benefits of implementing Schema Markup are evident, AEM’s complexities can make it difficult for SEO teams to implement robust Schema Markup at scale. In this section, we will dive into the various methods of implementing Schema Markup on AEM to help you determine the option that best suits your team’s abilities and goals.

1. Manually Implementing Schema Markup on AEM

There are two primary approaches to manually implementing Schema Markup on AEM, both with their own unique challenges:

• creating static markup and pasting it into the post HTML, or
• creating a dynamic but complex solution.

Let’s dive in.

Write the Markup Manually and Paste it Within the Post HTML

You can manually write the Schema Markup and insert it into the HTML of each post. This method involves authoring the Schema Markup in JSON-LD and adding the markup directly to the page’s source code, which is not dynamic or scalable.

With this method, every time the content on a page is updated, the Schema Markup must also be manually updated to reflect the updated content. This approach results in static Schema Markup that requires constant maintenance and is not ideal for large-scale implementations.

Create a Dynamic Schema Markup Solution in AEM Manually

Since AEM is highly customizable, there are currently no standard plugins that can automatically inject default Schema Markup across pages.

If you want to dynamically generate Schema Markup based on the latest content on your page, you must manually develop a solution that maps AEM components to Schema.org properties. This involves identifying the components on each page and defining how their properties correspond to Schema.org properties.

Due to AEM’s lack of standardized components (i.e., title, featured image, author, etc.), this method will require you to manually structure the data and map each property to the appropriate Schema Markup, which can be tedious. Each page may have different components and subcomponents, making it challenging to create a one-size-fits-all solution.

Challenges and Considerations for this Approach

Implementing a dynamic Schema Markup solution in AEM is labor-intensive and typically not feasible for marketing teams to manage independently. It requires a dedicated IT team to build and maintain the system, and depending on the organization’s resources, it may not be a practical trade-off.

While manual implementation of Schema Markup on AEM is possible, it demands skilled execution and significant development time and resources to ensure the solution is effective and sustainable.

2. Leverage a Schema Markup Solution for AEM

If you want to implement Schema Markup on AEM at scale without dealing with the complexity, the best alternative would be to partner with a full-service Schema Markup solution like Schema App.

Schema App offers an end-to-end Schema Markup solution specifically designed for enterprise teams, covering everything from strategy and authoring to achieving measurable results.

When you work with Schema App, you will get an assigned Customer Success Manager who will create your Schema Markup strategy and author your Schema Markup using our authoring tools. This includes our Schema App Highlighter, which generates dynamic Schema Markup for your page categories and deploys the markup to your AEM site (headless or not) at scale without requiring manual coding.

Our solution offers flexibility to ensure your site benefits from improved search engine understanding and visibility, regardless of its architecture.

How does Schema App deploy Schema Markup to AEM?

Deploying Schema Markup to Adobe Experience Manager (AEM) can be complex due to its high customizability. At Schema App, we offer two methods to simplify this process:

1. Using the Schema App Connector for AEM (Server-Side Deployment)

The Schema App Connector for AEM is a plugin that integrates the Schema App platform with your AEM system.

The Connector receives your Schema Markup from Schema App and stores it server-side, ensuring that the markup is readily available for deployment. Through a cloud services configuration, the Connector inserts the markup into the page in real-time during page load, making it easily accessible to search engines.

This method increases the reliability of Schema Markup delivery and reduces page rendering time.

Your development team will only be required to set up the integration. Once the Schema App Connector is installed as a dependency in your AEM setup, any Schema Markup you create with Schema App will be automatically deployed.

2. Using a Tag Manager (Most Popular for its Dynamic Capabilities and Ease of Use)

Schema App can also deploy Schema Markup to AEM using a Tag Manager like Adobe Launch, Google Tag Manager, or similar tools.

This approach is popular among Schema App customers because it is:

• easy to use,
• quick to install and
• doesn’t require input or resources from your development team.

How does it work?

The Tag Manager method adds a JavaScript element to your AEM installation. This script dynamically generates Schema Markup by interacting with the final rendered page, regardless of where the content originates.

When a user visits your page, the script is loaded from a Content Delivery Network (CDN) and generates the markup on the fly. Even if components load outside of AEM, the script can still capture and mark up this information.

This approach reflects changes instantly without caching, making it a highly dynamic solution.

Choosing the Best Method

You can choose the method that best suits your web environment and preferences. During the sales process, our team will assist you in determining the most suitable integration method for your AEM system.

Beyond the dynamic deployment capabilities, partnering with Schema App also offers additional benefits:

• Schema Markup Strategy Guidance: You’ll be assigned a Customer Success Manager (CSM) to help you identify the properties to target for achieving rich results or enhancing your knowledge graph.
• Ongoing Support and Content Recommendations: After the initial implementation, you’ll receive ongoing content recommendations to optimize your website for Schema Markup, and measurable insights through Schema Performance Analytics (SPA) and timely business reviews.

Read this article to learn how our Customer Success Team will manage your Schema Markup for long-term success.

Implement Schema Markup on Your AEM Website With Schema App

Implementing Schema Markup on your AEM site can enhance your website’s search visibility and user engagement. By offering search engines clear and structured information about your content, you can achieve rich results, increase click-through rates, and drive more conversions to your website.

Whether you choose the Schema App Connector for AEM or the dynamic and easy-to-use Tag Manager method, Schema App’s end-to-end Schema Markup solution will empower your organization to generate robust Schema Markup at scale with speed, agility, and accuracy.

Contact us today to see how we can help you implement Schema Markup on AEM and drive better results.

The post How to Implement Schema Markup on Your AEM Site appeared first on Schema App Solutions.

By leveraging Sitecore’s capabilities, businesses can create, manage, and optimize customer experiences effectively.

Importance of Implementing Schema Markup on Sitecore

Implementing Schema Markup when using a Content Management System (CMS) like Sitecore is critical to your website’s success.

When you implement Schema Markup on your website, you translate your content into a machine-readable format. This can help search engines understand and contextualize the content on your website, leading to improved search performance, increased click-through rates (CTR), and higher conversions from search.

Apart from supporting your SEO efforts, implementing Schema Markup can also:

• Enhance your website’s visibility in search engine results pages (SERPs) through rich results and other enhanced search features
• Result in higher click-through rates and increases in non-branded queries, which showcase measurable results and ROI
• Build your organization’s content knowledge graph, supporting AI initiatives and deep machine understanding of your content and brand.

Within Sitecore’s Content Hub, users have access to a configurable data model, which is a structured representation of the underlying Content Hub database. This includes definitions of entities like assets, products, or projects. However, this can still be ambiguous to search engines and machines.

Therefore, by implementing Schema Markup to describe these entities in your data model, you can ensure that search engines and machines can understand the data in detail and with proper context.

How to Implement Schema Markup on Sitecore

Although the benefits of Schema Markup for your website are clear, challenges can arise when implementing it within a complex CMS like Sitecore. Before jumping into implementation, it’s important to first know your options and what best suits your team’s capabilities and business goals.

1. Implementing Schema Markup Manually

One of the ways you can implement Schema Markup within Sitecore is to manually author your markup in JSON-LD and manually add it to the HTML of the page. You can review Perficient’s “How to Implement Schema.org in Sitecore” article on the exact steps.

While it is possible to implement Schema Markup manually within Sitecore, the process is technical and labor-intensive. If you choose to go this route, potential challenges include:

• Lack of Scalability: Manually implementing Schema Markup becomes impractical when dealing with thousands of pages or multiple domains. The process is not only time-consuming but also costly.
• Maintenance Difficulties: If your organization frequently updates your site’s content, you’ll need to maintain your Schema Markup constantly to ensure it aligns with the content on your page.

