Google Hummingbird update was launched in the fall of 2013. It provides assurance of an increasingly sophisticated understanding of the intent of the users’ queries. The objective of this update fetching more relevant results. It is one of the most significant upgrades to the google search algorithm. This update revolutionized the way searches were conducted on the internet.
The focus of Google Hummingbird update was queries or searches on smartphones. To accommodate this, the conversational search method was added to the Hummingbird algorithm. It was designed to focus on the meaning of the query, rather than individual components of it. Hummingbird made it more convenient for the users to search for what they intended to say or mean through their query rather than just relying on individual keywords of the query.
How does it work?
Before diving deeper into Hummingbird, it’s important to understand the pre-existing features it impacted the most. Earlier it focused only on semantic search and the knowledge graph.
Google launched its knowledge graph a year before the release of Hummingbird. It’s a set of SERP features that provides swift, accurate answers to users’ queries. The search results don’t contain standard links to suitable websites. They contain a rich set of knowledge graph data, including an answer box or a feedback box that contains featured search results.
The semantic search feature reflects the intent of the searcher queries and adequately addresses their needs. Furthermore, the semantic search works towards matching the search results with the language of the users’ queries. It focuses on user intent beyond the meaning of the keywords. It takes the broader context into account which it learns over time through continuous feedback from all the users the world over.
Hummingbird’s main purpose was to combine the learnings and applicability of both semantic search and knowledge graph. Its purpose is to serve the users with better search results. This update gives central importance to user’s intent rather than on the plain meaning of the keywords
Hallmarks of Hummingbird
There were four essential components or trademarks that were the main focus of Hummingbird:
Conversational Search
With the help of natural language processing, the search results would become more specific and more customized for the users. The semantic search would help to gauge the intent of the users better. Thus, it helps in providing better search results. Hummingbird thus allowed the users to search for any topic without any hesitation of receiving irrelevant results.
Human Search
Hummingbird was able to focus on various diversified meanings of one singular phrase which might mean different in different geographies or different cultures with the help of a knowledge graph and extensive learnings over the years. Hummingbird educates people about what they don’t know and curate results that help users find what they’re looking for. Thus, In this way, Hummingbird enabled Google to become something more human.
Voice Search
Hummingbird was seen as Google’s way toward the mastery of the inevitable rise of voice search. Semantic search and knowledge graph provided a route to Google to focus its attention on hands-free voice search on smartphones. Keyword searches were fast becoming one-dimensional which results in voice search eas seen as the next big thing in the tech world
Local Search
Use of semantic search and NLP ( natural language processing) to accentuate the quality of search results increased. Moreover, this update starts focusing on how humans think, what they desire, and how they expect the results. As a result, the age-old practice of stuffing the metadata of a website with keywords quickly becoming obsolete. But, Website owners and developers stills used this approach today. But, it shifted importance from stuffing the metadata mindlessly with keywords to a more nuanced approach.
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