Semantic Technology's Rise
Semantic Web data is represented using a technology standard called Resource Description Framework (RDF). RDF is a graph (web-like) structure that links data elements together in a self-describing way.
RDF is perhaps best understood in contrast with how enterprise information has traditionally been represented for the past 30 years -- relational databases. The semantic web was originally a buzzword in the early 2000s and few companies truly understood the transformation this tool would have on marketing.
Within the next few years it will likely become an essential part of the internet and a necessity in marketers’ toolboxes. Gartner identified semantic technology as a top technology trend impacting information infrastructure in 2013.
Companies using this technology successfully include Google, IBM and Facebook. Facebook’s Open Graph is a great example of semantic metadata and is used throughout the world by marketers to engage with their audiences and tailor communication at an individual level.
Google’s Knowledge Graph, introduced in 2012, uses semantic technology to uncover the relationship between objects; creating a connection between products and services. IBM’s Sentiment Analysis uses unstructured data such as the recent push of the "Social Sentiment Index" which uses analytics and natural language processing to predict future consumer trends by parsing through social platforms.
How is this made possible? Through semantic technology.
Google leverages graph-based data to provide individualized search engine results to consumers, rather than the user having to click-through to aggregate sites based on preferences. Google now displays comparative results showcasing prices, ratings and location, and provides other recommendations on users’ personalized results page keeping more of the traffic on Google and creating a better end user experience.
The goal of this tool is to use this information to resolve queries without directing individuals to other sites to gather the information themselves. All of this is enabled by semantic markup; The Schema.org vocabulary is the standard vocabulary adopted by Google, Bing, Yahoo and Yandex.
Mining Data to Know Your Audience
Semantic searches need to not only decipher a query, but decipher the query in relation to the profile of the searcher. By utilizing semantic information that showcases the data in a visually appealing way, Google can quickly disseminate the given information and make rational decisions based on relevant data.
In other terms, semantic technology is introducing a new phase of the Web where we stop searching and start finding. Google is using semantic technology to effectively look at who is initiating the search -- what device they are using, where they are physically located, what user profile attributes are available, other recent searches, etc. -- all to better understand why they are making this search query in order to provide the most relevant results to that particular user at that particular time. This in turn is creating a new type of thinking about online marketing content.
Google is using semantic technology to market content specifically to users to generate relevant results that are individualized per request. If two users inquired about a particular topic using this tool, it is likely that based on the time of day they asked the question and where they are located in the world will provide two separate responses.
Every day, as users insert queries on their mobile devices, personal computers and work stations their data is being collected for advertising purposes -- whether they know it or not. Successfully targeting key audiences is where marketers face difficulty -- as endless amounts of data is being collected it’s difficult to know which data to keep and utilize for communications with prospective audiences and which can essentially be thrown out.
A marketer’s purpose is to understand what their customers want, when they want it and how they’d like it delivered. Typical marketing practices include focus-groups and door-to-door advertising to gain insights. Semantic Web has the ability to bring meaning to a majority of the unstructured data (typically text heavy data including information such as dates, numbers and facts).
Interestingly, around 85 percent of enterprise data is unstructured making it seemingly impossible to decipher. Having the ability to successfully crunch this data with the help of semantic technology, along with the use of natural language processing and sentiment analysis will open up endless opportunities for marketers that were previously only dreamt about.
The lesson here is that when Google considers a source of information to be important enough to provide value to its search results, it will go to exceptional lengths to parse and structure unstructured or semi-structured data. Semantic technology is boundless and is the key to the future of search in both search and social engines. Thanks to companies like IBM, Facebook and Google seeing semantic technology as an innovation investment, data will soon have the face of context that it so desperately needs.
Title image courtesy of Jezper (Shutterstock)
Editor's Note: Want to read more about semantic technologies? Read Lee Feigenbaum's The What and Why of Semantic Web Technologies