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.

The Rich Results status reports identify any errors in your structured data that could be preventing content from being eligible for rich results in search engine page results. 

What has changed in the Google Search Console rich results status reports?

Google Search Console is not reporting on any new errors related to rich result eligibility. The recent change is specifically adding more information about errors it already checks for, including:

• Invalid attribute string length
• Invalid attribute enum value
• Invalid object
• Type conversion failed
• Out of numeric range

What’s exciting is that these additional details may not have been exposed in Google’s now deprecated Structured Data Testing Tool (SDTT), which has been replaced with the Schema Markup Validator (SMV). Google is helping to make these errors more actionable for SEOs, so that we can ensure that our structured data is valid and eligible for rich results.

That being said, eligibility does not mean that Google will always reward your content with a rich snippet, but you are setting your content up for the opportunity to be awarded with one. You’re doing all you can from a technical standpoint, but you should also focus on building more credibility with search engines to set your website up for long-term success. For example, by increasing your E-E-A-T (experience, expertise, authoritativeness, and trustworthiness), Google will start to understand how your website and business overall relates to entities in its knowledge graph. This streamlines Google’s ability to match a user’s search query to the most relevant content from your site!

We keep an eye on updates to Google’s structured data documentation so that you don’t have to! If you’re looking for help with your structured data implementation, we’d love to hear from you. We help you go beyond the fundamentals of search engine optimization, leveraging structured data to showcase your unique value in search. In a rapidly changing SEO environment, we introduce agility to your digital team, saving you time and resources for managing other aspects of your business portfolio. We deliver to your online business goals using our structured data expertise and advanced technology.

The post New Error Reporting in Google Search Console appeared first on Schema App Solutions.

The SMV is a replacement for Google’s Structured Data Testing Tool (SDTT). Google originally intended the Rich Results Testing Tool to replace the SDTT. However, Google received backlash about this change. They ultimately decided to incorporate validation tooling into Schema.org to support SEOs as they test their Structured Data.

Here is the official announcement from Schema.Org:

As agreed last year, Schema.org is the new home for the Structured Data validator previously known as the Structured Data Testing Tool (SDTT). It is now simpler to use, and available for testing. Schema.org will integrate feedback into its draft documentation and add it more explicitly to the Schema.org website for the next official release.

Structured Data Testing Tool Deprecation: A History

The SEO community was rocked in 2020 when Google announced that they would be deprecating the Structured Data Testing Tool and replacing this resource with the Rich Results Testing Tool, which had just come out of beta. However, the Rich Results Testing Tool has some drawbacks compared to the Structured Data Testing Tool.

The SDTT validates all schemas, whereas the Rich Results Testing Tool only supports a subset of Google-approved schemas and does not validate all types of rich results. SEOs were not happy; enter the SMV.

On August 9th, 2021, Google officially replaced the Structured Data Testing Tool with the Schema Markup Validator. The SDTT now redirects to a landing page to help you choose the right testing tool for your markup.

To learn more about how to test if your Schema Markup is working, our guide How Do I Know If My Schema Markup is Working is a helpful reference!

Schema Markup Validator Features

The Schema Markup Validator is based on the Google Structured Data Testing Tool. The service, provided by Google for the Schema.Org community, can validate Schema.org based Structured Data embedded in web pages, otherwise known as Schema Markup.

The SMV can:

• extract JSON-LD, RDFa, and Microdata markup,
• display a summary of the extracted Structured Data, and
• identify syntax mistakes in the markup.

Our Schema App solution will provide you access to an enterprise-level site-wide Schema Markup testing tool (aka the Schema App Analyzer) that can further help you analyze your Structured Data. If you use the Schema App Editor or Highlighter to generate your markup, both tools will allow you to test your markup with the Schema Markup Validator and the Rich Result Testing Tools before you publish your markup. 

The post What is the Schema Markup Validator (SMV) appeared first on Schema App Solutions.

We’ve compiled this ultimate guide to teach you all you need to know about LocalBusiness schema markup.

Adding LocalBusiness Schema Markup to your website can make you eligible for rich results, and these results can help you stand out in search, generating higher click-through rates, higher organic traffic, and more conversions.

What is LocalBusiness Schema?

When we talk about LocalBusiness schema, we’re really talking about Types and properties within the schema.org vocabulary that are used to categorize and define information about local businesses.

The LocalBusiness Schema Type, or one of its associated Types, should typically be used to markup your homepage. Adding LocalBusiness markup to your website translates your human-readable content into the machine-readable language of JSON-LD.

Within the schema.org vocabulary, the LocalBusiness Type is a subtype of both Organization and Place, so it inherits the properties of both these Types.

Schema.org defines LocalBusiness as “A particular physical business or branch of an organization. Examples of LocalBusiness include a restaurant, a particular branch of a restaurant chain, a branch of a bank, a medical practice, a club, a bowling alley, etc.” You’ll notice that the definition lists many more specific kinds of local businesses.

Much like this list, the LocalBusiness Type contains a wide variety of subtypes that can be used to define your business more specifically. The full list of schema.org Types can be found in their Full Hierarchy, where indentations denote a subtype relationship in the hierarchy of terms.

We encourage you to check out schema.org’s definitions for any Types that are relevant to your business, that way you can be sure you’re using the most accurate Type.

What kind of Local Business Organization Are You?

The next step is to identify what kind of business you are optimizing.

As you can see from the list above, schema.org provides you with a lot of options. When choosing a type, you want to be as specific as possible. If nothing fits well, don’t worry. Pick a more generic type, like LocalBusiness or Organization, and use the sameAS property to connect to a Wikipedia or Wikidata entry that further defines your business type.

 TIP! Both Wikipedia and Wikidata can help you specify your business, but if given the option, link to Wikidata. Wikidata has been optimized for machines, while Wikipedia is meant for human readers.

The most general type of business is an Organization.

