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.

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.

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.

Beyond this, implementing Schema Markup can also result in a reusable content knowledge graph for organizations looking to train their internal LLMs, gain a semantic advantage in AI search, and manage their internal data more efficiently.

Let’s take a look at what Schema Markup is and the value it adds to healthcare organizations like yours.

What is Schema Markup?

Schema Markup, also known as structured data, is metadata based on the Schema.org vocabulary that you can add to your website to help search engines better understand and contextualize your web content.

When you implement Schema Markup on your site, you use the Schema.org vocabulary to describe the entities on your web page and how they relate to other entities on your site and across the internet. This helps search engines clearly understand what your web page is about and enables them to provide users with more accurate and relevant search results.

For example, your healthcare organization might have a physician page with content about the physician’s medical specialties, practice location, ratings and reviews, and contact information. When you apply Schema Markup to that page, you express this information in machine-readable format using the Schema.org types and properties. This helps to disambiguate your content topics and support search engine comprehension.

Common Schema Types for Healthcare Providers

In the Schema.org vocabulary, types are how you categorize the various entities on your page, and properties are attributes or characteristics that provide additional details and contextual information about a given entity.

Healthcare organizations can use more general types such as Organization, Physician, MedicalClinic, and more. However, the Schema.org vocabulary contains a Health and Life Sciences extension of over 200 Types and 160 properties specific to the medical space.

These include everything from terms for describing diseases and injuries, such as AnatomicalStructure and MedicalSignOrSymptom, to systems of medicine, such as TraditionalChinese and WesternConventional.

In addition to those listed above, here are some other examples of types of content that you can use to explain information about your healthcare organization:

• MedicalOrganization – Home page
• Hospital – Hospital pages
• IndividualPhysician – Physician pages
• MedicalCondition or MedicalProcedure or MedicalTest– Medical Services pages

The main purpose of implementing Schema Markup is to help search engines understand and contextualize the content on your site. Therefore, it is best practice to choose the most appropriate type and properties that best describe the content on your page.

In some cases, adding Schema Markup can also enhance the appearance of a search result on Google’s search engine results page (SERP). This is known as a rich result.

Common Types of Rich Results for Healthcare Providers

A rich result is a visually enhanced and information-rich search result displayed in the SERP, achieved through structured data. Rich results can include star ratings, reviews, and other details, making your healthcare organization’s search appearance more attractive and informative.

Pages with rich results tend to see an increase in click-through rates, higher-quality traffic, and appointments booked, offering measurable results.

Google has specific eligibility and structured data guidelines for each rich result. Aligning your markup with these criteria enhances your chances of achieving various rich results. Here are some common types of rich results that healthcare websites can achieve through structured data.

Review Snippet

Patient engagement is important for any health organization. 94% of healthcare patients leave online reviews about their experiences. Many physician or location pages tend to include reviews and ratings. By nesting the appropriate Schema Markup on your physician or location pages, these pages can achieve a review snippet.

Review Snippets can help organizations display their credibility and build trust during the search journey. When our customer, Sharp Healthcare, achieved Review Snippets for their Physician pages, the CTR for those pages increased by 119%.

Job Posting Rich Results

Hiring talent is top of mind across most healthcare organizations, and Schema Markup provides innovative opportunities around healthcare recruitment.

Healthcare organizations can use Job Posting Rich Results to showcase their job openings directly on Google’s search results, providing key details like job title and location. This boosts visibility, attracts qualified candidates, and streamlines the hiring process.

Our customer, Baptist Health, saw an 1194% increase in CTR when the job posting rich result was awarded.

Product Rich Results

If your healthcare organization sells products such as CPAP machines or flu shots, you can leverage Product Rich Results to display key product information such as price, reviews, and availability directly on the search result.

This provides users with clear and immediate details, which can help them make quick decisions and increase your web conversions.

Recipe Rich Results

If your organization publishes healthy recipes on your site, you can make that content eligible for a Recipe rich result by marking them up with Recipe structured data.

These are just some of the rich result opportunities that healthcare organizations can leverage to stand out in search. However, the value of Schema Markup far exceeds rich results.

Why is Schema Markup Important for Healthcare Providers?

Search engine advancements have transformed the conventional approach to healthcare, with a growing number of patients seeking relevant health-related information directly on the SERP.

Schema Markup is a powerful yet underutilized SEO strategy that can help healthcare organizations stand out in this competitive search landscape and provide answers directly in the search results when prospective patients need it most. Beyond achieving rich results and bringing pertinent information about your organization to the SERP, Schema Markup supports several other healthcare organizations’ SEO initiatives.

Enhanced Search Visibility

Schema Markup helps search engines better understand the content on a healthcare provider’s website. This improved comprehension can lead to higher accuracy in search results. This can improve the provider’s visibility to individuals searching for relevant healthcare information.

Improved Customer Journey

Users can obtain critical details directly from the SERP, including facility location, hours, specialties, and reviews. This fosters transparency, credibility, and trust (contributing to your organization’s E-E-A-T) from the start of their customer journey. The streamlined journey leads to easy navigation to booking pages, reducing steps for user-friendly appointment scheduling.

Develop a Reusable Content Knowledge Graph

By implementing Schema Markup on your site, you can create a reusable content knowledge graph that helps generative AI search engines understand and infer knowledge from your content. This content knowledge graph can also be reused to power internal AI initiatives and ground LLMs with accurate information about your organization.

By developing your content knowledge graph, you can control how your brand is understood and presented in search.

The Challenges of Implementing Schema Markup at Scale

Despite all the benefits of implementing Schema Markup for your healthcare organization, creating and implementing a Schema Markup strategy at scale can be costly, complex, and time-consuming.

SEO teams often lack the expertise and the IT resources to deploy and update Schema Markup at scale across their websites. That’s where Schema App comes in. At Schema App, we provide an end-to-end, HIPAA-compliant, Schema Markup solution for leading healthcare organizations.

Benefits of Schema App for Healthcare Organizations

1. Measurable Results

One of the best things about Schema Markup is that it is measurable. This makes showing the return on investment from your work with Schema App easy. When you optimize your web pages with Schema Markup and start achieving rich results, Google Search Console reports on the impressions and clicks you achieve specifically from the URLs that are getting these decorated results.

When you start working with Schema App, we ask about your organizational goals and what success looks like from your work with us. We ensure that you have tangible results to show how Schema Markup is contributing to your organization’s goals.

The most common measures are impressions, clicks and click-through rates from rich results achieved on your site. Upon achieving those results, we’ll continue to optimize your Schema Markup strategy and ensure your content evolves with the changing SEO world.

How do you convert clicks to dollars?

If you don’t have a way to correlate clicks or sessions on your website to appointments booked, you can do a simpler calculation by taking your cost-per-click and multiplying it by the number of clicks you get from rich results. The result is the number of dollars you saved from paid advertising through increased organic traffic. Our customers often see an ROI greater than 10X.

