Profitable Linked Data
@jaymyers’ talk from Best Buy
Product attributes are valuable data, and it’s the secret behind the passion of Linked Data that Jay is presenting on.
The goal (personal) is to “provide more visibility to products, services, and locations to humans and to machines.”
The good news, for retailors, is that the tools are already available!
RDF(a), Microformats, GoodRelations, and HTML
Use Case:
Brick and mortar stores (Best Buy)
Location info (i.e. where the store is) is locked away, it’s siloed. So, the first step was to publish a page for every store. You can think of each store (or page about the store) as a bundle of interesting data (where the store is, what’s in stock, when’s it open?)
The next step was to change the pages into individual blogs. Each store has two people who can update the blog with very simple data, like changes to opening times. Behind the scenes, they’re publishing metadata about the store, as RDFa in GoodRelations.
Big, unintentional win, being a huge increase in search traffic without any intentional keyword or other traditional SEO investment. Sounds, to me, a lot like the results BBC’s wildlife finder found.
Use Case
Open Box Products (i.e. returned, fully-functioning goods)
The stores can be seen as a little data silo, holding information on how many, of which products are being returned.
This costs the industry billions.
So, the store employees were given a form with the SKU number of the returned product, and a few fields for what the discount was (i.e. how much it should have been, and by how much it was discounted), as well as the reason for its return.
This is published as RDFa, and they’re seeing the beginning of a relationship between products, returns, locations and reasons emerging.
Business Benefits
- SEO and product visibility (semantics are hugely useful for these)
- Reduction of proprietary data feeds.