Organization has the following types:

• Airline
• Consortium
• Corporation
• EducationalOrganization (more specific types include College, University, Elementary School, High school, Middle School, Preschool, School)
• FundingScheme
• GovernmentOrganization
• LibrarySystem
• LocalBusiness (*see more below)
• MedicalOrganization (more specific types include Dentist, Hospital, Pharmacy, Physician)
• NGO
• NewsMediaOrganization
• PerformingGroup (more specific types include Dance group, Music Group, Theatre Group)
• Project (more specific types include funding Agency, Research Project)
• SportsOrganization (more specific types include Sports Team)
• WorkersUnion

Local Business has the following types:

• AnimalShelter
• ArchiveOrganization
• AutomotiveBusiness (more specific types include AutoBodyShop, AutoDealer, AutoPartsStory, AutoRental, AutoRepair, AutoWash, GasStation, MotorcycleDealer, MotorcycleRepair)
• ChildCare
• Dentist
• DryCleaningOrLaundry
• EmergencyService (more specific types include FireStation, Hospital, PoliceStation)
• EmploymentAgency
• EntertainmentBusiness (more specific types include AdultEntertainment, AmusementPark, ArtGallery, Casino, ComedyClud, MovieTheater, NightClub)
• FinancialService (more specific types include AccountingService, AutomatedTeller, BankOrCreditUnion, InsuranceAgency)
• FoodEstablishment (more specific types include Bakery, BarOrPub, Brewery, CafeOrCoffeeShop, Distillery, FastFoodRestaurant, IceCreamShop, Restaurant, Winery)
• GovernmentOffice (more specific types include PostOffice)
• HealthAndBeautyBusiness (more specific types include BeautySalon, DaySpa, HairSalon, HealthClub, NailSalon, TattooParlor)
• HomeAndConstructionBusiness (more specific types include Electrician, GeneralContractor, HVACBusiness, HousePainter, Locksmith, MovingCompany, Plumber, RoofingContractor)
• InternetCafe
• LegalService (more specific types include Attorney, Notary)
• Library
• LodgingBusiness (more specific types include BedAndBreakfast, Campground, Hostel, Hotel, Motel, Resort)
• MedicalBusiness (more specific types include CommunityHealth, Dentist, Dermatology, DietNutrition, Emergency, Geriatric, Gynecologic, MedicalClinic (COVIDTestingFacility), Midwifery, Nursing, Obstetric, Oncologic, Optician, Optometric, Otolaryngologic, Pediatric, Pharmacy, Physician, Physiotherapy, PlasticSurgery, Podiatric, PrimaryCare, Psychiatric, PublicHealth)
• ProfessionalService
• RadioStation
• RealEstateAgent
• RecyclingCenter
• SelfStorage
• ShoppingCenter
• SportsActivityLocation (more specific types include BowlingAlley, ExerciseGym, GolfCourse, HealthClub, PublicSwimmingPool, SkiResoirt, SportsClude, StatiumOrArena, TennisComplex)
• Store (more specific types include AutoPartsStore, BikeStore, BookStore, ClothingStore, ComputerStore, ConvenienceStore, DepartmentStore, ElectronicStore, Florist, FurnitureStore, GardenStore, GroceryStore, HardwareStore, HobbyShop, HomeGoodsStore, JewleryStore, LiquorStore, MensClothingStore, MobilePhoneStore, MovieRentalStore, MusicStore, OfficeEquipmentStore, OutletStore, PawnShop, PetStore, ShoeStore, SportingGoodsStore, TireShop, ToyStore, WhoesaleStore)
• TelevisionStation
• TouristInformationCenter
• TravelAgency

Required and Recommended Properties for Local Business Structured Data

Google maintains documentation explaining exactly what’s required for “LocalBusiness” markup to be eligible for rich results within search.

We’ve captured the required fields below, as listed when this post was published. You must populate the required properties for your content to be eligible for display as a rich result. Recommended properties add more information to your structured data, which could provide a better user experience.

https://Schema.org/LocalBusiness

 TIP For more information about adding Rating and Review markup, check out our tutorial Creating “Review” Schema Markup Using the Schema App Editor.

The following types (GeoCoordinates, OpeningHoursSpecification) were listed above as being recommended by Google. However, adding these to your markup can make rich results more robust. These recommended types have their own required and recommended properties:

https://Schema.org/GeoCoordinates

 TIP! Don’t know your business’ geo coordinates? They can be found by searching for the associated address in Google Maps. The URL of the location will have both the latitudinal and longitudinal values.

https://Schema.org/OpeningHoursSpecification

 TIP If certain days have different opening hours, create a separate OpeningHoursSpecification data item for those days.

Google’s documentation also lists some types that are specific to the FoodEstablishment type, or it’s more specific subtypes (e.g Bakery; BarOrPub; Restaurant). These are:

https://Schema.org/FoodEstablishment

As you can tell from the number of properties at your disposal, there’s a lot you can leverage with your LocalBusiness schema markup. Wondering how all of it might fit together? This diagram illustrates an example of LocalBusiness markup in the form of a graph. It shows all the required properties (in yellow), and some of the more common recommended properties (in blue).

 TIP For the most current guidelines on required and recommended fields, reference the Google documentation on Local Business markup.

Preparing Your Local Business Schema Markup

Before we start creating your schema markup, you’ll need to gather the information found in the table below. This strategy piece will be the most time-consuming part of your LocalBusiness markup, but it makes the process more efficient in the long run.

Examples of the various fields have been provided as well as additional guidance to help you complete the list. Note: the homepage of the business is usually what you markup as the LocalBusiness.

We also have a handy Google Sheets template that you can use to do this prep work for your markup.

By defining objects on your homepage as unique entities using schema markup, you are effectively connecting them to a search engine’s knowledge graph. This adds context and relevance to your site content, supporting your E-E-A-T and establishing relationships between your local business and other defined entities across the Web.

How to Add Schema Markup If You Have Two or More Locations

If your business has multiple locations, there are a few different ways you can mark them up. Your strategy should be informed by the architecture of your site.

Under the circumstance that the business defined on the homepage DOES NOT have an address, use the Organization type.

