The evolution of search
Many of us might not have noticed the quiet revolution taking place in the world of search. Rather than examining search query terms and matching them to keywords it finds on websites, search engines are now trying to “understand” users’ queries and offer links that provide answers to them.
To accomplish this, a transition from examining keywords to examining meaning is needed. The call for a more “semantic” web is nothing new. Already in 1998, Tim Berners-Lee articulated his vision of a world wide web that understands meaning so that search engines are able to do more than just locate files that contain certain keywords. However, what is easy for us is still difficult for a machine. It will take a long time until machines are able to understand natural language.
Google has already taken a big step towards a more intelligent search by introducing the Knowledge Graph. The Knowledge Graph allows users to learn about people, places and things all without having to leave the first search engine result (SERP) page. Until recently, users typically clicked themselves through link after link jumping from one website to another until they found what they were looking for. With the Knowledge Graph, Google is providing the answers to the most popular queries on page one of its search results.
The Knowledge Graph is basically a display box that lists the most important facts and references of a growing number of different subjects in “knowledge panels” alongside traditional search results. When it was launched in 2012, Google said that the Knowledge Graph draws from about 3.5 billion facts about 500 million of the most searched objects from “authoritative sites” such as Wikipedia, CIA World Factbook, and Freebase, a Google-owned knowledge database. The number of categories, subjects and facts is slowly growing as users—or “the community”—contributes to the database.
However, Google is not just building another Wikipedia. Even more important than facts and figures on a particular subject are the relationships between subjects—or “entities” as Google names them. Graph is basically Geekspeak for a visualization of these relationships. For example, if a user asks a knowledge question about a film, Knowledge Graph will also list the film’s director as well as the actors that were in it, thus providing answers to related questions a user might not even have thought to ask. This helps users to acquire a broader knowledge about a specific topic. To prevent that users are overwhelmed by facts, Google picks out the facts and figures for each object that are most sought for and suggests further topics in a “People also searched for” section.
While the new display box is very useful for the average searcher, it has also raised concerns about the future of search—especially among marketers. SEO specialists and online marketers are worried about the fact that the average searcher will no longer be willing to click on any results if he can find the information he needs on page one in the Knowledge Graph. To alleviate worries about losing organic traffic and keyword impact, Google has invited everyone—including businesses—to become a “member” of the Knowledge Graph community.
Joining this community might have more benefits than sophisticated SEO strategies. It would establish a business’s website as an authoritative source for information on a particular subject which would, in turn, also boost organic traffic. As a consequence, businesses might be forced to improve content they feature on their websites even further. This is not the first time that changes in search algorithms have led to a boost of content quality as a positive side-effect. And the race to be featured on the Knowledge Graph has begun.
However, the shift from examining keywords to examining meaning remains difficult. And understanding human language remains one of the biggest challenges in today’s field of artificial intelligence. Even Google announced that the Knowledge Graph is merely just a “baby step” towards understanding meaning.
For support in examining how the Knowledge Graph may affect your content strategy, contact Thomas Bosshard.