Hummingbird, the Knowledge Graph, and the Evolution of Search
Hummingbird is here! Run for the hills! The launch of Google’s newest algorithm update Hummingbird got me thinking about the way people search, and how it affects everything online businesses are trying to do. To better understand what Google is attempting to do, I set out to explore how changes in the way Google provides search results could affect businesses going forward.
For anyone unaware, Hummingbird is the newest algorithm update from Google. While its full effects aren’t entirely clear yet, we know it uses Knowledge Graphs to try and derive context from search queries. The Knowledge Graph is essentially a collection of words that are semantically interconnected to show relationships and derive meaning. It uses context clues to display information related to, but not just expressly written in, your search. One example provided in the Knowledge Graph informational video is as follows:
Let’s say you search for “Leonardo Da Vinci.” Google understands you may also want to see information on the Renaissance, or even other painters. Using the Knowledge Graph to find related topics or words, they display additional results on the right side of the page (pictured right) that they consider to be relevant to searchers. In this case, Google has displays basic information on the artist such as a brief synopsis and birth and death dates, as well as his most famous works and relevant searches for other artists.
In addition, many searches these days are not conducted on a computer, or are even typed. Due to the rapid introduction and adoption of smartphones across the world, many people find themselves searching by “asking Siri,” or another speak-to-search interface. As a result, many searches today are phrased as questions (Siri, how far to the nearest gas station? What’s the capital of Mozambique? Will my fantasy football team ever win?). I think Google may have introduced Hummingbird in part to better serve these types of question-based mobile searches. The Knowledge Graph allows Google to draw context from searches, helping Google to better answer the question asked as opposed to merely showing results matching the triggered keywords. For example, I did a search for “where is the best Italian restaurant in Brooklyn,” and got the results below:
As you can see, thanks to the Knowledge Graph, Google was able to derive the meaning of my search and show me a list of top rated restaurants to scroll through at the top, accompanied with reviews, addresses, and a map to find them. In addition, when I conducted the same search on my mobile phone, the results included a vertical listing of these restaurants along with the same rating and location information provided on a desktop. This exposure shows why marketing firms focusing on things like search engine optimization are more important than ever. As a business, you want your company to show up for relevant searches with content that answers potential customers’ questions.
While the knowledge graph is still a work in progress, you can imagine its’ potential. There are billions of Google searches every day, and with each one the Knowledge Graph learns and grows. Google Product Manager Director Johanna Wright says, “We’re in the early phases of moving from being an information engine to becoming a knowledge engine…” Thinking about it, I can’t help but be reminded of IBM’s Watson, who was able to defeat Ken Jennings and Brad Rutter on a special episode of Jeopardy. The super computer was able to use context clues to derive meaning from complex human questions, much like what Hummingbird is attempting to do now. As the Knowledge Graph continues to learn, it will become better and better at understanding how words are linked in various contexts, continually improving search results.
From an SEO standpoint, I expect this will boost pages with a breadth of high quality content that answers searchers’ questions. The more relevant information you have on a topic, the more likely it is to be picked up in searches for related keywords. In addition, as Google better understands what searchers are looking for compared to what a website is offering, the Knowledge Graph could theoretically help ensure websites show up more in relevant searches, and less in irrelevant searches. A hypothetical example of this could be a discount auto insurance company no longer showing up in a search for “cheap auto” but showing up on a search for “auto coverage.” While there is no way to know the full effect yet of Google’s attempt to create a “knowledge engine,” the possibilities for your business are exciting, and in the right hands could lead to increased exposure, leads, reputation and profits.
What do you think? Comment below or tweet me @El_Mattador101!