It seems like Google updates more frequently than what we can keep up with them. Their latest update, the Hummingbird Update was announced recently even though they had been using it for about a month prior to the announcement. Some could take it personal when they are not “in the know” about which update is being initiated. The latest update to the algorithm is the Hummingbird update and it is one in which the entire algorithm has undergone a complete overhaul. Unlike some of the earlier updates like Penguin or Panda, Hummingbird is a total change to the algorithm. Penguin and Panda each dealt with one aspect of the algorithm, not the entire method. The latest update has refined how search results are gathered and displayed for users and it has sent ripples of discontent across SEO professionals. Knowing how the Hummingbird Update changes the world of search is important to web marketers and SEO specialists everywhere.
Who hasn’t said, “It’s okay, I’ll Google it.”? This has become the standard response of the day when we do not know the answer to a question. But with literally millions of sites, how do we know Google will come up with the right answer to our question? How does Google find a restaurant or business in our general vicinity when we need one? The web is growing exponentially every day, but how does it come up with the answers to our queries?
Users tend to want more from search results today than ever before. What we really want is for the search engines to know exactly what we mean by the query we entered. It can be frustrating trying to sort through irrelevant search results trying to find what we were looking for in the first place. Search engines are smart, aren’t they? Shouldn’t they know what you want? This is the premise behind the latest changes in search engines and how they produce results. Both Google and Bing are starting to look for ways to give users the precise information they are looking for in a much faster way. The latest changes in the way searches are conducted are attempts to make the results more relevant by figuring out what the user meant by the query. This in a nutshell is semantic search.