# of Clicks from Rich Results X Avg CPC = Value of work done with Schema Markup & Schema App

This allows marketing teams to easily prove the return on investment in their SEO efforts.

2. Retaining Talent through Agility and Scale

In addition to the measurable ROI from clicks, Schema App offers healthcare organizations a return on investment by adding agility to their teams.
Agility is critical to any business’s success. With Schema App, SEO teams no longer need to learn Schema Markup or wait for internal IT teams to update their markup.

Our Schema App Highlighter tool allows SEO teams to generate and deploy dynamic Schema Markup to thousands of similarly templated pages within minutes. Combined with our team of expert Customer Success Managers, SEO teams can access a Schema Markup expert and make updates to their Schema Markup quickly to see results. We aim to ensure we deliver our client’s quarter-over-quarter results with speed and agility.

On top of delivering greater results, staying agile can also help with employee retention. Operational inefficiencies can hold teams back and be demotivating, resulting in lower employee retention. When your team sees their Schema Markup strategies come to life in little to no time, they are empowered by the results, which motivates them to keep performing.

3. Show Value Cross Functionally and to your Physicians

Many of our clients have already tried to do Schema Markup on their own.

SEO specialists spend countless hours trying to learn how to write Schema Markup (JSON-LD) page by page before submitting it to IT to be implemented on the page. With our Schema App Highlighter tool, SEO teams can generate Schema Markup (JSON-LD) dynamically at scale and deploy it across pages in just a few clicks. They can also reduce their dependency on their development team and get the job done quickly.

Schema Markup not only benefits SEO efforts but also supports physicians within healthcare networks by:

• showcasing reviews and ratings,
• enhancing visibility and appearance on the SERP, and
• building trust with current and prospective patients.

This, in turn, can drive more appointments for these physicians and improve reputability. This can make your physicians more inclined to stay with your healthcare organization, thus aiding physician retention.

Our partnership with Schema App reassures us that this important component of our SEO strategy is being managed. The data we have been able to get out of this is great. Providers love to see how good their marked-up listings look in search results. It’s great evidence of the work we do behind the scenes to increase visibility in our market.”

– Julie Goldstein-Dunn, Director, Experience Insights & Analytics, Henry Ford Health System

Working with Schema App

In the healthcare industry’s competitive landscape, it’s essential to stand out in search results to maintain relevance and visibility among competitors. Integrating innovative strategies like Schema Markup is key to distinguishing your brand. If you haven’t already integrated Schema Markup into your strategy, now is the ideal time to do so, especially as search algorithms increasingly prioritize semantic understanding.

At Schema App, we provide an end-to-end Schema Markup solution. We partner with healthcare networks and other organizations to help their content be better understood by search engines so they can stand out in search. Our aim is to empower organizations like yours to deliver a seamless healthcare experience to their customers with ease and scale.

The post The Value of Schema Markup for Healthcare Organizations appeared first on Schema App Solutions.

However, we’ve seen a lot of changes in rich results and the overall search experience this past year. The uprising of generative AI-powered search engines, accompanied by the volatility in rich results, has prompted our team to dive deeper into the semantic value of Schema Markup and entity linking as it pertains to search today.

In this article, we will share the value of entity linking, the tools enabling you to do it at scale and the results we’ve seen from implementing entity linking with our Enterprise clients.

Growing Importance of Entities in Search

Over the past decade, search engines have shifted from lexical to semantic search to improve the accuracy and relevancy of their search results.

As a result, how we think about search engine optimization also has to change. We have to move away from adding keywords to a page and go towards identifying entities on a page to help search engines and machines understand and contextualize the content on our pages.

Entities are a single, unique, well-defined, distinguishable thing or idea. An entity can be anything from a person to a place to a concept, and they possess defining characteristics or attributes (i.e. colour, price, name). But they need to be described in relation to other things to have meaning. For example, Schema App is an entity that can be described by its name, location, website URL, founders, employees and more.

Your website content contains entities related to your organization, and you can help search engines identify the entities on your page using Schema Markup.

When you implement Schema Markup on your page, you are identifying and describing the entities in your content, which helps search engines better understand your content.

While having entities defined on your site is good, you can go one step further and improve your markup by doing entity linking to build a connected, robust content knowledge graph.

A content knowledge graph is a collection of relationships between the entities defined on your website, defined using a standardized vocabulary like Schema.org. It enables search engines and other machines to gain new knowledge about your organization through inference.

What is Entity Linking?

Entity linking is the act of identifying entities mentioned in text, and linking them to corresponding entities that have been defined in a target knowledge base.

In the context of Schema Markup, entity linking is the act of linking the entities on your site to the corresponding known entities on external authoritative knowledge bases such as Wikipedia, Wikidata and Google’s Knowledge Graph using Schema.org properties. Examples of connector properties include sameAs, mentions, areaServed, and more.

External authoritative knowledge bases can differ by vertical or content type. For example, if you are in the medical or finance industry, there may be a governing body or glossary that best defines the entities within your content.

Entity linking can help you define the terms and entities mentioned in your content more explicitly, thus enabling search engines to disambiguate the entity identified on your site with greater confidence and provide users with more accurate and relevant search results.

For example, if your page talks about ‘London,’ this can be confusing to search engines because there are several cities in the world named London. You can help search engines disambiguate which London you are referring to in your content by linking to the same known entity described on Wikipedia, Wikidata or Google’s Knowledge Graph.

Suppose we are talking about the city of London in Ontario, Canada. In that case, we can use the sameAs property to link the entity on your site to the known entity on Wikipedia, Wikidata and Google’s Knowledge Graph. Doing this entity linking makes it explicit to search engines that the content on the page is about ‘London, Ontario, Canada’ and not ‘London, England’.

  "mentions": {
    "@type”: "Place",
    "name": "London",
    "sameAs": "https://www.wikidata.org/wiki/Q92561",
    "sameAs": "https://en.wikipedia.org/wiki/London,_Ontario",
    "sameAs": "kg:/m/0b1t1",
}

Entity linking is even more vital if your organization is in an industry where being specific is essential (such as defining a medical condition or a specific financial instrument like new construction financing).

Approaches to Entity Linking

You could take two main approaches to entity linking: a general approach and a more strategic one.

General Approach to Entity Linking

You could take a general approach and identify any entity on your site, check if it is a known entity on an external authoritative knowledge base, and, if it is, link that entity to the known entities.

For example, if you are a technology company, your product pages might mention entities like SOC2, Solution, and the United States. Using the general entity linking approach, you can link these entities to the known entities on external authoritative knowledge bases.

Strategic Approach to Entity Linking

Alternatively, you can take a more strategic approach and identify a specific type of entity on your site (for example, locations mentioned on your site or a particular term mentioned on your site), check if it is a known entity on an external authoritative knowledge base, and if it is, link that entity to the known entities.