IT teams and digital marketers often struggle to find the time to update structured data across large, complex websites. With enterprises that have extensive content spread across multiple domains, manual upkeep can become increasingly difficult and inefficient in time.

An alternative would be to use a plugin to implement your Schema Markup. Most organizations seek a solution that is easy to maintain and can scale dynamically with their content, something that an internal manual approach often cannot provide. However, there are currently no Schema Markup plugins that can automate Schema Markup deployment in Sitecore.

2. Leverage a Schema Markup Solution

The most optimal way to implement Schema Markup on Sitecore would be to utilize an end-to-end Schema Markup Solution like Schema App.

Partnering with Schema App can simplify the process of implementing and managing Structured Data on your Sitecore website. By using Schema App, you can achieve scalability, easy maintenance, comprehensive reporting, and access to strategic content recommendations and ongoing support.

How does Schema App Implement Schema Markup on your Sitecore Website?

1. Create Your Schema Markup Strategy

When you first partner with Schema App, you’ll be assigned a Customer Success Manager (CSM) to oversee your Schema Markup strategy throughout the engagement.

Your Customer Success Manager will work with you to develop a Schema Markup Strategy for your website. This includes aligning your goals for implementing Schema Markup and scoping your website for appropriate Schema.org types and properties

2. Author Your Schema Markup using the Schema App Highlighter

Once your team has defined and approved the strategy, your Customer Success Manager will start authoring your Schema Markup using the Schema App Editor and Highlighter.

One of the key features that sets Schema App apart from other Schema Markup solutions is the Schema App Highlighter. The Highlighter allows users to create Schema Markup templates by highlighting specific elements on a page and mapping them to the relevant Schema.org property. This template can then be applied to other similarly templated pages (i.e. blogs, recipes, location pages, product detail pages, etc.), ensuring the Schema Markup aligns with the content on the page at scale.

Furthermore, the Highlighter will dynamically update your Schema Markup whenever content changes are made. as your content changes. This means that your Schema Markup evolves in real time and always reflects the most current version of your content.

Within the Highlighter, you’ll also find our Omni Linked Entity Recognition (Omni LER) feature. If you want to build a knowledge graph and disambiguate entities on your site, Omni LER will automatically link your entities to external identifiers from authoritative knowledge bases. This adds clarity and context, making your content more precise and authoritative in search.

3. Deploy Your Markup on Sitecore

Once your Schema Markup has been authored using Schema App’s authoring tools, we will work with you to set up the integration between the Schema App platform and Sitecore.

At Schema App, we typically use JavaScript to deploy Schema Markup to Sitecore. This method is both efficient and scalable, requiring the implementation of a JavaScript tag in the HTML head or the setup of a tag manager. You can learn more about our JavaScript implementation here.

Once the initial integration is set up, any Schema Markup authored by your Customer Success Manager for your website will be deployed seamlessly to Sitecore.

4. Perform Ongoing Maintenance and Monitoring of Your Schema Markup

Schema Markup is not a one-and-done process. Similarly to how your content will change and be updated over time, factors outside of your control may also change, demanding shifts in your Schema Markup strategy. These changes could include:

• Changes to Google’s structured data documentation
• Required properties for rich result eligibility may change
• Updates to the Schema.org vocabulary
• Shifts in your organization’s goals

Whatever it may be, staying current with these changes is essential. To ensure the long-term success of your Schema Markup strategy, your Customer Success Manager will work with you to manage and optimize your Schema Markup deployment. You can read this article to learn about the ongoing services offered by our Customer Success team after the initial implementation process.

In addition to implementation and management, your Customer Success Manager will also provide strategic content recommendations that are invaluable for both existing and new pages within your Sitecore CMS. These recommendations will help you:

• Tailor your content to a specific Schema.org Type or topic
• Identify opportunities to enhance your Schema Markup for better search features and rich result eligibility
• Create a more robust content knowledge graph

5. Measure the Performance of your Schema Markup to inform Future Planning

Performance measurement is crucial to the long-term success of your Schema Markup strategy. When you work with Schema App, you’ll get access to our Schema Performance Analytics (SPA) platform where you can track the performance of your Schema Markup.

In addition to having access to SPA, your Customer Success Manager will also perform Business Reviews to help you understand the impact of your Schema Markup strategy and areas for improvement. This ensures ongoing improvement in your Schema Markup processes and outcomes.

As SEO trends and best practices evolve, your schema strategy must adapt to keep pace with these changes.

Implement Schema Markup on Your Sitecore Website With Schema App

Implementing Schema Markup on Sitecore can enhance your website’s search visibility and user engagement. On top of providing search engines with greater clarity about the content on your site, implementing Schema Markup can help you achieve rich results, higher click-through rates, and ultimately, drive more conversions on your site.

While Sitecore’s powerful customization capabilities make it an ideal platform for large enterprises with dynamic content, this complexity can pose challenges when implementing Schema Markup at scale. That’s where partnering with an external solution like Schema App comes in.

Schema App enables you to implement and manage your Schema Markup with agility, ease, and minimal time investment. Our combination of semantic technology and customer success simplifies the Schema Markup process, allowing you to concentrate on creating great content while enjoying the benefits of improved search performance.

Contact us today to see how we can help you implement Schema Markup on Sitecore.

The post How to Implement Schema Markup on Sitecore appeared first on Schema App Solutions.

Before diving into implementation, ask yourself: what am I aiming to achieve through Schema Markup? Which key content or business entities do I want to highlight in search results? How can Schema Markup support our overall SEO and content strategy?

A thoughtful Schema Markup strategy can help you:

• Target the right rich results
• Develop your content knowledge graph
• Increase organic traffic and CTR in search
• Identify gaps in your content and inform your content strategy

In this article, we outline the steps you can take to create a Schema Markup strategy for your website.

Let’s get started!

Step 1: Identify Key Entities in Your Content for Structured Data Opportunities

The first step to implementing Schema Markup is identifying the key entities that represent your business and where they are located on your site. This process will help you recognize the structured data opportunities across your website.

1.1 List the Key Entities That are Relevant to Your Business

You can start by creating a list of key entities that make up your business, such as:

• Business name and contact information
• Products or services
• Key personnel (e.g., owner, management team)
• Locations (for businesses with multiple branches)
• Authoritative content about your industry or expertise

For example, Pizza Palace is a local pizza restaurant owned by Enrico Picolli with over 20 locations across Ontario, Canada. Pizza Palace sells different types of pizzas (i.e. pepperoni, Hawaiian, etc.) and appetizers through their online site. Pizza Palace, along with its products, locations, and owner are key entities related to the business. These entities are also described across their website content.

1.2 Locate Relevant Web Pages

Once you’ve identified your key entities, you can identify which page on your website best describes each entity. This will help you determine which top-level Schema.org type you should use to mark up each page.

As per our previous example, the Pizza Palace home page has detailed information (i.e. address, logo, telephone number, etc.) about the organization. Therefore, it should be the entity home for the organization Pizza Palace.

Similarly, Pizza Palace has product detail pages for each of its pizzas. Therefore, these product detail pages should be the entity home for each product.

Pro Tip: If you don’t have a page about any of your key entities, this is an opportunity for you to create new content to describe the entity.

1.3 Map Content to Schema.org Types

Once you have your list of entities and where they live on your site, you can identify the corresponding Schema.org type for each entity.

Back to our example— “Pizza Palace,” being the organization’s name, would best correspond with the Organization type. Therefore, you would mark up the homepage with Organization markup to help search engines clearly understand the key information about the Organization.

Pro Tip: If you’re new to the Schema.org vocabulary and need more clarity on identifying types and properties within your content, we recommend reading our guide to the Schema.org vocabulary.

