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.

Google has continued to expand the properties around Product structured data, enabled Merchant Listing experiences through structured data, and provided more opportunities for web publishers to enhance their Product rich results with more information like return and shipping details.

Additionally, Google can now award Product rich results even without structured data. This, in theory, might sound great. But the problem is that even Google can get it wrong sometimes.

So what do we do when our Product rich results aren’t showing up as expected? Let’s jump in.

Different Types of Product Rich Results You Can Achieve

Firstly, it is important to distinguish the types of Product rich results available as this might modify how you tackle correcting the enhanced search result.

When reviewing website performance on Google Search Console, you’ll see three different types of Product search appearances in your performance report:

• Product results
• Product snippets
• Merchant listings

Product Results = Product Snippets + Merchant listings

Product results are an all-encompassing view of performance around your Product rich results. This can include Product rich results awarded directly by Google, Product rich results awarded through the use of structured data, and Merchant listings results.

Product Snippets

Product snippets are a type of Product rich result that are awarded through structured data. They typically include information such as ratings, reviews, prices and stock availability.

Example of a Product Snippet

Merchant Listings

Merchant listings, also known as merchant listing experiences, are another type of Product rich result that you can achieve through structured data or through Google Merchant Center. They tend to have more detailed information than product snippets and can show up in the Popular Products, Shopping Knowledge Panel and Google images section of the SERP.

Example of a Merchant Listing Experience

How To Determine If Your Product Rich Result Isn’t Showing Up Correctly

The answer is simple, but often overlooked industry-wide.

The easiest way to determine if your Product results are not showing up as expected is to simply find them on the search engine results page (SERP). This should provide you with all the details you may need to determine if the rich result achieved is aligned with your product details.

So, is that it? Assuming you’ve reviewed your Product rich results on the SERP, everything looks good and your traffic is increasing, then yes, it’s as simple as that!

But, let’s say your Product rich result is not showing up the way you want and you want to correct those issues. In that case, here are some of the common Product rich result pitfalls and what you can do to fix them.

Common Product Rich Results Mistakes

1. Not utilizing structured data

Google has the ability to grant Product rich results on your behalf. However, giving away control of your search appearance means you might not always get your desired display.

In our experience, we’ve seen Google award Product results to blog pages based on a price stated in a headline, or target an incorrect price on a Product page with different prices that varied depending on membership standing.

Adding Product markup to your pages is the first step to regaining control over the information you want presented on your Product rich result in the SERP. This means that you’ll need to add Product structured data to all your product detail pages and manage the markup on an ongoing basis, which can be tedious if done manually. At Schema App, our Highlighter tool allows SEO teams to automatically create and deploy Schema Markup dynamically to thousands of pages at once. If you struggle to implement and manage your Product markup at scale, we can help.

As previously mentioned, Google can award your pages the merchant listing experience based on the data in your Google Merchant Center feed. If you are not relying on structured data for your Product rich results, you should ensure that the product information on your Google Merchant Center feed is accurate and up-to-date.

2. Not utilizing the recommended Schema.org Product properties

Do you have an aggregate rating for your Product that is not showing up alongside your pricing information? Are you hoping to show off some of your shipping or return details?

All this comes down to ensuring you’re incorporating the recommended properties from Google’s Product feature guide. In the guide, Google lists all the result enhancements that you can achieve for your Product rich results by adding the relevant content and recommended properties in your markup.

For example: If you want to highlight your offer of free shipping with your product, you can include the shippingDetails property in your product markup. Your Product rich result will then showcase the free shipping offer.

It is important to follow each of the examples to determine which result enhancement is best suited for your pages and how you want to stand out in search.

3. Highlighting incorrect information

As a user who makes informed decisions based on details provided on the SERP, it can be disheartening to see the information presented on the rich result differ from the information displayed on the product detail page.

Examples of this could include indicating an incorrect price, incorrect aggregate review values or counts, and stating a product is in stock when it actually isn’t. This can easily happen when you implement structured data manually on your site and make updates to your content without updating the structured data accordingly. More commonly known as Schema Drift, this mistake can impact the accuracy of the information shown in your Product rich results and reduce your rich result eligibility.

These are challenges that need to be addressed within the structured data. If you notice your Product rich result displaying incorrect information for any of the required and recommended properties, it is important to revisit your Schema Markup to avoid any possible manual action levied against your site for presenting incorrect information.

The Schema App Highlighter can help you overcome the issue of schema drift by creating Schema Markup templates for similar page sets. Your Schema Markup will update dynamically based on the content on the page. Contact us to learn more.

4. Not correcting errors in GSC

If there is an error with your structured data, you’ll likely see it in the enhancement report on Google Search Console.

The product snippet and merchant listing enhancement reports in Google Search Console will show you:

1. Valid items that are eligible for product rich results
2. Valid items that could be improved in appearance
3. Invalid items that are not eligible for rich results and the reason for invalidity

Improve item appearances
Items that show up in this category are valid items that could be presented with more features if more recommended properties and content were included.

This can be viewed as an opportunity to ensure you’re calling out those properties where content permits. It is quite common, however, for Products to have a list of “issues” in this section because most product pages will rarely include all the recommended properties and content for those properties.

Invalid items
Items that show up in this category are invalid items that have issues preventing Google from using your structured data. This will render your page ineligible for the rich result until the issue is rectified.

If you see any invalid items on your enhancement report, you need to revisit the product markup on those pages and ensure your markup, at the very least, includes the product’s name, and either a review of the product, an aggregate rating, or a price.

5. Not being more semantic with your product markup

Search engines are shifting to semantic search and it is important for your organization to include as many details in your Product markup as possible and be more semantic with your Schema Markup.

You can be more semantic with your Product markup by linking the entities on your page to other entities on your site. For example, you can link your Brand to your Product markup under the brand property. This tells search engines that the product on this page is maintained or associated with your brand.

You can also be more semantic by linking entities on your page to external authoritative knowledge bases like Wikipedia or Wikidata. For example, if you offer free shipping within the US, you can link the USA wikidata page (https://www.wikidata.org/wiki/Q30) using the sameAs property to the DefinedRegion of the shippingDestination.

That way, search engines have a clear understanding of which destination you offer free shipping to.

Linking the entities on your site and beyond can help you develop a knowledge graph and provide search engines with more contextual information about your organization. It can also future-proof your organization for a more conversational style of search through AI chatbots like Google’s Search Generative Experience, ChatGPT or even your own chatbot.

Consider how users might engage with a chatbot where they request a product that has a certain pattern, free shipping in the United States, and is a suitable gift for a female – these can all be informed through Schema Markup!

