SEO for Hummingbird: What It Does and How to Deal with Google’s Newest Update

We have all been on our toes ever since Google started rolling out high-impact updates to its algorithm. Panda had web developers check the quality of their articles and web content, removing poorly-written, scraped, and duplicated content. Penguin had everyone scrambling to audit their link profiles, burning the evening oil to comb through thousands of links and contacting other websites for link removal requests.

Now we have another major algorithm update which is changing the nature of search as we know it.

On August 20, 2013 Google implemented the Hummingbird update. It was actually announced only a month later, on September 26.

Hummingbird 101

Hummingbird is a brand new search algorithm (one that longtime SEOs say is an improved version of 2010′s Caffeine update). As Danny Sullivan from Search Engine Land puts it, it’s as though Google is an antique car and its engine has been replaced with a newer model. That new engine is Hummingbird. It is different from the Panda and Penguin updates, which, if the car analogy is to be continued, are like updates to specific parts of the old car engine.

Google Hummingbird

This doesn’t mean though that all the other updates implemented before August 20 became null and void. No, in fact, Panda and Penguin are still very much alive and in action (poor-quality content and link spamming are still no-no’s people!). Hummingbird may have replaced the search algorithm, but it has retained the most effective features of the old version.

What Hummingbird Does

The purpose of the Hummingbird update is for Google to get a better understanding of search queries. It evaluates the context or meaning of a long-tail, complex or “verbose” search instead of focusing on each word in the query as though it were a separate keyword. Basically it will consider “conversational search” at face value instead of honing in on the vital keywords of the search.

For example, if you want to know “what type of people will benefit from skin tanning,” Google will take that as a query about who will be the ideal candidates for skin tanning as opposed to showing you web articles about the benefits of skin tanning.

Hummingbird is able to disambiguate search queries through Metaweb technology, and also because it was launched simultaneously with the newer and improved features of Knowledge Graph.

Just a quick recap: Knowledge Graph was added in 2012 to enhance the search engine’s ability to generate correct results that are relevant to the search query. It penetrates through semantics. It even predicts what can possibly be the next queries of the searcher in relation to the first query. It produces results that contain other information that the searcher will possibly be interested in as well. This is why if you type in something as basic as “Who invented the light bulb?” you won’t just find Thomas Edison’s name but also his biography, accounts of his accomplishments, and even the different kinds of light bulbs in the market today.

According to Amit Singhal, Google’s Senior VP, software engineer, and head of Google’s core search quality department, this update allows the search engine to “take synonyms and knowledge graph and other things… to understand meaning[,] to rethink how we can use the power of all these things to combine meaning and predict how to match your query to the document in terms of what the query is really wanting...”

As you can see, Hummingbird sounds like the ideal search algorithm, the one that Google has always been gunning for in its quest to provide users with accurate, relevant and valuable search results.

Effects of Hummingbird

The combined powers of Hummingbird and the improved Knowledge Graph allow Google to determine the point behind complex searches, find out the meaning of semantics, and begin returning results as though it were a cognitive being.

Well that is the ideal goal, anyway. At present the effect of the algorithm is not yet felt that much. There are still conversational searches that are not generating very relevant results because certain keywords seem to continue having a strong pull on the search algorithm (either that or there really are no relevant data published on the Internet, but even that is too hopeful a stretch). It should also be noted that there seems to be less fanfare for the Hummingbird compared to the time when Panda and Penguin were first introduced. It took months before people got over them and the effects they experienced because of the updates.

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