1.4 Create an Entity Mapping Table

Next up, it’s time to organize your findings in a table format for clarity. Here’s an example continuing with our hypothetical local pizza business:

Step 2: Review Eligible Rich Results for Your Pages

Once you’ve identified your key entities, the next step is determining which rich results are available and relevant to your content. This will help you prioritize your Schema Markup efforts for maximum visibility in the search results.

2.1 Understand Available Rich Results

Before you dive into rich results, we recommend familiarizing yourself with the types of rich results offered by Google. Google has over 30 rich results, some more applicable than others. The most common types of rich results include:

• Review Snippet
• Local Business
• Product
• Job Posting

Within Google’s structured data guidelines, you can see which Schema.org properties are required and recommended to achieve your target rich results. If your page does not have the content for the required properties, you must add the content to your site before you markup the required property.

2.2 Match Your Content to Eligible Rich Results

You can review your key content identified in Step 1 and determine which rich results each page might be eligible for.

For example, Pizza Palace has 25 product detail pages (PDPs), each with reviews and ratings related to the relevant product. Since the PDPs have the right content, they should be eligible for a review snippet-rich result when we add AggregateRating and Review markup.

When you’ve identified the rich results each page could be eligible for, you can add it to the previous table you’ve created. Here’s an example continuing with the table we created for the pizza business in Step 1:

2.3 Ensure Your Content Aligns With the Structured Data Requirements for Each Rich Result

Before implementing Schema Markup, it’s crucial to verify that your content meets the requirements for each desired rich result if that is your goal. This step helps ensure your markup efforts are effective and compliant with search engine guidelines.

Other actions to consider in this step include:

Review Google’s guidelines: Check the requirements for each rich result type you’re targeting. These requirements may be content-related (e.g. Aggregate Ratings require the reviewCount), but they also may be more general guidelines (e.g. There should only be one Product or ProductGroup per page). Google provides detailed documentation for each rich result in their structured data documentation.

Audit your content: Compare your existing content against the requirements. Look for any gaps or missing elements.

Update content if necessary: If your content doesn’t fully meet the requirements, now is the time to update it. This might involve adding more detailed information, reorganizing content, or creating new page sections.

Step 3: Assess Implementation Methods for Ease and Coverage

After identifying your key entities and desired rich results, it’s time to consider how to implement your Schema Markup strategy effectively. This step focuses on balancing high-value opportunities with practical and manageable implementation methods.

3.1 Analyze Pages for Individual or Repeating Content

The implementation strategy for one-off or individual pages will likely be different than highly templated or repeating page types. For this reason, we recommend determining whether your content follows single or recurring patterns:

• Individual Page: Unique content, generally dissimilar to other pages on the website (e.g. About Us or Contact Information pages)
• Recurring Pages: Pages with a similar content structure repeated across multiple URLs (e.g. product detail or location pages)

3.2 Assess Existing Capabilities

From here, evaluate your current technical setup:

• Check if your Content Management System (CMS) has built-in Schema Markup functionality
• If it does, determine whether it meets your requirements or needs enhancement from other methods or sources

3.3 Consider Implementation Methods

There are many ways to implement Schema Markup. We recommend exploring the different available approaches to implementing Schema Markup to decide what best suits your organization’s needs and capabilities:

• Manual Implementation: You can author your markup for each page manually and add it directly into the HTML of the page
• Plugin or SEO Tool Implementation: You can use Schema Markup plugins designed to generate Schema Markup (these can be limited in their capabilities)
• Full-Service Schema Markup Solution Providers: You can also hire an end-to-end Schema Markup solution Schema App to help you author, implement and manage your Schema Markup on an ongoing basis

3.4 Assess Automation Possibilities

Implementing Schema Markup manually can be tedious, complex, and time-consuming. This is especially true for large organizations managing thousands of content pages or even multiple domains.

This is when it becomes crucial to identify and leverage opportunities to automate your Schema Markup implementation:

• For recurring content patterns, consider templated solutions like the Schema App Highlighter
• Explore API integrations for dynamic content
• Investigate tools and plugins that can generate and update markup automatically and dynamically

Schema App automatically deploys Schema Markup to your website at scale, so you can save time, make updates faster, and reduce delays caused by waiting for IT/developers. It works with all website platforms because of our integrations with Tag Manager, JavaScript, or our custom add-ons for WordPress, Shopify, BigCommerce, Drupal, etc. Explore our integration options.

3.5 Plan for Scalability

A common goal for most organizations is to grow. Therefore, planning for scalability is a must!

Ensure your implementation strategy can grow with your business:

• Choose methods that can easily accommodate new content or site sections
• Consider future rich result types you may wish to target

By completing this step, you’ll have a clear understanding of how to implement your Schema Markup strategy efficiently and at scale, taking into account your current capabilities and future business needs.

Best Practices for Schema Markup

Here are some things to keep in mind as you develop your Schema Markup strategy and evaluate your site content.

1. Use JSON-LD (rather than microdata or RDFa), as recommended by Google
2. Use the most specific Type possible
3. Only markup content that is visible on the page
4. Identify one key page for each business concept
5. Include an @id attribute to the entities in your Schema Markup
6. Nest the entities in your Schema Markup to accurately showcase their relationships on a page

So now you know how to identify which pages you should optimize and how to determine the best approach depending on the page type.

At Schema App, we help you go beyond the fundamentals of SEO, leveraging structured data to showcase your unique value in search. In a rapidly changing SEO landscape, we introduce agility to your digital team, saving you time and resources for managing other aspects of your business portfolio.

See how our end-to-end Schema Markup and knowledge graph solution can help your website stand out in search.

The post How to Develop a Schema Markup Strategy for a Website appeared first on Schema App Solutions.

With user behaviors and search engine algorithms constantly changing, it is crucial to ensure that your new and old content remains comprehensive, relevant, and helpful to humans and machines.

Enter Schema.org, a collaborative, community-driven initiative launched in 2011 by tech giants Google, Bing, Yahoo, and Yandex. The Schema.org vocabulary provides a standardized framework for structuring and organizing data on the web. It offers a comprehensive set of Types and properties that website owners can use to describe the entities and content on their site.

While Schema.org is widely known for helping search engines and machines understand the content on your site, its potential extends far beyond that. This vocabulary can be a game-changing checklist for improving your website’s content and formatting and identifying information gaps on your pages. By aligning your content with relevant Schema.org Types and properties, you can identify opportunities you may have overlooked, enhancing your overall content strategy.

In this article, we’ll explore how you can leverage the Schema.org vocabulary to develop a thorough and robust content strategy for your website.

Identifying Content Gaps on Your Website

Your primary focus should always be creating high-value content that serves your users’ needs. That said, the Schema.org vocabulary can serve as a roadmap during the content creation process, outlining information commonly found on certain types of web pages.

The Schema.org vocabulary provides a detailed framework for describing the entities on your website and their relationships. By examining the properties associated with relevant Schema Types, you can:

• Identify potential gaps in your existing content
• Fill those information gaps for your audience
• Add depth to existing page content
• Create new, supplementary content

Whether you’re creating new content or revamping existing pages, Schema.org can provide valuable guidance. Let’s explore a few examples.

For a healthcare organization creating a new page about a medical condition, you’ll need to decide what information you should include. The MedicalCondition Type in Schema.org has a list of properties such as signOrSymptom, possibleTreatment, and more that capture information that is commonly found on these types of pages. Reviewing the full list of properties associated with a Type can spark ideas about what entities are well-suited for supplementing your content.