6. Not monitoring performance

You might’ve reviewed the mistakes we covered above and not made any of them. But that does not guarantee improved performance with your Product rich result.

E-commerce is a competitive space and your customers’ purchasing decisions could easily be swayed – both positively and negatively – based on the enhanced results provided in the SERP.

If you find your click-through rate declining when a Product rich result is awarded, you need to analyze the factors that might be influencing performance and run experiments to determine whether it needs to be corrected.

Example 1: If your product listing page contains poor reviews and you’ve included aggregate rating markup on that page, your Product rich result is very likely to showcase these poor ratings and reviews. Buyers could see the rating on the SERP and choose not to explore your product further, thus reducing clicks and click-through rate to your page. In this situation, you can consider removing the aggregate rating markup to see if your click-through rates improve after.

Example 2: If your product is expensive and you have a high price tag on your Product rich result, at first glance you might see your traffic decline. But you should also consider whether the decline is impacting your website conversion rate. Having users qualify themselves might not be a bad thing as long as it doesn’t affect sales. In fact, it might better align with user intent and lead to higher-quality traffic for your site.

At the end of the day, your rich result performance should align with your desired outcomes. If it isn’t aligning with your organization’s goals, you should consider enhancing it with different information or maybe even targeting a completely different rich result as a whole.

Scalability of Product Rich Results

Despite all of Google’s recent rich result changes, Product continues to be an exciting rich result to pursue. However, you should consistently monitor how your products are showing up in search to fully maximize your performance through this rich result.

Many of the recommendations we’ve provided can be easily tackled on a page-by-page basis. But if you’re having difficulty finding a scalable solution to help you drive performance through your Product rich results, Schema App can help.

Get in touch with us today to learn more!

The post 6 Common Product Rich Result Mistakes You Might Be Making appeared first on Schema App Solutions.

Schema Markup, also known as Structured Data, is a standardized vocabulary that helps search engines like Google understand the information on your web pages.

What are the Benefits of Schema Markup?

When your pages contain Schema Markup, it allows search engines and AI powered machines to gain a deep, semantic understanding of your website content, which offers a host of SEO related benefits for your business.

Schema Markup also enables search engines to display your content as a rich result under certain circumstances. These rich results are displayed prominently on the SERP and include extra information about a page, like ratings and reviews of local businesses.

However, as rich results come and go, the one thing that remains consistent is the semantic value of Schema Markup.

Here are some of the top benefits of Schema Markup.

1. Help Search Engines Better Understand Your Content

Humans are great at inferring the meaning of online content. Google, on the other hand, has to teach its tech to understand your content using machine learning.

That’s why search engines need extra help interpreting the meaning and intent of your site content. You can assist them by adding semantic Schema Markup to your web pages.

Schema Markup is a standardized vocabulary developed by Google, Yandex, Yahoo, and Bing. As such, these search engines can easily interpret the Structured Data on your page, allowing the algorithms to present users with content that better aligns with their search intent. It also helps search engines be more efficient because their machine learning and algorithms are built to understand Schema Markup.

2. Build a Knowledge Graph and Re-Use It Within Your Organization

At Schema App, we do more than just generate Schema Markup. We utilize our semantic technologies to generate connected Schema Markup to build a reusable marketing knowledge graph. This knowledge graph can then be used to inform search engines or train your LLMs using structured information about your business.

When you implement connected Schema Markup, you are defining the objects in your content as individual entities with their own properties and relationships to other entities. Once defined, these entities can be connected with the people, places, things and concepts that other authorities have described like Wikipedia, Wikidata, and Google’s Knowledge Graph. Your Schema markup can even enhance your Google Knowledge Panel in search.

Building a knowledge graph using Schema Markup enables search engines to better understand the connections between your content, your organization, and other entities on the web. Search engines can use this information to infer new knowledge with greater context and accuracy.

At Schema App, we implement semantic Schema Markup and entity linking to assist customers in developing their knowledge graph. This knowledge graph enables search engines to effectively match your page with user search queries, driving higher qualified traffic and boosting click-through rates.

3. Be AI-Search Ready

Search engines are increasingly relying on artificial intelligence (AI) to provide users with more relevant answers to their queries. By implementing Schema Markup, you can enhance search engines’ understanding of your content. This, in turn, enables them to accurately match your content with your target audience, ensuring a more precise and effective user experience.

In Google’s podcast titled, “Structured Data, What’s it all about?”, Ryan Levering shared how machine learning and structured data go hand in hand. When you take into consideration that machine learning is the building block for AI, an action you can take to prepare for more AI in search (such as Bard and ChatGPT) is to adopt structured data to inform the machine learning about your content and have it be fully understood.

By using semantic Schema Markup to develop your knowledge graph, AI can tap into this resource and be grounded in more context. This provides them with a richer understanding of your brand and its associated entities.

By developing your knowledge graph, you are creating AI search-ready content.

4. Control How Your Brand Appears in Search

Adding Schema Markup to your web pages lets you exercise greater control over your brand’s appearance in search, empowering you to shape and manage your brand image. One of the key advantages of implementing Schema Markup lies in its capacity to establish a robust control point within your Knowledge Graph, by enabling you to communicate essential information about your organization and entities directly to AI search engines.

Without structured data, search engines rely on algorithms to infer details about your business, which can lead to inaccuracies and misunderstandings. However, with Schema Markup, you take the reins, grounding and informing the AI systems with precise, structured data. By doing so, you mitigate the risk of search engine “hallucinations” – where the algorithms misinterpret or misrepresent your brand.

Imagine your website displays two prices for the same product: one for members and another for non-members. Left unchecked, AI search engines might not recognize the difference, potentially displaying incorrect information in the SERP.

This lack of differentiation can severely impact the trustworthiness and clarity of your brand. However, by clearly indicating which pricing you want displayed using Schema Markup, you can accurately communicate these distinctions, guiding search engines to present the correct pricing information to the users.

Schema Markup is your safeguard against such discrepancies, ensuring your brand and products are accurately represented and preventing any potential confusion for users.

5. Help You Stand Out in Search With Rich Results

When Google understands your Schema Markup, it can use this data to show your content as a rich result (also known as rich snippets) on the SERP.

A standard search result will deliver a title, URL, and meta description. However, rich results include captivating images that draw users’ eyes to your search result and web page.

In total, Google has more than 32 different types of rich results. You can classify your content as local business content, recipes, articles, event pages, and more. If you’re promoting an event, you can improve its visibility by adding Event Structured Data, making your page eligible to appear in the event experience section on Google.

Once you add Schema Markup to your page, you can use Google’s rich results test to see which rich result your page is eligible for. We also suggest using the Schema Markup Validator on Schema.org to detect any mistakes in your Structured Data.

