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E-commerce SEO Using Schema.org Just Got A Lot More Granular

Ramanathan V. Guha of Google announced on 8 November that, effective immediately, e-commerce schemas from the GoodRelations project have been integrated into schema.org. This vastly increases the number of schema.org classes and properties available for e-commerce websites.

Put another way, this means that webmasters can now provide Google, Bing, Yahoo and Yandex with much more granular information about products and offers on e-commerce sites in a manner that is officially sanctioned by these search engines. In terms of e-commerce SEO, this is potentially a pretty big deal:  it is a means of providing very exact e-commerce information to the search engines in exactly the form they want it.

The Integration Of GoodRelations Into Schema.org

As Barbara Starr emphasized in a previous article, GoodRelations and schema.org are both vocabularies, and should not be confused with the syntaxes available to encode these vocabularies. Both of these vocabularies can be marked up in HTML using either the RDFa or microdata syntax (although initially, schema.org was very much geared toward microdata).

Until now, these were related but separate vocabularies. With this integration, however, the bulk of the GoodRelations vocabulary has now been made available in schema.org.

For those who had been using RDFa to markup GoodRelations, the situation is unchanged. The developer of GoodRelations, Martin Hepp, said in a post on the technical background of the integration with schema.org that “GoodRelations will remain an independent vocabulary, and usable in RDFa and other RDF syntaxes.”

The majority of sites using schema.org, however, have been employing microdata, including e-commerce giants like WalMart, Overstock and eBay. For these sites, the type of e-commerce information that can be marked with microdata has been vastly extended.

New Product Types & Offer Properties In Schema.org

While the integration of GoodRelations has resulted in a multitude of new types and properties being made available in schema.org, the types most obviously extended by GoodRelations are schema.org/Product and schema.org/Offer.

The schema.org Product and Offer Classes Before and After GoodRelations Integration

The schema.org Product (left) and Offer (right) classes before and after integration with GoodRelations

The number of Product-specific properties have grown from eight to 25, and three product-specific types have been added where previously there were none.

The additions now make it possible to describe physical properties of a product, allows relationships between products to be defined, and extends the number of product identifiers (like SKUs and part numbers) that can be associated with an item.

  • Product physical properties
    color, depth, height, weight, width, itemCondition
    These properties now make it possible to provide structured data about the physical dimensions, appearance and condition of products.
  • Product relationships
    isAccessoryOrSparePartFor, isConsumableFor, isRelatedTo, isSimilarTo
    These properties now make it possible to formally link related products. Previously, there was no way in schema.org to indicate which camera a lens cap fit onto, or what battery that camera required: now, these relationships can be explicitly declared.
  • Product numbers
    gtin13, gtin14, gtin8, mpn, sku
    These properties allow much more specific product identifiers to be declared than the previously all-purpose property productID.
  • Specific product types
    IndividualProduct, ProductModel, SomeProducts
    Allows everything from very specific products (such as a laptop with a specific serial number) to very general products (such as multiple, similar laptops) to be described with Product properties.

The number of Offer-specific properties have grown from ten to 37. These additions make it possible to provide much more detailed information about prices and offer conditions, as well as allowing vendors to describe e-commerce offers other than the sale of physical products.

  • Offer conditions
    acceptedPaymentMethod, addon, eligibleQuantity, eligibleRegion and other properties
    These properties facilitate the description of all types of offer conditions, such as the payment types that the vendor accepts, or the geographical regions for which that offer is valid.
  • Offer availability
    availabilityEnds, availabilityStarts, availableAtOrFrom, availableAtOrFrom, availableDeliveryMethod
    These properties make it possible to state the length of time an offer is available, where the offer (usually, but not always, a product) can be obtained, and what delivery method is available for the offer (which can be everything from a specific delivery service to a computer download).
  • Offer business function
    The property businessFunction and its expected type, BusinessFunction
    This allows markup of offers besides simple offers to sell, representing a huge extension of types of transactions supported by schema.org. Apartment rentals, car leases, maintenance agreements and even offers to buy can now be marked up.
  • Offer warranties
    The property warranty and its expected type, WarrantyPromise
    The duration of a warranty and the precise scope of services a warranty covers can now be explicitly stated with schema.org.