For example, you can use a place-based entity linking approach to explicitly identify the place entities mentioned on a page and link them to the known entities on Wikipedia, Wikidata and Google’s Knowledge Graph.

If your website has different location-based landing pages for your offering, you can implement place-based entity linking in your Schema Markup. Doing so would help search engines understand the locations that your organization is servicing and enable your page to perform better on ‘near me’ and other location-based searches.

The entities you target with entity linking should be purposeful. Instead of linking all the entities on a page with corresponding known entities, you should focus on linking the most essential ones for clarity.

How we do Entity Linking at Schema App

At Schema App, we believe that entity linking is crucial to developing a robust content knowledge graph. It can add value to your SEO efforts and prepare you to get further insights from your content. So, how can you do entity linking within your markup?

You can manually link the entities on your page to the known entities on external authoritative knowledge bases. However, this solution is not dynamic nor scalable, so keeping the data updated and accurate can be resource-intensive and time-consuming.

The Schema App team developed the Omni LER feature to apply entity linking in a scalable, dynamic manner to solve the scale and accuracy of entity linking.

Omni Linked Entity Recognition (LER) is the automated process of identifying entities mentioned in texts and linking them to the corresponding entities on authoritative knowledge bases (like Wikipedia, Wikidata and the Google Knowledge Graph).

Today, Schema App’s Omni LER feature uses natural language processing to identify entities within a block of text automatically and embed them within the Schema Markup based on the Schema Markup configuration in the Schema App Highlighter.

In the future, we’ll introduce a controlled vocabulary feature to help our customers identify which entities they want to map to for entity linking. This evolution will give organizations even more control over the topics and entities they want to be known for and how they want to define those entities.

Entity Linking Experiments and Results

The impact of entity linking on SEO has yet to be explored widely. This prompted our team to experiment with entity linking to see if it has any measurable impact on SEO metrics.

Using our Omni LER feature, we implemented entity linking on over 60 enterprise customer accounts in healthcare, finance, B2B technology and other industries.

We ran general and place-based entity linking experiments on a variety of pages (i.e. blogs, location pages, medical pages, etc.) over three months and measured the impact on search performance. Here’s what we saw as the results.

General Entity Linking Experiment

We took the general entity linking approach on pages with long-form content, such as blogs. The Omni LER feature within the Schema App Highlighter identified the named entities in the text and embedded the known entities in the markup using the mentions and sameAs properties within the schema markup for the page.

For example, one customer had a blog article about rashes caused by amoxicillin. We used the “mentions” property to identify ‘Amoxicillin’ as an entity on the blog post and further clarified the entity by nesting the equivalent entities defined on Wikipedia and Google’s Knowledge Graph for Amoxicillin.

The Omni LER feature also identified other entities on the page, such as ‘Benadryl’, ‘Keflex’, ‘Mononucleosis’ ‘National Institutes of Health’, and linked these entities to the known entities on Wikipedia, Wikidata and Google’s Knowledge graph under the relevant schema markup property.

After implementing entity linking on that blog article, the customer saw a 336% increase in click-through rate for the query ‘Amoxicillin rash’ and a 390% increase in click-through rate for the query ‘Rash from amoxicillin’. The number of queries for that blog also increased by 86.75%.

Across our customer set, we saw an overall trend where the clicks and click-through rates increased for relevant keywords while the number of irrelevant keywords dropped for each page.

Placed-based Entity Linking Experiment

In a second experiment, we took the placed-based entity linking approach on location-based landing pages. This customer had a set of location-based landing pages to cater to their audiences in different states across the US.

We implemented placed-based entity linking on 11 test pages and kept 4 control pages to compare the results.

On the test pages, we added spatialCoverage and audience property in the markup to identify the state this page pertained to (in this example, it was for the state of California) and then further clarified which ‘California’ we were referring to by nesting the equivalent entities defined on Wikipedia, Wikidata and Google’s knowledge graph using the sameAs property.

After running the experiment for 85 days, the test sites saw an increase in the number of queries containing the state name and ‘near me’, leading to a 46% increase in impressions and a 42% increase in clicks for non-branded queries.

By clarifying the locations serviced on the site, this customer’s pages showed up for more location-based queries.

Do Entity Linking at Scale

Based on the early results we’ve seen, entity linking can help search engines disambiguate the entities mentioned on your site and help your pages show up for more relevant search queries, increasing the clicks and click-through rate to the pages. It is a great way to stand out in search and drive more qualified traffic to your site.

Entity linking can also help your organization build a more descriptive content knowledge graph. You can learn more about content knowledge graphs through our free ‘Content Knowledge Graph Fundamentals’ course.

If you want to implement entity linking at scale or build a content knowledge graph for your site, contact us.

The post Measurable Impact of Scaling Entity Linking for Entity Disambiguation appeared first on Schema App Solutions.

In this article, we dive into what Product Schema Markup is, its benefits, and how you can achieve greater visibility and engagement on search by leveraging it on your product web pages.

Expanding on its multiple benefits, adding Product Schema Markup can help your eCommerce website in two ways:

1. Product Schema Markup enhances how your store and products appear on the search engine results page (SERP).

These enhancements, formerly called rich snippets and now known as rich results, can include star ratings, reviews, price, availability, and much more!

You’re probably familiar with star ratings and reviews, as they really stand out in search results as they do in the following example for Ariat. In addition to ratings and reviews, Product rich results can also highlight shipping and return information.

2. Product Schema Markup provides context for the content on your web pages so search engines can better understand and match your products with a user’s search intent.

Schema Markup has benefits that extend beyond achieving rich results for your products and services in search. Through Schema Markup, you can define objects on your web pages as distinct entities with their own properties and relationships to other entities. Once defined, you can connect these entities to a search engine’s knowledge graph, which streamlines your content to be matched with a relevant search query.

For example, if your eCommerce store sells vegan snacks and alternatives, your structured data markup informs Google that these snacks are products for sale and that it’s not, for example, a blog post about the best vegan alternatives to snack on.

Distinguishing Between Product Snippets and Merchant Listings

According to Google, there are two classes of Product rich results: Product snippets and merchant listing experiences.

Merchant listings serve as an extension of the product snippet item, providing more comprehensive search results that consistently feature a price. A carousel may showcase these listings alongside similar products from various sellers or within a knowledge panel in the SERP.

While Product rich results do not appear in the shopping tab, merchant listings do. Notably, they manifest differently within the shopping tab. Incorporating merchant listings allows you to customize your approach as you enhance your target product with additional properties. This is a process that requires the integration of Product markup.

Merchant listings come with a broader set of recommended properties compared to product snippets. These expanded features allow you to segment results based on factors such as seller, brand, pattern, size, and more.