1. If the other locations (and their addresses) are also listed on the homepage, select the Organization’s subOrganization property, and create LocalBusiness markup for each of the locations.
2. If each location has its own page, create a separate LocalBusiness data item for each location page. Then, from each LocalBusiness data item, use either the parentOrganization or branchOf property to connect back to the main Organization data item.

If the business defined on the homepage DOES have an address and could be considered a “Headquarters”, use LocalBusiness or one of the more specific subtypes.

1. If the other locations (and their addresses) are also listed on the homepage, select the main LocalBusiness’s subOrganization property, and create LocalBusiness markup for each of the subsidiary locations.
2. If each subsidiary location has its own page, create a separate LocalBusiness data item for each location page. Then, from each subsidiary LocalBusiness data item, use either the parentOrganization or branchOf property to connect back to the main LocalBusiness data item.

If you don’t feel the subOrganization, parentOrganization or branchOf properties adequately describe the relationship between your entities, use the Schema Paths tool to see all the properties that are available to the types you’re connecting.

How to Create Local Business Schema Markup

Step One: Add Required Properties

Add the required schema.org properties for LocalBusiness 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.

Learn how to create LocalBusiness schema markup using Schema App with our how-to tutorial.

Step Two: Follow Google’s Structured Data Guidelines

Check that your schema markup follows Google’s structured data guidelines. 

Step Three: Deploy your Markup

If you are satisfied with your markup, ensure that your integration method is set up, and the markup will deploy to your page. Google recommends using JSON-LD, which is also our favourite format for deployment.

Step Four: Test your Markup

Test that your schema markup is working using Google’s Rich Results Testing Tool and the Schema Markup Validator, which has officially replaced Google’s Structured Data Testing Tool. Read more about this change in our news post here.

How to Check Your Local Business Schema Markup

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.

Rich Results Preview Testing

To validate and preview your structured data, use Google’s Rich Result Test. This tool will indicate if your page is eligible for rich results. Please note that Google’s Rich Result Test is only valid for certain supported rich result types.

Tips to Manage Existing Schema Markup

Schema markup is constantly evolving and as such, it is not something you can simply set and forget. It also has limitless possibilities beyond just your homepage markup. We will provide you with some tips to manage your existing markup and also leverage new opportunities.

1. Maintain your LocalBusiness Schema Markup

It’s important to update your schema markup based on content changes on your site and updates to Google’s documentation.

Google has recently begun posting all changes regarding structured data on their “What’s new” page. Keeping an eye on this will help you stay on top of any changes.

Another great resource is Google’s Webmasters Blog. You can subscribe via email and get all the latest news right in your inbox.

2. Expand your Local Business Schema Markup

You’ve done your homepage markup and are now wondering: What next? That’s a great question!

Here is a summary of schema types you may want to use for other common pages on your website. To make things even simpler, you’ll find links to tutorials further defining each of these.

Contact Us

If you have a “Contact Us” page on your website, you can create a ContactPage data item and connect the various types of locations and phone numbers as ContactPoints.

For example, if you have a sales line and a technical support line, you can have these as Contact Point data items, linked to the Contact Page data item via the “main entity” property.

Learn how to mark up business contact info here.

About Us

For your About Us page, you can create an AboutPage data item. You will see that there are no required or recommended fields for this data item. That being said, you can still fill out the relevant fields. We recommend linking the homepage data item using the about property.

Based on the kind of information you have on your About page, you can use as many or as little properties as you want to describe this data item.

Blog

If you have a blog and blog posts on your site you will want to add Blog and BlogPosting markup. This can be done via a plugin, such as our WordPress plugin, manually via our Schema App Editor or at scale (lots of pages) and dynamically through our Schema App Highlighter. BlogPosting data items are often connected back to the LocalBusiness using the about, author, publisher, or sourceOrganization properties.

News

If you have news articles on your website you can add NewsArticle markup with a plugin or with our tool. Check out this video which shows how to add article markup via the Schema App Editor. Properties to connect NewsArticle markup back to the LocalBusiness are similar to those used for BlogPosting.

Product

If you have products on your website you could be eligible for rich results if you apply the Product schema markup correctly. If you are on Shopify, BigCommerce or WooCommerce, you can install our easy to use plugin which will automatically markup your product pages.

Additionally, we have a highlighter tool, which is part of our premium subscription which can help you create markup and apply it across all our pages. Check out this great tutorial to learn more about product markup with our highlighter tool. It’s best to connect Products back to your LocalBusiness via the manufacturer or brand properties provided they appropriately define the relationship.

 TIP Markup you create for other pages should always connect back to your homepage in some way since it’s the heart of the knowledge graph of your content.

Frequently Asked Questions about LocalBusiness Schema Markup

Is it better to use LocalBusiness or Organization markup?

Use the LocalBusiness type (or one of its subtypes) if the business is a brick-and-mortar facility that has address information publicly available. If the business doesn’t have an address associated with it—for example it’s an eCommerce business or a service provider that does house calls—the Organization type may be the better choice.

Both of these types are eligible for rich results within search, but LocalBusiness rich results are more robust.

If you’re still unsure which type to use, ask yourself the following questions:

1. Does the business have a physical location people would walk into? If the answer is no, you should probably use the Organization type.
2. Is there a schema.org type/class that fits well? If yes, use that type. If not, use a broader type, and provide a more specific definition by linking to Wikipedia or Wikidata by way of the additionalType or sameAs property.

What is a multi-type entity and when should I use it?

A multi-type entity (MTE) is one entity that is defined using multiple schema.org types (though usually not more than two). Creating a multi-type data item allows you to utilize all the properties available to both types.

You may want to create a multi-type entity for your business if, for example, you’re using the Physician LocalBusiness type and want to add alumni information that’s only available to the Person type. To resolve this, your local business would be typed as both Physician and Person.

Can I use external ratings and reviews (e.g. Google or Yelp) to add Review or AggregateRating markup to my Local Business?

AggregateRating and Review markup can only be created if the content is visible on the page. According to Google’s documentation, this markup is only eligible for review snippet rich results if the information is coming from a third-party application to show impartiality.