Recall that you can only mark up content that exists on your page. Therefore, if you want to incorporate content for these properties to give readers more comprehensive information about the subject, you’ll want to identify those opportunities early in the content creation process.

Our customer, Sharp Healthcare, successfully applied the Schema.org vocabulary to form a long-term content strategy. During their website migration process, the Sharp team ensured that each page focused clearly on a specific Schema.org Type when establishing their content structure. They also incorporated content for the properties suggested by Schema.org for each chosen Type.

Enhancing Rich Results Potential

Aligning your content with Schema.org properties not only helps fill content gaps but also improves your rich result eligibility on Google’s search engine results pages (SERPs). Rich results can lead to enhanced visibility on the SERP and increased click-through rates for your website.

To be eligible for rich results, specific content elements must often be present on your pages. Each rich result type typically has both required and recommended properties:

1. Required properties: These are essential for eligibility and must be on your page.
2. Recommended properties: While not mandatory, Google has stated that including more recommended properties can improve the quality of rich results for users and that rich result ranking takes extra information into consideration.

By incorporating both required and recommended properties into your content strategy, you can simultaneously improve your content quality and rich result eligibility.

Let’s look at product snippet requirements and recommendations as an example:

Product Snippet
To be eligible for product snippets on the SERP, it is required that you include the following:

• name (of the product)
• At least one of the following is required, but all are recommended:
  • review
  • aggregateRating
  • offers

You can further enrich your product rich result by adding content around the pros and cons of your product. That way, you can markup the content using the positiveNotes and/or negativeNotes properties and potentially have these pros and cons show up on your product rich results.

CAPREIT successfully leveraged Schema.org to enhance their rich result potential. By structuring their content according to Schema.org guidelines, they were able to improve their visibility in search results for their property listings and job postings.

Continuous Content Optimization

While Schema.org is an excellent tool for identifying content gaps and structuring information, it’s crucial to remember that creating helpful, high-quality content should always be your primary goal.

You must have substantive, relevant content in place before implementing Schema Markup. Without this foundation, you won’t be eligible for rich results. Moreover, attempting to markup non-existent or irrelevant content could be seen as spammy, potentially leading to penalties from Google.

Use Schema.org as a starting point to spark ideas and ensure your content is comprehensive, but don’t let it constrain your creativity or limit the value you provide to your audience.

By balancing user-focused content creation with Schema.org’s structured guidance, you can develop a content strategy that provides genuine value to your users and enriches the Schema Markup on your site.

Schema App Provides Content Recommendations Using the Schema.org Vocabulary

The digital landscape is constantly changing, and with it, Google’s structured data documentation and the Schema.org vocabulary continue to evolve. By keeping up with the latest updates, you can continually refine your content strategy and ensure your website content remains aligned with best practices.

At Schema App, we help our customers stay current with the latest changes in Schema.org and Google’s documentation. We also provide content recommendations to help our customers improve their rich result eligibility and enhance the richness of their content.

The post How to Improve Website Content Using the Schema.org Vocabulary appeared first on Schema App Solutions.

During the webinar, we discussed topics such as:

• The shifts in user experience and behavior after the introduction of AI search
• Strategies to enhance SEO and maintain relevance in the evolving search landscape
• How the measure of success in search is changing

If you didn’t get a chance to attend the live session, here are the essential insights from our webinar to help you navigate AI search effectively.

How is the User Experience Changing with AI Search?

As search engines have evolved, so too has the way users search.

Today, search queries have become longer and more nuanced. Users no longer search with short and simple keywords; they ask long-tailed detailed queries. For example, instead of searching “best hospital in NY,” users might now search for “best female physician that can see me for X problem within 5 miles in the next 3 weeks.”

These detailed queries require AI search engines to infer knowledge, such as finding local specialists for a specified problem available within specific time frames. Modern search experiences involve advanced machines that can understand context and relationships within queries and present relevant answers more accurately.

Changing Platforms and Search Methods

Not only are users changing how they search, but they are also changing where they search.

Generative AI engines like Perplexity, ChatGPT, and Google’s AI Overviews are gaining popularity. Therefore, it is crucial for websites to ensure their content can be read and accessed by these alternative search engines.

Nowadays, people are looking for direct answers to their queries. The traditional search experience of receiving ten blue links to sift through has evolved. Instead of a list, users now receive a single, comprehensively aggregated answer deemed most relevant by AI search engines.

This shift makes it challenging for site owners to secure the top spot in search results. Previously, being in the top three positions was sufficient, but now, the goal is to be a part of the one precise answer. We say “a part” of the top answer because AI search engines now create an aggregated experience, summarizing the best answer to a query, sometimes using a number of different sources.

This evolution parallels the online travel experience users are already used to, as seen with aggregators like Expedia, which simplify the search process by presenting the best options across the web based on user criteria. If you’re booking a hotel, these sites have their aggregated options compared directly in search.

The Shift to Aggregated Search Experiences

Now, this aggregated approach has moved into the search experience, where AI search engines have begun to “aggregate the aggregator” with verticals that extend beyond travel.

Now that AI search engines can provide users with all the relevant information, this will impact the typical buyer’s journey. Users will no longer need to go to your website and click through all the pages when they can get summaries and make a quick decision directly in search. Website owners must accept the reduced visibility of the user journey in this new search experience.

What Can Digital Marketers Do To Stay Relevant And Perform in This New Search Landscape?

Paid search is currently not an option for most AI search engines. Therefore, your content and the context you build around it for search engines to consume is the key to maintaining visibility.

Manage the content off your website

It’s important to remember that AI search engines are not just feeding off the content on your website. They’re also feeding off content on user-generated platforms like Reddit and LinkedIn. In fact, we’ve seen Google over-indexing and prioritizing this user-generated content on the SERP, making it even harder for brands to ensure users get the right information in their search results and maintain their online reputation.

Therefore, it is crucial for brands to do social listening and manage their reputation on these platforms.

Manage the content on your website

Having trustworthy and authoritative content on your website is also critical. While user-generated platforms provide fresh content with a wide range of perspectives, they have a tendency to provide misinformation.

As such, having trusted, accurate content that exhibits E-E-A-T on your website can help AI search engines improve their accuracy.

I do believe that over time, we’ll see Google come to a more normal level of which they’re indexing and prioritizing this user-generated content like Reddit, primarily because the answers are likely to be wrong. Especially in the healthcare space, the fact that they’re giving wrong answers is a very high risk. Historically, we did see Google state that they would move slowly into healthcare and finance, however, the data has shown that that is not the case. They’ve accelerated the introduction of SGE and AI Overviews in healthcare. I’m unsure what’s motivating them there, but we need to understand that that is something they’re leaning into.”

– Martha van Berkel

Beyond that, you must also ensure your brand and content is clearly understood by both users and machines. While Google has emphasized creating helpful content for users, it’s equally important for this content to be machine-readable to ensure it reaches the right audience.

So how can you help AI search engines understand the content on your website? The answer is Schema Markup.

Created by Google, Yahoo, and Bing in 2011, Schema Markup acts as a “data translation layer”, helping search engines understand your content and its relationships. This enhances visibility and reduces the risk of misinterpretation.

Historically, Schema Markup was used for rich results like star ratings and reviews to improve click-through rates. Today, it is a vital strategy for brands to thrive in AI search experiences.

By implementing robust, connected Schema Markup, you can control how machines interpret your content, adding context and structuring your information to reveal richer details about your brand. This allows search engines to infer additional connections between your content and user queries.

Aside from its SEO benefits, implementing Schema Markup can also help you develop a content knowledge graph that can support internal AI initiatives beyond search.

How is the Measure of Success Going to Change?

