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.

Here is a summary of v13 from schema.org:

This release includes improvements proposed via the Pending section, in particular a number of terms proposed by the Bioschemas project, alongside other additions around e-commerce returns policy markup, job postings, and MediaReview markup.”

There are quite a few updates to the schema.org vocabulary via the Pending section, but here are the additions that we are most excited about.

Product Updates in Schema.org Version 13.0

Version 13.0 brought many additions to merchant return policies, including adding:

• ReturnLabelSourceEnumeration (lists several types of return labels for product returns, such as ReturnLabelCustomerResponsibility, ReturnLableDownloadAndPrint, ReturnLableInBox)
• ReturnMethodEnumeration (lists several types of product return methods, such as ReturnAtKiosk, ReturnByMail, ReturnInStore)
• additionalProperty and itemCondition were added to MerchantReturnPolicy
• hasMerchantReturnPolicy was added to Offer

Ways to define return fees were added, including the following properties:

• returnMethod (the type of return method offered)
• itemDefectReturnFees (the type of return fees for defect products)
• customerRemorseReturnFees (the type of return fees for returns due to customer remorse)
• returnShippingFeesAmount (the amount of shipping cost for product returns)
• itemDefectReturnShippingFeesAmount (the amount of shipping costs for defect product returns)
• customerRemorseReturnShippingFeesAmount (the amount of shipping cost for products returned due to customer remorse)
• returnLabelSource (the method by which a customer obtains a return shipping label)
• itemDefectReturnLabelSource (the method by which a customer obtains a return shipping label for a defect product)
• customerRemorseReturnLabelSource (the method by which a customer obtains a return shipping label for a return due to customer remorse)
• restockingFee (a fixed restocking fee for product returns)
• returnPolicyCountry (the country where the product has be to sent for returns)

To improve compatibility with GS1, an organization who develops and maintains global standards for business communication such as the all-familiar barcode, countryOfLastProcessing and countryOfAssembly were added for Product.

Healthcare Updates in Schema.org Version 13.0

The following additions were proposed by the Bioschemas community.

Bioschemas aims to improve the Findability on the Web of life sciences resources such as datasets, software, and training materials.”

Several new basic life science concepts were added, including:

• Taxon (a set of organisms asserted to represent a natural cohesive biological unit)
• BioChemEntity (any biological, chemical, or biochemical thing)
• ChemicalSubstance (a subtype of BioChemEntity)
• MolecularEntity (any constitutionally or isotopically distinct atom, molecule, ion, etc)
• Gene (a discrete unit of inheritance, which affects one or more biological traits)
• Protein (in the schema.org vocabulary, Protein is used in its widest possible definition: as classes of amino acid-based molecules)

Video Updates in Schema.org Version 13.0

SeekToAction

SeekToAction is a schema.org type, and is the Action of navigating to a specific timestamp of a VideoObject. startOffset was accidentally omitted from previous SeekToAction definitions, but has been added with the latest release. startOffset is the start time of the clip, expressed as the number of seconds since the beginning of the video.

InteractionCounter

InteractionCounter is a summary of how users have interacted with the CreativeWork type, such as books, movies, photographs, software programs, etc. Subtypes can be used to specify the type of interaction. 

Added:

• location
• startTime
• endTime

Read more about all changes in schema.org’s Version 13.0  here.

We always get excited by updates to the schema.org vocabulary! Not only do these updates reflect Google’s continued investment in schema markup, but as the vocabulary expands we keep identifying new ways for our customers to maximize their results from structured data!

The post Schema.org Version 13 Release: Products, Healthcare, Videos, and more! 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.

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.