If you want to ensure that your Schema Markup efforts align with your overall branding strategy, here are some examples of rich results you can consider using.

Review Snippets

Review snippets provide prospective customers with reviews and ratings from your past customers and help improve your brand’s credibility in search results.

Product

Product rich results reveal sought-after details like pricing, availability, etc. You can generate more leads and increase interest in your product offerings by providing consumers with this information on the SERP. Beyond the fundamentals, you can also expand your Product rich result to include price drops, ratings, reviews, shipping details and more.

6. Drive Business Results

Schema Markup is an SEO strategy that can provide your company with measurable results and a strong return on investment.

You can use tools like Google Search Console and Schema Performance Analytics to closely monitor how your newly marked-up pages are performing.

When implemented strategically, Schema Markup can:

• Help ensure that your content appears in search results for highly relevant queries. This means that the traffic you receive is more likely to be interested in your products or services, which leads to increased CTR and an overall higher likelihood of conversion and engagement.
• Make your search results more appealing and informative to users, leading to higher CTR. Rich results can provide users with additional information about your content, such as star ratings, prices, and product availability, making them more likely to click your link.
• Be particularly beneficial for local businesses. By marking up local business information, you can improve your visibility in local search results and map listings, driving foot traffic to your physical locations.

Achieving robust results with Schema Markup isn’t unusual. At Schema App, we’ve seen customers across a wide range of industries achieve great results with this SEO strategy.

For instance, SAP saw a 400% growth in clicks from rich results after working with our team, and Sharp Healthcare enjoyed an 843% increase in clicks in just nine months.

As more businesses recognize the benefits of Schema Markup, implementing it can give you a competitive edge. Your content will stand out in search results and provide a more comprehensive, informative, and trustworthy experience to users.

7. Attract Job Applicants

You can incorporate Schema Markup into job postings to help attract quality talent. By applying Structured Data to your job listing pages, your job posting will be eligible for display among Google’s job search experience results.

Top listings are displayed at the top of the SERP. If your listings make the cut, they’ll feature reviews, ratings from past employees, job details, and your company logo.

8. Improve Your Content Strategy

Chances are that you’re already investing heavily in creating SEO content, optimizing it for priority keywords, and engaging in other on-page SEO tactics to rank higher on the SERP. Unfortunately, your competitors are likely doing the same.

Fortunately, you can beat the competition and inform your content strategy by utilizing Schema Markup. Thinking about your content from the perspective of the rich results you want to achieve can help to generate ideas for new content or existing content. If you want your page to be eligible for a Review Snippet, you can improve your content by adding customer reviews and ratings on your site.

Start by looking at Google’s Structured Data Guidelines, then generate the required Schema Markup using Google’s Structured Data Markup Helper or our Schema App Editor. Once you’ve generated the markup, you can add the Schema Markup to your pages so your content can stand out as a rich result.

You can go one step further to create connected Schema Markup by linking the topic covered in your content to the Wikipedia or Wikidata page for the specific topic within your Schema Markup.

Read our step-by-step guide to learn how to develop a Schema Markup strategy for your website.

Start implementing Schema Markup today

The benefits of Schema Markup are undeniable.

When you add Schema Markup to your website, you’ll help search engines understand your content and make your pages more visible in organic search. In turn, you’ll increase your click-through rates and generate more organic traffic for your web pages.

Any business with an online presence can generate measurable results using Structured Data. However, to tap into the full potential of Schema Markup and stand out online, you must build, manage and optimize it as part of your ongoing site strategy. Otherwise, you’ll encounter issues like Schema Drift which hinder your ability to achieve rich results.

The good news is you can streamline the implementation and management of your Schema Markup by working with Schema App. We work with enterprise SEO teams to fully leverage the benefits of Schema Markup. Contact us today to learn more.

The post 8 Benefits of Schema Markup and Why It’s Important for SEO appeared first on Schema App Solutions.

There are benefits to having both paid and organic traffic for your brand, including the opportunity to show up more than once on a search engine results page. Yet focusing solely on paid advertising doesn’t cut it anymore. Up to 80% of users focus exclusively on organic search results and ignore paid ads altogether.

While everyone is investing in SEO strategies, an effective—and often overlooked—advanced SEO approach is schema markup.

Schema Markup (also known as structured data) is a language created by Microsoft, Yahoo!, Google and Yandex to help search engines understand the content on your website. By marking up products on your e-commerce website, your content could be eligible for rich snippets in search. However, they need to be marked up correctly.

Take a look at how schema markup can make your brand stand out in search engine page results.

Product Schema Markup

Shoppers are getting smarter, and search engines are always evolving to find new ways to match user intent to results in search.

Rich results can make your product information more eye-catching so that you don’t even need to be at the top of a search engine results page to stand out. Marking up your product pages can even provide additional information in Google images.

You may already be familiar with product and rating rich results, which help your customers to see the price, availability and customer ratings of your products right on the search engine results page. Look at the difference between these two search results for a Blue Yeti Microphone. The Amazon result really stands out even though it was below the Blue result on the page.

Here are the essential product markup properties that we recommend:

• Price
• Product Name
• Product Description
• High-Resolution ProductImages
• Availability
• Brand
• Reviews
• Breadcrumbs

To be eligible for product rich results in search, Google recommends marking up individual product pages instead of a category or list of products. Read more about Google’s guidelines for product schema markup here.

Not only will marking up your product information make your page eligible for a rich result on the SERP, it also displays the information in Google Images. 

Since September 2020, Google has been evolving the product search engine page results, showing types of pricing and illustrating pricing changes. Google requested new pricing properties in Schema.Org and we expect these properties to be included as recommended properties for products in the future.

Review Snippets for E-commerce Websites

Let your customers speak for you by encouraging them to leave reviews. Then take these reviews even further with schema markup.

Online reviews are seeing a rise in consumer trust. 97% of consumers are influenced by reviews when making a purchase, and customer reviews can increase conversions by up to 270%.  In an age where information is so readily available online, it’s important to put your brand in front of readers with as much clarity and credibility as possible.

You don’t need thousands of reviews to make an impact. In fact, BrightLocal’s 2020 local consumer survey revealed that consumers look for an average of 10 customer reviews before trusting a star rating. And that star rating? Only 48% of consumers would use a business with a rating under 4 stars. 

After receiving excellent reviews from your customers, showcase them in search by marking up your website. Adding review structured data to your web pages can make your content eligible for the Review Snippet rich result.

If Google finds a valid review or rating markup, your content could display a short excerpt of the reviews and an aggregate star rating in search.