With the advent of AI search, we’re likely to see an increase in zero-click searches. Traditional metrics like clicks, impressions and click-through rates will probably be impacted. Therefore, organizations should look at conversions and downstream actions to understand success.

Redefining the Quality of Website Traffic

As search becomes more contextual, users who click through are likely more qualified because they’ve asked deeper and more comparative questions before deciding to click.

For organizations that are regional or location-based, when you add further context and truly define the region or location of your facilities, clinics, stores, etc., we’re seeing queries related to local “near me” increase significantly after adding more robust disambiguating Schema Markup and entity linking.

Additional Business Measures

Business measures around cost efficiency and agility will continue to gain importance. They can help teams get buy-in from the CEO level for more innovative SEO tactics and will be a metric many organizations will want to monitor.

Having a data layer that you can control and build upon allows you to be agile, especially for larger organizations. Partnering with Schema App gives you cost efficiency, return on investment, agility, and an innovative partner.

Preparing Your Strategy for AI Search

Digital marketers must adopt a comprehensive measurement strategy beyond single-channel metrics. They should focus on driving conversions, connecting with different audiences, and sharing varied and personalized experiences in search.

To even get a chance to play in this new AI search landscape, you must implement robust Schema Markup to help search engines understand and contextualize the content on your site.

At Schema App, we provide enterprise SEO teams with an end-to-end Schema Markup solution using our semantic technologies and high-touch support services.

If you need help implementing a robust Schema Markup strategy for your site, get in touch with us today.

The post How to Navigate AI Search as a Digital Marketer appeared first on Schema App Solutions.

Multilingual websites offer content in multiple languages—for example, a U.S. healthcare organization can provide users with both English and Spanish versions of its site. On the other hand, multi-regional websites target users in different countries or regions, often adapting content to local preferences and regulations.

Some websites combine both approaches, serving as multilingual and multi-regional platforms. For instance, an eCommerce site operating in the USA and Canada might offer content in English, French, and Mandarin, tailoring the language to each region’s demographics.

While implementing Schema Markup on monolingual single-domain sites is relatively straightforward, managing Schema Markup for multilingual and multi-regional domains presents unique challenges.

This article will explore the challenges of implementing Schema Markup across diverse multilingual and multi-regional sites and the solutions to these challenges.

Common Issues When Marking up Multilingual Sites

1. Schema.org documentation is currently only available in English

One of the most frequent questions we encounter is, “Does Schema Markup support languages other than English?” The answer is a resounding yes. While Schema.org Types and properties are represented by English words and the Schema.org documentation is written in English, the content you map to those types and properties can be written in any desired language.

This means you can still mark up your pages if you have a site in a different language from English. For example:

{
   "@context": "https://schema.org",
   "@type": "Article",
   "headline": "Comment économiser de l'énergie à la maison",
   "author": {
      "@type": "Person",
      "name": "Marie Dupont"
      },
   "datePublished": "2024-06-14T17:50:16+00:00"
}

This example shows French content mapped to the property represented by the English word “headline”.

The real complexity arises when you must accommodate different formatting conventions across languages and regions manually or even using a plugin.

Why is it difficult for website owners to implement Schema Markup on their own?

Many site owners are unaware that you can still apply the Schema.org vocabulary to non-English pages and often neglect to add Schema Markup to their multilingual sites. This oversight can lead to missed opportunities for enhanced search engine understanding and visibility in the SERP.

Even when site owners apply Schema Markup to non-English pages, they may still face limitations if they’re using a plugin. Most Schema Markup plugins are black boxes and do not give site owners the flexibility to adjust the markup. If your website has additional complexities, plugins might not be able to mark up your site accurately.

Some plugins may also not recognize the language on your site, so you might be required to author your markup manually. Implementing and managing this across thousands of pages can be tedious and requires Schema Markup expertise to execute.

Schema App offers an automated and dynamic solution

Unlike typical plugins that struggle with scale, formatting, and language variations, Schema App’s dynamic markup deployment capabilities can help you easily manage complex, multi-domain, and multilingual sites.

The Schema App Highlighter is a Schema Markup generator that deploys dynamic Schema Markup to thousands of similarly templated pages. If you have a product detail page in seven different languages, the Schema App Highlighter can deploy accurate markup to all those pages regardless of which language the page content is written in. It can also recognize special characters and include them in the markup on your site.

With our solution, you also get a dedicated Customer Success Manager who can provide content and formatting recommendations to ensure your content is optimized for Schema Markup implementation.

Ensuring Schema Markup is properly implemented and formatted for each language and region is crucial for presenting your content to the right audiences, maintaining rich result eligibility, and providing consistent user experiences across your websites.

2. Handling Currency Formatting for Different Regions

Another issue many site owners face with marking up multilingual and multi-regional domains is currency formatting.

Schema.org can accommodate any currency format and gives users the ability to specify a “price” and a “priceCurrency” separately. However, if you are looking to target a Product rich result, you will want to follow Google’s more specific formatting requirements.

Using a comma (,) instead of a period (.) as a decimal separator will result in errors in the Rich Results Test (e.g. €100,50 should be written as €100.50). This may go against grammar rules but is critical for being Rich Result eligible.

Furthermore, websites may use periods or commas as digit group separators to support readability. We recommend omitting all digit group separators, but more importantly, avoid using periods as digit group separators. For example, the number one thousand should never be represented as 1.000, as Google will parse the period as a decimal separator and interpret the value as one (1).

Many European countries use a comma (,) as a decimal separator and a period as a digit group separator in their prices. Using this formatting in your markup can lead to several issues, including:

• Ineligibility for rich results like Product Listings
• Misinterpretation of price data by search engines

Challenges Scaling Different Currency Formatting

These nuances to differing currency formats are challenging at scale because you must manually update your Schema Markup on each page to accommodate price formatting and ensure machines understand that your price-based content is a price value.

Converting it to the format Schema.org accepts is necessary for machines to read it and incredibly tedious for anyone doing it manually across thousands of pages.

Most Schema Markup plugins cannot automatically reformat pricing into the Schema.org accepted format, making this a challenge for site managers who rely on plugins to implement their Schema Markup.

Common Formatting Issues

Decimal placements in your currency formatting aren’t the only issues that could arise with multilingual and multi-regional content. Other elements that may require attention include:

• Currency symbol placement (e.g., “500$” instead of “$500”)
• Date/time formats (e.g. “2024-07-03T12:50:15+4:00” instead of July 3, 2024 at 12:50pm)

All these elements must adhere to the conventions defined by the Schema.org vocabulary (e.g. following ISO-8601 time formatting).

A Scalable Solution

The Schema App Highlighter can omit or remove commas used as digit group separators to improve Rich Result eligibility. Additionally, you can also set conditional rules in the Schema App Highlighter to account for different currency formats and ensure that your prices are correctly marked up, regardless of the currency denomination.

Check out how we helped CAPREIT overcome their currency denomination challenges.

Schema App Simplifies Schema Markup for Multilingual Sites

Manual implementation of Schema Markup on a multilingual site becomes tedious and error-prone when dealing with thousands of pages across various languages and regions.

While plugins may seem like a solution, many do not allow website owners to customize their markup or do conditional formatting for their multi-lingual sites. This can hinder your ability to achieve rich results and ensure search engines understand your content.

This is why global enterprises with complex multilingual, multi-regional sites choose to work with Schema App.

Schema App’s end-to-end Schema Markup solution gives users access to tools like the Schema App Highlighter to manage currency formatting and ensure compliance with Google’s structured data requirements. You’ll also get an assigned Customer Success Manager to manage your markup, ensure your content is optimally formatted, and offer recommendations to further optimize your pages for Schema Markup implementation.

