A Semantic Web Case Study
This series on the semantic web started with an introduction in Part I, continued with the business case in Part II, and turned to complementary technologies in Part III. It’s now time to put theory into practice with a case study. With the requisite background out of the way, let’s look at what one company is doing with the semantic web and related technologies. And this isn’t some obscure company of which no one has heard. This is Best Buy.
Best Buy is using the GoodRelations ontology to make its sales’ data much more meaningful to everyone and everything, including suppliers, real and potential customers, applications, systems, and the public at large.
Of course, this begs the question: What is GoodRelations? According to its website, GoodRelations is an e-commerce ontology that allows for the use of “a standardized vocabulary for product, price, and company data that
- can be embedded into existing static and dynamic Web pages and that
- can be processed by other computers
This increases the visibility of your products and services in the latest generation of search engines, recommender systems, and novel mobile or social applications.”
Best Buy was smart in going semantic. It did initially go all in. Rather, as Jay Myers points out, Best Buy initially rolled out GoodRelations across a number of stores. Buoyed by early successes, only then did the company embrace GoodRelations company-wide. Today, it’s at least “a little semantic” at each of its more than 1,000 stores.
Simple search means that traditional SEO dictates what appears at the top of searches. In other words, it can be difficult for a company to reach its intended customers–or, more accurately, for potential customers to reach the right company. To be sure, Google is amazing at simple search and smart folks type in additional words to provide greater context to basic searches. In the end, many ultimately find more relevant results with their queries.
However, at present, one thing is obvious: simple searches often do not find the most meaningful results. Bottlenecks and frustrated customers can result that, in turn, reduce sales. (For more information on some of the challenges of simple search and how semantic technologies such as GoodRelations can overcome these, check out this presentation.)
If you’re anything like me, you’re not patient when trying to find something. This is not 1995, when search first appeared. Results were laughably inaccurate and people often gave up without finding what they wanted. While we have made a great deal of progress with search, in large part thanks to two folks name Larry and Sergei and a horde of imitators, there’s still a great deal of room for improvement. We are at the just the tip of the iceberg with search, as Google CEO Eric Schmidt recently pointed out on the Charlie Rose show.
Companies such as Best Buy should be commended for being proactive. They understand where the web is going and, despite being a market leader, they are avoiding The Innovator’s Dilemma.
The adoption of GoodRelations has hardly been universal and I certainly can’t claim that it’s the best or only ontology that meet retailers’ needs. But focusing on “the best” of anything often misses the point. What are the odds that everyone in any company–much less one as big as Best Buy–would agree on what to do and how to do it?
Best Buy has already seen concrete results by utilizing GoodRelations. Myers recently revealed that “since they launched their beta Semantic Product Web, augmented with GoodRelations and RDFa, they’ve seen a 30% increase in traffic to their pages. Again, there could be many reasons for this—not a perfectly controlled experiment—but the correlation is remarkable.”
It takes a great deal of work to transform data from a bunch of structured or unstructured junk into the accurate, contextual, and complete information capable of supporting the semantic web. Absent good data, GoodRelations or any other ontology is likely to yield disappointing results. Web 3.0–or whatever you want to call it–hinges upon technologies, good data, and proactive management. It’s refreshing to see a large company lead the way and avoid the complacency often associated with organizations typically content to maintain the status quo.
On a different level, Best Buy is instructive for refusing to take baby steps. So often with large companies–and I speak from years of personal experience, naysayers and opponents of substantive change block efforts to dramatically improve technologies, data, and management practices. Clearly, this is not the case with Best Buy. I have no doubt that they’ll benefit from deploying semantic technologies in the long-term.
What say you?
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