The properties required and recommended for merchant listings are more exhaustive, providing a more detailed and nuanced representation. For example, product snippets don’t require an image, but merchant listings require one.

The effectiveness of merchant listing experiences hinges on specific product data, such as price and availability. It’s important to note that only pages that directly support the product purchases are eligible for merchant listing experiences; pages containing links to other sites selling the product do not meet the criteria.

For reference, see the following example of another Ariat product that achieved an enhanced merchant listing. Notably, it has price listed, a large and clear image of the product, delivery information, ratings, and shipping information.

Product Result Reporting

Each type of rich result—product snippet and merchant listing—comes with distinct enhancements and reporting, each adhering to its own set of requirements and recommendations.

As per an announcement from Google Search Central, they conveyed through a tweet that, “In January 2024, [GSC] will stop reporting the Product results search appearance, both in the Performance report and the API”.

This decision to deprecate Product results aligns logically with the prior split into merchant listings and product snippets. Given that Product results essentially represent a combination of the two, the decision to deprecate it is a move towards more detailed and nuanced reporting for each.

Required and Recommended Properties for Product Structured Data

Google maintains documentation that explains what is required for “Product” structured data.

We’ve captured the most common required and recommended fields below. It is important to keep in mind, however, that the requirements and recommendations may differ between Product Snippets and Merchant Listing eligibility.

For an exhaustive list of requirements and recommendations for both Merchant Listings and Product Snippets, visit the Product Information section in their Structured Data Documentation for Product.

You can see in the example below that you can toggle between the specific properties for “Product Snippets” and “Merchant Listings” exclusively.

You must populate the required properties in order for your content to be eligible for display as a rich result in search. Recommended properties add more information to your structured data, which can provide a better user experience.

Looking for additional guidance implementing Product structured data? Read our article “6 Common Product Rich Result Mistakes You Might be Making” for more tips.

Product

https://schema.org/Product

It’s important to note that Product Structured Data requires only one of the following properties:

• Review
• aggregateRating
• Offers

Once you fulfill one of these requirements, the remaining properties will become recommended rather than required. That being said, it is always best to markup all three properties as they can provide more information in the rich result.

TIP! Add Review, aggregateRating, and Offers properties to provide more information in the rich results.

We created the following visual to help conceptualize the structure of Product Schema Markup. With Product as the starting point, the required properties are used to connect to information in the form of text, URLs, or other data items containing their own properties.

The required and recommended properties for the Review, AggregateRating, and Offer data items are as follows:

Review

https://schema.org/Review

AggregateRating

https://schema.org/AggregateRating

*Note: You must have at least one of ratingCount or reviewCount.
**Note: only required if the rating system is not a 5-point scale (1 = worst rating, 5 = best rating)

Offer

https://schema.org/Offer

TIP! While itemReviewed is required for standalone Review and AggregateRating data items, these should not be used when embedded within the Product template.

FYI: For the most current guidelines on required and recommended fields, reference the Google Developers Reference Guide.

How to Create Product Structured Data

There are two types of pages where you would typically create Product structured data:

1. A product page listing a single product and
2. A shopping aggregate page listing a single product with information from other sellers offering that product.

Learn more in Google’s Product structured data documentation.

To help you get started, we have compiled the fundamental steps for creating Product Structured Data:

Step 1: Add Required Properties for Product Structured Data

Add the required Schema.org properties for Product structured data markup using our reference above. We recommend our own tools, the Schema App Editor and Schema App Highlighter, but there are many different options out there.

You should add all of the recommended and required properties, but also ensure you are connecting the entities on your site. For example, if the brand of your product on your website is also your organization, you want to make sure that the “brand” property connects back to your organization’s entity.

The Schema App Highlighter is a product of the brand, Schema App. Therefore, we can nest the Schema App Organization markup under the brand property to reflect the connection between the Schema App Highlighter and Schema App.

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "@id": "https://schemaapp.com/highlighter/#Product",
  "name": "Schema App Highlighter",
  "brand": {
    "@type": "Organization",
    "@id": "https://schemaapp.com/#Organization",
    "name": "Schema App",
  }
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.7,
    "reviewCount": 63, 
  }
}

Step 2: Review your Product Structured Data to ensure it follows Google’s Structured Data Guidelines

Google’s Product structured data feature guide has specific technical guidelines as well as content guidelines.

Your structured data and website content have to adhere to all these structured data guidelines to be eligible for a Product rich result. Read our article to learn How to Optimize Your Content to Achieve Google’s Rich Results.

Step 3: Deploy your Product Structured Data to the Relevant Pages

Once you’ve finished authoring your markup and ensuring your content aligns with Google’s guidelines, it’s time to deploy your markup.

Google recommends using JSON-LD, which is also our favourite format for deployment!

Step 4: Validate your pages to make sure the Structured Data is working

To test that your Product structured data is working properly, you should use:

1. The Schema Markup Validator (SMV)
2. Google’s Rich Results Testing Tool

Using the Schema Markup Validator

The Schema Markup Validator (SMV) was modelled after and has officially replaced Google’s Structured Data Testing Tool (SDTT). Many SEOs still prefer the SDTT, as the SMV only validates your schema.org syntax and does not show your eligibility for rich results.

Using the Rich Results Testing Tool

Google’s Rich Results Testing Tool helps you to see which rich results can be generated by the structured data it contains.

If you’ve done everything correctly, you should start achieving Product rich results for your pages. However, it is important to note that eligibility for a rich result doesn’t guarantee that the rich result will be awarded to your page.

Google’s goal is to present users with the most relevant search results. If they do not deem a rich result to be relevant to the searcher’s query, they will likely present your page as a regular search result.

Step 5: Manage your Structured Data on an Ongoing Basis

As mentioned earlier, adding structured data to your site not only allows you to be eligible for rich results, it also enhances the search engine’s understanding of your content. This enables search engines to provide users with more relevant and accurate search results.

Therefore, it is imperative for you to continue managing your structured data on an ongoing basis even after you’ve achieved a rich result. To maintain your rich result eligibility, you’ll need to ensure the content on your page matches the structured data.

As we shift towards AI search, maintaining your structured data can also help you control how AI search engines interpret your brand and content. Thereby futureproofing your organization’s web visibility and contributing to the development of the semantic web.

Having a dynamic Schema Markup solution like the Schema App Highlighter can help you update your markup whenever the content on your page changes. Get in touch with our team to learn more.

Scaling Your Product Schema Markup

At Schema App, we don’t just focus on achieving Product rich results – we’re dedicated to unlocking the full semantic potential of your content.

By applying Schema Markup to your product pages, you not only make them eligible for rich results, but you also provide clarity and contextual understanding to search engines through your content markup. This approach lets you take charge of how your brand appears in search, improving visibility and enhancing relevance in search results.

