Released! Human Product Discovery Via Machines, RDFa and “Shop URLs”

Well folks, we’re at it again. The month by month the journey continued Monday into Tuesday night to semantify the hallowed templates of bestbuy.com. One of April’s goals: to enhance machine understanding of Best Buy’s considerable product offerings while retaining human searchability and readability. After long wait, we have deployed code to the search templates to establish a human-readable and machine-parseable front-end API.

Many moons ago (even before all this RDFa goodness), we established a URI scheme we call “shop URLs”. Basically it’s an easy way to pass a search term in a URI and get a visual list of up 50 products our search appliance considers relevant. However, when you have a catalog of 400K+ products, simple visual results may not be the best or most efficient way to sort through the cruft and get at what you’re looking for. Enter stage left our friendly machine helpers: Search Engines, Parsers and Aggregators — this deployment activity is focused on feeding you! We’ve deployed step one of enabling a solution to product visibility and discovery issue by unleashing the result data in RDFa (with GoodRelations, Dublin Core, FOAF, Google Ratings vocabs) for maximum machine parseability.

After all this grandeur and hype, I’m hoping you’re still interested in how it works. You may point your eyes and parsers here:

http://www.bestbuy.com/shop/search+term*

* Please note, due to marketing and business considerations, some of the more popular terms may redirect you to a dataless “category page”. To get a RDFa-enabled result, simply append a * to your search term, e.g., http://www.bestbuy.com/shop/ipods* (how dare those marketing people stand in the way of good data!)

Let’s dive deeper with a quick example. So I’m a bit eclectic and looking for a thermometer online. I would like to see results of the “thermometers” from bestbuy.com, plus pass the data to my machine friend, an application I am building to help me make the right product choice.

First I type access my human-friendly representation using a “shop URL” directly in the browser:

http://www.bestbuy.com/shop/thermometers

Which results in a human-readable web page:

human-readable shop url

Looks like I have 15 product offers that match and are available via bestbuy.com or in store. Excellent.

I’m going to take that same URI and pass it on to my machine helper who just wants the data, no fluff. Let’s say we’re working with RDF/XML…on the surface, the 15 product offers may appear like this:

rdf extract from shop url

Expanding an individual offer yields the following data-rich result:

expanded data extract of shop url

So endeth the second phase of sematification. Make sure and leave your API keys at home, this search data is all open! Tune in for more later this week, I will be discussing another one of April’s goals, expanding RDFa markup to Best Buy’s product detail pages.