Google has a new search algorithm, the system it uses to
sort through all the information it has when you search and come back with
answers. It’s called “Hummingbird” and below, what we know about it so far.
What’s a “Google search algorithm?”
That is a technical term for what you can think of as a
recipe that Google uses to sort through the more than of web pages and other
information it has, in order to return what it believes are the best answers.
What’s “Hummingbird Algorithm?”
It’s the name of the Google search algorithm, one that
Google says should return better search results.
So that “Page Rank” algorithm is dead?
No. Page Rank is one of over 200 major
“ingredients” that go into the Hummingbird Algorithm recipe. Hummingbird looks
at Page Rank — how important links to a page are deemed to be — along with
other factors like whether Google believes a page is of good quality, the words
used on it and many other things.
What does it mean that Hummingbird is now being used?
When Google switched to Hummingbird, it’s as if it dropped
the old search engine out of a Search Engine Marketing and put in a new one. It
also did this so quickly that no one really noticed the switch.
Google struggled to recall when any type of major change
like this last happened. In 2010, the “Caffeine
Update” was a major change. But that was also a change mostly meant to help
Google better get indexing rather than sorting through the information.
Panda, Penguin and
other updates were changes to parts of the old algorithm, but not an overall
replacement of the whole. Hummingbird is a like new search engine, it continues
to use some of the old parts like Penguin and Panda.
What type of “new search activity” does Hummingbird help?
“Conversational
search” is one of the greatest
examples Google gave. People, when speaking searches, may find it more useful
to have a conversation. Hummingbird should better focus on the meaning behind
the words. It may better understand the actual location.
In particular, Google said that Hummingbird is
paying more attention to each word in a query, ensuring that the whole query —
the whole sentence or conversation or meaning — is taken into account, rather
than particular words. The goal is that pages matching the meaning do better,
rather than pages matching just a few words.