Through the powerful combination of our Schema Markup expertise and advanced semantic technology, we empower your digital team to be more agile and effective in their SEO strategy and preparation for the future of AI-driven search.

We’ve helped eCommerce brands such as Avid Technology and Keen Footwear become leaders in the online shopping industry by showcasing their unique value in search with structured data.

If you’re struggling to find a scalable solution to enhance your Product rich results and drive performance, Schema App is here to help. Get in touch with us today.

Frequently Asked Questions about Product Schema Markup

What is Product Structured Data?

Product Structured Data, also known as Product Schema Markup, is code you can add to the backend of your website so that search engines can provide additional information about your products in search through enhanced features like product rich results.

Schema Markup is a standardized vocabulary that uses the properties and types defined at Schema.org, a resource for SEOs created by Google, Microsoft, Yandex, and Yahoo back in 2011.

How do you Create Product Structured Data?

1. Add all of the required Product schema.org properties to your individual product pages. Google recommends using JSON-LD, as do we!
2. Validate your structured data markup using Google’s Rich Results Testing Tool.
3. Deploy your structured data markup, and use the Schema Markup Validator to analyze your schema.org syntax for any errors.
4. Request that Google recrawls your newly marked-up web page using Google Search Console.

How do you Fix Product Structured Data Errors?

Product structured data seems complex because of three common errors that appear for this type of structured data: “offers”, “reviews”, and “aggregate rating” showing up as ‘either “offers”, “review”, or “aggregateRating” should be specified’. To fix this error, you’ll need to use these three schemas in your Product markup. Product structured data requires including either “offers”, “reviews”, or “aggregateRating” in your Schema Markup.

Once one of these has been fulfilled, the remaining properties will become recommended rather than required. It is always best to markup all three properties as they can provide more information in the rich result. Learn more about how to tell if your Schema Markup is working in our guide.

The post Creating “Product” Schema Markup appeared first on Schema App Solutions.

However, we’ve seen the role of Schema Markup shift over this past year. This article explores the journey of Schema Markup and its changing role in SEO throughout 2023, emphasizing the growing importance of its semantic value over just rich results.

Early 2023 – Fluctuations in Rich Results

In 2022, the performance of rich results experienced fluctuations, and 2023 has been no different.

In April 2023, Google stopped showing Video rich results on the SERP for pages, favouring YouTube results, or pages where the video was the main element of the page. As such, many organizations can no longer rely on video-rich results to drive traffic to their site.

At the same time, Schema Performance Analytics saw the performance of FAQ rich results declining on mobile for unexplained reasons. However, John Mueller mentioned in an unofficial statement that “sites love adding FAQ markup; it gives them more room to search, and at some point, it makes the results less useful. The right balance makes sense to re-evaluate from time to time, like with any other search element.” This was perhaps Google’s test to see how the removal of FAQ rich results would impact the search experience.

To mitigate the risk from these rich result fluctuations, Schema App’s High Touch Support team made content recommendations that would allow our customers to diversify the types of rich results they were achieving. When it came to making changes with agility, the Schema App Highlighter was used to make quick edits, as it enables the creation of Schema Markup templates that can easily be updated when changes to content occur.

February & May 2023 – The Introduction of Generative AI Search Engines

In February 2023, Microsoft rolled out the new Bing, which included its AI chatbot, Bing Chat. Google followed suit, unveiling the experimental Search Generative Experience (SGE) at the Google I/O conference in May 2023, sparking significant changes in the dynamic of search.

SGE, though in its testing phase, disrupted search results by relegating organic search results, including rich results, lower on the SERP.

Furthermore, these generative AI search engines were prone to hallucinations and biases, resulting in inaccurate search results. This raised critical questions for organizations: How could they control the way generative AI search engines interpreted their content to ensure accurate information on SGE?

The evolving AI landscape generated both excitement and concern, with uncertainties about its impact on SEO. Amidst the ambiguity, the key question persisted on whether Schema Markup aided AI algorithms in comprehending website content.

Preparing for AI-Search

During his Pubcon keynote speech, Fabrice Canel, Principal Program Manager for Bing, shared that SEOs could prepare for this new AI-enabled search by creating great content and annotating it with Schema Markup. As such, many SEO professionals leaned towards implementing Schema Markup.

Recognizing it as the language that search engines used to understand site content, Schema Markup emerged as a concrete way for SEOs to stay relevant during the rapid AI evolution. This approach provided a sense of control over how search engines interpreted content and was adopted by many forward-looking organizations.

The semantic value of Schema Markup, which refers to the underlying meaning and context it adds to the content, became increasingly apparent to SEOs at this time. However, it did so in a somewhat hypothetical manner. Unlike rich results, the quantitative measurement of this semantic value of Schema Markup posed challenges.

At this time, Search Engines didn’t provide any analytics on how content was performing in SGE or Bing Chat. Consequently, SEO teams often relied on rich results as a tangible metric to gauge the effectiveness of their Schema Markup strategy.

August 2023 – FAQ & How-to Deprecation: A Turning Point

Despite the announcement of SGE, the performance of rich results seemed relatively stable on Google. However, between August and September 2023, a significant turning point unfolded as Google deprecated How-to rich results and dramatically reduced the frequency of FAQ rich results. The latter were then restricted to display exclusively on “well-known, authoritative government and health websites.”

Drop in clicks after deprecation of How-To rich results

The deprecation of FAQ, a previously widely utilized rich result, reignited concerns about the continued relevance of Schema Markup. While there are still over 30 rich results available, few had the flexibility like FAQ to use on diverse content.

In a year where marketing budgets were critiqued, and leaders required measurable ROI for initiatives to be approved, the absence of clicks and impressions from rich results made it challenging to quantify the value of Schema Markup. Many marketing teams asked: “Is there a point in implementing Schema Markup if rich results can’t be achieved?” The answer, unequivocally, is yes.

Prioritizing the Semantic Value of Schema Markup

Even without the immediate gratification of rich results, Schema Markup remains important for organizations looking to future-proof for search.

Generative AI search engines like SGE and Bing Chat revolutionized user search experiences. They presented multi-modal answers and provided follow-up questions to user queries.

However, the underlying search algorithms that power both the regular search engines and generative AI search engines have shifted from lexical to semantic. Instead of matching keywords, search engines assess the meaning and intent behind a query, providing searchers with results of the closest relevance.

Using Schema Markup to Define Your Entities

Schema Markup plays a crucial role in this understanding by allowing web publishers to define the entities on the site and showcase the relationships between entities in the form of a content knowledge graph.

In the past, when rich result eligibility was the main focus, many organizations would implement Schema Markup, but not in a manner that defined the relationship between the primary things (aka entities) on their pages. They simply added the minimum Schema Markup required to be eligible for the desired rich result rather than applying connected Schema Markup to improve search engine understanding.