Reviews demonstrate to search engines like Google and other consumers that you have a great product or service. Investing in your brand’s credibility will be rewarded time and time again. 

Schema Markup and the Customer Journey

Schema markup can have a positive impact across the customer journey, from the research phase to converting a sale. Online spending in the United States was over 21% of total retail sales in 2020, up 44% from the year before. With the pandemic and global lockdowns forcing more people to shop from home, this isn’t all that surprising. Changing consumer habits reshape marketing funnels, and a user could interact with your brand at various stages of their customer journey.

There are three basic types of search intent: 

• Informational – the intent is to answer a question or to learn something 
• Navigational – the intent is to locate a specific website 
• Transactional – the intent is to buy something

Transactional search intent usually leads to higher e-commerce conversion rates since the buyer has already decided to make their purchase. But there are opportunities to capture a user’s attention through other types of search intent as well.

If your product is marked up properly, this information can be eligible for rich results to improve visibility in search. You want your product or service to be suitably matched to a consumer’s needs, and this is what search engines seek to accomplish as well.

Technical SEO Best Practices for E-commerce Websites

You may be asking yourself, why can’t search engines determine important product information themselves without our help?

They’re increasingly intelligent and they can continuously crawl website content. The fact is, Google can’t pull all of the vital information from product pages by itself. We can however help Google along by providing this information through structured data, product feeds, or Google Merchant Center. 

Google won’t display product information as enhanced search results unless it’s confident about the product information.

This is similar to the concept of E-A-T, which stands for  Expertise, Authoritativeness and Trustworthiness. E-A-T has become a core concept for advanced SEO, and is essential to improving a brand’s search rankings. For both rich results and E-A-T, Google needs to be confident in your brand and the information that you’re publishing. The more information that you can supply to search engines, the more confident they will be displaying your brand in search results.

Set Your E-Commerce Brand Up For Success

These strategies will help to set up your e-commerce brand for success, but the investment doesn’t stop there. To remain relevant in an ever-changing digital market, it’s important to keep informed on the trends in advanced SEO. Sign up for our newsletter to stay updated, or contact us if you want to help your products stand out in search. 

Frequently Asked Questions

What are the best rich results for e-commerce websites?

You may already be familiar with the Product rich result, which can display the name, price, availability, etc., of your e-commerce products in search. There are many other rich result opportunities for e-commerce websites, such as frequently asked questions (FAQs), HowTo, Videos, and more! See our Guide to E-commerce Structured Data to learn more.

How do I get stars and ratings on my products in search?

The stars and ratings that you see on products in search results come from Product schema markup. To unlock this rich result in search, follow Google’s structured data guidelines, including all required and any recommended properties that will make your rich result more robust in search.

We help you think beyond the product rich result and strategize with you to stay ahead of the competition. We’ve helped some of the biggest e-commerce brands, including Keen Footwear, Home Hardware, and Ariat, become leaders in the online shopping industry by setting new standards above the existing baseline.

The post Ecommerce Schema Markup Strategies for Successful Brands appeared first on Schema App Solutions.

These strategies are: 1. Simplified and Aggregate Product Offers 2. Each Variant as an Individual Offer and 3. Each Variant as a Product Model.

What is a Product Variant?

Generally, variants are identified as having their own Store Keeping Units (SKUs) which are unique to the Product group and used for eCommerce and Supply Chain information systems. Below is what WooCommerce and Shopify, two popular eCommerce platforms, say about Product Variants.

WooCommerce Variable Products are a product type that lets you offer a set of variations on a particular product such as price, stock, size and more. For example, they may be used on a shirt that’s offered in large, medium and small sizes and in different colours.

Shopify Product Variants are used on products that come with more than one option, such as color or size. Each combination of options is a variant of that product. For example, you might sell a t-shirt with two options, such as size and color. The size option might have three option values: small, medium, or large. The color option might have two option values: blue or green. A variant of these options could be a small, blue t-shirt.

1. Simplified and Aggregate Product Offers

For situations where you don’t have all the data readily available, or want to start off with something basic, you can simplify the product models. With this approach, your Product markup would only use the properties that are shared across all variants such as, name, image, and description. The Product type would then use the offers property to connect to either an Offer, if no variation in pricing was present, or an AggregateOffer if pricing changed among the product variants.

For example, if you’re selling shoes, there may be variations in sizing and colour, but all of them are the same price. You could create markup for a single Product, excluding all sizing and colour information, and connect it to an Offer data item with the price shared across all product models. This is what the markup would look like:

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "name": "Clarks Falalala Shoes for Men",
  "image": "https://example.net/shoes/clarks-falalala.jpeg",
  "description": "A great comfortable walking shoe, carried in sizes 9-11, but you wouldn’t really know that unless you applied fancy NLP to this string",
  "offers": {
    "@type": "Offer",
    "price": 45.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  }
}

If you were selling something that varied in price—for instance, Soap that comes in 250ml, 500ml and 1000ml bottles—then you could call out the lowest price and highest price using AggregateOffer:

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "name": "Super Suds",
  "image": "https://example.net/soap/super-suds.jpeg",
  "offers": {
    "@type": "AggregateOffer",
    "lowPrice": 5.99,
    "highPrice": 17.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  }
}

2. Each Variant as an Individual Offer

This first option doesn’t tell the machine-channel anything about the variation of products you carry, nor does it provide the granularity of stock information by individual SKU. The next level of detail would be to include each variant’s price and availability as a separate Offer. Each Offer should have (as recommended by Google) a sku to differentiate it from other variants, along with its price and availability. Using the same example as before, we might generate:

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "name": "Clarks Falalala Shoes for Men",
  "image": "https://example.net/shoes/clarks-falalala.jpeg",
  "description": "A great comfortable walking shoe, carried in sizes 9-11, but now size 11 isn’t in stock",
  "offers": [ {
    "@type": "Offer",
    "sku": "QWERTYSHOE-9",
    "price": 45.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  },{
    "@type": "Offer",
    "sku": "QWERTYSHOE-10",
    "price": 45.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  },{
    "@type": "Offer",
    "sku": "QWERTYSHOE-11",
    "price": 45.99,
    "priceCurrency": "EUR",
    "availability": "OutOfStock"
  } ]
}

The Soap Suds example shows varying Offer properties sku, name, price, priceCurrency (in ISO 4217 currency format) and availability;

