Breaking Down Results With Hummingbird

on under Search Engine Optimization.

GoogleHummingbirdDissection-NorthcuttA recent post on Search Engine Watch delved a little deeper into Google's latest algorithm change. Hummingbird was not an update; it was a complete overhaul of the existing search engine algorithm, a feat that hasn't been completed in over a decade. We featured an introduction to Hummingbird and now we've taken snippets from Grant Simmons' post to further update you on just how involved this change has become.

While many have been stating that Hummingbird is simplifying queries, this is true for that exact statement, but the complete converse for how the search engines actually deliver the information to you. The manner in which Google serves the information follows a much more involved process - one that I simply marvel at.

Understanding A Query Down To The Last Word

The way that Grant Simmons breaks down search queries and the results that are fed seems completely apt. When you think of sentence structure in English class, you remember how each one is made up of articles, verbs, prepositions, nouns etc. Search queries seem to be broken down in a similar way. Grant used the example of "where can I buy a Larry Bird shirt?" Larry Bird being the ex-professional basketball player for Indiana Pacers.

If you take a look at the search query, you see that much like a basic sentence structure, the query can be broken down into separate parts:

Where [location - matched to user location] can I buy [intent is to purchase] a Larry Bird [person - basketball player and coach] shirt [product - link to supply or ecommerce store].

In order to return the most relevant results that depict a clear understanding of the entire search query, there needs to be an association between the last two items - Larry bird and the shirt. Results that combine the two would be considered of primary importance. That's the connection that offers users the gold, combined with location specific results that are relevant to the user.

Making Search More Relevant

When you think of the amount of data is searched through to return the refined and exact results, it's pretty astounding that information can be fed in such a precise manner. The only way that it could logically be done is to break down each part of the query into the who, what, when, where and how of each query.

  • Who is the user, what does their search history say about them and their preferences?
  • What are they searching for?
  • When could pertain to the time of day or year and add relevance to queries - queries carried out now could automatically be linked to the festive season or end-of-year holidays
  • Where is the user based?
  • How has the query been structured - common conversational elements can be looked at, including sentence elements such as articles and prepositions

How Does This Affect Marketing Efforts?

It doesn't, not if you're already creating great content that feeds your user's brains and queries. Queries are being answered in as close to human language as possible, making it essential for content to speak to these queries, answers and human needs. It's the same thing that marketers have been talking about for ages; create compelling content that your users will be interested in reading and sharing, and you're also going to be answering to search results.

One thing you should look out for is whether or not your content answers to all of the broken down elements of each search query. Call it sentence structure, call them elements or attributes; deconstruct your content offering and label each piece according to the attribute it answers to using schema.org.

Image courtesy of vacodadesign.

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