In this new world of AI and Large Language models, Schema Markup for rich results alone is insufficient. By implementing proper connected Schema Markup and establishing connections between the entities on your site and on external authoritative knowledge bases, you are creating your organization’s content knowledge graph.

Building Your Content Knowledge Graph

Your content knowledge graph is a structured information data layer that can help search engines disambiguate the entities mentioned on your site. By providing this, you can shape how search engines understand your content, gaining greater control over how users perceive your brand. This ultimately provides users with more accurate and relevant search results.

The value of Schema Markup in ensuring your content is correctly understood is now significantly more strategic than just achieving rich results.

October, November, & December 2023 – Evidence From Google That Rich Results Hold Semantic Value

Don’t believe us? Google is also telling us that the value of Schema Markup is for understanding AND rich results. Search News released a new episode in early October 2023. During the episode, John Mueller talked about how some rich results would go away – in reference to the deprecation of How To rich results and reduction in FAQ rich results – and new rich results would be introduced. And boy did they hold true to their word.

Over the span of October, November, and December 2023, Google rolled out 6 new rich results:

• Oct 16: Added Vehicle Listing structured data documentation.
• Nov 15: Added Course Info structured data documentation.
• Nov 27: Added Profile page structured data documentation, Discussion forum structured data documentation, and expanded recommendations for Q&A Page structured data documentation.
• Nov 29: Added new Organization structured data documentation
• Dec 4: Added Vacation Rental structured data documentation

Structured Data Offering a Mutually Beneficial Relationship Between Google and SEOs

Google’s ongoing rich result opportunities highlight the symbiosis between search engines and SEOs. By offering rich results in exchange for detailed structured data, Google stimulates the supply of credible information, contributing to the development of the semantic web. It’s a win-win!

Google grants rich results as a reward for making it easy and less costly for search engines to comprehend the content on your website. By providing Schema Markup, you inform them about the content and how it relates to other topics on the web and on your website. By providing this information, the search engines don’t have to process the data to infer the meaning or relationships.

This helps search engines understand content without having to spend as many computing resources. This incentive provides content creators with the motivation needed to support the semantic initiatives crucial for the future of search.

Let’s look at two of the new rich results, Profile Page and Organization, and call out their characteristics that emphasize the value they bring to the semantic web.

Profile Page & Organization Structured Data Helps With Disambiguation

Among the newly introduced rich results, Profile Page and Organization stand out, playing a crucial role in disambiguating entities such as organizations, individuals, and authors within your content. These elements tie into E-E-A-T and empower you to assert greater control over structured data, articulating your identity and authority in connection to your content.

Organization structured data enables search engines to understand context, even when your website does not visually present certain information. For instance, properties recommended within the Organization structured data guidelines, such as identifier codes (i.e. duns, taxID, etc.), may not be visible to users but aid Google in disambiguating and identifying your organization within your content.

This background information adds a layer of context, facilitating search engines in relating your content to search queries and other web information through a knowledge graph.

Vehicle Listing and Vacation Rental Structured Data (Feed)

Last but not least, we’re seeing structured data become a data feed. The introduction of the new Vehicle Listing and Vacation Rental Structured Data supports this concept. You can achieve the Vehicle Listing rich result by adding structured data to your site or uploading a vehicle listing feed file to Google. Similarly, you can now achieve the Vacation Rental rich result by adding structured data, instead of the historical method of uploading an XML list feed to Google. Unlike list feeds, structured data is a cleaner way for data providers to transfer data to Google.

While the consecutive release of new rich results is exciting, it’s crucial to recognize that the purpose of structured data has expanded beyond merely attaining rich results, particularly in the past year. Google’s introduction of these rich results reflects a clear effort to improve the semantic nature of the search experience.

As SEOs, our focus should shift towards creating semantically understood content, empowered by Schema Markup.

The Value of Schema Markup Today: Prioritizing Semantic Understanding

Schema Markup remains valuable for search engines in 2023, emphasizing the critical need to prioritize the semantic aspect of structured data over just achieving rich results. While rich results come and go, semantic understanding is instrumental in laying the groundwork for contextual content that is poised to shape the future of search.

By connecting entities and developing a Knowledge Graph, organizations can ground Language Models (LLMs), support internal AI initiatives, and build authority by linking to authoritative databases. Schema Markup, originally created for search engine comprehension, continues to play a vital role in navigating the dynamic landscape of digital marketing.

In essence, Schema Markup not only provides quick wins through achieving rich results but also sets the stage for ongoing and agile content optimization as search evolves.

Interested in learning how you can apply Schema Markup to stay agile in search? Get started here.

The post The Evolving Role of Schema Markup: From Rich Results to AI Understanding appeared first on Schema App Solutions.

On November 27, 2023, Google released the new Profile Page structured data and Discussion Forum structured data. This comes after they announced the new Course Info structured data on November 15 and Vehicle Listing structured data on October 16. This holds to what John Mueller mentioned in the October 2023 Google Search News Update that some rich results would go away, and new ones would be introduced. Never before have four new rich results been announced in such a short time period.

Despite deprecating How-To structured data and reducing the frequency of FAQ rich results being shown, these 4 new rich results reflect a new investment in structured data from Google. And the reason for their investment in structured data is simple.

Structured data, also known as Schema Markup, helps search engines and machines (AI) understand and contextualize the content on your site to provide users with more relevant search results. As Google and Bing invest in generative AI search experiences driven by Large Language Models (LLMs), the Schema Markup on your site helps them reduce errors and delight their customers. Read more about the evolving role of Schema Markup and Knowledge Graphs.

Let’s dive deeper into these two new rich results to see how you can maximize them to stand out in search.

Profile page (ProfilePage) structured data

ProfilePage structured data is great for websites that have creators (person or organization) who share first-hand perspectives. It can be used to describe author profile pages on a news site, employee pages on a company website, and user profile pages on a forum or social media site. Google can use this information in features such as Perspectives and Discussions and Forums.

It can also be nested in other structured data features that have authors such as Article, Recipe, Discussion Forum and Q&A page.

By adding ProfilePage markup and the required/recommended properties to your page, Google can highlight the creator’s information, such as their name, follower count, content popularity, social media handles, and more, on the Search Engine Results Page (SERP).

But more importantly, Google can leverage this markup to disambiguate the creator. Even though search engines like Google use natural language processing models like BERT to gain a better understanding of your content, these models are still prone to errors.

When you use structured data to identify the creator as an entity and connect them to the articles or posts they’ve written, you are building your knowledge graph. Your knowledge graph showcases the relationships between the things on your site and helps search engines understand and contextualize who wrote your content with greater accuracy.

When search engines have an in-depth understanding of the person or organization that wrote the content on your site, it can also boost your E-E-A-T. Information such as follower count and the number of posts written are signals of experience, expertise, authority and trust.