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "name": "Super Suds",
  "image": "https://example.net/soap/super-suds.jpeg",
  "offers": [{
    "@type": "Offer",
    "sku": "egsoapsuds-250",
    "name": "Soap Suds 250 ml",
    "price": 5.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  },{
    "@type": "Offer",
    "sku": "egsoapsuds-500",
    "name": "Soap Suds 500 ml",
    "price": 10.99,
    "priceCurrency": "EUR",
    "availability": "OutOfStock"
  },{
    "@type": "Offer",
    "sku": "egsoapsuds-1000",
    "name": "Soap Suds 1000 ml",
    "price": 17.99,
    "priceCurrency": "EUR",
    "availability": "InStock"
  }]
}

3. Each Variant as a Product Model

If your products have significant variations among their critical properties, you may want to use the Product Model approach. Essentially, you define a schema.org/Product as the base product, adding properties that are common across all variations. Then, to express properties that are variable, use the ProductModel type. For example, the iPhone 11 is a Product with certain consistent characteristics, but there are different options for GB of memory, colour, and pricing. Each combination of these properties would be a different instance of ProductModel:

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "name": "iPhone 11",
  "description": "A great device, loads of memory, 1 million different apps preloaded, outstanding camera, and even makes phone calls!",
  "image": "https://example.net/phones/apple-iphone11-jpeg",
  "offers": {
    "@type": "AggregateOffer",
    "lowPrice": 599.00,
    "highPrice": 899.00,
    "priceCurrency": "USD",
    "availability": "InStock"
  },
  "additionalProperty": {
    "@type": "PropertyValue",
    "name": "Memory",
    "unitCode": "E34", 
    "unitText": "GB",
    "value": "64"
  },
  "model": [ {
    "@type": "ProductModel",
    "name": "iPhone 11 with 64GB",
    "color": "White",
    "offers": {
      "@type": "Offer",
      "price": 599.00,
      "name": "White iPhone 11",
      "availability": "InStock"
    }
  },{
    "@type": "ProductModel",
    "name": "iPhone 11 with 64GB",
    "color": "Red",
    "offers": {
      "@type": "Offer",
      "price": 649.00,
      "name": "red usually costs slightly more because it's faster",
      "availability": "InStock"
    }
  },{
    "@type": "ProductModel",
    "name": "iPhone 11 with 128GB",
    "color": "White",
    "offers": {
      "@type": "Offer",
      "price": 899.00,
      "name": "White iPhone 11",
      "availability": "InStock"
    },
    "additionalProperty": {
      "@type": "PropertyValue",
      "name": "Memory",
      "unitCode": "E34",
      "unitText": "GB",
      "value": "128"
    }
  }]
}

Note that ProductModels themselves may contain other ProductModels. This relationship can be defined using the isVariantOf property.

ProductModel Examples in the Wild

If you’d like to see more ProductModel examples in the wild, you can use PublicWWW to search for any schema class: see example.

unitCode Lookup Values

If you’re wondering where the unitCode “E34” comes from, then you’ll want to look up UN/CEFACT Common Codes for specifying the unit of measurement. Here are some common codes for various units of measurement. A spreadsheet is available to download here.

We want your schema markup to be successful! Schema markup can be time-consuming and complicated. That’s why we’re always looking for ways to make things easier for customers through our comprehensive solutions. Book a strategy call with our technical experts today!

The post Schema Markup for Product Models 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 haven’t already done so, you may want to consider creating a Google Merchant Center account. You’ll be able to manage your appearance across all Google e-commerce products, upload product information (like pricing & pictures), and be displayed in Google Shopping searches.

What is Google Merchant Center?

Google Merchant Center is an online dashboard where you can manage your shop and product appearance and make it available to shoppers across Google. You can upload and maintain product information and your online listings where needed, including pictures and pricing that can be displayed in Google Shopping searches. Google Merchant Center also integrates with other Google services like Google Business Profile, allowing you to reach potential customers at different stages of their buyer journey.

What is Google Shopping?

Google Shopping isn’t technically an online marketplace. It’s more of an ad platform where you can advertise your products, providing shoppers an opportunity to browse physical products based on a search query. Google Shopping is also known as a Comparison Shopping Engine (CSE), where shoppers search for, compare and shop for physical products across different retailers.

Fun fact! When Google Shopping was released in 2002, it was called Froogle.

Structured Data Markup for Google Merchant Center

You can use structured data to mark up your organization and your products so that search engines can reliably retrieve up-to-date information from your website and display these details in search. In Google Merchant Center, this structured data markup can be used to update your product data, simplifying the creation and maintenance of your product feeds.

What is structured data?

Structured data, also known as Schema Markup, is a type of code that can be added to your website, making it easier for search engines to crawl, organize and display your content in search.

When you mark up information on your website with structured data, you are basically explaining to Google what your data means. Through structured data or schema markup, you can define objects in your data as distinct entities with their own properties and relationships to other entities. Once defined, entities can be linked to a search engine’s knowledge graph through schema markup. Knowledge graphs represent the linking of information and data across the Web, providing context for search engines as they crawl your website.

For e-commerce, structured data markup unlocks great opportunities to display products and store information in search results so customers can engage with your brand before even entering your website.

Structured Data Markup for Products

It’s recommended that you add new schema markup to your product pages to help Google reliably retrieve up-to-date information, and enable click-driving search features like Automatic Item Updates, Google Sheets Merchant Center add-on, and Product Rich Results. This ensures that you’re set up optimally and simplifies the creation and maintenance of your product feed in search.

Product entities and review snippets are two of the most important considerations for any brand with an e-commerce presence. Customers want to know the most up-to-date information about your products and/or services, and like to see what other customers have to say about your brand through reviews. Having an aggregate star rating and reviews can improve click-through-rates and conversion rates – when they’re over 3 stars!

Here are the essential product markup properties that we recommend:

• Price
• Product Name
• Product Description
• High-Resolution Product Images
• Availability
• Brand
• Reviews
• Breadcrumbs

Google recommends marking up individual product pages instead of a category or list of products. Read more about Google’s guidelines for product schema markup here.

If you’re looking to set up your product schema by hand there are a number of things to keep in mind. Be sure to follow all the Structured Data General Guidelines and abide by the Google Merchant Center requirements for structured data markup.

Once you’re comfortable with that, you’ll want to know which corresponding attributes and accepted values are supported by Google Merchant Center, and how to handle a single offer vs multiple offers with product variants.

If you’re new to schema markup, this can seem daunting.

Schema App for Google Merchant Center

Schema App has a much easier solution. To start, you’ll need to sign up for our Schema App end-to-end solution. This will give you access to our Highlighter, Editor, Schema Performance Analytics, as well as our Google Merchant Center integration.

With Schema App’s Google Merchant Center integration, you can start processing and generating JSON-LD Schema Markup from the product data in your Google Merchant Center account. This will allow you to quickly generate and deploy robust product Schema Markup to your product pages.