What’s more, while the LocalBusiness type is eligible for rich results with AggregateRating and Review markup, the Organization type is only eligible for rich results with Review markup.

For more information about how to create review markup, see Creating “Review” Schema Markup Using the Schema App Editor.

How should I mark up an action?

Google no longer supports potentialAction markup but instead states: If you want to help users to make a reservation or place an order directly in Search results, you can use the Maps Booking API to enable bookings, payments, and other actions. If you’re interested in creating SearchAction markup to be eligible for the Sitelinks Searchbox feature, see How to create Sitelinks Searchbox markup.

There are many benefits to LocalBusiness structured data markup. The more robust and comprehensive your schema markup, the better search engines can match users with the products and services being offered.

The information included in your markup will also be used to enhance your Google Knowledge Panel and enhanced search features, which support your credibility and E-E-A-T as Google crawls your web pages.

We’ve helped businesses of all shapes and sizes to stand out from the competition in search, across multiple industries. Read more about their experiences with Schema App in our case studies, or if you’re ready to get started with your schema markup reach out to our technical experts today! We’d love to hear from you.

The post Ultimate How-to Guide for LocalBusiness Schema Markup appeared first on Schema App Solutions.

If you don’t yet have this type of content on your website, we recommend adding it so you can leverage the power of schema markup.

Before You Implement Review Schema Markup

As you scroll through search engine page results, you can visibly see which websites are utilizing the power of structured data and which are not. Star ratings and reviews help your brand to stand out from the competition by showing additional information about your organization, products or services.

Review snippets are short excerpts of a review or rating from a review website. When Google finds valid reviews or ratings structured data markup, your content will be eligible to show a rich result that includes stars and other summary information from the markup.

These reviews could also show in your Google Knowledge Panel.

Showcase your credibility in search by letting customers and users write reviews. Then, mark up these reviews with Review structured data. Not only will your website be eligible for enhanced Google features in search results, but search engines will better understand and contextualize your content.

Building Your Knowledge Graph With Structured Data

When you mark up your content with structured data, you are also creating connections between your data and a search engine’s knowledge graph. As you define objects as distinct entities with their own properties and relationships to other entities, you can link your entities to Google’s Knowledge Graph through structured data like schema markup.

Knowledge graphs represent the linking of information and data across the Web, providing context for search engines as they crawl your site.

Beyond rich results, structured data markup can also help you enhance your Google Knowledge Panel. Knowledge panels are the information boxes that appear in search engine page results. They pull this information from markup on your website or other sources that search engines trust like Wikipedia.

Schema markup gives you more control over how your content appears in search results, and in your Google Knowledge Panel.

Currently, Google supports ratings for the following schema classes:

• Book
• Course
• Event
• Local business
• Movie
• Product
• Recipe
• Software App

Google also supports reviews for the following schema.org classes:

• CreativeWorkSeason
• CreativeWorkSeries
• Episode
• Game
• MediaObject
• MusicPlaylist
• MusicRecording
• Organization

Required and Recommended Properties

Google maintains documentation to explain exactly what is required for “Review Snippet” markup. We’ve captured the required fields below, as listed when this post was published. You must populate the required properties for your content to be eligible for display as a rich result. Recommended properties add more information to your structured data, which could provide a better user experience.

https://schema.org/Review

https://schema.org/AggregateRating

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

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

How to Create Review Structured Data:

Step One: Create a Review Data Item

• In the Schema App Editor, use the class tree to search for “Review”. Once selected, click “Create”.
• Assign the data item a name and a URL.
• Once created, the page will refresh and the data item will be in Edit mode.
• You are required to have an author, item reviewed, and review rating. Date published is only recommended.

Step Two: Create a Person/Organization Data Item

• Type the name of the person or organization who wrote the review into the “author” field and click “Convert to Data Item”.
• You’ll be prompted to add the URL of this new data item, as well as its schema.org property type. Make sure to adjust the type depending on whether an individual wrote the review (i.e. person) or if it was provided by an organization.
• Once selected, the Editor automatically appends a “#anchor” tag to the end of the URL.
• The base URL should always reflect the page on the site where the Review resides.
• Once you have the correct URL, anchor tag, and property type, click “Create”.

Additional Fields

If there are additional required and recommended fields for this new data item, make sure to include them here.

Step Three: Create an Item Reviewed Data Item

• If you’re creating a review data item from within a product data item, then you do not need to have the item reviewed field populated. This is an example of a nested review. We recommend making the connection between a product and review in this way.

Step Four: Create a Review Rating Data Item

• Type a name for the “review rating” and click “Convert to Data Item”.
• When there, double check that the URL is pointing to the page the review is on and that the #anchor is correct.
• Click “Create”.
• The only required field is the review rating. If the rating is not on a 1-5 scale, then also popular the best and worst rating fields.
• Click “Done”.

Other fields to populate

• If you have a publish date listed for your reviews, use the calendar for the “date published” field.
• Other fields to popular include: review body, publisher, image, etc. These will depend on the content that you have on your site.

How to Create Aggregate Rating Schema Markup:

If you have more than one review, Google recommends you create an Aggregate Rating.

1. Create an “AggregateRating” data item in the Schema App Editor. Use the class tree to search for “Aggregate Rating”. Once selected, click “Create”.
2. Double-check that the URL reflects where the rating is shown on your site and that the anchor tag is correct.
3. Now you will have the required and recommended fields. In this case, no further data items are needed as they are easily populated with integers.
4. For the item reviewed field, simply create a new data item for whatever is being rated and reviewed.

Nested Data Items vs Singular Data Items

You can create an aggregate rating data item from within your “thing” data item for the item being reviewed. In this case, you wouldn’t need to populate the item reviewed field, just as was the case with the review markup above.

The connection between the “thing” being reviewed and its reviews and aggregate rating needs to occur in only one direction. This is why we suggest you nest the reviews and aggregate rating within the “thing” data item.

Watch our Review Schema Markup video tutorial that walks you through your review schema markup process. We hope you find it helpful!