On top of yielding rich results for your organization, adding ProfilePage markup to your site can also help improve the semantic understanding of your site.

The enhancement report and performance report for ProfilePage structured data is now available in Google Search Console.

Discussion forum (DiscussionForumPosting) structured data

Discussion forum structured data can be used to describe user-generated content on forum-style websites such as gaming forums. However, it shouldn’t be used for content primarily authored by the website publisher or their agents (i.e. article or blog posts with comments, product reviews provided by the users).

Forum sites that add this Schema Markup can help Google better identify the online discussions happening across the web and highlight them on features such as Perspectives and Discussions and Forums.

Discussion Forum Schema Markup is very similar to the existing Q&A Schema Markup. However, Discussion Forum markup should be used on pages where the responses to the thread are comments. For example, the threads on the subreddit ‘r/mildlyinteresting’ would be appropriate for Discussion Forum markup because the user is making a statement and expecting other users to comment on the thread.

Conversely, you should only use Q&A markup when the page has questions and answers. For example, the threads on Quora would be appropriate for QAPage markup because the user is posing a question on the page and expecting answers to be provided in the comments.

Unlike other structured data features, Google recommends web publishers provide the DiscussionForumPosting markup in Microdata or RDFa, instead of JSON-LD. This prevents publishers from having to duplicate large blocks of text within the markup. However, using JSON-LD will not impact your eligibility for this rich result.

The enhancement report and performance report for Discussion forum markup is also available on Google Search Console.

Read Google’s document for more information on how to use DiscussionForumPosting markup.

Conclusion

Based on the rich result changes we’ve seen this year, one thing’s for sure. Google can add new rich results as fast as they can take them away from us.

To thrive in this ever-changing environment, organizations need to be agile and ready to implement new or update their existing semantic Schema Markup markup to stay relevant and leading in search.

If you want to increase your visibility and relevance on search, we can help! Contact us to learn more about our scalable semantic Schema Markup solution.

The post Profile Page & Discussion Forum Rich Results Now Available on Google Search appeared first on Schema App Solutions.

Available only to verified car dealerships in the US or US territories, the new Vehicle Listing rich result allows car dealerships to display the vehicle inventory they have for sale on various Google surfaces such as Google Search and the dealership’s Google Business Profiles. People can also search, filter and easily access information about the vehicle’s availability, pricing, mileage and other key information.

The Vehicle Listing rich result is a great way for car dealerships to stand out in search and shorten the buyer journey. Pages with rich results typically see a higher click-through rate on the site.

In this article, we’ll discuss the pros and cons of implementing the new Vehicle Listing rich result through structured data compared to using a file feed and share how this announcement is an exciting followup to the overall Search update on structured data earlier this month.

How to achieve the Vehicle Listing rich result

Unlike most rich results that solely rely on structured data, the Vehicle Listing rich result can be achieved through two methods.

1. Adding Car structured data to your Vehicle Listing page.

As with any rich result on Google, you must markup your vehicle listing page with the required structured data properties and are encouraged to also markup the recommended structured data properties listed on the structured data feature guide.

It is, however, important to note that you can only markup content that is visible on your vehicle listing page.

For example, if you do not have any pricing information on your vehicle listing page, you cannot add the offers.price property to your markup. Doing so will make your listing page ineligible for the rich result.

2. Uploading a vehicle listings file feed to Google’s vehicle listings partner portal. 

You can upload your vehicle listing feed file to Google’s vehicle listings partner portal in CSV format to achieve a rich result.

Your feed file should contain the list of vehicles you want to show on Google as well as the required attributes about each vehicle listed in the Feed specification.

Some of the attributes in the Feed specification are optional. However, providing Google with more information will help improve their understanding of your listings to better match the searcher’s query.

Pros and Cons of Both Methods

If implemented properly, both methods should make your vehicle listing pages eligible for the Vehicle Listing rich result. However, there are pros and cons to each method.

Pros and Cons of adding Car structured data to the vehicle listing page

Pro: Easy to implement and maintain structured data markup on your website. 

Similar to the file feed, structured data is a data feed about the content on your website.

If you use a tool like the Schema App Highlighter, you can implement structured data to your vehicle listings page at scale. Your structured data will also automatically update whenever the content on your page changes. This is important because you’ll want to avoid schema drift and make sure the rich result is always showing the latest information like availability and pricing.

Con: It could take longer for Google to detect changes on your website. 

Unlike the uploaded feed file method, you’ll have to wait for Google to re-index your page before it can register any updates to your structured data. At Schema App, we advise our customers to re-index their pages right after making any structured data updates to their pages so that Google can detect the changes quickly.

Con: No 1:1 support from Google. 

Similar to other rich results, Google will have an enhancement report on Search Console for the Vehicle Listing rich result. The enhancement report will show any errors or invalid items for your vehicle listing rich results. But you’ll need to figure out what is causing these errors and rectify them yourself.

If you are using Schema App’s end-to-end Schema Markup solution, you’ll receive support from our customer success team whenever any structured data errors appear. Even if you don’t get the 1:1 support from Google, you can still get support from our team.

Pros and Cons of Uploading a vehicle listings file feed to Google’s vehicle listings partner portal

Pro: All inventory data in feed files is recognized by Google. 

However, you need to ensure your vehicle data conforms to the feed specification and Google’s policies and restrictions.

Pro: 1:1 support is available to address any issues with feed uploads at the vehicle listings partner portal.

This means that Google will provide your team with support through the vehicle listings partner portal. After you’ve submitted your vehicle listing file feed, you can also look at the Diagnostics page to see the full list of issues.

Pro: Feeds support more detailed properties for vehicle inventory. 

The file feed method will allow dealerships to include more information than the structured data method and some of the additional information can also be shown in the rich results on Google.

For example, information about the vehicle’s installed options and packages, fuel efficiency, legal disclaimer and vehicle history report link are additional information you can add through your file feed to further enhance your Vehicle Listing rich result.

Information about the vehicle’s EV range, CO2 emissions, fulfillment options, and link to the Monroney sticker are additional information you can add through your file feed to provide more context to Google about your product. This information will not be shown on Google.

Con: Maintaining the feed files can be challenging and time-consuming.

Google recommends dealerships upload the latest versions of their feed files every four hours to preserve the data freshness and to detect outages faster. If done manually, this process can be incredibly tedious and time-consuming. It is also yet another data platform that you’ll need to maintain, on top of having to maintain the information on your website.

That said, you can use both methods at the same time to provide Google with as much information about your vehicle listing pages. However, you’ll need to ensure the data is consistent across both the structured data on your site and the vehicle listings file feed. Otherwise, the information on the file feed would override the information on the structured data, even if the information on your structured data is accurate.

Adding structured data to your vehicle listing page is probably the easiest way for your car dealership to be eligible for these rich results, especially if you’re already adding structured data to your pages.