Note: The Schema App Google Merchant Center integration is not available for customers on our Pro subscription.

Here’s how you can use the Google Merchant Center Integration on the Schema App platform:

1. Login to Schema App and choose the Active Project you want to set up.
2. Go to https://app.schemaapp.com/merchantcenter
3. Authenticate with Google – If you have Merchant Center authority, you can directly Authorize Access to Merchant Center. Once connected, Schema App will start processing and generating Schema Markup JSON-LD from the Product. You are done!
4. Request Access – If you do not have Merchant Center access directly, you can request a colleague delegate the access. We provide an email template that invites them to connect the account. The system will generate a link to set up the authorization that expires after 72 hours.
5. Request Access – your colleague will receive an email, click on the link, and proceed with the Authorization.

If you have any questions, please reach out to our support team.

So long as you have set up one of our integration methods, this is a TWO-CLICK solution to completing all your product markup.

Considerations for Google Merchant Center Structured Data Markup

While structured data can help to showcase your e-commerce store and products in Google Merchant Center, there are some considerations you should keep in mind:

• Don’t change your product or store landing pages based on the user, such as adjusting prices based on the customer’s location
• Your structured data should be present in the HTML returned from the web server and not generated with JavaScript AFTER the page has loaded
• Only mark up information that is shown to the user on your landing pages, which means even the prices in your structured data markup should match the values shown on the page

Maintaining schema markup for e-commerce products can be tedious as prices may change and supply may shift. That’s why Schema App offers dynamic structured data services that can update your markup in tandem with any content changes on your web pages. Learn more about our e-commerce solutions.

We’ve helped retailers from Keen Footwear to Home Hardware overcome website challenges and reach their e-commerce goals through structured data. If you’d like to learn more about what we could do for your online business, get in touch!

The post Structured Data Markup for Google Merchant Center Feed appeared first on Schema App Solutions.

While this reality does not exist today, elements of it do, and evidence to how the “futuristic” parts are really more reality than fiction.

I never went to a site to shop, I merely asked for the information I needed to make a decision, reviewed the styles based on my personal taste and look and then proceeded to make the transaction all while never landing on a retailer’s website, or browsing their catalog.

This change requires companies to start managing their brands for machines. Machines like Google, Bing, Alexa, Siri, and extending as far as a Tesla car or your connected fridge. It means that marketers have a new role, they need to not only think about their brand in the context of how humans understand your content, but also machines.

This was the specific topic of a panel I chaired at Retail Week’s Tech conference in London, UK where Wendy Stonefield of Deloitte Digital, Nick Wilsdon of Vodafone, and Dawn Anderson of Move-it-Marketing shared how we saw the world changing.

“Brands are still spending large sums to build, promote and portray their brands as they wish them to be perceived across various channels. Proctor and Gamble is at the number 1 slot of the spenders with an impressive $7.12 billion in 2017, a collection of 17 auto brands spent $51 billion, and internet companies are rising through the ranks of spenders – such as Alibaba, Tencent, Rakuten and Amazon who is number 11 with a budget of $5 Billion ahead of Ford Motors, Coca-Cola and McDonald’s.” says Wendy Stonefield of Deloitte Digital London.

Building, managing and sustaining brand image is more important than ever, but more and more challenging in the world where the customer experience is becoming fractured and owned by Google, Amazon, Apple, and not the brand itself.  

Loss of the Customer Experience

There is plenty of evidence that supports that brands are losing control of the customer experience. Here are a few that illustrate the change and I believe are support for where things will be going.

Job Search

If you do a job search in Google, you see a list of jobs for your area or discipline, can filter based on needs (full time vs part-time), and also keywords. But here’s the kicker, if you choose a filter, Google takes you directly to the job post to read the details!

We see the same behaviour for Events, and answers to common questions.

Health Information

Over the years we have seen the knowledge panels and answers in search evolve. Today, if you do a search for a specific medical condition, for example, Hashimoto’s disorder, details, and common questions are listed directly in search.

Product Research and Purchase

When searching for products, if you are a visual buyer, you can find out information about the product, the price, reviews directly in the image search results. The impact is that the research is being done off your website, so there is no evidence of interest until they purchase or don’t.

It makes sense that Google wants to keep you in the search results as long as possible, since the longer you are there, the more ads they can display, and the more money they make.

Voice Search

Don’t believe me that the customer experience is moving away from your website? OK, let’s talk about Alexa. Amazon has done a great job getting us excited about asking Alexa questions, having her build our shopping list, or playing “We will Rock You” for dance parties in the kitchen. What we haven’t all realized is that Alexa’s presence means that we are informing Amazon of our preferences, family habits, and are being provided with very easy access to a single ordering channel. As a working parent, I can’t help but revel at the experience of creating my personalized shopping list and having it ordered, never having to get out pen or paper, or leave my home.

I believe that Google and Amazon are only at the tip of the iceberg with this trend. We know that Apple is playing already in the voice assistant world with Siri, Google too with Google Home, and that Facebook are working on their voice strategy.   Microsoft recently announced how they are using Bing across their customer experience to bring data from search, email and the desktop into results.

Challenges for Retailers and Large Organizations

Retailers are already struggling with the changes of the current internet with online brochures/flyers, ecommerce, and social. The largest retailers not only have to keep up with the pace of change across channels, but they also have the challenge of being large, slow and complicated. Their size alone makes it difficult to keep up.

And now they have to figure out how to manage their brand for the machine channel?

Wendy adds, “The  introduction of voice search, the Internet of Things (IoT), Chatbots, are all there for the taking or breaking of brands.”

The challenges are real. How do you get a large organization to be nimble enough to change, and move quickly to take advantage of these changes, while bringing value to the organization in the process?

Nick Wilsdon from Vodafone, shared his biggest challenge in trying to be agile in this very fast, evolving “machine channel” In his role as the Head of Search, he is challenged with finding ways for Vodafone to show up in search in Google, but also in voice, on Alexa. Simply put, his challenge is Data.

“Data is spread out and siloed. For example, the team built a well-received Vodafone Alexa Skill  to let pay monthly customers to retrieve their bill amount, question bill differences over the month and find information on new services. However, this application currently only works for accounts paid monthly and not pay as you go (PAYG) or B2B customers.”

“In addition, driving change is slow. To overcome this, we come up with small tasks that move things forward and celebrate their achievements. For example, organise a hackathon with your developers over pizza. Create an agile environment, where teams can try new things and use the outputs to show executives the business value in managing the brand for these new channels.”