If you’re struggling to implement Schema Markup for your multilingual or multi-regional website, we’re here to help. Contact us today to learn how Schema App can streamline your Schema Markup process and boost your global online presence.

The post How to Implement Schema Markup for Multilingual or Multi-Regional Sites appeared first on Schema App Solutions.

It’s crucial to express Schema Markup in a format accepted by major search engines to take advantage of the Schema.org vocabulary, become eligible for rich results, and accurately describe your website content.

Popular search platforms like Google and Bing recognize three primary formats for Schema Markup:

1. Microdata
2. RDFa
3. JSON-LD

Implementing the appropriate format ensures that your structured data is accurately understood, enhancing your site’s visibility, aligning your content with more relevant search queries, and supporting rich result eligibility.

Understanding the Different Schema Markup Formats

Microdata, RDFa, and JSON-LD have unique features and implementation methods. Each of the three available formats has unique features and implementation methods. Let’s examine the pros and cons of each format to help you understand which format you should utilize for your website.

What is Microdata?

Microdata is an open-community HTML specification used to nest structured data within HTML content. Similar to RDFa, it utilizes HTML tag attributes to name the properties we want to present as structured data.

Microdata is typically implemented within the <body> element but can also be used in the <head> element.

<div itemscope itemtype="https://schema.org/Organization">
 <span itemprop="name">Schema App</span>
Contact Details:
 <div itemprop="address" itemscope itemtype="https://schema.org/PostalAddress">
  Address:
   <span itemprop="streetAddress">412 Laird Road</span>
   <span itemprop="postalCode">N1G 3X7</span>
   <span itemprop="addressLocality">Guelph</span>
   <span itemprop="addressRegion">Ontario</span>
   <span itemprop="addressCountry">Canada</span>
 </div>
  Tel:<span itemprop="telephone">+1 855-444-8624</span>,
  E-mail: <span itemprop="email">support@schemaapp.com</span>

Pros of Using Microdata Format for Schema Markup

1. Markup is Dynamic

The microdata is added as an attribute for individual HTML elements, so your markup will be updated dynamically if any content changes are made.

For example, consider a <div> element attributed to the “Organization” type. This <div> can contain properties like “name” and “address.” If you change the content within any of these elements, the markup will automatically update to reflect the latest content.

2. Easy to Implement

Microdata can be easily inserted into HTML, making it more straightforward for those without coding skills to implement the Schema Markup. Microdata is generally easier to understand and maintain than other formats like RDFa.

Cons of Using Microdata Format for Schema Markup

1. Less Suitable for Advanced Schema Markup

While microdata works well for basic Schema Markup, it can become more complicated when dealing with advanced Schema Markup involving many nested entities.

Consider the Product schema type, which requires HTML elements for various attributes like price, ratings, reviews, and return policies to be nested. If your product page only had an image and a price, you can easily use microdata to markup your page.

However, the complexity increases with additional elements such as FAQs located lower on the page, branding information in a separate section, and ratings and reviews in a separate tab. These extra layers make the implementation messy and difficult to manage.

2. Messy Implementation

Since microdata has to be applied to each individual element on the webpage, the markup can become cluttered and messy, especially for larger websites, where your code can become “bloated” very quickly.

3. Unsuitable for Larger Websites

Due to the potential for clutter and the limitations of complex schemas, microdata is generally better suited for smaller websites with simpler structured data requirements.

What is RDFa?

RDFa (Resource Description Framework in Attributes) is an HTML5 extension that supports linked data. It does this by introducing HTML tag attributes that correspond to the user-visible content you want to describe for search engines.

RDFa is considered a W3C (World Wide Web Consortium) recommendation, meaning that it is a web standard. It can be used to chain structured data vocabularies together, which is especially useful if you want to add structured data that extends beyond the limits of Schema.org.

You can breathe a sigh of relief, however, as RDFa isn’t much different from Microdata. Similar to microdata, RDFa tags are incorporated with your webpage’s preexisting HTML code and are commonly used in both the <head> and <body> sections of an HTML page.

<div vocab="https://schema.org/" typeof="Organization">
  <span property="name">Schema App</span>
Contact Details:
  <div property="address" typeof="PostalAddress">
    Address:
     <span property="streetAddress">412 Laird Road</span>
     <span property="postalCode">N1G 3X7</span>
     <span property="addressLocality">Guelph</span>
     <span property="addressRegion">Ontario</span>
     <span property="addressCountry">Canada</span>
</div>
  Tel:<span property="telephone">+1 855-444-8624</span>,
  E-mail: <span property="email">support@schemaapp.com</span>

Pros of Using RDFa Format for Schema Markup

1. Flexibility

RDFa allows you to combine multiple vocabularies, making it more flexible than Microdata or JSON-LD for complex structured data requirements.

2. Widely Adopted Standard

Since RDFa is a standardized format recommended by the W3C, it ensures broad compatibility across various platforms, browsers, and search engines. This means that structured data marked up with RDFa will be more consistently interpreted and utilized by different web services.

3. Integrates with Existing HTML

Like Microdata, RDFa seamlessly integrates with your existing HTML code, making implementation easier.

Cons of Using RDFa Format for Schema Markup

1. Steep Learning Curve

RDFa has a steeper learning curve compared to Microdata or JSON-LD, as it requires a deeper understanding of linked data principles and vocabularies.

2. Messy implementation

Also similar to microdata, RDFa markup can become verbose and cluttered, especially for complex structured data implementations.

3. Limited Browser Support

While search engines support RDFa, some older browsers may have limited or no support for rendering RDFa markup.

Overall, RDFa offers a flexible and standards-compliant approach to structured data markup, but it may be more suitable for advanced use cases or when combining multiple vocabularies is necessary.

What is JSON-LD?

JSON-LD stands for JavaScript Object Notation for Linked Data. It is a method of encoding structured data using the JSON format, which is a lightweight data-interchange format that is easy for machines to parse and generate.

The key difference between RDFa, Microdata, and JSON-LD is their implementation method on a page. Both RDFa and Microdata are added as properties within the content itself. Conversely, JSON-LD is added independently, typically in the header or footer of the HTML.

This resolves the issue of messy and cluttered implementation associated with both RDFa and microdata.

<script type="application/ld+json">
{
   "@context": "https://schemaapp.com",
   "@type": "Organization",
   "name": "Schema App",
   "address": {
      "@type": "PostalAddress",
      "addressLocality": "Guelph",
      "addressRegion": "Ontario",
      "addressCountry": "Canada",
      "postalCode": "N1G 3X7",
      "streetAddress": "412 Laird Rd",
      },
   "email": "support@schemaapp.com",
   "telephone": "+1 855-444-8624",
}

JSON-LD is also a W3C recommendation and Google’s recommended format for structured data due to its simplicity and readability for both machines and humans. It offers several advantages.

Pros of Using JSON-LD Format for Schema Markup

1. Easiest Format for Machines to Interpret

JSON-LD is designed to be easily parsed and understood by machines, making it an efficient and accessible format for structured data.

2. Easy to Implement and Update

JSON-LD can be read even when dynamically injected into the page’s contents via JavaScript code or embedded widgets. It can be used to describe all types of media on a website—videos, audio, images, and interactive content—not just what exists in HTML documents.

JSON-LD also exists as a single block of code embedded within HTML, so you are not restricted by the structure of the content you are marking up.

3. Ability to Handle Complex Schema Markup

JSON-LD supports the management of complex, nested structured data, making it ideal for advanced use cases. Unlike Microdata, JSON-LD is not restricted by the content and structure of the HTML, offering greater flexibility. For instance, the ratings and reviews for a product can be positioned anywhere on the product page. With JSON-LD, you can easily nest the properties and values in the structured data regardless of where the content is placed in the HTML.

