In the latter half of 2013 Google released an updated version of their search algorithm. The new version of the algorithm, called “Hummingbird,” was a major change, a complete refresh of the engine, and one that was more significant than any other update since 2001, according to Senior VP and Google Fellow Amit Singhal. Previous recent changes to the Google search algorithm, such as the Panda and Penguin updates of 2011 and 2012 (respectively), were changes to parts of the search algorithm—infrastructure updates—not a complete overhaul of the search engine. The reason behind the search algorithm overhaul, apart from Google’s interest in continually improving their foundational Internet services product, was to address changes in the way that searchers are using Google—specifically, how “conversational search” has been introduced by the addition of the voice search feature on many smartphones and other mobile devices.
Google has already added voice search to their search app for Apple iOS, Android and Chrome browsers. With that technology in place, Google believed it was time to study how it would be utilized. In their study of the changing nature of search, Google engineers found that it’s not uncommon, when searching for products and services through the use of a desktop or laptop computer, to enter the desired search item followed by the zip code or city name. However, due to the conversational nature of search via voice on a mobile device, the search engine algorithm needed to be able to clearly understand what was being asked and what it needed to return in the form of search results in order to satisfy the needs of the user. As an example of the difference between typical search requests via keyboard entry and voice, consider the two following entries.
Keyboard entry: “Population of Kansas City.”
Voice entry: “How many people live in Kansas City?”
Currently, both of the above entries return search results that offer the answer to the question (464,310 as of today), as well as a wealth of related information and links on the subject. From a human perspective, the questions posed aren’t much different. But to a computer, they can appear strikingly different.
As more people are using Google search on their mobile devices, as well as choosing to use natural (conversational) language for their search queries, Google decided to meet this demand with changes to the algorithm that addressed the issues. Additionally, Google understood that location information (when made available by the mobile device user) also needed to figure into the search results. One element of the Hummingbird algorithm update finds “meaning” in search requests by paying close attention to each word in the search query, as well as taking into account how the use of certain words changes the whole sentence or entry. Another aspect of the Hummingbird update takes location into consideration. If a searcher asked Google “What’s the closest place to my home where I can buy the Kindle Fire?” The old version of the algorithm may have completely missed a number of semantic cues and directed the searcher to the Amazon.com website to purchase a Kindle Fire online. Clearly, this would not be the search result needed, given the nature of the request. With the Hummingbird algorithm in place, the same search query should result in a nearby retailer such as Best Buy, Walmart, or Target, along with contact information, location data, and store hours.
Due to the changing nature of search requests, and the introduction of the Hummingbird algorithm update, those who are looking for ways to improve their position in the Google search results pages have a few items to add to their task list. At the top of the list—which will likely include mobile optimization for your site and implementing social media best practices—is a focus on content.
High-quality content is a crucial element, along with some level of keyword optimization. The Hummingbird update is much more adept at recognizing, deciphering, and solving long-tail queries, so web marketers and site owners are free to utilize long-tail keywords to their benefit. Having a greater understanding of what your reader (end-user) expects from your content will help you create relevant, valuable content that attracts attention and drives response.
by Steve J. Scearce