These are cursory descriptions of just the main additions to Product and Offer in schema.org as a result of GoodRelations integration.  E-commerce site owners would to well to examine the Product and Offer classes in detail to determine which specific properties might apply to their products and services (keeping in mind that what constitutes an e-commerce site, from a schema.org perspective, has been vastly extended).

As well, the impact of GoodRelations integration extends well past these two e-commerce-specific classes. OwnershipInfo, for example, provides a way of formally describing the ownership history of a product.

OpeningHoursSpecification supports a more granular way of specifying hours of operations, as well as making hours of operation applicable to more things, such as places. And so on… Again, there’s a lot to discover for anyone not previously familiar with the GoodRelations vocabulary.

Rich Snippet Benefits

Functionally, the chief benefit of the integration is that it extends the number of things that you’re able to describe to the search engines using structured data markup, especially things in the realm of e-commerce.

Currently, the chief SEO benefit of providing such markup is increased visibility in the SERPs when search engines generate rich snippets for a product in the search results. Here’s a rich snippet in Google for a camera on eBay, which uses schema.org Product, Offer and Review markup.

A Rich Snippet for a Camera on Ebay

It’s still far too early to see if the search engines will produce rich snippets for any of the GoodRelations types and properties newly integrated into schema.org (things like “For rent from $623 per week” or “1 year warranty”). However, I’d be very surprised if we don’t see more product and offer information appearing in the SERPs based on the extension of the schema.org vocabulary.

Certainly, e-commerce sites desirous of a competitive advantage won’t want to wait until new rich snippets start appearing before adding new markup to their pages. And businesses whose offers weren’t adequately addressed by the original schema.org vocabulary will certainly want to add markup if that now allows them to provide detailed structured data to the search engines about their products and services.

Rich Snippet & Structured Data Testing

As reported by schema.org’s Dan Brickley, Google’s Structured Data Testing Toolwas updated before we pushed the new site.”

Accordingly, the Testing Tool should now validate or provide error messages for code using the extended schema.org vocabulary.

The Testing Tool certainly didn’t have any problems validating an example snippet contained in Martin Hepp’s post detailing the integration, although testing hiccups are likely to occur during the initial phases of the roll-out.

GoodRelations-Integrated schema.org Code and Structured Data Testing Tool Results

SEO Benefits Beyond Rich Snippets… & Benefits Beyond SEO

Will supplying even more specific e-commerce information to the search engines result boost a site’s organic rankings? However, it stands to reason that sites capable of correctly offering more extensive e-commerce information will by necessity be well-structured, rich in detail and technically sound — attributes generally regarded as favoring higher rankings.

Outside of the realm of SEO, this integration has potential repercussions for the entire ecosystem of commercial transactions on the Web. Search engines are, after all, not the only data consumers that can digest and make use of semantic markup.

OpenLink founder Kingsley Idehen openly pondered the implications of the integration and said, first of all, that “structured data driven e-commerce at Web-scale is now a reality — think Amazon.com on steroids as a natural feature of the Web.” It also facilitates serendipitous discovery of offers, wish-lists, products etc., and does all of this without compromising privacy.

In short, it brings us closer to the realization of the linked open commerce model that he, Martin Hepp and Aldo Bucchi have been working on since 2009. The model envisions the interlinking of e-commerce platforms, big Web retailers, product catalogs and ontologies — with GoodRelations providing the universal e-commerce model.

Linked Open Commerce Datasets

Pretty geeky, right? Fortunately, the site also provides a very concrete example of where linked open commerce might take us.

Linked Open Commerce Consumers

Even if this integration doesn’t usher in a brave new world of intelligently linked e-commerce information, it certainly does allow e-commerce webmasters using schema.org the opportunity to provide more detailed information to the search engines about what’s offered on their websites.

Linked open commerce images above used under a Creative Commons license from linkedopencommerce.com.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


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