With no shortage of retailers on the Web today, merchants are finding it difficult to market their products in the natural listings of search engines, such as Bing and Google.

And in the hopes of getting their products to stand out on the search engine result pages (SERPs), merchants are turning to sophisticated product microdata integrations as part of their search engine optimization (SEO) practices.

For the unfamiliar, product microdata is a type of structured data that allows merchants to better define and distinguish their products (based on qualities and characteristics) from those of their retail competitors. Consumers, as a result, are able to discover products listings that are most appropriate for their unique search query and merchants can market their products (more effectively) to interested buyers.

Merchants use product microdata in a variety of ways, primarily in product feeds and on reviews. These days, however, there is a growing need for more detailed and granularly specific product-based vocabulary. Of course, growing reliance on microdata markup is having an impact on the way merchants approach SEO — and the way many are building their digital presence from the beginning.

The “Good” News for Merchants

Last year, Google, Yahoo! and Bing joined forces to help develop Schema.org, a site that provides webmasters with a set of guidelines for utilizing structured data (including product microdata) based on a unified agreement between the three search engines and others, including Yandex. However, Schema.org has proven to be insufficient for many e-commerce related scenarios.

For those interested in a markup language with more of a focus on merchants, several years ago Martin Hepp developed a standardized vocabulary, or “ontology,” known as GoodRelations. It is meant to simplify product microdata usage for retailers, while also increasing the visibility of their products in search engines, as well as recommendation systems and other applications.

Hepp’s goal with GoodRelations has been to offer an industry-neutral data structure, one that is equally valid across the different stages of the value chain, and to be syntax neutral. This means it should work with microdata, RDFa, RDF/XML, Turtle, OData, GData, JSON and more.

To do this, Hepp followed the Agent-Promise-Object Principle, which correlates with most industries that use four simple entities to represent e-commerce scenarios: an agent (e.g. a person or organization), objects (e.g. products) or services, a promise to transfer the rights to the object or provide the service and the location of the offer.

Markup languages do more than just show rich snippets to search engines. They indicate the relevance of a page for a specific query by allowing webmasters to include a different layer of information for search engines, which could result in a higher page rank when it is a relevant match. This can include a store’s location, the countries it ships to and the payment options it accepts. GoodRelations gives retailers the opportunity to not only improve their Google ranking, thanks to greater data specificity, but it also makes it possible to include pricing information in Google search results, allows for data reuse and gives retailers the ability to preserve as much of the data semantics and structure as they have at the origin.

The Future of Merchant Microdata

More than 10,000 Web and e-commerce companies, including major brands like Best Buy, Sears, Kmart, Volkswagen UK and many others, already use GoodRelations. Big business’s widespread adoption has led both Google and Yahoo! to recommend GoodRelations for publishing structured information about a merchant’s products or services, with Bing also indicating that it will add GoodRelations support to its crawlers in the future.

Unlike Schema.org, GoodRelations was specifically designed to be used by retail brands, as opposed to a broader range of websites. Its vocabulary focuses on ecommerce scenarios, such as business, store, product, offer, warranty, payment, delivery and other information. This enables merchants to identify their most valuable data and share it with consumers that are using search engines to find a specific product or service.

Surprisingly, there is very little overlap between the GoodRelations and Schema.org vocabularies. A minimal amount of Schema.org and GoodRelations’ classes cover the same entities. Consequently, online retailers that are utilizing product microdata without referencing the GoodRelations vocabulary may be missing valuable opportunities to increase the visibility of their products or offers. That being said, merchants can combine GoodRelations and Schema.org to maximize the impact of their markup; and, the two are currently devising a way to integrate GoodRelations into Schema.org’s core — so stay tuned.

The use of e-commerce-specific microdata will likely become the norm for SEO-conscious merchants. So how can merchants get started with GoodRelations?

Good to Have GoodRelations

For interested merchants, there are a number of ways to implement GoodRelations. Those using popular Web shop applications (e.g. Magento, Joomla/Virtuemart, WordPress/WPEC and others) can download free extension, modules or plugins that add GoodRelations RDFa for semantic SEO, which is the simplest way to incorporate the ontology into your e-commerce store. If a software package doesn’t offer a GoodRelations extension, users can ask their platform providers to add it using a special “recipe,” which comes with free support from GoodRelations.

On the other hand, users can also integrate GoodRelations vocabulary the old-fashioned way using various HTML patterns. On the GoodRelations wiki site (http://wsm.co/RBBCn8), users can copy, insert and customize the patterns of additional HTML markup into their Web pages. Of course, the customization part is essential, as that is what identifies each product or page as unique to the user’s business. Then, all they must do is add links between the patterns and modify the header information of each respective page.

The wiki site offers three distinct pattern classes for a “Company,” “Product/Offer” or “Shop, Restaurant or Store and Opening Hours” to add to a Web page. It also provides code for adding links. This allows users to link an offer or product back to the original company or from the company to its stores, shops and restaurants. Finally, it provides copy-ready code for updating XHTML/HTML page headers, including a minimal solution and code for XHTML 1.0 Strict, XHTML 1.1, XHTML 1.0 Transitional, HTML 4.x and, of course, HTML5.

As you can tell, utilizing GoodRelations can be a relatively simple process that, like using other types of structured data, increases in complexity based on how much information you want to expand upon (e.g. how many products or offers you have).

Embracing Change

E-commerce-specific product microdata will no doubt become an area of considerable interest to online merchants. They should make it a priority to provide search engines with unique information for a better shot at appearing (high) in the rankings for particularly relevant queries. As merchants try to stand out on the Web, they should know that the ability to display their products to the most interested consumers is doable by using a retailspecific markup language like GoodRelations.