Structured data is not obsolete

Earlier this month, John Mueller, Search Advocate at Google, mentioned in a Google Search News update that they will continue to introduce new Types and some Types may go away over time.

This year, Google stopped using structured data for How-To rich results and changed the eligibility for the FAQ rich results to only be shown for well-known authoritative government and health sites. Many SEOs started to ask if there was value beyond rich results.

The answer is YES! Structured data provides you with the ability to help generative AI search engines understand and contextualize the content on your page and develop your knowledge graph.

The Vehicle Listing rich result is the first new rich result they’ve introduced awhile, albeit it is restricted only to US dealerships for now. This tells us that structured data isn’t obsolete and Google is still giving content publishers control over the information provided to their search engines.

As Mueller reiterated in his update, structured data (also known as Schema Markup) is a machine-readable code that you can add to your web pages which search engines can use to better understand the content.

Therefore, you should implement structured data primarily to help search engines clearly understand the content on your site and consider rich results an added value. That way, search engines can provide users accurate answers to queries like ‘How much does an Audi A6 cost’ and ‘white Toyota Camry for sale’ to drive more qualified traffic to your site.

Finally, Mueller concluded the section on structured data by recommending SEOs to use a solution that allows you to easily implement and manage the structured data on your site to save you time. This is exceptionally important for dealerships who want to maintain the accuracy of their structured data at all times. The last thing you’d want is for a potential customer to enquire about their dream car on your vehicle listing only to find out that the car is no longer available.

If you are a US-based car dealership looking to implement structured data on your site, we can help!

At Schema App, we help organizations leverage Schema Markup to inform search engines, achieve rich results and develop a reusable marketing knowledge graph. We implement and manage your Schema Markup programmatically through our semantic technology platform and high-touch support.

Get in touch with us today to learn more!

The post New Vehicle Listing Structured Data on Google appeared first on Schema App Solutions.

This past August, Google first removed How-To rich results on mobile. As a result, we saw a huge decline in clicks and impressions for How-To rich results across our customers. This updated announcement will undoubtedly remove all traffic and impressions from the rich result.

Why is this happening?

Prior to this change, content publishers would add HowTo Schema Markup to pages with instructional content that defined the steps needed to successfully complete a task. If appropriate, Google would then award the page with a How-To rich result that outlined the steps in the SERP.

However, we’ve often found How-To rich results to be somewhat controversial. On one hand, rich results were supposed to increase user engagement and drive click-through rates to a site. On the other hand, How-To rich results usually provided users with the answer directly on the SERP, resulting in a lower click-through rate. As such, How-To rich results were not as widely adopted as other rich results like product, review snippets and FAQ.

That said, How-To rich results still provided users with valuable information on the SERP and could help organizations improve their customer journey. So why is Google removing this rich result from the SERP?

In their announcement, Google mentioned that this was a continued effort on their end to ‘simplify search results’. This year, Google has made some significant changes to the SERP.

• They introduced Search Generative Experience (SGE) – their generative AI-powered search interface.
• They stopped awarding video rich results to pages that did not have a video as their main content.
• They stopped awarding FAQ rich results on both desktop and mobile for most websites and will only be showing FAQ rich results for well-known, authoritative government and health websites.
• They deprecated How-To rich results entirely from the SERP.

However, this begs the question: What does Google mean by simplifying search results?

Are they trying to declutter the search engine results page? They did reduce the visibility of video and FAQ rich results in the past few months, possibly because people were abusing them. However, the SERP is still littered with advertisements, making it tougher for users to identify the most appropriate result for their query.

Or could they be simplifying search results that SGE can also provide? As seen in SEO expert, Glenn Gabe’s tweet, the content from the same How-To was shown in SGE and in the first position in the SERP as a How-To rich result.

Ah, yes. But this is about the desktop version being removed. This is how it looked. See my listing below SGE (when HowTo was still there on desktop). pic.twitter.com/S1nqtYukNa

— Glenn Gabe (@glenngabe) September 14, 2023

One of the glowing features of SGE is its ability to provide users with answers and additional relevant information that they might need. If you search up how to perform a task, SGE can provide you the steps to perform the task successfully and links to a few pages that also capture those steps.

If you search for the top Italian restaurants, SGE can provide you with a list of restaurants together with a map showing where they’re located in proximity to you, and links to aggregator sites that also have a list of top Italian restaurants in your city. These are just two of the many examples of how SGE creates helpful experiences based on the wealth of information on the web.

At its core, Google’s mission is to organize the world’s information and make it universally accessible and useful. Rich results were first introduced to provide users with more useful information in search, help them make better decisions and find answers. It was also a way for Google to incentivize website owners to add structured data to their sites to help search engines understand the content on a page.

But with SGE providing the information in a simplified way, more rich results could be rendered obsolete in the coming years. That said, this does not mean that you should abandon adding Schema Markup to your site.

What should you do next?

Schema Markup helps machines understand and contextualize the content and information on your website.

Even though you will no longer achieve a How-To rich result on your page, you should still add Schema Markup to your pages to futureproof your organization for search.

This is a paradigm shift that requires SEOs to think about the value of Schema Markup beyond rich results. 

Over the past few years, search algorithms have shifted from lexical to semantic search. Instead of ranking pages based on keyword matching, search engines are ranking pages based on the relevance of the concepts and entities in the page’s content to the searcher’s query.

And how do you identify and define the entities on your website for search engines? You can define the entities on your website using Schema Markup.

By marking up the content on your site, you are helping search engines understand the concepts and entities on your website and providing them with contextual information about these entities. In return, they can better match your page to a query and ideally improve your ranking on search in the long run.

If you are interested in learning more about entities and semantic search, you can tune in to our recent webinar with Mike King or Schema Markup expert, Dave Ojeda’s latest interview on iPullRank’s Rankable podcast.

Generative AI search engines like SGE and the new Bing still face hallucination challenges resulting in inaccurate results. At Schema App, we’ve been advising our customers to think about the semantic value of Schema Markup.

Instead of implementing Schema Markup on a handful of pages for the sole purpose of achieving a rich result, you should implement Schema Markup across your site to define the entities and concepts on your site and link them to develop your very own marketing knowledge graph.

Knowledge graphs are a structured and organized information data layer that can help search engines to improve the accuracy of their answers and provide your organization with a control point to inform generative AI on your web content. Your marketing knowledge graph can also be reused for other AI initiatives.

As the SEO industry continues to see changes from Google and on search, organizations need to prepare to stay ahead of the competition. If you are looking to learn more about semantic Schema Markup, we can help.

Contact us to see how we can help your organization build a marketing knowledge graph and future proof your organization for AI search.

If you are a Schema App customer with concerns regarding the changes in rich results, please get in touch with your Customer Success Manager to see how we can support your organization through these changes.

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