For more information on how to create Review Schema Markup, see our Knowledge Base support article.

Testing Your Review Schema Markup

Schema Markup Validator

Export the JSON-LD and run it through the Schema Markup Validator (SMV) to view any errors or warnings. Again, this serves as an alert to either correct the markup or to highlight gaps in the content. Many SEOs preferred Google’s Structured Data Testing Tool (SDTT), as the SMV only shows errors in schema markup syntax and not rich result eligibility; however, Google officially deprecated the SDTT and officially replaced it with the SMV on August 9th, 2021.

Rich Results Preview Testing

To validate and preview your structured data, use Google’s Rich Result Test. This tool will indicate if your page is eligible for rich results. Please note that Google’s Rich Result Test is only valid for certain supported rich result types.

Deploying Your Review Schema Markup

Depending on your content management system, there are many deployment options to ensure robust, comprehensive, and error-free schema markup.

If you are a Schema App customer, explore your deployment options in the Integrations menu of the Schema App platform. We’ve grouped different methods of deployment into the following categories:

1 – Plugin / Add-ons:

• BigCommerce
• WordPress & WooCommerce
• Shopify
• HubSpot
• Drupal

2 – Add a tag once and you’re done:

• Google Tag Manager
• Tealium

3 – APIs:

• JavaScript
• Squarespace

If you didn’t see the integration option you were looking for, get in touch! We can deploy markup to any content and any content management system.

Frequently Asked Questions

How do you implement Review Schema Markup on a website?

1. You should only mark up content visible on your website. Start with exploring Google’s Search Gallery to find rich result opportunities that align with your online business goals.
2. Mark up your content with required schema.org properties, as well as any recommended properties that are applicable for your content and can add more depth to your markup.
3. Validate your schema markup using Google’s Rich Results test.

How do you add Review Schema Markup to a page with multiple reviews?

1. If you have an item reviewed by more than one person, we recommend using AggregateRating schema markup.
2. Clearly refer to a specific product or service by nesting your review within the markup of another schema.org type, or by using a schema.org type as a value for the itemReviewed property.
3. Make sure that users can clearly see the marked-up reviews and ratings on the page.
4. Add the required schema.org properties to your data item, and any recommended properties that will make your schema markup more robust, where applicable.
5. Validate your schema markup using Google’s Rich Results test.

With Schema App, you have the opportunity to work with schema markup experts who can help you develop a customized structured data strategy, maximizing results from your markup!

The post How to Create “Review” Schema Markup appeared first on Schema App Solutions.

If you don’t yet have this type of content on your website, we recommend adding it so you can leverage the power of Schema Markup!

It’s important to mention that you should only use “FAQPage” markup if your page has a list of questions with answers. If your page has a single question and users can submit alternative answers, use “QAPage” instead.

We’ve seen FAQPage Structured Data Markup drive more clicks, impressions, and user engagement to customers, such as SAP and Keen Footwear. Marking up your content with FAQPage Structured Data will not only make your content eligible for enhanced Google features in search results, but you are helping search engines to better understand and contextualize the data on your website.

Required and Recommended Properties for FAQPage Schema Markup

Google maintains documentation to explain exactly what is required for “FAQPage” Structured Data Markup. We’ve captured the required fields below. You must populate the required properties for your content to be eligible for display as a rich result. Recommended properties add more information to your structured data, which could provide a better user experience.

To mark up the FAQ page, start by creating a data item for the page itself. Then you’ll need to create an embedded data item for every Question, each of which will have its own embedded data item for its Answer.

FAQPage

Question

Answer

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

We created the following visual to help conceptualize the structure of a FAQPage markup.

How to Create FAQPage Schema Markup

To help you get started, we put together the fundamental steps for creating FAQPage Schema Markup:

Step One: Required Properties

Add the required schema.org properties for FAQPage 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.

Step Two: Structured Data Guidelines

Check that your markup follows Google’s structured data guidelines

Step Three: Deployment

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

Step Four: Validation

Test that your Schema Markup is working using Google’s Rich Results Testing Tool and the Schema Markup Validator, which has officially replaced Google’s Structured Data Testing Tool. Read more about this change in our news post here.

This short video demonstrates the basics of creating FAQPage Schema Markup using the Schema App Editor:

Learn how to create FAQPage Schema Markup using Schema App with our how-to tutorial here.

Testing your FAQPage Schema Markup

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.

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.

Frequently Asked Questions about FAQPage Schema Markup

What is FAQ Schema Markup?

FAQPage Schema Markup indicates that your page has a section with frequently asked questions (FAQs) and answers. When you mark up those questions and answers with structured data, your content will be eligible for a collapsible menu under your search engine page result with the question, that when clicked on will reveal the answer.

What are the benefits of FAQ Schema Markup?

FAQPage Schema Markup increases your website’s visibility in search results both through enhanced Google search features like rich results, and by showing a wider variety of keywords thanks to the content in your FAQs. This is an example of how rich result opportunities should inform your content strategy, as the more SEO keyphrases that you’d like to rank for can be included in your FAQs where it makes sense to do so.

Do you see opportunities on your website for FAQPage Schema Markup? If you don’t already have a section of your website for frequently asked questions, we recommend adding one and marking it up with structured data. It’s a great way to boost your search engine optimization performance! If you need help getting started, don’t hesitate to get in touch.

The post How to Create “FAQPage” Schema Markup appeared first on Schema App Solutions.

By marking up your how-to instructions with HowTo structured data, not only will your content be eligible for enhanced Google features in search results but search engines will be able to better match your data to a user’s search query.

Required and Recommended Properties for HowTo Schema Markup

Google maintains documentation to explain exactly what is required for How-To markup. We’ve captured the required and recommended fields below. You must include the required properties for your content to be eligible for display as a rich result. Recommended properties add more information to your structured data, which could provide a better user experience.