One of the key challenges is ownership. Is this new world of brand marketing a Marketing Initiative or IT.  Dawn Anderson of Move-it-Marketing explains that “there are so many technological choices and options afforded to organizations, and at various stages of maturity, often knowing which is the optimal path to take is overwhelming.”  So where should you start and who should lead it?

How to Start Building a Foundation for the Machine Channel

In my 15+ years working with Enterprise customers at Cisco and now at Schema App, I am a big believer that wherever you start, you need to be able to show value quickly, to support ongoing investment, and also to keep the teams engaged, and motivated.

Start with Structured Data

Marketing teams have an easy, high-value opportunity to help Google, Alexa, and other machine consumers understand their content using the advanced SEO strategy called Structured Data (aka Schema Markup).  

What is Structured Data? In 2011, Google, Yahoo and Bing created a vocabulary called schema.org (a machine language), to help them understand content on web pages. This vocabulary enables companies to translate their content into machine language, aka code, and as a result of doing this translation, Google rewards the website with features in search and better-matched traffic because the content is fully understood.

We experience these enriched search results through review rich snippets, images in search, prices in rich results and more.

In November 2017, Gary Illyse from Google stood up and said, “[Add] structure data to your pages because, during indexing, we will be able to better understand what your site is about.” SEMpost

Today, Google, Bing, Alexa and others identify features as a result of embracing structured data, and we only see these accelerating. In the recent months, we’ve seen Google release new features, such Media, Speakable, Podcasts, and Fact Check. With Speakable being a specific feature to enable control on what is an answer is Voice Search.

Brands can leverage tools like Schema App Highlighter, or built in Apps in their Ecommerce Platform to add schema markup to content on your site you want customers to find, and therefore want the search engines and voice to understand.   Many of these solutions require little to no IT involvement, empowering marketing to start managing the brand for machines, and speed to value.

As a result of taking this first step into managing your brand for machines, there will be tangible benefits such as increased organic search traffic, increase clicks, higher customer engagement and perhaps the opportunity to reduce paid Ad investments all while starting to future-proof the brand.

Voice Search Alexa Skill Pilot

Nick Wilsdon of Vodafone said it best, buy a couple of pizza’s and a couple of developers and build something simple. What should you build? We recommend looking at the top questions customer service teams get and turn them into a skill. Often companies are already answering these questions on their phone system (IVR).  One digital marketing company, decided to create an Alexa Skill to answer the top questions in their area of search expertise, so that they could showcase the value of owning that answer.  Retailers might start with answering questions about their locations opening hours. Something I can imagine asking Alexa as I sit on the couch browsing clothing in search results.

Take Control of How your Brand is Understood by Machines

We have lost control of the customer experience, and it is only just starting. Retailers and Brands can start taking control of this new sales and marketing channel with some advanced SEO tactics, and through experiments to show value, and the experience of the future.

Marketers have a new role, they need to not only think about their brand in the context of how humans understand your content, but also machines.

If you need a hand getting started with your structured data strategy, we’ve helped customers such as SAP and Keen Footwear drive more quality search traffic to their websites. 

The post Future Proof your Brand for the New Search and Voice Assistant Age appeared first on Schema App Solutions.

We recently had a project that started as a National Retailer wanted to pilot Google’s Local Inventory Advertising (LIA) program. The Advertising program bridges the online and offline world. The retailer, which has 500+ stores nationwide, could advertise products that are in stock locally. If you search for “Bauer Excaliber hockey skates” you would not only get an advertisement from the retailer but also if it’s schema.org/InStock at a location and distance to that store. It’s a powerful conversion opportunity, exploiting the retailer’s vast network of store and inventory, consumers get actionable information to go pick it up physically.

Local Inventory Ads Example

Part of the conditions to LIA program is to have Schema.org data on Product detail pages at a level that details the availability in each store. For each schema.org/Product and its schema.org/ProductModel, we need to expose their schema.org/Offer and its schema.org/availableAtOrFrom StoreID.

Approaches considered

Like many large businesses, the Marketing team has numerous initiatives dependent on IT for delivery. They had an aggressive timeline, 8-10 weeks, when started we provided them several schema.org at scale options to consider. To maximize the number of data consumers of schema.org data we wanted to render the schema.org data server side, so that it is available in the HTML Document Object Model on page load.

1. Custom Programming: Typically this meant encoding data into the Product Detail Page template, using either Microdata or JSON-LD This approach, however, relies heavily on the IT team which couldn’t meet the aggressive schedule due to other commitments.
2. Bulk Data Transformation: Our next best option was to implement a bulk data transformation, which would take the same Google AdWords Feed and supplement with BazaarVoice review data.
3. Javascript Rendering: The third approach is to implement Javascript which builds the JSON-LD dynamically after page load.

Ultimately, we chose #3 Javascript Rending because it involved no IT, it could meet the LIA requirements for Google in a short time and the data/code remained within the control of the Business.

Problems with SDTT & GTM Datalayer

The initial implementation by the team was to provide schema.org data mapped from Google Tag Manager Datalayer variables. The data layer had Product Information, Offers for different skus for the selected store and the BazaarVoice review data (AggregateRating). The only catch was, this data while convenient was only available after 5-10 seconds because of all the Javascript on the page to prepare the data. To add complexity, the retailer has different pricing for different stores. For example, Rural stores which incur more shipping costs could have higher prices than urban centers. Therefore, on each page load needs to first geolocate the user and suggest the closest store, before the prices could be shown. Similarly, BazaarVoices elements loads using Javascript and its data is loaded after a few seconds as well.

When we tested the schema.org data, we found the <script type=”application/ld+json”> when we inspected the HTML. However, when we tested with Google’s Structured Data Testing Tool, the tool which does a good job processing Javascript, simply cut off the page after several seconds of Javascript processing and wouldn’t show the data.

The Additive Experiment method

We set up a workshop to go through step-by-step, testing the limits of what could be done. The relevant Product information was spread throughout the webpage, so we wanted to explore the extent of what was possible. In order for this to be successful, we relied heavily on the Google’s ability to reconcile JSON-LD data by its @id values. For example, given the two sample JSON-LD inputs below:

{
  "@context": "http://schema.org/",
  "@type”: "Product",
  "@id": "#product",
  "name": "Blue Widget"
}

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "@id": "#product",
  "image": "http://cdn.amazon.com/TheEnterprise/product_blue_widget.jpeg"
}

Would be reconciled by Google as:

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "@id": "#product",
  "name":"Blue Widget",
  "image": "http://cdn.amazon.com/TheEnterprise/product_blue_widget.jpeg"
}

Therefore, we would deconstruct the data into logical parts, then the additive data elements available to SDTT at the time it cuts off would show the problematic data by whats not shown. The first element, Basic Product Data that’s available in the HTML DOM that comes from the server before any Javascript. When viewing a webpage, if you right-click and View Page Source, that HTML is what comes from the server. This is data which is immediately available to Javascript for parsing and could be published immediately. There, we found Product Name, one image in the meta og:image, the Product Description. We coded some Javascript selectors, e.g. document.querySelector, to build out a basic Product schema JSON-LD data block. As an example, to get the Product Image URL:

document.querySelector('meta[property="og:image"]') 

We implemented this as a GTM Tag that triggers on DOM Ready and Published, ready for our first live test.