Cons of Using JSON-LD Format for Schema Markup

1. Learning Curve

JSON-LD can be difficult to learn and write manually, especially for those without prior experience with JSON or linked data concepts.

2. Technical Complexity

Implementing JSON-LD may require a higher level of technical expertise compared to Microdata or RDFa.

3. Update to Schema Markup Required If Done Manually

If you author the JSON-LD manually, you’ll need to update the JSON-LD code whenever you make content updates, as it’s separate from the main content.

This is why our customers love using the Schema App Highlighter, a scalable Schema Markup tool that generates and deploys JSON-LD Schema Markup to thousands of similarly templated pages on your site.

The Schema App Highlighter dynamically updates the Schema Markup on your page when content changes are made. This ensures that all content changes are automatically reflected in your JSON-LD markup in real time. This prevents Schema Drift and reduces the risk of manual coding errors.

What Format Should I Use for Schema Markup?

While Microdata, RDFa, and JSON-LD are all accepted formats for Schema Markup, JSON-LD emerges as our recommended choice. This is due to its flexibility and scalability for complex structured data implementations.

Despite its steeper learning curve and technical expertise requirements, JSON-LD is the format also endorsed by Google and other major search engines for its ease of readability for both machines and humans.

At Schema App, we understand the challenges of implementing JSON-LD at scale. This is why we created tools like the Schema App Highlighter to enable SEO teams to generate and deploy dynamic JSON-LD markup at scale.

With our end-to-end Schema Markup solution, we can help your team deploy robust Schema Markup to your site seamlessly, ensuring optimal search engine understanding and accurate representation of your brand in search results.

Get started with us today and unlock the full potential of JSON-LD Schema Markup for your organization.

The post What is the Recommended Format for Schema Markup? appeared first on Schema App Solutions.

This approach communicates clear relationships, giving machines context about the different entities described on your web pages. By improving search engine understanding of your content, it can lead to better visibility and more accurate presentation in search results.

Here’s a breakdown of nesting in Schema Markup:

Main Entity: This is typically the primary entity or item that your webpage is about. For example, if you’re describing a recipe page, the Recipe itself would be the main entity.

Nested Entities: These are secondary entities on the page that are closely related to the main entity. For instance, if your main entity is a Recipe, nested entities could include AggregateRating and VideoObject.

Image pulled from Google’s General Structured Data Guidelines.

Why is it Important to Nest your Schema Markup?

Nesting your Schema Markup serves several purposes:

1. It clarifies the relationships and hierarchy between different entities defined on your web page.
2. It helps build your content knowledge graph.

Nesting Helps Clarify Hierarchy and Entity Relationships

When implementing Schema Markup, many SEOs often create separate markups for multiple entities on a single page. For example, a page might feature a product along with its color variations and also include reviews and ratings of the product. All this visible content should be marked up with structured data.

However, if you specify each of these entities separately, you miss the opportunity to clearly communicate to search engines the primary focus of your page and the relationships between these entities. Are the reviews and ratings specific to that product, or are they unrelated to the product and pertain to the organization selling it?

This example shows that structuring your entities in a clear hierarchy helps search engines better understand the properties associated with your defined entities and how they all relate to each other.

This leads us to our second purpose for nesting your markup: the development of your knowledge graph.

Building Your Content Knowledge Graph Using Nested Schema Markup

Implementing nested Schema Markup is crucial for building a robust content knowledge graph. A knowledge graph is a collection of relationships between things, aka “entities,” defined using a standardized vocabulary, like Schema.org, from which new knowledge may be gained through inferencing.

Simply put, it is a way to organize your website content into a graph of interconnected entities, enabled through connected Schema Markup.

As search engines advance with AI technologies, establishing a well-defined and interconnected knowledge graph for your organization using Schema Markup is critical to staying ahead. AI search engines can utilize your structured data to uncover new insights about your organization and interpret valuable information from your website’s content and relationships more effectively.

This, in turn, allows your content to show up more accurately and relevantly for user queries.

Additionally, you can use your content knowledge graph to support internal AI initiatives and LLMs like ChatGPT. You can learn more about that in this article.

How do you Nest Schema Markup?

Now that you know what nesting is and why it’s important, it’s time to dive into the “how.” Nesting your Schema Markup can be broken down into several steps.

1. Identify the Main Entity

Determine the primary entity or topic of your web page. The main entity is easier to identify on some pages than others. If you’re unsure which Schema.org type to use, ask yourself what the intent of the page is. Is it selling something? If so, it’s likely a Product or Service. Is it informing an audience about a particular topic? In that case, it’s probably an Article or Blog Posting.

2. Identify Related Entities

Identify the other entities on the page that are associated with the main entity. For example, if your main entity is a Recipe, the webpage containing that recipe may also contain information about the author, reviews and ratings, or even a video showing the steps in the process. Each of these “things” is a related entity that you’ll want to represent in the structured data about that Recipe.

3. Implement a Nested Structure

Use the correct properties to connect your main entity and related entities together. In our Recipe example, we might use the author, review, aggregateRating, and video properties to connect the related entities we identified in the previous step.

Going to the Schema.org page associated with the type of your main entity will help you figure out which properties are available to that type. However, many types have more than 40 properties available to them, so finding the right one can be challenging.

Good news! If you’re unsure which Schema.org properties you should use to connect your entities, you can use our free Schema Paths Tool to identify all possible connections. To use this tool, select the two Schema.org types you want to connect, and it will output all the available properties that connect the two types.

The Schema Paths Tool in the image below shows that you can connect Recipe and VideoObject entities using a number of different properties. In our case, the subjectOf or video properties would both work. But since Recipe is eligible for a rich result, we would also want to consult Google’s Structured Data Documentation to see what they recommend. In this case, VideoObject should be connected to a Recipe using the video property.

Read our article for more information on how to use the Schema Paths Tool.

4. Validate your Schema

The Schema Validator will show all the markup on a single webpage and check for any syntax errors in the code. If the Schema Markup you’ve added aims to achieve a rich result, Google’s Rich Results Test will help you test which rich results your page is eligible for based on the structured data it contains.

5. Maintain Hierarchy

Keep in mind that effective Schema Markup requires ongoing maintenance and management, as on-page content and Google’s structured data requirements are subject to change. This ongoing maintenance will prevent schema drift and ensure you are optimizing your markup for search engine comprehension.

When Shouldn’t You Nest Schema Markup?

If the entities on your page are distinct and unrelated, nesting them within a hierarchical structure may not accurately represent the content. For example, a page featuring both a recipe and a list of unrelated events should use separate Schema Markup for each entity instead of nesting them together.

Additionally, some Schema types and properties are designed to be standalone and should not be nested within other types. For example, BreadcrumbList is used for navigational purposes, while the rest of your Schema Markup is probably intended to represent the meaning (semantics) of the page’s contents. As a result, these markups should not be nested.

Start Nesting Your Schema Markup Today

Implementing proper nested Schema Markup requires expertise and ongoing maintenance. Before worrying about nesting your markup, you must ensure your markup first aligns with your page content and that your entities are properly defined. Although this adds to the challenge, the benefits of this approach can significantly enhance your semantic SEO and provide your organization with agility in response to AI-driven search.

As we rapidly approach a future where AI powers search engines, you can implement nested Schema Markup to help them infer and access new knowledge about your organization. This can improve your visibility to potential customers in search results.

At Schema App, we understand the importance of nested Schema Markup and have designed our solution to help you easily create, connect, and manage your markup.

Don’t let the complexity of Schema Markup hinder your success. Get in touch with us to learn more about our end-to-end Schema Markup solution.