HowTo

https://schema.org/HowTo

HowToStep

https://schema.org/HowToStep

HowToDirection

https://schema.org/HowToDirection

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

How to Create HowTo Schema Markup

To help you get started, we put together the fundamental steps for creating HowTo schema markup:

Step One: Add the required properties for HowTo Schema Markup

Add the required schema.org properties for HowTo Schema 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.

Step Two: Review your HowTo Schema Markup to ensure it follows Google’s Structured Data Guidelines

Check that your markup follows Google’s structured data guidelines

Step Three: Deploy your HowTo Schema Markup to the relevant pages

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

Step Four: Validate your page to make sure the Schema Markup is working

Test that your schema markup is working using Google’s Rich Results Testing Tool and the Schema Markup Validator, which has officially replaced Google’s Structured Data Testing Tool. Read more about this change in our news post here.

This short video demonstrates the basics of creating HowTo schema markup using the Schema App Editor.

Learn how to create HowTo schema markup using Schema App with our how-to tutorial here.

Testing Your HowTo Schema Markup

Schema Markup Validator

The Schema Markup Validator (SMV) was modeled 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.

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.

Frequently Asked Questions about HowTo Schema Markup

What is HowTo schema markup?

HowTo schema markup is code you can add to the backend of your website, explaining to search engines what your content is and what information you would like displayed in search results. When HowTo content on your website is properly marked up with structured data, you will be eligible for Google search enhancements like rich results, helping your content to engage with users before they even enter your website.

When should you use HowTo schema markup?

You should only mark up content that is visible on your web pages. If you have how-to content, or see an opportunity to add this content to your website, marking it up with HowTo structured data will make that content eligible for Google search enhancements like rich results. Additionally, you will be improving your E-E-A-T by demonstrating to Google your expertise in that subject matter.

Do you see opportunities for how-to content on your website? Structured data not only enhances your existing content, but SEO experts use rich result opportunities to actually inform their content strategy. If you’re looking for a way to stand out in search results and take control of what information is being shown about your brand and website, get in touch! We’d love to help.

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

Assuming you want to know both, this article breaks down which tools to use, and how to use them.

Schema Markup doesn’t stop with deployment. By properly defining entities in your content through structured data like Schema Markup, these entities can be linked to a search engine’s knowledge graph. Knowledge graphs connect information from all across the web, and structured data helps search engines like Google contextualize your content to better match your site with search queries.

Your content can also be eligible for rich results in search, which can help your brand stand out from the competition.

For example, for two eCommerce stores selling the same product, if one displays the price, customer ratings, and reviews and the other does not, our eyes are typically drawn to the differences. This additional information can all be included in your Schema Markup as long as you follow Google’s structured data guidelines.

Test that your Schema Markup is working using the following methods so that your website doesn’t miss out on the opportunities of structured data.

Has my Schema Markup Been Successfully Deployed?

The first step is to make sure that your markup is on the page.

If you are copying and pasting the JSON-LD into the page, you can simply right-click on the web page, view the source and search within the elements tab for “LD+JSON” to see if the code is there.

If you are using Schema App or Google Tag Manager to deploy your code, it’s easier to use Google’s Rich Result Testing Tool for rich result eligibility and the Schema Markup Validator (SMV) for any errors in your Schema Markup syntax.

Alternatively, you can wait and check within Google Search Console to report on the rich results or features tied to certain structured data. This could take anywhere from a few days up to a month, depending on how regularly Google crawls your site.

For websites that populate the Schema Markup dynamically, e.g. using JavaScript, then only the Schema Markup Validator will show these results.

Dynamic Schema Markup requires the structured data testing tool to load the HTML and process JavaScript, something Google has supported for a couple of years.

If you create Schema Markup using inline HTML (e.g. microdata, RDFa) or the JSON-LD is created Server side, all tools should work.

Are There Any Errors in the Implementation?

It’s very important that you check your Schema Markup to ensure it is working hard behind the scenes for your website. While you are waiting for the Google Search Console results to appear, there are a variety of tools that allow you to check for any errors or warnings that your markup may be generating.

Schema Markup Validator (SMV)

The Schema Markup Validator went live May 2021, and officially replaced Google’s Structured Data Testing Tool on August 9th, 2021. Google originally intended the Rich Results Testing Tool to replace the SDTT, but following backlash about this change Google decided to incorporate validation tooling into Schema.Org to support SEOs as they test their structured data markup.

The Schema Markup Validator is based on the Google Structured Data Testing Tool and is essentially a Schema Markup checker. The service, provided by Google for the Schema.Org community, can validate Schema.Org based structured data embedded in web pages, otherwise known as Schema Markup.

The SMV has the ability to extract JSON-LD, RDFa, and Microdata markup, display a summary of the extracted structured data, and identify syntax mistakes in the markup.

Rich Results Testing Tool (RRTT)

The Rich Results Testing Tool supports all rich result features, and is most closely aligned with Google Search Console. This tool lists all the rich results one page may be eligible for, and—in some instances—shows you a preview of how your rich result could appear in the SERP.

It’s important to remember that the Rich Results Testing Tool only validates schema.org Types that are eligible for rich results in search. If you’re using Types that aren’t eligible for rich results, view the “raw” JSON-LD, to ensure it’s being crawled, but that’s it.

If you want a comprehensive view of all markup on a page, rather than only the types that are eligible for rich results, this tool is best used in tandem with other structured data testing tools.

Schema App’s Analyzer

The Schema App Analyzer validates markup site-wide, for up to 10K pages. Run the Analyzer on any site and discover JSON-LD, RDFa and microdata, even when loaded dynamically.

Once the site has been crawled, the Analyzer provides a comprehensive health report in the form of data visualization and a list of “Items Analyzed” by Type. Clicking “Show Details” for a specific item presents a list of each URL containing that item and a breakdown of any errors or warnings.

Since this tool validates schema.org syntax, it follows more stringent rules. These can guide your Schema Markup beyond just the requirements of Google features.

The Schema App Analyzer identifies markup that Google won’t be able to read as a result of site speed issues. If you see errors or warnings about “missing” properties that definitely exist on your page, you should investigate site speed to ensure all your markup is visible to search engine crawlers.