Testing & Validation

When testing on Google we found the data was being discovered.

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "@id": "#product",
  "name": "Blue Widget",
  "description": "Lots of great features!",
  "image": "http://cdn.amazon.com/TheEnterprise/product_blue_widget.jpeg"
}

While it was a good first test step, we were still missing necessary aspects, including Offers and Reviews. The next attempt we made was to retrieve Offers. We looked backward from the data layer, to see how it was populated. We discover a Custom Javascript Event that published the Offers once a Store was select. We setup the trigger and once we found the pricing and availability information we were able to add the Offer. We appended this JSON-LD data block by referring back to the #product defined earlier and use the additive information.

{
  "@context": "http://schema.org/",
  "@type" :"Product",
  "@id": "#product",
  "offers": {
    "@type": "Offer",
    "price": 45.00,
    "priceCurrency": "USD",
    "availability": "InStock"
  }
}

If the store is selected, we could include the schema.org/availableAtOrFrom: “StoreID123”. This StoreID has to match those in the Google Business Profile (GBP) account. These are unique identifiers the Retailer assigns to them and reused for LIA and in schema.org markup.

This Offer data works great for Product with no variants or when for Multi-variant Products whose ProductModel (sku) is selected. In scenarios in which a Product has multiple variants / skus, instead of Offer we would show AggregateOffer with a lowPrice.

Rich Snippet Using AggregateOffer

When testing this data block, we were less certain that the data would be available in time for the Javascript rendering for the SDTT. In this test it was available and the data automatically merged into the earlier data block.

Next, we wanted to get the BazaarVoice data for AggregateReting data. We found the Javascript code that loads BazaarVoice and looked for a way to hook into the function. Being that the BazaarVoice Javascript was included in the Page Load DOM, our GTM tag is loaded too late to mutate the Javascript function. We instead attached a Javascript onChange listener to the DIV Review element. When that changes, we would get the rating count and rating value data from DOM elements innerHTML. We could then emit a third JSON-LD data block and tie in with the earlier data using the same @id : “#product”

{
  "@context": "http://schema.org/",
  "@type": "Product",
  "@id": "#product",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingCount": 12,
    "ratingValue": 4.6
  }
}

When we published the tags and ran it through Google, the data was available in time and Google rendered the compiled JSON-LD data blocks. The Testing Tool also showed us the Preview button and Product rich result. Had the Javascript had too many delays and didn’t make the cutoff, we knew which was data source was the culprit. A decision would be made whether to include what was discoverable. The data that doesn’t show, we would revisit the Javascript event model to discover alternative methods.

SDTT != Search Console Report. In our experience, if you find schema data is shown in the Structured Data Testing Tool you will find it in the Search Console Structured Data report after 3-5 days (unless its a large site and the pages haven’t yet been reindexed). The opposite, however, isn’t always true. There have been times where we have not seen data in the SDTT but we do find the data in the Search Console. So, even if we’re at wit’s end trying to get the data to show in Search Console, I would leave the GTM Tag in place until we confirm the Search Console report.

Future Work

I really like the additive capability of composing schema.org markup data block by data block. Sometimes all the information isn’t available at runtime and to meet the needs of an early adopter you need to experiment to make it work. In the future, our work with the client will involve adding How-To Videos, cross-sell products, upsell products, related links, additional images all using the additive method.

Of course, this is all great for the retailer, they now receive Google rich snippets and LIA in time for the holiday shopping season. For other schema.org consumers, however, we are less fortunate as they less often support handle Javascript rendering like Google does. For these other consumers we need to include the data from the Server as part of the HTML sent back to the client. This is a business decision, however, what is the additional cost of the IT project to implement weighed against the provable ROI of supporting other data consumers.

If you need a hand getting started with your structured data strategy, we’ve helped customers such as SAP and Keen Footwear drive more quality search traffic to their websites. 

The post Additive Schema.org Data for Local Inventory Advertising appeared first on Schema App Solutions.

Google Features Enabled by JSON-LD

• Rich Results: Schema markup for things like recipes, articles, and videos usually appear in the form of Rich Cards, as either a single element or a list of items. Other kinds of schema markup can enhance the appearance of your site in Search, such as Breadcrumbs, or a Sitelinks Search Box. A sitelinks box is usually found underneath a website’s main webpage result. It shows popular pages on the site as well as in-site search box.
• Product Reviews: If you’re a merchant, you can give Google detailed product information that they can use to display rich results. This can include adding information about product ratings from your website. Google may then take this rating information and display it within the search engine results page.
• Knowledge Graph Cards: If your website is reputable enough to be considered an authority on a subject, Google may treat the content on your site as factual and import it into the Knowledge Graph, where it can
  power prominent answers in Search and across Google platforms. This is most easily displayed when you search for definitions of complex concepts such as “structured data”. Knowledge Graph cards appear for authoritative data about organizations, and events. As you can see in this example, this knowledge card appears on the right side of the search engine results page when you search for “Home Depot Company”. Simply searching “Home Depot” usually gives you a knowledge card of the location nearest you, and not necessarily a company overview.
• Actions in Gmail: JSON-LD markup can be used to enhance interaction with your customers directly in Gmail. It presents users with call-to-actions such as an event RSVP, subscription renewals, social media actions, etc. It can even prompt a product review that can be written without leaving Gmail. These actions enhance user experience by integrating some of the most common actions in one place, creating a more engaging experience for new and existing customers.

JSON-LD is very useful, however, it is very difficult and time-consuming to create your markup manually. Schema App is the most powerful JSON-LD creation tool in the world, allowing you to quickly and easily markup entire websites using the full schema.org vocabulary. Other major search engines like Yahoo, Bing and Yandex have similar features to those listed above, which can all be enabled by implementing JSON-LD markup. Schema App is your one-stop shop for JSON-LD creation and deployment, making it the simple solution for your website’s search result needs.

If you need a hand getting started with your structured data strategy, we’ve helped customers such as SAP and Keen Footwear drive more quality search traffic to their websites. 

The post How Does Google Reward You for Using JSON-LD? appeared first on Schema App Solutions.