The post What is Nesting in Schema Markup? appeared first on Schema App Solutions.

In the digital marketplace, incorporating robust Schema Markup is one of the most critical steps you can take to get noticed. Schema Markup enables search engines to understand your web page content, effectively rank it, and present users with relevant search results.

What Is Schema Markup?

Schema Markup, also known as Structured Data, is data that you can add to your web page’s HTML code to explicitly define entities, properties, and relationships within your content. By doing so, it assists search engines in better comprehending and contextualizing your page content, thereby enabling them to deliver more accurate search results to users.

Schema Markup is created using the Schema.org vocabulary, a collaborative project involving major search engines like Google, Bing, Yahoo, and Yandex. The primary objective of Schema.org is to establish a standardized vocabulary for describing content on web pages, making it simpler for search engines to understand and interpret the meaning of various elements present on a webpage.

Although search engines use sophisticated machine learning algorithms, machines do not process or interpret information in the same way as humans. What might seem simple to a person may be unintelligible to a computer. Schema Markup helps fill in the blanks for search engines so that they know exactly what your page is about.

For instance, let’s say you have a product detail page containing an image and description of a handsaw, along with an image of the brand in the header.

A person reading this would immediately realize that the handsaw is from the brand “Dewalt,” but it might be difficult for search engines to understand that explicitly. You can use Schema Markup to identify that the brand of handsaw on this page is “Dewalt” so that the search engine can present this content for individuals searching phrases like “Dewalt handsaw.”

What are the main SEO benefits of using Schema Markup?

1. Help search engines understand the content on your page

Schema Markup enriches your website content by organizing its data in a way that is easily and accurately interpreted by search engines.

This gives search engines a more semantic understanding of what entities and topics your page covers, leading to more relevant search results. It also grants you more precise control over how search engines understand your content.

As such, search engines can intelligently display your content to the appropriate users. This targeted visibility can lead to higher clicks, impressions, and click-through rates, ultimately driving better-quality traffic to your site.

To delve deeper into how Schema Markup impacts your SEO efforts, refer to our ‘Common Questions About Schema Markup for SEO’ blog article.

2. Develop a Content Knowledge Graph that supports Generative AI Search

Structured data provides the foundation for developing your organization’s content knowledge graph.

Schema Markup not only describes the entities on your site but also outlines their relationships to other entities on your site and across the web. By implementing robust connected Schema Markup, you are building a content knowledge graph—a reusable data layer that captures relationships between various entities on your site using a standardized vocabulary like Schema.org.

This structured data framework is crucial for training and grounding generative AI search engines and other LLMs, which rely on factual data to mitigate errors and hallucinations.

Gartner has also identified knowledge graphs as a critical enabler for generative AI adoption, further highlighting Schema Markup’s fundamental role in AI advancements.

3. Achieve Rich Results

Implementing certain types of structured data can also enable search engines to display visually enhanced search results (aka rich results) instead of generic “plain blue link” results listings.

Rich results enhance standard search results by presenting additional information, such as a business location, images, product reviews, etc. Rich results are also referred to as enriched results or rich snippets, as they provide snippets of information about a page, brand, or business.

Example of a Product Rich Result

Example of a Review Snippet

Rich results are visually appealing and informative, making your listings stand out on the SERP and improving the overall search experience for users. By incorporating structured data, you cater to both customer needs and search engine algorithms, increasing your competitiveness in search results.

What types of Schema Markup are there?

There are many different types of Schema Markup that you can incorporate into your online content. Some of the most commonly used markup types include:

• Reviews: This type is used to mark up reviews for products, services, or other items. It includes properties like the reviewer’s name, rating, and review text.
• Product: Product markup is used for e-commerce sites to describe specific products. It includes details such as name, description, price, availability, and more.
• Local Business: This markup type is ideal for businesses with physical locations. It includes properties like name, address, phone number, opening hours, and geographical coordinates.
• Person: Person markup is used to describe individuals, including properties such as name, job title, contact details, and social media profiles.
• Organization: Similar to local business markup but broader, organization markup can be used for any type of organization, including corporations, educational institutions, non-profits, etc. It includes details like name, logo, contact information, and social profiles.
• Event: Event markup is used for marking up events such as concerts, workshops, or conferences. It includes properties like event name, date, location, and ticket information.
• Media Objects (images, videos, audio): Markup for media objects like images, videos, or audio files. It can include properties such as caption, thumbnail URL, and duration.
• Creative Works (movies, books, music, TV series, recipes): This type covers a range of creative content, including movies, books, music, TV series, and recipes. It includes properties specific to each type, such as author, director, actors, duration, and ingredients for recipes.

Choosing the right schema type depends on the nature of your content. Each type comes with its own set of properties that you can use to provide detailed and structured information about the content on your webpage. You can view the full list of Types here and learn more about the Schema.org vocabulary here.

What is the recommended format for implementing Schema Markup?

The most commonly used formats for implementing structured data are JSON-LD, microdata, and RDFa. However, Google recommends using JSON-LD due to its readability for both humans and machines.

Implementing JSON-LD (JavaScript Object Notation for Linked Data) is easier than implementing other formats like microdata or RDFa, and you can seamlessly incorporate it within the HTML of your web pages. This format is favored for its simplicity and effectiveness in conveying structured data to search engines.

How to implement Schema Markup on your site

Manually generate your own code and paste it on your site

One way to implement Schema Markup is to do it manually using the following steps.

1. Review Page Content: Examine each page on your site and identify what the page is mainly about.
2. Choose Schema Types: Select the appropriate schema type and properties that best describe the content on your page.
3. Write the JSON-LD: Create the Schema Markup in JSON-LD using the chosen schema types and properties.
4. Embed JSON-LD in HTML: Incorporate the Schema Markup JSON-LD into the HTML of your webpage.
5. Test Markup: Use tools like Google’s Rich Results Testing Tool (if you aim to achieve a rich result) or Schema.org’s Schema Markup Validator to validate and ensure correct implementation and desired results.

If you have the technological savvy to write the JSON-LD and can meticulously work through each page of your site’s content, this approach is a viable option.

However, the manual method of implementing Schema Markup is incredibly labor-intensive—especially if you have a huge website. Similarly, bringing in your own IT team to write and deploy the code can also be costly and time-consuming.

Use a Schema Markup Plugin

Instead of implementing the markup manually, you can opt to use a Schema Markup plugin to implement Schema Markup programmatically.

There are many Schema Markup plugins available for WordPress, Shopify and other CMSes that will allow you to add markup to your page programmatically. However, many Schema Markup plugins tend to be limiting in terms of the Schema type and properties you can leverage. You will also have little control over marking up each page.

Learn more about the pros and cons of using a Schema Markup plugin here.

Hire a Schema Markup Expert

The best way to implement advanced custom Schema Markup would be to hire a Schema Markup solutions provider like Schema App. At Schema App, we provide an end-to-end Schema Markup Solution through our leading semantic technology platform and a team of experts.

Our platform includes tools like our Highlighter and Editor that allow users to generate, deploy, and manage their structured data at scale. Our team of Schema Markup experts will also help you manage your structured data from strategy to results, deploying Markup at scale without diverting your in-house IT resources.

You can focus on your core marketing activities and trust us to deal with the complexities and nuances of your structured data.

Navigate the Complexities of Schema Markup with Schema App

Whether you choose to implement Schema Markup independently or require a solution like Schema App to expertly manage your organization’s Schema Markup, leveraging structured data offers a myriad of advantages for your SEO, AI, and semantic strategies.

If you need help implementing a robust Schema Markup strategy for your site, get in touch with us today.

The post What Is Schema Markup? A Guide to Structured Data SEO appeared first on Schema App Solutions.