Best Buy: Next Steps Into the Semantic Web

By   /  May 2, 2011  /  No Comments

Just a few months ago Jay Myers, lead web development engineer at Best Buy, talked to The Semantic Web Blog about using RDFa to mark up the retailer’s product detail pages and more semantic things he’d like to do, including mashing up its online catalog data with some other data sources.

Well, in just the last week he’s been stoking the semantic data foundation – pushing Best Buy’s product visibility and discovery further along with the help of RDFa and pulling in some semantic data too, all geared to building up what he calls the company’s Insight Engine. And there’s more coming soon, as Myers’ has a personal agenda of stretching RDFa just about as far as he can in Best Buy product pages. “My goal is to make our web site as data- rich as possible while preserving the front-end user experience we have now,” he says. “It’s totally possible and I think we achieved that so far.”

The first announcement he made last week is geared to promoting machine discovery of information without sacrificing the human readability component. BestBuy has for some time had its ShopURLs capability to get consumers visual results of the top 50 things its search appliance considers relevant to a particular search term (see screen shot above). Now, utilizing RDFa, it can open up its search utility to the outside world for delivering rich data about the products it offers to all the machines out there, based on a list of search terms, in an automated way.

“Traditionally we have used RDFa and the semantic web to put rich markup on product detail pages. That’s great but there are a couple of different layers to get to those product detail pages,” he says. Now it’s possible for, say, a search engine to come in, ping the URL, and do something with what it finds – such as delivering information about the top items Best Buy’s search appliance thinks is relevant to “digital cameras” right in its results page.

“This is way for us to open up our product catalogue in a fairly unique way. It’s humanly available and also available for machines,” he says. “I’m personally very much into making data more contextual and more available – and if it raises us in search engine results or ranking on pages, so be it.”  He says he’s hearing a lot from outside developers interested in parsing the data and seeing what they can do with it. “The first step was exposing the data and I’m excited and enthused to see what will come out of it,” he says.

Later in the same week Myers posted that BestBuy encoded all its music product detail pages with RDFa, using GoodRelations, the Music Ontology, Dublin Core, and Google Rich Snippet Breadcrumbs vocabularies – and also a little thing called the Facebook Open Graph markup. The work was also aimed at helping machines get to valuable product data directly through the browser, such as individual song track details for albums with the help of the Music Ontology. “The Music Ontology is a good way of exposing what tracks are on a specific release and RDFa makes that available to machines,” Myers says. “And that could be helpful for search engines but also to parsers to consume this rich data about tracks and music releases.”

This is just the first of more product detail pages to be infused with more semantic web goodness – hard goods like DVD players and TVs, then movie titles, then software and other categories should get similar treatment in the next few months.

The Open Graph aspect is interesting. While getting that in there was, as much as anything, “throwing something up to see if it sticks,” Myers says, it’s also true that BestBuy sees a decent amount of social activity around some products. So there is potential value in turning its product pages into objects on the Open Graph, as shown above for Justin Bieber’s My World 2.0 CD. Creating relationships between the products liked on FaceBook and those who like them and tying these entities and the information back to BestBuy can translate into gaining more insight into customers’ needs in a near real-time way. “Can we ping the FaceBook data we made available semantically to make better decisions about what to put on sale, or are there product trends to identify through what happens on a social network to better tailor our product offerings to customers?” he says.

The work on RDFa with its product catalogue data is going on hand in hand with an overall project to widen Best Buy web pages. “There doesn’t have to be a specific reason to throw RDF into the mix and you don’t have to specifically spin up projects to mark up RDFa,” Myers says. It’s one of his mantras. “Just promote a development culture where it’s something we just do, just make it part of our coding routine. It’s a bit of a learning curve but after that anyone can make part of what they do everyday, and we will make the web much smarter with the structured data we create.”






About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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