Ultimately, this tool provides a micro and macro view of the overall health of your markup, pointing out what to revisit for enhanced performance.

The Analyzer is available to all Schema App subscribers from Pro through to Enterprise.

Note: Be on the lookout for imminent changes to the Analyzer, as we are readying reports to provide new ways of understanding your Schema Markup:

• Schema Markup by Type
• Schema Markup by Error / Warning
• Schema Markup by Page Path
• Schema Markup by Google Feature

Moreover, an updated user flow and historical view of your data will show how your markup is trending over time.

Schema App’s Structured Data Tester 

The Schema App Structured Data Tester can be found in the “Maintenance” tab in Schema App. Enter any URL, and this tool will display the Schema Markup found on that page. It is the only testing tool that displays dynamic schema.org data and does not cache the results.

Having a testing tool integrated within Schema App improves your markup workflow so you don’t always have to go to another site to check your markup.

We recommend getting into the habit of using at least one of these tools when authoring your markup. It not only confirms whether it’s deployed correctly but also gives you an idea of the scope of your markup, allowing you to assess its accuracy.

Google Search Console

Google Search Console is an excellent tool for monitoring both whether your markup is valid, and the impact it’s having on site performance. For more information about using Google Search Console, check out our article How to Measure the Impact of Structured Data.

Frequently Asked Questions About Testing Schema Markup

How do I know if my site has Schema Markup?

There are several tools you can use to know if your site has Schema Markup.

Google Search Console provides insights into how Googlebot views your website. Within Google Search Console, you can check the “Enhancements” section to see if Google has detected and processed your structured data.

Schema.org Validator allows you to input a URL and check for Schema Markup. It provides a detailed report of the structured data found on your webpage.

Rich Results Testing Tool is another valuable tool provided by Google for checking and validating structured data on a webpage, specifically focusing on how it may impact search results. This tool will state whether the markup is valid to create an eligible rich result and whether any opportunities exist to improve the item’s appearance. From there, it also states whether there are any errors in the markup to identify what needs to be addressed to create a valid instance. This is particularly useful for websites looking to visually enhance their appearance in search using structured data.

Before you add custom schema markup to your website, it is important to review your site for any existing markup. Many SEO plugins like Yoast tend to automatically inject Schema Markup on your site. Though convenient, the markup added by these plugins tends to be generic and less customizable.

Therefore, we recommend checking to see if your site has any existing Schema Markup before you go ahead and implement custom Schema Markup that accurately describes your website content. That way, you can remove any existing markup added by any plugins and prevent duplicate markup issues.

Where do I start with Schema Markup?

When you decide to implement Schema Markup on a website, first identify what pages you want to optimize. From there, decide what part of the schema.org vocabulary will achieve the best organic search results and most Google rich results. Start with developing your schema strategy using our guide: How to Develop a Schema Markup Strategy for a Website.

Then, move to authoring and deployment. Schema App makes Schema Markup implementation and validation easy. Our expert tools help you mark up your content with structured data—no coding required on your part! Validate your Schema Markup using the tips and tools we mentioned in this article.

How do I find errors in my Schema Markup?

The first step is to make sure that your markup is on the page using the Schema Markup Validator (SMV). You can also use Google Search Console to report on the rich results or features tied to certain structured data. Another powerful tool is Schema App’s Analyzer, which validates markup side-wide for up to 10K pages.

What is the purpose of Schema Markup?

Adding Schema Markup to existing pages helps search engines find information and present it to users through engaging rich results. Schema Markup is code added to your website that translates content into a language search engines understand. This advanced SEO strategy can increase your E-E-A-T, improve your brand findability, and help your online business drive more quality organic traffic to your website.

There are plenty of helpful tools out there to gauge whether your markup is working. We have experience with testing Schema Markup for enterprise organizations and have created testing tools for testing at scale. We help you go beyond the fundamentals of search engine optimization, leveraging structured data to showcase your unique value in search.

In a rapidly changing SEO environment, we introduce agility to your digital team, saving you time and resources for managing other aspects of your business. We deliver your online business goals using our structured data expertise and advanced technology.

The post Schema Markup Checker: How to Test If Your Schema Markup Works appeared first on Schema App Solutions.

Frequently Asked Questions

What is microdata and what’s the difference between microdata and json-ld?

Microdata is an older format of schema markup. Schema App uses json-ld, as this is preferred by Google and other search engines.

Are there large platforms that support only microdata for their features?

For awhile, Facebook ads used exclusively microdata for its targeting functionality. After a recent review of Facebook’s documentation, this support has now expanded to json-ld.

I have microdata on my site. Will it conflict with the markup generated by Schema App?

This would depend on what markup is in the microdata and what markup is being included by Schema App. There is potential for a conflict that impacts site performance, so we recommend removing the microdata and ensuring that the markup being created or deployed to these pages.

There are errors within the microdata. Can I resolve these and how?

The Schema App Team has created a Schema Filter which will remove the microdata from the page so that these errors are not published and seen by Google’s crawler. We include the microdata filter in our WordPress, Shopify, and BigCommerce plugins. The filter can be toggled on from within the respective platforms’ plugin settings.

If you are not using the platforms mentioned above, you can still use the microdata filter by including the JavaScript tag, which we’ve shared via our Microdata Filter GitHub page. Additionally, the filter can be configured to remove certain markup by following the Microdata filter documentation. For more information on the Microdata filter, please see our how-to article, Schema Markup Filtering Javascript Library.

I have enabled the microdata filter, but when I test the page in Google’s Structured Data Testing Tool, I still see the microdata and any errors associated with them. Is the microdata filter working on my page?

Unfortunately, the Structured Data Testing Tool, which has officially been replaced with the Schema Markup Validator (SMV), did not trigger the JavaScript and showed the result after the microdata has been filtered, so the microdata still showed when testing the live page as seen above. Google’s crawler, however, will see the pages with the microdata filtered and therefore no associated microdata errors.

If the Structured Data Testing Tool does not accurately display the microdata filtered results, how can I tell what Google’s Crawler is seeing?

If you are in the Google Chrome Browser, you will need to right click on the page you are looking to test and then click on the inspect option.

From here you will see the html for the site. At the very top if you right click on the tag that begins with “ <html ” and go to Copy then click on Copy element this will copy the page’s code.

Next you will need to navigate to the Schema Markup Validator (SMV) to run a new test and test the validity of your schema markup syntax. You should supplement the SMV with Google’s Rich Result Testing Tool to analyze your rich result eligibility.

From the new test pop-over window you will need to select the code snippet option and paste the page code you had copied previously, then run the testing tool. This page code will show the results after the microdata has been filtered.

Additionally, you may notice that this shows the preview button when there are duplicate products. Please see our previous blog post, Strange Behaviors in Google’s Structured Data Testing Tool, on this and other odd behaviors seen with Google’s Structured Data Testing Tool.

SEOs still prefer Google’s Structured Data Testing Tool to the Schema Markup Validator, as the SMV currently only shows schema.org syntax errors and not eligibility for rich results. Google’s Rich Results Test, however, does show rich result eligibility! At Schema App, we see schema markup as an iterative process. We use errors in structured data markup as content opportunities to make your markup more robust and comprehensive. Maximize your results from structured data by getting started with our technical experts today!

The post Microdata Filter Questions and Answers appeared first on Schema App Solutions.

Introduction & Thesis

I’ve spent a good part of the past month looking closely at the product markup on pages and experimenting, when I came across something interesting with Google’s Structured Data Testing Tool, which has officially been replaced by the Schema Markup Validator. Namely, when you have multiple products marked up on a page, I was not able to achieve a preview within the Structured Data Testing Tool. However, if you remove all but one of these Product instances, you will receive a preview in the Structured Data Testing Tool.

The following example contains both micro-data and JSON-LD product markup with no preview showing.

After removing the micro-data, the preview button will appear as follows:

The next question that arose from this was, if I don’t get a preview with multiple products, do I get rewarded with a rich result if I have more than one product on the page. For awhile during my experiment it seemed that this was the case, however after a number of attempts I was able to view a rich result for a page with multiple product markup that did not show the preview in the Structured Data Testing Tool.

Assumption

At this point my assumption is that you are more likely to achieve a rich result when there is only on Product instance in the markup and the preview is showing in the Structured Data Testing Tool, however it is possible to achieve a rich result for pages with multiple products marked up.

Hypothesis & Next Steps

Next, I sought to investigate what made this product page different from those that were not achieving the rich result. I began to hypothesize that the sites achieving the rich result were reaching a certain higher threshold of traffic, than those not receiving the rich result. At this point, we do not have a data set with a significant time period or a suitable method to test this, however this will inform the next steps in our research. If you have seen similar behavior in Google’s Structured Data Testing Tool or have further insight, we would love to hear from you!

OfferCatalog with Greater Than 20 Offers

In another product related instance, we had seen an aggregateRating rich result disappear when the offerCatalog size exceeded 20 Offers. This could be a bug, or it could be intended to limit the amount of offers on a single page. To circumvent this, we limited the markup to 20 Offers for each offerCatalog, which ensured that the rich result was still being achieved.

Multiple hops issues

With Schema App we attempt to decrease the amount of code being injected into the page by limiting the markup to stop showing connected data items more than three “hops” from the original primary entity. These hops occur as you move from a certain Class to another, connected by a property. The pattern when connecting data items across your graph and from page to page would be as follows:

Class > Property > Class > Property

This would always end on a property, and each level from Class to Class, would be the “hops” I had referred to earlier.

The next question might be, well if the advantage of Schema Markup is that I can connect my content and provide context to search engines and other technologies, then why would I want the code cut off? As you might have guessed, the process of connected Classes together can result in long code and the data items connected multiple hops down might be less relevant to the current page being marked up. Thus, we cut this off for maintainability. In addition, there is a practical benefit in that this creates simpler and more clear connections for a crawler to interpret. However, these additional connection are not lost.

Another part of how we condense or cut off markup has to do with the Uniform Resource Indicator (URI) for the data item. This can be seen in Schema App in the bottom left of the Editor window, beside “selected resource:” as seen here:

We use the URI to create an @id so that any technology that crawls through the markup can follow the @id to find the full set of markup. The Structured Data Testing Tool doesn’t crawl page to page, rather it loads a single page. This is a limitation of the testing tool and brings us to our next issue.

Testing Nested Schema Markup Against Expected Rich Result

In some cases we have noticed behaviours of the Structured Data Testing Tool when showing results for certain nested Schema Classes that were tied to rich results. Specifically, the Structured Data Testing Tool was firing errors for a Person with a hasOccupation property connecting an Occupation class, as it was testing against its expectations for the Occupation rich result as it is mentioned in Google’s Structured Data Documentation. While the primary entity on the page was a person, the Structured Data Testing Tool validates the connected Occupation data item and show errors for any missing fields. In combination with the way in which Schema App shortens the code after a certain amount of “hops” this results in Occupation properties that are not being displayed from the Person top level entity.

Thus, the markup could be correct in terms of what is included in Schema App, however the Structured Data Testing Tool can show errors as it runs tests on connected data items and does not continue to follow the @id.

Blog Article Preview

We also noticed a similar quirk with the Blog Posting markup in Google’s Structured Data Testing Tool. The preview button will not show if there is no amp html link in the code. With the amp link included, you will likely see a preview button that links to results similar to the following example:

Additionally, if you notice in the right corner there is a small amp lightning icon for these results. Without the amp link in the html, these previews will not show and it is very likely that the page is not eligible for these type of rich results. To ensure you achieve these rich results, be sure to set up your site with accelerated mobile pages (AMP).

We love using insights from the Structured Data Testing Tool to inform content strategy. Instead of seeing errors negatively, take them as opportunities to make your schema markup more robust. Set up a call with our technical experts to get started!

The post Strange Behaviors in Google’s Structured Data Testing Tool appeared first on Schema App Solutions.